C RITICAL R EVIEW
The Validity and Reliability of Pain Measures in Adults With
Cancer
Mark P. Jensen
Abstract: To be most useful, clinical trials of cancer pain treatments should use pain measures that
are both reliable and valid. A great variety of measures are now available that may be used to assess
cancer pain. However, there are not yet any clear guidelines for selecting one or more measures over
the others. The purpose of this article is to summarize the evidence concerning the validity and
reliability of cancer pain measures. One hundred sixty-four articles were identified that provided
psychometric data of pain measures among patients with cancer. The results indicate that commonly
used single-item ratings of pain intensity are all valid and adequately reliable as measures of pain
intensity, although some scales appear to be easier for patients with cancer to understand and to use
than others. Multiple-item measures of pain intensity are reliable, but evidence concerning their
validity is lacking. There is a paucity of research examining the psychometric properties of measures
of cancer pain interference, pain relief, pain site, the temporal aspects of pain, and pain quality. This
lack of evidence limits the conclusions that may be drawn concerning the reliability and validity of
these other pain measures. Composite measures that combine ratings of pain intensity and pain
interference into a single score appear to be both valid and reliable for describing patient populations, although their usefulness in clinical trials may be limited because they can obscure the
contributions of intensity and interference to the total score. Proxy measures of cancer pain (pain
ratings made by someone other than the patient) may be useful when patients are not able to
provide pain ratings, but they should not be used as replacements for patient ratings when patient
self-report measures are available. The discussion includes specific recommendations for selecting
from among the available pain measures, as well as recommendations for future research into the
assessment of cancer pain.
© 2003 by the American Pain Society
Key words: Cancer, cancer pain, pain assessment.
C
linical trials of cancer pain treatment are essential
for identifying and estimating the effectiveness of
interventions that provide cancer pain relief. For
the results of such trials to be deemed valid, the pain
measures used must have proven reliability and validity.
However, despite the existence and use of many different pain measures, there has not yet been a review and
synthesis of empirical findings regarding the reliability
Received March 11, 2002; Revised June 20, 2002; Accepted June 20, 2002
From the Department of Rehabilitation Medicine, University of Washington School of Medicine, and Multidisciplinary Pain Center, University of
Washington Medical Center, Seattle, WA.
Supported by funding from the American Pain Society’s Clinical Practice
Guideline Program.
Address reprint requests to M. P. Jensen, PhD, Department of Rehabilitation Medicine, Box 356490, University of Washington School of Medicine,
Seattle, WA 98195-6490. E-mail: mjensen@u.washington.edu
© 2003 by the American Pain Society
1526-5900/2003 $30.00 ⫹ 0
doi:10.1054/jpai.2003.1
2
and validity of the measures commonly used in cancer
pain research. The primary purpose of this article is to
perform such a review to provide clinicians and researchers with data that may be used for selecting pain measures. Following a brief introduction to the concepts of
validity and reliability, the methods and results of the
review are presented. The discussion summarizes the
findings from the review, presents specific recommendations concerning the selection and use of cancer pain
measures, and suggests directions for future research
that will clarify the psychometric properties of these
measures.
Validity
Validity refers to the appropriateness, meaningfulness,
and usefulness of a measure for a specific purpose. Validity is generally seen as the most important consideration in the evaluation of a measure.2 With respect to
The Journal of Pain, Vol 4, No 1 (February), 2003: pp 2-21
CRITICAL REVIEW/Jensen
cancer pain measures, validity refers to the extent to
which the measure(s) under question are valid and useful
indicants of cancer pain or are useful predictors of important outcomes such as survival or quality of life.
Although several types of validity can be considered,
the most common types examined are content, construct, and criterion validity.2 A measure’s utility can also
be considered an indication of that measure’s usefulness
or validity. Content validity concerns the degree to which
the items of a measure are representative of some defined universe or domain of interest and is usually determined by the use of expert judgments. Construct validity
refers to the extent to which a measure assesses the specific domain or construct of interest. Evidence supporting
the construct validity of a measure or assessment protocol comes from a variety of sources rather than a single
source or study. Criterion validity refers to a measure’s
associations with one or more outcome criteria. Primary
importance in pain assessment concerns the criterion of
sensitivity to the effects of treatment or to changes in
pain over time, because pain measures are used primarily
for these purposes. However, pain measures may also be
used to monitor or to predict the course of a disease
state, to test hypotheses concerning the impact of pain
on other outcomes or measures of functioning, or to
place patients into specific diagnostic groups. Criterion
validity data provide evidence for or against the use of
the pain measure for these purposes.
A measure’s utility concerns its specific usefulness in
particular settings and with particular populations. A
measure may have a great deal of validity but may be too
long or too difficult to administer, to understand, and to
score to be of much practical use in clinical settings. Another measure, although useful for assessing pain in
some situations or with some patient populations, may
be difficult to administer in other settings or with other
patient groups. Evidence concerning a measure’s relative
utility, then, may be used to identify the specific situations, settings, and populations that are most appropriate for that measure.
Reliability
Reliability refers to the extent to which a score is free
from errors of measurement. Many factors in addition to
a patient’s experience of pain could potentially influence
his or her response to a pain measure or scale. Such factors might include the specific assessment setting (eg,
laboratory versus clinic), the person administering the
measure (eg, a research assistant, clinician, primary
health care provider, or family member), other subjective experiences and feelings (eg, being more or less fatigued or upset), or even motivational factors (eg, desiring to appear stoic, desiring to communicate a need for
analgesic medications). Some measures may be difficult
for patients to understand, adding another potential
source of measurement error if these measures are used
with patients who have limited cognitive abilities. The
variance associated with these other factors, which is not
associated with the specific domain of interest, is consid-
3
ered error variance. The most common estimates of reliability in pain assessment research are reliability coefficients, which can be used to estimate a measure’s
internal consistency (eg, coefficient alpha, which reflects
the association among items in a scale) and stability over
time (eg, test-retest stability coefficients).
The Purpose of This Review
Although a great deal of research has been published
on the psychometric properties of cancer pain measures,
to date, a comprehensive review of this literature has not
been published. The purpose of this article is to present
such a review by (1) identifying studies that include data
concerning the reliability and validity of cancer pain
measures, (2) summarizing and synthesizing the findings
concerning the psychometric properties of the measures
used in these studies, (3) making recommendations for
the use of these measures, and (4) making recommendations for future research concerning the validity and reliability of cancer pain measures.
Methods
Article Identification
Potential articles for this review were initially identified by performing a series of MEDLINE searches by using
6 key word combinations: cancer and pain and reliability;
cancer and pain and validity; cancer and pain and quality
of life; cancer and pain and assessment and 1999; cancer
and pain and assessment and 2000; and cancer and pain
and assessment and 2001. (The years 1999 through 2001
were added to the latter 3 searches because without
these the search resulted in too large of an article selection to be practical). This was followed by a series of
searches with key words that included specific measures
that emerged in the initial searches (McGill Pain Questionnaire, MPQ, Visual Analogue Scale, Visual Analog
Scale, VAS, Numerical Rating Scale, NRS, Verbal Rating
Scale, VRS, FLIC, QLQ-C-30, QLQ-C33, QLQ-C36, SF-36;
each combined with the key words cancer and pain). The
titles and abstracts of the articles identified from these
searches were read to select those that might contain
psychometric data concerning cancer pain measures. These
articles were then read, and those that met the inclusion
criteria (listed below) were selected. The reference list of
each selected article was also reviewed to identify additional potential articles that might meet the inclusion criteria. The search resulted in the identification and review
of 273 potential articles. From these, 164 articles were selected that met the following 4 inclusion criteria: (1) some
or all of the study subjects had cancer, (2) at least 1 measure
of pain was included, (3) the pain measure was described
adequately enough to be able to classify the specific type of
scaling used and the dimension(s) of pain it assessed, and
(4) data were presented that address the psychometric
properties of the pain measure(s) included in the study. A
list of the articles included in this review can be obtained
from the author via e-mail (mjensen@u.washington.edu),
or they can be seen at www.jpain.org.
4
Summarizing of Study Findings
The 164 articles were read, and the psychometric data
were summarized into a table that included the following information: author(s) and date, pain measure(s)
used/examined, study design, description of sample(s)
and setting(s) (sample size, diagnosis/diagnoses of subjects, age of subjects, sex of subjects, setting[s] of the
study, and sample selection procedures), findings concerning the measure’s(s’) validity, findings concerning
the measure’s(s’) reliability (most often test-retest stability and/or internal consistency), findings concerning
measure utility (eg, comments concerning specific difficulties with the measure(s)/frequency of subject inability
to use measure[s]). The final column in the summary table listed conclusions that may be drawn from the study
concerning the validity and/or reliability of the measure(s) studied, as well as any comments concerning the
methodologic strengths or weaknesses of the study regarding the interpretation of the findings. A copy of the
table that includes the coded data can be obtained from
the author via e-mail (mjensen@u.washington.edu), or it
can be seen at www.jpain.org. Data describing the subjects (subject number, cancer diagnoses, sex, age, ethnicity), cancer pain dimensions and measures assessed, and
type(s) of validity and reliability data presented in these
studies were entered into a database for study descriptive analyses (see below).
Results
Description of the Study Samples
The total number of subjects with cancer reported in
these studies was 36,128, and the average number of
subjects per study was 220 (range, 6 to 1897). The types
of cancer diagnoses held by the study subjects were not
always specified; 11,401 or 32% of the subjects in these
studies were reported to have cancer, but no specific
cancer diagnosis or site was given. In those studies that
did identify cancer diagnosis or site, the diagnoses most
often carried by the study participants were breast
(14%), lung (11%), prostate (10%), head and neck (7%),
metastatic (6%), gynecologic (4%), myeloma (4%), gastrointestinal (2%), colon, rectal, or colorectal (2%), and
genital (2%) cancer. Melanoma, oral, lymphoma, liver,
bone, hematologic, brain, cervical, stomach, orofacial,
esophageal, reproductive, soft tissue, bladder, nasopharyngeal, testicular, kidney, and thoracic (all less then 1%)
cancer were represented less often by the study participants.
Both sexes were represented in this body of research.
Of the 24,979 subjects whose sex was specified, 13,349
(53%) were male and 11,630 (47%) were female. Age
ranges varied, with the youngest subject in each study
ranging from 12 to 64 years (average youngest age,
29.80 years) and oldest subject in each study ranging
from 47 to 99 years (average oldest age, 81.56 years).
Average mean age for the 122 studies that reported the
mean age of their sample was 58.72 years. Ethnicity of
the samples was reported in only 30 of the studies. When
Cancer Pain Assessment
reported, the majority were reported to be white or Caucasian (average percent, 73.83%; range, 0% to 100%
across studies), but other ethnic groups were often included. In the 21 studies that classified subjects by ethnic
group with more specificity than just white/Caucasian
versus other ethnicity, on average, 10.73% were reported to be black/African American (range, 0% to 41%),
15.85% Asian (range, 0% to 100%), 3.89% Hispanic
(range, 0% to 24%), and 1.04% other ethnicity (range,
0% to 8%).
Dimensions Examined
The psychometric properties of a number of different
measures assessing a variety of pain-related dimensions
were examined in these studies, including those that assessed pain intensity (examined in 74.4% of the studies),
pain intensity and pain interference combined into a single composite score (examined in 29.3% of the studies),
pain interference (14.0% of studies), pain relief (10.4%
of studies), pain quality (10.4% of studies), affect/unpleasantness/bothersomeness (8.5% of studies), pain site
(1.8% of studies), and temporal aspects of pain (1.2% of
studies). The types of measures used to assess these dimensions also varied and included single rating scales
(eg, Visual Analog Scales, Numerical Rating Scales, Verbal Rating Scales, Graphic Rating Scales, and Mechanical
Visual Analog Scales) and composite measures (of pain
intensity, pain interference, pain affect, pain quality,
and multiple-dimension composite measures).
Results Concerning Validity and
Reliability of Self-Report Measures
All 3 major types of validity (content, construct, and
criterion) were reported in these articles. Construct
(61.0% of studies) and criterion (50.6%) were addressed
much more often than content (2.4%) validity was. In the
articles reviewed, construct validity was usually evaluated by examining the associations between the pain
measures and measures of the same pain dimension or
other pain-related constructs. Less often, and for multiple-item scales, construct validity was evaluated through
factor analyses to show whether the items on a scale
loaded together onto a single factor. Criterion validity
was most often determined by (1) a measure’s sensitivity
to changes in pain with treatment or (2) a measure’s
ability to predict important outcomes, such as mortality
or disease progression. Reliability of measures was examined less often than validity; only 26.8% of studies provided reliability data. It was most often presented as either an internal consistency coefficient for multiple-item
scales (18.9% of studies) or as a test-retest stability coefficient (9.8% of studies).
Validity and Reliability of Single-Item
Ratings of Cancer Pain Intensity
Visual Analogue Scale of Cancer Pain
Intensity
A Visual Analogue Scale of pain intensity (VAS-I) consists of a line, usually 100 mm long, with each end of the
CRITICAL REVIEW/Jensen
line labeled with descriptors representing the extremes
of pain intensity (eg, no pain, extreme pain). Respondents place a mark on the line that represents his or her
pain intensity level, and the distance measured from the
“no pain” end to the mark is that person’s VAS pain
score.
The VAS-I has consistently demonstrated sensitivity to
changes in cancer pain associated with treatment or time
(eg, Stambaugh and Sarajian, 1981; Anderson et al, 1991;
Sandouk et al, 1991; Moore et al, 1994; Ingham et al,
1996; Tannock et al, 1996; Talmi et al, 1997; Holland et al,
1998; Manfredi et al, 2000; Mercandante et al, 2000; Zeppetella, 2000) and usually shows strong associations with
other pain intensity ratings (Kremer et al, 1981; Walsh
and Leber, 1983; Ahles et al, 1984; Littman et al, 1985;
Wilkie et al, 1990; Gaston-Johansson et al, 1992; Grossman et al, 1992; Soh and Hui-Gek, 1992; Paice and Cohen,
1997; Sze et al, 1998; Ramer et al, 1999; Chang et al, 2000;
Klepstad et al, 2000). In only 2 studies did VAS-I correlate
less than .70 with other pain intensity ratings (eg, r ⫽ .29
to .56 with 0-10 Numerical Ratings scales reported by
Chang et al, 2000; r ⫽ .67 with a Verbal Rating Scale
reported by Fishman et al, 1987).
The VAS-I has also demonstrated criterion validity
through its associations with performance status (Hollen,
Gralla, Kris, and Cox, 1994; Chang et al, 2000), diagnosis
(cancer vs non-cancer, Padilla et al, 1983), setting (inpatients vs outpatients, Chang et al, 2000), measures of
psychological distress (Gaston-Johansson et al, 1992),
and measures of global quality of life (Coates et al, 1983;
but also see Hollen et al, 1994). VAS measures of pain
intensity have been shown to be distinct from VAS measures of pain unpleasantness, supporting the discriminative validity of both (Price et al, 1987). Change in pain
intensity, as measured by a change in the VAS-I score, has
been associated with both change in tumor status
(Coates et al, 1983) and with survival (Coates et al, 1992;
see also Coates et al, 1993).
Test-retest reliability of the VAS-I was examined in 4
studies, with time periods ranging from 5 minutes (r ⫽
.95; Grossman et al, 1992) to 1 week (r ⫽ .75; Chang et al,
2000). The average test-retest coefficient across these 4
studies (7 coefficients) was .80 (Padilla et al, 1983; Grossman et al, 1992; Hollen et al, 1993; Chang et al, 2000).
Despite support for the validity of the VAS-I demonstrated in the studies cited above, there is evidence that
VASs may be more difficult than other pain ratings for
patients to understand and to complete (see also comparison studies below). For example, Bruera et al (1991)
found that 16% of 101 palliative care patients were unable to complete a VAS-I, even with nurse assistance, and
that this number increased to 84% as disease progressed.
Numerical Rating Scale of Cancer Pain
Intensity
A Numerical Rating Scale of pain intensity (NRS-I) consists of a range of numbers (usually 0 to 10, but sometimes 0 to 100 or other ranges). Respondents are told
that the lowest number represents no pain and the highest number represents an extreme level of pain (eg, pain
5
as intense as you can imagine). They are asked to write
down, circle, or state the single number that best represents their level of pain intensity.
NRS-1 scales are used less often in research than VAS-1
scales. The findings of the research that has been performed supports the validity and reliability of NRS scales
and indicates that their psychometric properties are very
similar to those of VAS measures. For example, NRS-I
scales tend to show very strong associations with VAS-I
scales (Kremer et al, 1981; Wilkie et al, 1990; Paice and
Cohen, 1997; Sze et al, 1998) and Verbal Rating Scales of
intensity (Paice and Cohen, 1997). Only 2 studies have
shown associations less than .70; one was by Chang et al
(2000), which showed only moderate associations between NRS-I scales and a VAS-I, and the second was a
study that showed a correlation coefficient of .59 between a NRS-I and a Verbal Rating Scale of intensity (Kremer et al, 1981).
NRS-Is have also been shown to be sensitive to changes
(increases) in pain associated with radiotherapy (Trotti et
al, 1998) and physical therapy (Smith et al, 1998) and to
decreases associated with pain treatment (Farrar et al,
1998; Grond et al, 1999; Holzheimer et al, 1999; Leksowski, 2000; Wilkie et al, 2000; Meuser et al, 2001).
NRS-Is have demonstrated criterion-related validity
through their significant and positive associations with
analgesic medication use (Daut et al, 1983), perceived
need to contact health care providers (Sandbloom et al,
2001), pain interference (Daut et al, 1983; Owen et al,
2000), dyspnea (Smith et al, 2001), and a number of additional specific symptoms such as nausea, dry mouth,
dyspnea, lack of appetite, fatigue, and constipation
(Chang et al, 1999), and negative associations with treatment satisfaction (Lin, 2000) and measures of global
quality of life (Wang et al, 1999; Chang et al, 1999; Owen
et al, 2000; Poulos et al, 2001; Sandbloom et al, 2001).
Further support for the validity of 0-10 NRSs comes from
Portenoy, Payne, Coluzzi, et al (1999), who found that
the responses to this scale showed an appropriate dose
response to treatment with oral transmucosal fentanyl
citrate. In another study, a 0-10 NRS completed on one
occasion predicted subsequent decreases in functioning
among 93 persons with various cancer diagnoses (Dodd
et al, 2001).
De Wit et al (1999) showed that 86% of a sample of 156
patients with various cancer diagnoses were able to complete 2 months’ worth of daily diaries that included a
0-10 NRS. They found that patient ratings of average
pain provided during interviews every 2 weeks showed
strong associations with actual diary averages (r’s ranged
from .80 to .91), which provides some support for the
validity of retrospective ratings of average cancer pain.
However, patient retrospective ratings tended to be
higher by about 0.5 on the 0 to 10 scale, on average, than
their actual average pain intensity was (as calculated
from the diaries), calling into question the accuracy of
retrospective rating of past pain by using 0-10 NRSs.
Only one study examined the test-retest validity of
NRS-Is and found very good stability for NRS-I ratings of
worst pain (r ⫽ .93) and average pain (r ⫽ .78) but not for
6
current pain (r ⫽ .59) during about a 2-day period (Daut
et al, 1993). The coefficients were much lower (.34, .24,
and .22) when the time period was extended to about 91
days (Daut et al, 1993), although a high degree of stability in pain intensity ratings would not necessarily be expected during a 3-month period, because pain can
change over time.
Farrar et al (2000) performed a study that provides
important validity data concerning the meaning of
change in pain as defined by a 0-10 NRS. They operationalized a meaningful change in pain as that level of
change that is associated with a patient not requiring a
rescue dose as part of a titration phase of a clinical trial.
They found that an absolute change of 2 points (out of
10) and a percent change of 33% in the 0-10 NRS showed
the optimal sensitivity and specificity for detecting a
meaningful change in pain in a sample of 130 patients
with various cancer diagnoses. Although it will be important to replicate these findings in additional samples,
these data do support the utility of 0-10 NRSs in particular, because such guidelines are not yet available for
other measures of pain intensity (see below for their
findings concerning a 4-point VRS of pain relief).
Verbal Rating Scale of Cancer Pain Intensity
Verbal Rating Scales of pain intensity (VRS-I) consist of
a list of descriptors or phrases (eg, none, some, moderate, severe) that represent varying degrees of pain intensity. Each word or phrase has a number associated with it
(eg, none ⫽ 0, severe ⫽ 3). Respondents are asked to
select the single word or phrase that best represents his
or her pain level, and the respondent’s score is the number associated with the word chosen. In the cancer pain
literature, the number of descriptors in VRS-Is range
from 4 (eg, Bergman et al, 1994) to 8 (eg, Ingham et al,
1996). Like VAS-Is and NRS-Is, VRS-Is demonstrate sensitivity to changes in pain with treatment (Stambaugh and
Sarajian, 1981; Tannock et al, 1989; Bergman et al, 1992;
Bergman et al, 1994; Murphy et al, 1994; Ellershaw et al,
1995; Ingham et al, 1996; Tannock et al, 1996; Hammerlid
et al, 1997; Farrar et al, 1998; Rogers et al, 1998; Portenoy, Payne, Coluzzi, et al, 1999; Molenaar et al, 2001)
and show strong associations with other measures of
pain intensity (Walsh and Leber, 1983; Littman et al,
1985; Fishman et al, 1987; Paice and Cohen, 1997; Rogers
et al, 1998; Klepstad et al, 2000; but see Kremer et al,
1981, who found a correlation of only .59 between a VRS
and 0-10 NRS). VRS-I ratings have also been shown to be
associated with survival (Stockler et al, 1999; Tannock et
al, 1996), tumor size (Rogers et al, 1998), analgesic use
(Rogers et al, 1998), tumor stage (Rogers et al, 1999),
disease stage (Cliff and MacDonagh, 2000), and anxiety
about pain (Cliff and MacDonagh, 2000). Furthermore,
decreases in VRS-Is are associated with decreases in tumor size in response to chemotherapy (Bergman et al,
1992).
Only two studies examined the test-retest reliability of
VRS-Is. One found the VRS-I to be quite stable over a
matter of minutes (kappa ⫽ .71, Ellershaw et al, 1995),
and a second found the NRS-I to demonstrate relatively
Cancer Pain Assessment
low stability (r ⫽ .55, Sneeuw, Aaronson, Osoba, et al,
1997) during a 1-week period.
Other Single-Item Measures of Cancer Pain
Intensity
Single-item measures other than VAS-Is, NRS-Is, and
VRS-Is are used much less often to assess cancer pain
intensity. Measures that have been used include Mechanical Visual Analogue Scales, Graphic Rating Scales,
Faces Scales, a Finger Dynamometer, and various combination scales.
A Mechanical Visual Analogue Scale of pain intensity
(M-VAS-I) is very similar to the VAS-I, except that instead
of making a pencil or pen mark on a line on a paper, the
respondent moves a slider between the 2 extremes of
pain on a plastic or cardboard scale. The scale administrator then looks on the back of the scale and directly
reads the distance that the slider was moved from a ruler.
M-VAS-Is are very strongly associated with VAS-Is (r ⫽
.99, Grossman et al, 1992; r ⫽ .77, Ramer et al, 1999) and
other pain intensity ratings (Geddes et al, 1990; Ramer et
al, 1999). They are also highly reliable over a 5-minute
period (r ⫽ .95, Grossman et al, 1992). In short, they
appear to share many of the properties of VAS-Is.
Graphic Rating Scales of pain intensity (GRS-I) are also
similar to VAS-Is. The primary difference is that GRS-Is
add specific markers along the VAS continuum with labels associated with each marker. For example, the GRS-I
used by Greenwald et al (1987) consisted of a 100-mm
line with the numbers 1 through 5 evenly spaced along
the line and descriptors (no pain, slight pain, moderate
pain, very bad pain, pain as bad as can be) below each
number. Depending on the specific instructions, respondents to GRSs might circle the number or descriptor or
make a mark on the line (by using the numbers or descriptors as guidelines) that best represents their pain
intensity. Greenwald et al (1987) found the GRS-I they
used was associated with diagnosis (persons with pancreas cancer reported greater pain than those with lung,
prostate, and cervical cancer) and analgesic use. McMillan et al (1988) showed that a 0-10 GRS was sensitive to
decreases in pain that occurred when a pain monitoring
system in an inpatient cancer treatment center was established. No other study was identified that used GRS-Is
to assess pain in persons with cancer.
Face Scales of pain intensity present the respondent
with drawings of facial expressions representing increasing levels of pain intensity and suffering. Respondents
select the single drawing that best represents their pain
level, and their score is the number (rank order) of the
expression chosen. Two studies have used Face Scales
with patients with cancer. Ramer et al (1999) found the
Face Scale to show strong associations with other ratings
of pain intensity (eg, r ⫽ .82 between the Face Scale and
a VAS-I), and Shannon et al (1995) found that about 81%
of their sample with various cancer diagnoses were able
to complete the Face Scale (compared with 75% who
were able to complete a VAS-I and 89% a VRS-I). These
preliminary studies suggest that Face Scales could potentially be valid as measures of pain intensity. However,
CRITICAL REVIEW/Jensen
Ramer et al (1999) did comment that some of the male
patients in their study were uncomfortable with rating
their pain at the highest level by using the Face Scale
because the expression representing the most severe
level of pain had tears on the face of the drawing. This
raises the possibility that the Face Scale (or at least one
that includes tears) may underestimate pain intensity in
some patients with severe pain.
Wilkie et al (1990) examined the validity of a Finger
Dynamometer measure of pain intensity, with which respondents indicate their pain level by “squeezing as hard
as you hurt.” However, this measure was shown to be
only moderately associated with VAS-I and NRS-I measures (which were very strongly associated with one another), not supporting the Finger Dynamometer as a
measure of pain intensity.
Finally, different components of pain intensity measures can be combined into single scales (eg, combine
numbers with descriptors making a NRS/VRS-I, Grossman
et al, 1992; Campbell et al, 2000; Maunsell et al, 2000; or
a diagram with descriptors, Sneeuw et al, 1999; Sneeuw,
Aaronson, Sprangers, et al, 1997). The evidence from
studies looking at NRS/VRS-Is suggests that they, too, are
valid as measures of pain intensity, as shown by their
strong associations with other measures of pain intensity
(Grossman et al, 1992), association with analgesic use,
pain interference, and measures of global quality of life
(Maunsell et al, 2000), and association with treatment
history and concern about cancer (Campbell et al, 2000).
The two studies that used the diagram plus descriptor
measure of pain did so in the context of examining the
validity of proxy (clinician or caregiver) measures of patients’ pain, which is discussed in a separate section below.
Validity and Reliability of Multiple-Item
Ratings of Cancer Pain Intensity
By far the most frequently used multiple-item measure
of pain intensity in cancer research is the Pain Intensity
Scale of the Brief Pain Inventory (BPI).3 The BPI Pain Intensity Scale score is created by averaging four 0-10
NRS-Is (of current pain and worst, least, and average pain
during a specified period, usually the past week) into a
single pain intensity score. Six other composite pain intensity measures examined in this literature include (1) a
composite score made up of three 0-10 NRSs of average,
worst, and least pain (Cleary et al, 1995); (2) a 4-item Pain
Scale from the Rotterdam Symptom Checklist (de Haes et
al, 1990); (3) a 3-item Pain Scale from the EORTC QLQ-C36
(a precursor to the EORTC QLQ-C30, Sigurdartóttir et al,
1993); (4) a 4-item measure of pain in the mouth, jaw,
and throat area for patients with head and neck cancer
(Bjordal et al, 1994); (5) another 4-item measure of pain
to be used with patients with head and neck cancer (Terrell et al, 1997); and (6) a 3-item measure of pain associated with breast cancer (Stanton et al, 2001).
BPI Pain Intensity Scale
Four questions on the BPI ask respondents to rate their
current pain and past worst, least, and average pain on
7
0-10 NRS-Is, with “no pain” and “pain as bad as you can
imagine” as the descriptive end points. Most of the studies that have examined this measure in populations of
persons with cancer have used factor analyses to demonstrate that the BPI Intensity items load together onto a
single factor (Cleeland et al, 1988; Cleeland and Ryan,
1994; Caraceni et al, 1996; Wang et al, 1996; Uki et al,
1998; Ger et al, 1999; Radbruch et al, 1999; but see Saxena et al, 1999, for a finding that the worst pain item
loaded on both an intensity and an interference factor in
1 of 2 samples). These studies have also shown that the
scale is highly internally consistent, with coefficient alphas ranging from .78 to .97 in a variety of samples of
persons with cancer from many different countries (Serlin et al, 1995; Caraceni et al, 1996; Wang et al, 1996; Uki
et al, 1998; Radbruch et al, 1999; Saxena et al, 1999;
Mystakiou et al, 2001; Sandbloom et al, 2001). Research
comparing the psychometric properties of the BPI Pain
Intensity scale across cultures indicates that the BPI Pain
Intensity items are relatively free of cultural and linguistic bias (Serlin et al, 1995). The BPI Pain Intensity Scale has
also been shown to be associated with other measures of
pain intensity (McMillan et al, 2000), performance status
(Wang et al, 1996; Caraceni et al, 1999), pain interference
(Wang et al, 1996; Ger et al, 1999; Radbruch et al, 1999),
source of assessment (with physicians reporting lower
pain levels on the scale than patients did, Larue et al,
1995), and nationality (Vietnamese patients reported
higher pain levels than patients from the United States,
which was expected given that they were receiving
fewer analgesics, Cleeland et al, 1988). However, no
study was identified that examined the sensitivity of the
BPI Pain Intensity Scale to the effects of cancer pain treatment.
Other Multiple-Item Measures of Cancer Pain
Intensity
Clearly et al (1995) examined the psychometric properties of the Health-Related Quality of Life scale in a number of samples of men with advanced prostate cancer
(total, 487 subjects). This measure includes three 0-10
NRS ratings of average, worst, and least pain intensity.
The internal consistency coefficients (coefficient alphas)
of these 3 items ranged from .89 to .92 across samples,
and the composite pain intensity score made up of these
items was associated significantly with measures of a variety of quality of life dimensions such as emotional wellbeing (r ⫽ ⫺.40), social functioning (r ⫽ ⫺.48), and physical capacity (r ⫽ ⫺.58) among others (Clearly et al, 1995).
The Rotterdam Symptom Checklist asks respondents to
rate the intensity of sore muscles, low back pain, headache, and abdominal aches, among 30 other symptoms,
by using 0-3 Verbal Rating Scales. Factor analyses of the
responses to this scale showed a clear pain factor emerging in only 1 of 3 samples of patients with cancer (de Haes
et al, 1990). Although internal consistency (coefficient
alpha, .81) of a scale made up of these 4 items was good
in this 1 sample, the variability of the factor analysis findings suggests that multiple-item scales made up of items
8
representing pain in different sites may have limited reliability.
Sigurdardóttir et al (1993) examined the psychometric
properties of a 3-item cancer pain intensity measure
made up of a 1-4 NRS-I from the 36-item European Organization for Research and Treatment of Cancer Quality of Life Questionnaire for Cancer (EORTC QLQ-C36; a
precursor to the EORTC QLQ-C30, which has since been
used in many subsequent studies on quality of life
among persons with cancer), and two 1-4 NRS-I items
from a Malignant Melanoma assessment module that
assess pain intensity with movement and with rest. The
scale made up of these 3 items showed a good internal
consistency (alpha, .81), was moderately associated with
other measures of quality of life, and was associated significantly with types of metastases (superficial vs visceral)(Sigurdardóttir et al, 1993).
Bjordal et al (1994) describe the development of the
Head and Neck cancer questionnaire, which includes 4
items that assess pain (jaw pain, mouth pain, mouth soreness, throat pain). Although reliability and validity statistics were not presented in the original scale development study, they did detail the scale development
procedures and specifically interviewed head and neck
cancer specialists to identify issues relevant to patients
with head and neck cancer. These procedures support
the content validity of the measure. Hammerlid and Taft
(2000) subsequently showed that a scale made up of
these 4 items predicted survival in a sample of 135 patients with head and neck cancer. It has also shown appropriate associations with measures of different aspects
of quality of life, to have adequate internal consistency
(coefficient alpha, .72), and to have good test-retest stability (r ⫽ .72) during a 1-month period (Zotti et al, 2001).
Another multiple-item measure of pain associated
with head and neck cancer was described by Terrell et al
(1997). The Head and Neck Quality of Life Instrument
(HN QOL) they developed includes two 5-point VRSs of
the bothersomeness of mouth/jaw/throat pain and
shoulder/neck pain, a 5-point scale of frequency of pain
medication use, and a 5-point VRS of physical problems,
all combined into a single pain scale composite score. The
internal consistency (coefficient alpha) of this scale is adequate (alpha, .79), and its test-retest stability during a 5to 7-day period is high (r ⫽ .81). This measure was also
shown to be associated with physical and psychologic
functioning and with the 2-item SF-36 Bodily Pain scale
(r ⫽ .66), further supporting the validity of the measure.
A subsequent study provided further support for the HN
QOL Pain Scale by showing positive associations between
this scale and a rating of overall bothersomeness of pain
(r ⫽ .63) and a univariate association with employment
status (Terrell et al, 1999).
Stanton et al (2001) described a 3-item measure of
breast pain, shoulder stiffness, and breast sensitivity and
showed that it was internally consistent (Cronbach alpha, .81) and associated significantly with quality of life,
depressive symptoms, and fear of disease. In a subsequent study, this measure was not shown to be associ-
Cancer Pain Assessment
ated significantly with cosmetic outcomes or arm edema
(Krishnan et al, 2001).
Validity and Reliability of Measures of
Cancer Pain Interference
Pain interference refers to the extent to which pain
interferes with day-to-day functioning. The most common measure of cancer pain interference is the Brief Pain
Inventory Pain Interference Scale.3 This scale consists of 7
items that ask respondents to indicate the extent to
which pain interferes with general activity, mood, walking ability, normal work, relations with other people,
sleep, and enjoyment of life on 0-10 NRSs, with 0 ⫽ Does
not interfere and 10 ⫽ Completely interferes. The responses to the 7 items are averaged to form the Pain
Interference Scale score.
Factor analyses of responses show that the 7 interference items load together onto a single factor (Cleeland
et al, 1988; Cleeland and Ryan, 1994; Caraceni et al, 1996;
Wang et al, 1996; Uki et al, 1998; Ger et al, 1999; Radbruch et al, 1999; Saxena et al, 1999; Mystakidou et al,
2001) and that the scale has excellent internal consistency (with alphas ranging from .78 to .91; Serlin et al,
1995; Caraceni et al, 1996; Wang et al, 1996; Radbruch et
al, 1999; Saxena et al, 1999; Mystakidou et al, 2001). One
study used multidimensional scaling to determine the
factors underlying the BPI Pain Interference items in a
large sample of 1843 persons with metastatic cancer
(Cleeland et al, 1996). These analyses yielded 2 underlying interference dimensions: interference with activity
(walking, work, general activity, sleep) and affectivityrelated interference (relations, mood, enjoyment of life),
suggesting the possibility of alternate scoring and use of
the BPI Pain Interference Scale. However, this alternate
scoring has yet to be used or tested in additional samples
of persons with cancer. The BPI Pain Interference Scale is
associated, as would be expected, with measures of pain
intensity (Daut et al, 1983; Ger et al, 1999; McMillan et al,
2000). However, there has yet to be an examination of
the ability of this scale to detect changes in pain interference associated with cancer pain treatment.
Another multiple-item pain interference measure was
described by Ripamonti et al (2000). They performed a
factor analysis on 2 VRSs of pain intensity (at rest and
with movement), VRSs of pain’s effects on sleep, depression, nervousness, and concentration, and a number of
additional ratings such as the perceived cause of pain,
use of analgesic medications, and relief provided by analgesic medications. The 4 VRSs of pain impact/interference loaded together on a single factor, whereas the 2
intensity ratings did not. The 4 pain interference items
had an adequate internal consistency (alpha coefficient,
.73), and a scale score made up of an average of these
items was significantly associated with pain relief.
Maunsell et al (2000) asked 98 patients with various
cancer diagnoses to complete a pain diary on a daily basis
that also included a 5-item measure of pain interference.
The internal consistency of this scale was large (range,
.87 to .92; average, .91 across the 4 weeks of data collec-
CRITICAL REVIEW/Jensen
tion), and the measure was associated with pain intensity
ratings, number of analgesic rescue doses received, and a
variety of dimensions of quality of life.
Finally, a number of single-item ratings of pain interference have been examined in this literature. A quality
of life measure used in some cancer research, the Functional Living Index, Cancer Scale (FLIC) includes a 1-7 GRS
asking about the extent to which pain disrupts activity.
This item loaded on a physical well-being factor in a
factor analysis of the FLIC, providing further support for
the association between pain interference and overall
quality of life (King et al, 1996). Daut and Cleeland (1982)
examined 2 of the NRS interference items from the BPI
(activity and enjoyment of life) and showed that the association between pain intensity and pain interference,
as measured by these items, is nonlinear. A change in
worst pain intensity from a 4 (out of 10) to a 5 is associated with a larger increase in interference than any other
change in pain intensity. Ferrans and Ferrell (1990) found
that a 1 (not at all) to 7 (a great deal) NRS of pain interference was associated with a measure of global quality
of life, and another 7-point NRS of pain interference
tended to load more strongly with measures of physical
disability than with measures of pain intensity, supporting an important linkage between pain interference and
disability, as well as a distinction between pain interference and pain intensity (King et al, 1996).
Klee et al (1997) administered a cancer-specific quality
of life measure that includes a 4-point VRS of pain interference to 1041 women with breast or gynecologic cancer. They found that women with gynecologic cancer
reported greater pain interference with this measure
than women with breast cancer did. In addition, because
a 4-point VRS of pain intensity did not discriminate these
2 diagnostic groups, the findings provide further support
that pain intensity and pain interference are distinct dimensions of pain.
Validity and Reliability of Measures of
Cancer Pain Relief
Whereas pain intensity ratings ask patients to rate the
intensity of felt pain, pain relief ratings ask patients to
rate how much relief from pain they have experienced,
usually in reference to a specific treatment or intervention. Relief ratings have been shown to be sensitive to
the effects of treatment (VAS relief ratings: Wallenstein,
1991; Shannon et al, 1995; Manfredi et al, 2000; VRS
relief ratings: Stambaugh and Saragian, 1981; Littman et
al, 1985; Wallenstein, 1991). Also, in one study, relief
ratings were strongly and negatively associated with
pain intensity ratings (VAS relief rating, Fishman et al,
1987). However, in two other studies, the associations
between pain relief and pain intensity measures were
weak (VAS rating, Ramer et al, 1999; NRS rating, Daut
and Cleeland, 1982).
Supporting the validity of relief ratings as measures of
change in pain intensity, some studies have shown positive associations between pain intensity change scores
and relief ratings (VAS, Angst et al, 1999; NRS, De Conno
9
et al, 1994). Interestingly, however, the association between pain relief and change in pain intensity is not
always strong, so ratings of these 2 constructs (change in
pain, pain relief) appear to measure related but also distinct constructs. For example, Angst et al (1999) found
that when pain intensity and pain relief were assessed
10, 20, and 30 minutes after an infusion (pain intensity
was also assessed preinfusion), pain relief ratings tended
to increase as pain intensity decreased. However, for
many patients, pain relief ratings remained above 0 (indicating at least some relief) even when pain intensity
returned to preinfusion levels. Similarly, de Wit et al
(1999) demonstrated the distinction of a VRS rating of
pain relief from pain intensity by performing a factor
analysis of pain intensity ratings, a VRS rating of pain
relief, and other measures. They found that the pain
relief rating loaded with measures of treatment satisfaction and perceived adequacy of analgesia, but not with
the pain intensity ratings.
The findings of Farrar et al (2000) concerning the
meaningfulness of change in pain as measured by a
change in a 0-10 NRS were described above. These investigators also identified the specific rating of relief (with a
5-point VRS-R scale: none, slight, moderate, lots, complete) best associated with a meaningful change in pain.
They found that the rating of moderate relief best represented meaningful change to the participants with
cancer pain in their study, supporting this rating as a
reasonable treatment outcome goal.
Validity and Reliability of Measures of
Cancer Pain Site
There are 2 common methods to assess pain site in pain
research, a pain drawing and a pain site checklist. A pain
drawing consists of an outline drawing of a human body,
and respondents are asked to indicate on the drawing,
usually by shading appropriate areas, the specific sites of
pain or other sensations. Pain drawings can be coded by
placing a transparency template over the drawing and
coding whether the respondent shaded in specific areas.18 Site checklists simply ask respondents to indicate in
which of a list of possible sites (eg, head, neck, back,
arms) they experience pain. To date, only pain drawings
have been used in cancer pain research.
Zimmerman et al (1987) reported a “close correspondence” between patient-completed pain drawings and
the anatomic locations of disease in a sample of 40 persons with various cancer diagnoses, although no statistical test of this correspondence was reported. Wilkie et al
(1992) found that the number of pain sites was associated with pain intensity in a sample of 45 patients with
lung cancer. However, other than a single additional
study that examined the association between patient
and nurse reports of pain site (discussed in the section on
proxy measures of pain), no other study was identified
that presented data concerning the psychometric properties of pain drawings in persons with cancer.
10
Validity and Reliability of Measures of
the Temporal Aspects of Cancer Pain
The temporal aspects of pain, such as its variability,
frequency, and duration, as well as its pattern across time
(over minutes, hours, days, or months) can be assessed by
asking patients to rate their pain on multiple occasions
over time. For example, Maunsell et al (2000) asked 98
patients with various cancer diagnoses to complete daily
pain diaries with which they rated pain intensity and
pain interference. They found that 86% of the subjects
completed 1 week of diaries and that, of these, 90%,
84%, and 74% completed diaries in weeks 2, 3, and 4,
respectively. Thus, they demonstrated in 1 sample of patients that the majority of patients were willing to complete daily pain diaries (see also de Wit et al, 1999). Data
from such diaries can be coded to score many of the
temporal aspects of pain listed above. Variability can be
operationalized as the standard deviation of daily pain
intensity ratings, frequency as the number of times pain
intensity is above specific thresholds (eg, number of
times pain intensity is greater than 0 or even greater
than some level indicating moderate or severe pain24),
and average duration as the average amount of time
patients experience pain levels above specific cutoffs.
Specific time patterns of pain within or across days can
also be coded from these data (eg, no change over time,
increases or decreasing over time14). However, not every
clinician or researcher has the resources to be able to
administer and code diary data, and not all patients will
comply with requests for daily diary data. A more efficient way to assess pain frequency, duration, and variability, providing that research demonstrates patients
are able to provide accurate responses, is to ask patients
to recall and rate these temporal aspects of their pain
experience.
One temporal pain dimension assessed in the articles
reviewed for this article was the frequency of pain. Kaasa
et al (1995) used a 5-point VRS to measure the frequency
of pain that ranged from “All day” to “Not at all.” They
found that responses to this measure were strongly associated with a composite measure of pain intensity and
pain interference as measured by the QLQ-C30 Pain
Scale. Rathmell et al (1991) asked patients with head or
neck cancer to rate the frequency of their pain on 4-point
VRS with 1 ⫽ Never and 4 ⫽ Daily. Pain frequency, but
not pain intensity (also measured by a 4-point VRS-I), was
associated with type of treatment received, with patients who received both radiation and surgery reporting
greater pain frequency than those who received radiation alone. Samarel et al (1996) showed that a combination 5-point NRS/VRS of pain frequency (1 ⫽ Never to 5 ⫽
Always) loaded with measures of pain intensity and pain
upsetness into a single scale. This scale was subsequently
found to be significantly associated with other symptoms, such as fatigue, and with treatments received (chemotherapy vs no treatments). These preliminary findings
indicate that pain frequency is both related to, but also
might be distinct from, measures of pain intensity.
Portenoy, Payne, and Jacobsen (1999) defined break-
Cancer Pain Assessment
through pain as an episode of severe or excruciating pain
that occurs in the context of an ongoing (more that half
of the time during waking) background pain. They
found that the presence of breakthrough pain was associated with other important pain-related variables such
as average intensity of background pain, pain interference, and measures of both depression and anxiety.
Other than these 4 studies and despite the preliminary
indications that pain frequency or variability may be important determinants of pain’s impact on function and
quality of life, no other studies were identified that examined the validity or reliability of measures of the temporal aspects of cancer pain.
Validity and Reliability of Measures of
the Qualitative and Affective
Components of Cancer Pain
Pain has many sensory and affective qualities in addition to its intensity component. The most common measure of these aspects of pain in persons with cancer is the
McGill Pain Questionnaire, but the short-form McGill
Pain Questionnaire and single-item ratings have also
been used.
McGill Pain Questionnaire (MPQ)
The MPQ consists of 78 pain descriptors classified into
20 categories of pain that can be scored to assess 4 major
dimensions of pain: sensory, affective, evaluative, and
miscellaneous pain, as well as a total pain severity
score.20 Data support the conclusion that the MPQ qualitative scale scores assess something other than pain intensity. For example, Chung et al (2001) found very low
associations between a pain intensity rating and both
the MPQ-NWC (r ⫽ ⫺.09) and MPQ-PRI (r ⫽ .00). Other
investigators have found stronger associations between
MPQ scales and pain intensity ratings (Ahles et al, 1984,
r’s range from .49 to .57; Graham et al, 1980, r’s up to .40,
lowest r value not specified; Wilkie et al, 1992, r’s up to
.58, lowest r value not specified; see also Kremer et al,
1982). Although these associations are usually positive,
indicating that the MPQ scales and pain intensity assess
related dimensions, they are not strong enough to support the conclusion that MPQ scales and pain intensity
rating scales assess the same thing.
Further evidence for a distinction between the MPQ
scale scores and pain intensity ratings was found by De
Conno et al (1994). They performed 2 factor analyses
using a VAS-I, an NRS-I, a VRS-I, the MPQ-PRI score, and a
composite measure of the frequency of 5 different qualities of pain obtained at 2 different points in time in 53
patients with various cancer diagnoses. A single factor
emerged from each factor analysis, with the 3 pain intensity measures loading most strongly on this factor
(factor loadings ranged from .79 to .92) and the MPQ-PRI
showing a weak loading in one analysis (.39) and a stronger loading in the second (.72). Similarly, a factor analysis
of change scores in these measures from one time point
to the next, plus a 5-point rating of pain relief, resulted
in a single factor, with the pain intensity change scores
CRITICAL REVIEW/Jensen
showing stronger loadings (range, .80 to .83) and the
MPQ-PRI score showing a weaker loading (.47) on this
factor (De Conno et al, 1994).
The MPQ scales have been found to be positively associated with analgesic medication use (Ahles et al, 1983),
illness conviction (Dalton et al, 1988), quality of life
(Schipper et al, 1984), and the MPQ-Total score has been
shown to be sensitive to the effects of prednisone on
prostate cancer pain (Tannock et al, 1989), supporting
the validity of the MPQ scales as measures of pain. Support for the validity of the MPQ-Affective scale to assess
the affective component of pain specifically was reported by Ahles et al (1983), who found that this scale
was more strongly associated with measures of psychologic distress than with measures of pain intensity. Also,
Kremer et al (1982) reported that cancer patients with
low pain intensity report a greater affective component
of their pain on the MPQ-Affective scale than patients
with low back pain do, consistent with the hypothesis
that cancer pain may have greater affective associations
(eg, be more worrisome and cause more fear) than low
back pain.
Only two studies have examined the reliability of the
MPQ in patients with cancer. Both studies found that
patients with cancer are generally consistent in the MPQ
words they use to describe their pain from 1 week to the
next (Graham et al, 1980; Walsh and Leber, 1983). Concerning utility, one study found the MPQ to be difficult
for most persons with terminal cancer receiving palliative care to use (Talmi et al, 1997). However, a second
study found that 84% of a sample of patients with cancer
were able to complete the MPQ (Shannon et al, 1995).
Short-Form McGill Pain Questionnaire
(SF-MPQ)
The SF-MPQ consists of a subset of 15 descriptors from
the MPQ drawn from the sensory and affective categories.21 Responses to the 15 SF-MPQ items can be scored to
form a total SF-MPQ score as well as both Sensory and
Affect SF-MPQ subscale scores.21 Only one study has examined the psychometric properties of the SF-MPQ in
persons with cancer. Hollen, Gralla, Kris, Cox, Belani, et al
(1994) administered the SF-MPQ to 207 patients with
lung cancer and found that the 15 SF-MPQ items were
highly internally consistent (coefficient alpha, .91) and
that the 2 SF-MPQ subscales were strongly associated
with one another. This latter finding suggests the possibility that the 2 SF-MPQ scale scores may tap into a similar underlying construct.
Other Measures of Pain Affect
Ahles et al (1984) asked 37 patients with various cancer
diagnoses to rate the affective component of pain 4
times/day for 7 days by using a VRS of affective pain
descriptors (VRS descriptors compiled by Tursky et al30).
The study participants were also administered 2 measures of pain intensity (a VAS-I and an NRS-I). Although
the 2 intensity measures were strongly associated with
one another, the VAS-I showed only a weak to moderate
association (r ⫽ .30) with the VRS-Affective rating, sug-
11
gesting support for the conclusion that these measures
are tapping into different components of pain.
On the other hand, a different VRS of pain affect
showed a very strong association with a mechanical VAS
among 17 patients with Hodgkins’ lymphoma (r ⫽ .91;
Gaston-Johansson et al, 1992). In this same study, the
pain affect VRS showed associations with a number of
criterion measures that were very similar to those shown
by both a mechanical VAS and a VRS of pain intensity
(Gaston-Johansson et al, 1992). The low number of subjects in this study may have been at least partially responsible for the strong association found between the VRS
of pain affect and the measures of pain intensity used.
Spiegel et al (1983) administered a 0-10 NRS of pain
intensity and a 0-10 NRS of pain suffering to 86 women
with breast cancer. They found that the 2 NRS scales were
very strongly associated with one another (r ⫽ .81). They
also found that the NRS of pain affect was significantly
associated with measures of maladaptive coping, emotional distress, and use of analgesics. Smith et al (1998)
also administered 0-10 scales of pain intensity and pain
affect (0 ⫽ Not unpleasant at all, 10 ⫽ As unpleasant as
you can imagine) to 32 patients with various cancer diagnoses and found that physical therapy increased the
intensity rating but not the unpleasantness rating of
pain. Such a finding supports the distinction between
pain intensity and pain unpleasantness, even though
measures of these 2 dimensions of pain may be strongly
associated with one another.12
Finally, Price et al (1987) examined the ability of a VAS
of pain intensity and pain affect to distinguish between
different diagnostic groups. They found that a sample of
patients with cancer (and patients with low back pain
and causalgia) showed a significantly larger difference
between the intensity and unpleasantness ratings than
patients with upper back pain, myofascial pain, labor
pain, or orofacial pain did. This further supports the distinction between the affective and intensity components
of pain and the ability of the VAS to assess each pain
component separately.
Validity and Reliability of Composite
Scores of Pain Intensity and Pain
Interference
Although pain intensity and pain interference are distinct dimensions of cancer pain, 2 commonly used measures of quality of life that have been used in samples of
patients with cancer, the EOTC QLQ-C30 and the SF-36,
combine individual ratings of each of these dimensions
into single composite pain scales.
European Organization for Research and
Treatment of Cancer Quality of Life
Questionnaire for Cancer (EORTC QLQ-C30)
The EORTC QLQ-C30 is a 30-item measure developed to
assess multiple dimensions of quality of life in persons
with cancer.1 In addition to assessing 6 domains of quality of life, the QLQ-C30 assesses 7 symptom domains,
including pain. The Pain symptom scale contains two
12
4-point VRSs that assess pain intensity and pain interference, which are averaged and then transformed into a 0
to 100 scale of pain severity.
The QLQ-C30 Pain Scale usually demonstrates adequate to excellent internal consistency (alpha coefficients range from .70 to .89) across a great variety of
patients with cancer (Aaronson et al, 1993; Bergman et
al, 1994; Bjordal and Kassa, 1992; Fosså, 1994; Osoba et
al, 1994; Ringdal and Ringdal, 1993; Wisløff et al, 1996;
Sneeuw et al, 1998; Fosså, 2000), although one study in
120 patients with various cancer diagnoses showed marginal internal consistencies at 2 time points (alphas, .57
and .56; Kyriaki et al, 2001). Also, among a sample of 103
patients with brain cancer, the internal consistency of
the QLQ-C30 Pain Scale appears to be reduced (alpha
coefficient, .59) as is test-retest stability over a 1-week
period (r ⫽ .44; Sneeuw, Aaronson, Osoba, et al, 1997).
However, Hjermstad et al (1995) found the QLQ-C30 Pain
Scale to have excellent test-retest stability (r ⫽ .86) over a
4-day period among 190 patients with various cancer
diagnoses (Hjermstad et al, 1995).
The QLQ-C30 Pain Scale has demonstrated appropriate
associations with various criterion measures, including
other dimensions of quality of life (Aaronson et al, 1993;
Bjordal and Kassa, 1992; Bjordal et al, 1999; Fosså, 1994;
Kassa et al, 1995; King et al, 1996; Kramer et al, 2000;
Osoba et al, 1994; Ringdal and Ringdal, 1993; Rogers et
al, 2000; Stockler et al, 1999), dispositional optimism (Allison et al, 2000), functional status (Aaronson et al, 1993;
Stockler et al, 1999; Jordhøy et al, 2001), disease stage
(Wisløff et al, 1996; Bjordal et al, 1999), clinical severity of
cancer (King et al, 1996), survival (Kramer et al, 2000;
Stockler et al, 1999; Camilleri-Brennan and Steele, 2001;
Jordhøy et al, 2001), prognosis (Ringdal et al, 1994), presence of metastases (Osoba et al, 1994), performance status (Osoba et al, 1994), change in disease status (Wisløff
et al, 1996), tumor size (Rogers, Lowe, et al, 1998), treatment received (patients who received esophagectomy
reported less pain than those who received palliative
care, Blazeby et al, 1995), and tumor response (Geels et
al, 2000). This measure predicts cancer diagnosis (patients with oral cancer report greater levels of pain than
patients with other cancer diagnoses, Bjordal et al, 1999)
and has demonstrated sensitivity to change in pain over
time and with treatment (Bjordal et al, 1999; Hammerlid
et al, 1997; Rogers, Lowe, et al, 1998; Ilson et al, 1999;
Roszkovski et al, 2000; Camilleri-Brennan and Steele,
2001; Fosså et al, 2000; Fosså et al, 2001; Kyriaki et al,
2001). The QLQ-C30 has also shown appropriate associations with patient ratings of global change in pain
(Sneeuw et al, 1998).
The QLQ-C30 Pain Scale has shown a sensitivity to differences in outcome with treatment (Tannock et al,
1996; Moore et al, 1994; Klepstad et al, 2000; Langendijk
et al, 2001) and to increases in pain caused by interferon
(Wisløff and Gulbrandsen, 2000). As would be expected,
the QLQ-C30 Pain Scale is associated with measures of
pain intensity (mostly in the .40 to .61 range, Bjordal et
al, 1999; Geddes et al, 1990; Stockler et al, 1999; Klepstad
et al, 2000; but see Kaasa et al, 1995, for a study describ-
Cancer Pain Assessment
ing stronger associations of rs ⫽ .71 to .85). The strength
of these associations is not generally as strong as those
typically seen between measures of the pain intensity
ratings, supporting the conclusion the QLQ-C30 Pain
scale is not necessarily a valid measure of pain intensity.
On the other hand, one study found the association between the QLQ-C30 Pain Scale and the SF-36 Bodily Pain
Scale (which is also a composite measure of pain intensity
and pain interference) to be very strong (r ⫽ .83; Rogers,
Lowe, et al, 1998), supporting the validity of both scales
as composite measures of pain intensity and pain interference.
SF-36 Bodily Pain Scale
The second composite measure of pain intensity and
pain interference that has been used with patients with
cancer (although less so than the QLQ-C30) is the Bodily
Pain Scale of the SF-36.31 The SF-36 is a measure of various quality of life dimensions and contains a pain intensity item and a pain interference item that are combined
into a single composite Bodily Pain score.
In support of the criterion validity of the SF-36 Bodily
Pain scale, Broeckel et al (2000) showed that cancer patients who had been successfully treated with chemotherapy (ie, they did not have current evidence of disease) reported higher levels of pain on the SF-36 Bodily
Pain scale than a noncancer control sample did. As with
the QLQ-C30 Pain Scale, the SF-36 Bodily Pain scale has
shown variable but rarely strong associations with measures of pain intensity, suggesting that the SF-36 Bodily
Pain scale is not a highly valid measure of pain intensity
alone (r ⫽ .59, Radbruch et al, 1999; r ⫽ ⫺.16, GastonJohansson et al, 1999). The SF-36 has shown significant
associations with measures of global quality of life (Rogers, Humphris, et al, 1998; Rogers et al, 2000), tumor
stage (Rogers, Humphris, et al, 1998), survival (CamilleriBrennan and Steele, 2001), and tumor size (Rogers,
Lowe, et al, 1998).
In one study examining the sensitivity of the SF-36
Bodily Pain Scale for detecting the differences between
fluoxetine versus desipramine in the treatment of
women with various cancer diagnoses, the investigators
found that a VAS-I, but not the SF-36 Bodily Pain Scale,
was sensitive to differences between the treatment conditions (Holland et al, 1998). Such a finding is consistent
with the conclusion that a composite score of pain intensity and pain interference is somewhat distinct from
measures of pain intensity alone and that the SF-36
Bodily Pain scale may be less sensitive than measures of
pain intensity to treatment effects (see below for more
detailed review of studies that compare different cancer
pain measures on sensitivity to treatment effects). Another study found that the SF-36 Bodily Pain scale was
sensitive to changes in pain from before to after surgery
for oral or oropharyngeal cancer (Rogers, Lowe, et al,
1998). A third study showed the SF-36 to be sensitive to
change in pain after mesorectal excision in 70 persons
with rectal cancer (Camilleri-Brennan and Steele, 2001).
These latter studies indicate that the SF-36 Pain Scale is
CRITICAL REVIEW/Jensen
able to detect changes in pain related to treatments on
some occasions.
Validity and Reliability of a Composite
Measure of Pain Experience and Pain
Cognitions
Arathuzik (1994) describes the development of the
Pain Inventory, a 38-item scale that includes items assessing a variety of cancer pain dimensions such as the temporal aspects of pain, pain quality, pain intensity, pain
distress, pain interference, and pain-related cognitions.
A primary strength of this measure was that its development included procedures for examining and then increasing the content validity of the items through an
initial review of potential items by 40 nurses for their
relevance to pain assessment. As a result of the review
and based on feedback from the nurse experts, 13 items
were subsequently either clarified or added to the measure.
The Pain Inventory was shown to have good split-half
reliability (r ⫽ .85) and internal consistency (Cronbach’s
alpha ⫽ .84) in 2 samples of women with breast cancer
(Arathuzik, 1994). Also, the total Pain Inventory score
was significantly and positively associated with pain intensity (r ⫽ .37), pain distress (r ⫽ .61), and negatively
with use of pain coping strategies (r ⫽ ⫺.22). Unfortunately, however, by combining so many pain dimensions
(eg, pain quality, pain intensity, distress, pain interference, cognitions) into a single scale score, the meaning of
the total score is obscured. Also, the measure has yet to
be used in any other study. However, the domains of
pain identified by the author do support the importance
of considering a variety of pain dimensions when developing assessment protocols and provide some guidance
concerning those cancer pain dimensions deemed most
important by the experts surveyed in this study.
Results Concerning Proxy Measures of
Cancer Pain
A line of research on cancer pain assessment concerns
the extent to which persons other than the patient, such
as family members, caregivers, or clinicians, are accurate
in their estimates of patient pain. Research on the validity of proxy measures is important to consider in this
review because they provide a potential source of pain
assessment if patients are unable to provide pain ratings.
Geddes et al (1990) asked 53 patients with lung cancer
and their nurses to rate patient pain (among other symptoms) by using a 4-point VRS/NRS in the context of a
randomized controlled trial. They found strong agreement between the 2 sources of data (kappa ⫽ .76, percent complete agreement ⫽ 71%). Hollen et al (1993)
reported that correlation coefficient between a patientrated VAS-I and a clinician-rated VAS-I in 52 patients with
lung cancer was “greater than .75.” Strömgren and colleagues also reported a high concordance rate between
patient self-report of pain by using the QLQ-C30 and
physician notes (Strömgren, Groenvold, Perdersen, et al,
13
2001) and between patient report and nurse records on
the presence of pain in the medical record of patients
with various cancer diagnoses (Strömgren, Groenvold,
Sorensen, et al, 2001; see also Velikova et al, 2001).
On the other hand, Grossman et al (1991) found much
weaker associations between patient and clinician
(nurse, house officer, or medical oncology fellow) ratings
of pain by using a VAS-I (r’s ⫽ .35 to .46). Sneeuw, Aaronson, Osoba, et al (1997) also found only weak to moderate associations between patient-rated composite scores
of pain intensity and pain interference (with the QLQC30 Pain Scale; r ⫽ .23) and headache (with a 4-point VRS
of headache; r ⫽ .57) and scores from a “significant
other” in a sample of 103 patients with brain cancer.
In a similar study with 307 patients with various cancer
diagnoses, Sneeuw et al (1998) found a fairly strong (r ⫽
.63) association between patient and significant other
composite scores from ratings of pain intensity and interference (with the QLQ-C30 Pain Scale), with significant others tending to overestimate patient pain on average. In a third study, these investigators found similar
associations between patient and proxy measures of
pain intensity between patients and a caregiver (often
the spouse; r ⫽ .53 and .71 at 2 assessment points) and
between patients and physicians (r ⫽ .64 and .72 at 2
assessment points; Sneeuw, Aaronson, Sprangers, et al,
1997). Physicians tended to rate patient pain as significantly lower and caregivers tended to rate patient pain
as significantly higher than patients did. These findings
were mostly replicated in a fourth study, with the associations between patient and significant other, patient
and physician, and patient and nurse ratings all between
.50 and .66 (Sneeuw et al, 1999). In this later study, significant others also tended to overestimate patient pain
and physicians underestimate patient pain, although
nurse ratings were not significantly different than patient ratings.
Cliff and MacDonagh (2000) found that significant others overestimated patient pain intensity in a sample of
164 men with prostate cancer. Deschler et al (1999) also
found that caregivers tended to overestimate patient
pain by using the SF-36 Bodily Pain scale, although
spouses provided more accurate estimates than nonspouse caregivers. Wilson et al (2000) also found that
partners provide more accurate estimates of patient pain
than physicians did in a sample of men with prostate
cancer (by using the QLQ-C30), but the associations between patient and proxy measures were not that large
(partner, r ⫽ .47; physician, r ⫽ .17). Moreover, these
associations were weak for both partners (r ⫽ .16) and
physicians (r ⫽ .29) in a separate sample of women with
breast cancer (Wilson et al, 2000). In both samples, physicians overestimated pain, on average, whereas partners only overestimated pain in the sample of patients
with breast cancer.
Nekolaichuk, Bruera, et al (1999) found that physicians
underestimated patient pain (with a VAS-I), as did
nurses, although the difference between nurse and patient ratings was not statistically significant. The associations between patient and nurse, and patient and phy-
14
sician ratings were not very strong (range, .40 to .62).
Similarly, Larue et al (1995) found that, across 20 different treatment centers, physicians tended to underestimate patient pain (with 0-10 NRSs). In a study designed
to examine the factors that contribute to patient pain
scores in 32 patients with advanced various cancers,
Nekolaichuk, Maguire, et al (1999) found a high level of
variability between patient, nurse, and family caregiver
ratings of pain by using the VAS-I. Hovi et al (1999) found
no significant differences, on average, between patient
and nurse VAS-I ratings of patient current and least pain,
but nurses significantly underestimated patient worst
and acceptable pain.
On the MPQ,20 patients used more words to describe
their pain, and on a pain drawing, patients described
more pain locations, than nurses did (Hovi and Lauri,
1999). Madison and Wilkie (1995) administered the MPQ,
a pain drawing, and a VAS-I to 18 patients with lung
cancer and a family member or friend. Although the low
number of subjects in this study makes definitive conclusions difficult, they found only a weak association between the 2 sources of data in number of pain sites
(rho ⫽ .26), and that patients reported more sites. The
VAS-Is showed only a moderate association between the
2 sources (rho ⫽ .50 and .48 at 2 assessment points), and
the specific MPQ subscales showed only weak to moderate associations (rhos ⫽ .10 to .42).
Miaskowski et al (1997) found that only 29% of family
members provided ratings of patient pain (on a VAS-I)
that were congruent (within ⫾ 10 mm on a 100-mm VAS)
with the patient ratings. In a preliminary study examining the effects of patient coaching on cancer pain assessment, Wilkie et al (1995) found that patient coaching
improved the congruence between patient and nurse
ratings and descriptions of patient pain. However, even
with coaching, they found a high level of discordance
between patient and nurse VAS ratings.
Results of Cancer Pain Measure
Comparison Studies
Although information concerning the psychometric
properties of cancer pain measures can be obtained
when only a single measure is used in a study, more
useful information can be obtained from studies that use
more than 1 measure. By administering 2 or more measures of pain in the same study and with the same population, it is possible to directly compare their psychometric properties without having to be as concerned
about possible confounds due to differences between
studies (eg, differences in samples and procedures) that
can impact the estimates of a measure’s validity and reliability.
Unfortunately, only a few studies provide such comparison data. The validity criterion most often compared
in such studies is that of sensitivity to change with time or
with treatment. In these studies, sensitivity is usually operationalized as a statistic that reflects the effect size for
detecting a change in pain (eg, pretreatment to posttreatment) or a difference between treatment and con-
Cancer Pain Assessment
trol conditions. Relevant statistics include the t statistic,
the F statistic, the P value associated with these statistics,
or some measure of change divided by a measure of
variance (eg, lambda). Larger t and F statistics and
smaller P or lambda values indicate greater sensitivity.
Wallenstein (1991) performed a reanalysis of 11 random controlled trials (RCTs) of analgesics for cancer (2
RCTs) and postoperative (9 RCTs) pain that had samples
ranging from 40 to 339 (total number of subjects across
all trials, 1863; total number with cancer, 347). In both
samples of patients with cancer, VAS measures of pain
relief were more sensitive to detecting treatment effects
than VRS measures of pain relief were. Stockler et al
(1998) compared the relative sensitivity of a VAS-I, a
6-point VRS-I, and the QLQ-C30 Pain Scale for differentiating the effects of palliative chemotherapy with intravenous mitoxantrone plus oral prednisone versus oral
prednisone alone in 143 men with prostate cancer. They
found that all 3 measures were able to detect the beneficial effects of palliative chemotherapy, although the
VAS-I was more sensitive that the other 2 measures, and
the QLQ-C30 was more sensitive than the VRS-I.
Gaston-Johansson et al (1992) administered a 15-item
measure of sensory pain (consisting of words that describe a variety of pain sensations such as sharp, dull, and
sore), a mechanical VAS of pain intensity, and an 11-item
measure of pain affect (consisting of 11 descriptors such
as annoying, nagging, and miserable) to 17 patients with
Hodgkins’ lymphoma. These scales were administered
before and then on 3 occasions after undergoing autologous bone marrow transplantation. They found the
VAS-I to be slightly more sensitive to changes in pain
than either the measure of sensory or affective pain,
although the low N of this study limits the confidence
that can be placed on the findings. Holland et al (1998)
administered a VAS of pain intensity, a VAS of pain relief,
an 8-point VRS of pain intensity, and the SF-36 Pain Scale
to 38 patients with a variety of cancer diagnoses before
and after 6 weeks of either fluoxetine or desipramine to
treat depression. Only the VAS-I showed significant effects of fluoxetine on pain. Moore et al (1994) administered a 6-point VRS of pain intensity, a VAS-I, and the
QLQ-C32 Pain Scale (which is a composite score of pain
intensity and pain interference) to 27 men with prostate
cancer before and after receiving mitoxantrone with
prednisone. All 3 pain measures were sensitive to the
expected decreases in pain over time, although it appears that the VRS-I may have been slightly more sensitive than either the VAS-I or the QLQ-C30 composite
measure of pain intensity and pain interference. In a
pretest-post-test study of the effects of prednisone on
pain associated with prostate cancer, both the MPQ-PRI
(P ⫽ .009) total score and a 6-point VRS-I (P ⫽ .011) were
able to detect treatment effects, whereas a VAS-I was
not (P ⫽ .12). Kucuk et al (2001) found very similar effect
sizes for 3 measures (a 5-point VRS-I, a VAS-I, and the
Short-Form MPQ Total score) in an analgesic trial.
Littman et al (1985) performed a reanalysis of 23 RCTs
of analgesics for postoperative, cancer, acute trauma, or
renal or ureteral colic pain (total number of subjects,
CRITICAL REVIEW/Jensen
1330; total number with cancer not specified). They
found that 3 scales (VRS-I, VAS-I, and a VRS of pain relief)
were similarly sensitive, although the relief ratings
tended to show slightly greater sensitivity than VAS-I
difference scores did, and VAS-I difference scores
showed slightly greater sensitivity than VRS-4 difference
scores did. Consistent with the finding that relief scales
may be more sensitive to change than intensity difference scores, Ohnhaus and Adler (1975) used a 5-point
VRS of pain relief and a VAS of pain intensity in a doubleblind crossover study comparing 2 analgesics to placebo.
Although neither of the measures detected significant
treatment effects, they found that the relief measure
was more sensitive than the VAS was. Similarly, Portenoy, Payne, Coluzzi, et al (1999) found that a 4-point
VRS of pain relief was more sensitive than a 0-10 NRS of
pain intensity for detecting the effects of oral transmucosal fentanyl citrate in a sample of 65 patients with
various cancer diagnoses.
On the other hand, Du Pen et al (1999) found that a
0-10 NRS of usual pain intensity (1 of the BPI pain intensity items) was more sensitive than a 0% to 100% rating
of pain relief (or a 0-10 NRS of worst pain, number of
pain sites, or quality of pain) for detecting the effects of
a cancer pain treatment algorithm. Stambaugh and Sarajian (1981) used a 5-point VRS of pain relief, a VAS-I, and
a 5-point VRS-I to determine the effects of 2 analgesics
compared with placebo in a double-blind crossover
study. In this study, all 3 measures were essentially equivalent in their ability to detect treatment effects.
A second criterion on which various pain measures
have been compared is the frequency of failure rates and
preferences for the different pain measures. Littman et
al (1985), who performed a reanalysis of 23 RCTs, also
reported on the frequency of missing data in these clinical trials. Of the 167 subjects in these studies who were
missing data, 93 (56%) were missing data on all scales
(VAS-I, VRS-I, VRS-Relief). However, most of the rest (63,
44%) were missing data only for the VAS-I.
Kremer et al (1981) examined the preference and failure rates of a VAS-I, a 0-100 NRS-I, and a 5-point VRS-I
among 50 patients seen at a pain clinic, 32 of whom had
cancer. They also found that the VAS had the highest
failure rate (11%) and that the failure rates for the 0-100
NRS (2%) and VRS (0%) were very low. The mean age of
the persons unable to complete the VAS (73.3 years) was
significantly higher than those who were able to complete this measure (54.4 years). In this study, the VRS was
the scale most preferred (by 53% of the patients with
cancer), followed by the 0-100 NRS (25% of those with
cancer), and the VAS was least preferred by the patients
with cancer (16%).
Mostly replicating the findings of Kremer et al, Paice
and Cohen (1997) compared the preference and failure
rates of a VAS-I, 0-10 NRS-I, and 5-point VRS-I in 50 patients with various cancer diagnoses. Although 10 (20%)
of their subjects were unable to complete the VAS, all
were able to complete the VRS and NRS. Moreover, mean
opioid intake was significantly higher for subjects unable
to complete the VAS than for those who were able to
15
complete this measure. They found that half (50%) of
the patients preferred the 0-10 NRS, but that many (28%)
also preferred the VRS over the other scales. Only 6 (12%)
of the subjects preferred the VAS over the other scales.
Shannon et al (1995) administered the MPQ, 3 VAS
scales (of pain intensity, pain relief, and mood), a VRS of
pain intensity, and a Face Scale to 63 inpatients with
cancer. Again, the VAS scales evidenced the highest failure rate, with 89% able to complete the VRS, 84% the
MPQ, 81% the Face Scale, and 75% the VAS scales. Soh
and Hui-Gek (1992) asked 79 patients with various cancer
diagnoses to complete a VAS-I and a VRS-I. Although
they did not report specific failure rates, they did comment that the VAS was more difficult to explain to patients than the VRS was. Sze et al (1998) administered a
VAS-I and a 0-10 NRS-I to 95 patients with various cancer
diagnoses. Again, the failure rate for the VAS-I (14%)
was higher than for the NRS-I (3%). On the other hand,
Tannock et al (1996) found a 6-point VRS-I and a VAS-I to
have similar failure rates (8% and 11%, respectively) in a
sample of 136 men with prostate cancer.
Cognitive impairment may interfere with the comprehension and use of pain rating scales, although it may
impact the use of some scales more than others. Radbruch et al (2000) administered a Mini Mental Status
Examine (MMSE) to 108 patients with advanced cancer in
a palliative care unit and also attempted to administer
the BPI intensity and interference items (all 0-10 NRSs) to
these patients. If the patients were unable to complete
the BPI, they were asked to scale the intensity of their
pain on a 4-point VRS (none, mild, moderate, severe). If
they were unable to use the 4-point VRS, they were simply asked to confirm the presence or absence of pain (ie,
a 2-point VRS-I) along with other symptoms. Radbruch et
al found that only 75% of the patients were able to
complete the 0-10 intensity items and 62% the 0-10 interference items. Moreover, the number of missing responses for the BPI intensity items (r ⫽ ⫺.64) and interference items (r ⫽ ⫺.47) were both associated
significantly with the MMSE score, indicating that a patient’s degree of cognitive impairment impacts his or her
ability to respond appropriately to 0-10 NRS scales. However, many of the patients unable to complete the BPI
0-10 NRS items were able to complete a 4-point VRS of
pain intensity, and all of the patients, even those who
could not rate their pain by using a 4-point VRS, were
able to report on the presence or absence of pain.
Discussion
The results of this review summarize what is now
known concerning the validity and reliability of existing
measures of cancer pain. The findings support the multidimensional nature of cancer pain and provide varying
degrees of support for the validity and reliability of measures of pain intensity, pain interference, pain relief,
temporal pain patterns, pain quality (including affective
qualities of pain), composite measures of pain intensity
and pain interference, and proxy measures of patient
cancer pain. The findings also provide guidance for re-
16
searchers and clinicians concerning which measures may
have the most utility and suggest avenues of future research that will help to clarify the psychometric properties of cancer pain measures.
Measuring Cancer Pain Intensity
There are several conclusions that may be drawn from
the findings of the research on the psychometric properties of pain intensity measures. First and most importantly, each of the commonly used ratings of pain intensity, including the VAS-I, the NRS-I, and the VRS-I, all
appear adequately valid and reliable as measures of pain
intensity among the many different samples of persons
with cancer. Other pain intensity rating scales (eg, Mechanical Visual Analogue Scales, Graphic Rating Scales)
are used less often, but the research that has been performed by using these measures generally supports their
validity as well. Moreover, no one scale consistently
shows greater sensitivity than any other in their ability to
detect changes in pain. Of all the individual pain intensity ratings examined, only 1, a Finger Dynamometer,
showed poor psychometric properties.
Although reliability is an important issue for pain intensity measures, as it is for any measure, reliability can
be difficult to determine for single-item measures of
pain. Internal consistency, 1 of the most common measures of reliability, cannot be computed from single-item
rating scales. Also, test-retest stability coefficients for
measures of pain may not always reflect reliability, because pain can, and often does, change from one moment to the next. Such changes in pain can reduce the
test-retest reliability coefficient even for pain measures
that are highly reliable. For these reasons, a pain intensity measure’s validity coefficients (eg, associations with
other measures of pain intensity and with important criterion measures) are more important criteria than a measure’s reliability coefficient(s). As indicated above, the
findings from the studies reviewed support the criterion
validity of all commonly used ratings of pain intensity.
There do appear to be consistent and important differences between VRSs, NRSs, and VASs in terms of their
failure rates and in patient preference, however. VASs
usually show higher failure rates than NRSs and VRSs,
and NRSs tend (when differences are found) to show
slightly greater failure rates than VRSs. Similarly, VRSs
and NRSs tend to be preferred over VASs by patients.
Higher failure rates with VASs have been shown to be
associated with older age and greater amount of opioid
intake, and mental impairment has been shown to be
associated with inability to complete 0-10 NRS ratings of
pain intensity and pain interference. Many patients unable to complete 0-10 NRSs appear to be able to complete 4-point VRSs, however.
As a group, these findings suggest that VAS ratings
may not be the best choice for assessing cancer pain
intensity, especially among patients who are elderly or
who may be using opioid medications. NRSs, on the
other hand, appear to be well tolerated by most patients
and appear to be at least as sensitive and valid as the
more traditional VAS rating scales. Ten-point NRSs also
Cancer Pain Assessment
have the advantage of the existence of data that help
clarify the meaning of specific ratings and NRS change
scores,7,8,24 information that is directly tied to treatment
decisions according to current treatment guidelines.13,33,34 However, if the population is expected to
include patients with significant cognitive impairment, a
more simple 4-point VRS (eg, no, mild, moderate, or severe pain) may be the best choice.
In addition to the more frequently used single ratings
of pain intensity, pain intensity may also be assessed by
using multiple-item scales. The multiple-item intensity
measure used most commonly among patients with cancer is the Pain Intensity Scale of the BPI, which consists of
an average of ratings of current and of least, worst, and
average pain over a specific time period (eg, the past 24
hours) into a single summary score.3 This composite measure has shown excellent psychometric properties, including high internal consistencies and criterion-related
validity. A similar composite score of average, worst, and
least pain ratings has demonstrated similar psychometric
strengths (Clearly et al, 1995).
Although the sensitivity of multiple-item scales of pain
intensity to the effects of cancer pain treatments has not
yet been determined, there are several reasons to expect
that research will prove these measures to be sensitive
when tested. First, composite measures of pain intensity,
like the BPI, are made up of individual ratings that themselves have shown sensitivity to changes in cancer pain.
For example, one of the BPI intensity items (usual pain)
was shown to be sensitive to the effects of a pain treatment algorithm (versus standard care) in a sample of
patients with various cancer diagnoses, and another BPI
intensity item (worst pain) was sensitive to changes in
cancer pain over time6 (see also16). In addition, research
by using samples of patients with pain problems other
than cancer have shown the BPI Intensity scale to be
sensitive to the effects of pain treatment.25,27 What is
less certain is whether a composite pain intensity score
shows improved psychometric properties when compared with individual pain intensity ratings.
Other composite measures of pain intensity either
combine pain from multiple pain sites into a single score
(eg, de Haes et al, 1990) or combine pain ratings from
sites associated with specific cancer diagnoses (eg, head
and neck cancer pain scale that assesses jaw pain, mouth
pain, mouth soreness, and throat pain, Bjordal et al,
1994). The findings concerning these other composite
pain intensity measures indicate that the measure made
up of ratings from divergent pain sites may have limited
reliability, because having pain at one site (low back)
may or may not be associated with having pain at a different site (headaches) (de Haes et al, 1990). Trying to
combine the intensity of pain at these different sites into
a single score may therefore lose important information.
On the other hand, the findings concerning cancer diagnosis-specific measures provide some support for the reliability of assessing pain intensity in and around sites
associated with a specific cancer diagnosis, in that these
composite scales are internally consistent and demonstrate criterion-related validity.
CRITICAL REVIEW/Jensen
In terms of recommendations for future research,
there does not appear to be a strong need for future
studies to determine the psychometric properties of single-item ratings of pain intensity. The many findings that
are available provide a fairly clear picture concerning
their validity and reliability. However, there is a need to
determine whether anything is gained by using multipleitem measures of pain intensity (eg, the BPI Pain Intensity
scale or the Head and Neck Cancer Pain Questionnaire
Pain Intensity scale) instead of single-item ratings. Theoretically, multiple-item scales should be more reliable
and therefore potentially more sensitive for detecting
changes in pain associated with time or with treatment.22 Future studies may test this hypothesis by comparing multiple-item measures with single pain intensity
ratings in the context of longitudinal studies and clinical
trials.
Measuring Cancer Pain Interference
Pain interference refers to the extent to which pain
interferes with important daily activities, such as sleep,
mood, and mobility among many others. The most common measure of pain interference in cancer pain research is the Interference scale of the BPI.3 This 7-item
scale has shown excellent reliability (internal consistency) across a large number of different samples of patients with cancer pain. At least 2 other multiple-item
scales of pain interference have been described in the
cancer pain literature (Ripamonti et al, 2000; Maunsell et
al, 2000), which have also been shown to have adequate
to excellent internal consistency.
A number of single-item measures of pain interference
have also been used in cancer pain research, and the
findings indicate that such measures have good criterion-related validity through their significant associations
with measures of quality of life. Moreover, the research
indicates that ratings of pain intensity and pain interference can show different patterns of associations with
other criterion measures. These findings provide further
support for the conceptual and statistical distinction between measures of pain intensity and pain interference.
There are a number of important unanswered questions concerning the validity of pain interference scales
that should be addressed in future research. Although
some interference scales have shown sensitivity to the
effects of pain treatment in non-cancer pain patient
groups (eg, the BPI25,27), no research has yet determined
how well these measures detect changes in cancer pain
over time and with effective cancer pain treatment.
There is also a paucity of research to determine whether
the available pain interference measures differ in terms
of their sensitivity to treatment effects. In addition, very
few studies have examined the correlates of pain interference in persons with cancer. To what extent do measures of pain interference predict psychologic and physical functioning? What is the relative sensitivity of pain
interference measures to pain treatments compared
with measures of pain intensity or measures of global
functioning? Research that addresses these questions
17
will help to clarify the meaning and importance of pain
interference measures among patients with cancer.
Measuring Cancer Pain Relief
On the surface, many clinicians or researchers might
assume that a rating of pain relief after a treatment
represents, or should represent, the same thing as a pretreatment to post-treatment decrease in pain intensity.
If this were true, then asking patients to rate pain relief
after a treatment for cancer pain could be seen as an
alternative to assessing change in pain intensity pretreatment to post-treatment. However, even though
pain relief ratings are sensitive to the effects of treatment, pain relief ratings are not always strongly associated with pretreatment to post-treatment changes in
pain intensity ratings. Moreover, some patients rate
themselves as having experienced relief even when posttreatment pain returns to pretreatment levels. These
findings suggest that pain relief ratings should not be
interpreted to represent the same thing as pretreatment
to post-treatment changes in pain.15
The data from the studies reviewed do suggest the
possibility, however, that at least in some populations of
patients with cancer, ratings of pain relief may be more
sensitive to the effects of pain treatment than pain intensity change scores are. Thus, in situations in which the
ability to detect a treatment effect is of utmost importance, for example in clinical trials in which there may be
limited power because of a limited number of subjects,
researchers would be wise to consider including pain relief ratings as one of the outcome measures in the study.
By doing so, they may assess aspects of pain treatment
outcome not measured by simple pain intensity change
scores.
Regarding the selection of pain relief rating scales, the
data do not clearly support the use of any one type of
relief rating (eg, VRS, NRS, or VAS) over any other. However, practical considerations might suggest that a VRS
of pain relief (eg, no relief, slight relief, moderate relief,
lots of relief, complete relief) may help limit the chances
that patients will confuse the relief rating with pain intensity ratings, because NRS and VAS pain intensity measures can look very similar to NRS and VAS measures of
pain relief.
Measuring Cancer Pain Site
Very little research has been performed to evaluate
and validate measures of pain site in patients with cancer. Of the 2 methods most commonly used to assess pain
site in pain research, pain drawing and site checklists,
only pain drawings have been studied in patients with
cancer. The findings from this research indicate some,
but limited (because of the few number of studies), criterion validity for cancer pain drawings, as evidenced by
their correspondence with anatomic locations associated
with specific cancer diagnoses and through their association with pain intensity.
Whether patient-rated pain site measures are useful in
patients with cancer remains to be seen. However, re-
18
search among patients with chronic pain not associated
with cancer supports pain site as a distinct pain dimension that may play an important role in patient functioning over and above the effects of pain intensity alone.
For example, the number of pain sites has been shown to
have moderate associations with disability, pain intensity/interference composite scores, and return to work in
persons with chronic pain.23,26,29 In another study, pain
in the low back area (or low back plus head and neck
pain) was associated more strongly with disability than
the same intensity of pain in other sites.28 Given the
potential importance of pain site (and number of pain
sites) to patient functioning, there is a need for further
research to examine the validity and usefulness of pain
site measures as measures of treatment outcome, pain
distribution description, or as predictors of other important outcomes or variables in persons with cancer pain.
Measuring the Temporal Aspects of
Cancer Pain
Measures of the temporal aspects of pain, including its
variability, frequency, and duration, have not received
adequate attention in cancer research. The available evidence indicates that measures of pain frequency have
shown criterion-related validity through their association with pain intensity and interference composite
scores, type of treatment received, and pain affect (the
level of “upsetness” caused by pain). In at least one of
the studies reviewed, pain frequency was associated
with the type of treatment received, whereas the pain
intensity rating used in the study was not, suggesting
that pain frequency and pain intensity can be considered
distinct dimensions of cancer pain. Presence and frequency of breakthrough pain (periods of excruciating
pain in the context of ongoing background pain), another important temporal aspect of pain, were similarly
shown to be associated with pain interference, as well as
psychologic functioning.
It is possible, even likely, that temporal aspects of
pain such as the frequency and unpredictability of
breakthrough pain (or even, alternately, the frequency of pain-free periods) may have an impact on
patient functioning over and above any effects of
global average pain intensity. It is also possible that
cancer pain treatments that impact such variables may
have a greater impact on patient quality of life than
treatments that focus exclusively on background or
baseline pain would. To test these important hypotheses, valid and reliable measures of the temporal aspects of cancer pain are needed. Unfortunately, although the studies that have been performed indicate
that pain frequency and variability can be assessed,
there is a paucity of research that evaluates the psychometric properties of measures of the temporal aspects of pain or that develops additional measures of
this important pain dimension that can then be evaluated.
Cancer Pain Assessment
Measuring the Qualitative Aspects of
Cancer Pain
Pain is known to have qualities in addition to its intensity. It can be experienced as hot, cold, tingly, deep, dull,
worrisome, or any one (or more) of many other qualities.
Measures of the qualitative and affective components of
pain may be used to more fully describe cancer pain. Such
measures could also potentially contribute to improved
evaluation and treatment of cancer pain. Given the likelihood that some pain treatments will be found to impact some pain qualities more than others, inclusion of
pain quality measures in clinical trials will help determine
the specific qualities of pain that would most benefit
from each pain treatment that is evaluated.5 Moreover,
to the extent that a treatment might impact a relatively
few subset of pain qualities, ratings of specific cancer
pain qualities may turn out to be more sensitive to the
effects of some treatments than ratings of global pain
intensity. If so, then systematic use of pain quality measures in clinical trials of cancer pain may help identify
effective treatments that might otherwise have been determined to have little effect on pain.
The MPQ is the measure most often used to assess the
qualitative aspects of pain, including cancer pain. Discriminative validity of the MPQ is evidenced by the moderately strong associations between the MPQ scale scores
and measures of pain intensity. These associations are
strong enough to indicate that the MPQ scores assess
pain but also not so strong to suggest that MPQ scores
assess only pain intensity. The findings also show that the
MPQ scales are associated with measures of quality of
life, and in at least one study were shown to be sensitive
to the effects of cancer pain treatment. Evidence supports the validity of the MPQ-Affective subscale, in particular, for assessing pain-related distress, given the
stronger associations of this scale with measures of psychologic distress than with measures of pain intensity
and the relatively high scores on the MPQ-Affective scale
among persons with cancer pain compared with persons
with low back pain. However, the MPQ is a relatively
lengthy measure (listing 78 descriptors), and many of the
descriptors may not be appropriate or needed in patients
with cancer pain. Moreover, the MPQ scale scores represent composite measures of multiple pain qualities, so
that the MPQ may have limited utility for identifying the
effects of treatment on specific cancer pain qualities.
The Short-Form MPQ has some strengths that may
make it more practical than the MPQ to use in cancer
pain research. First, it includes only 15 descriptors instead
of 78, markedly reducing the assessment burden on subjects. In addition, it retains descriptors from 2 of the MPQ
primary categories (sensory and affective), making it
possible to assess these dimensions of pain quality. Finally, unlike the MPQ, which requires patients to select
no more than a single word from each of 20 categories of
pain, respondents to the SF-MPQ are allowed to rate the
severity of each pain descriptor on a 0-3 scale. This allows
for scoring and analysis of each specific quality of pain.
Unfortunately, only one study has examined the psycho-
CRITICAL REVIEW/Jensen
metric properties of the SF-MPQ in patients with cancer.
Although this one study found the measure to have excellent internal consistency, it also found a very strong
association between the 2 SF-MPQ subscales, raising the
possibility that these scales may be assessing a similar
underlying construct. Much more research is needed to
determine the utility of the MPQ, the SF-MPQ, or even
measures of the qualitative aspects of cancer pain not yet
evaluated in cancer pain populations (eg, the Neuropathic Pain Scale9) for measuring cancer pain.
Composite Measures of Cancer Pain
Intensity and Interference
Two quality of life measures commonly used in cancer
research, the EOTC QLQ-C30 and the SF-36, include scales
that combine pain intensity and pain interference into
composite scores. There are strengths and weaknesses to
combining these distinct dimensions of pain into single
composite scores. Because, typically, measures of pain
intensity and pain interference show at least moderate
associations with one other, a scale made up of items
reflecting these dimensions would be expected to show
good internal consistency. Also, combining measures of
intensity and interference into a single summary score
could reduce the number of variables in analyses involving pain severity as a predictor (independent) or criterion
(dependent) variable, thereby potentially increasing the
power of statistical analyses in a research study. Such a
composite measure also provides clinicians and researchers with an overall indicant of pain and its impact that
has an intuitive appeal. Finally, especially for the SF-36
Bodily Pain scale, there are published norms from numerous samples of persons with and without specific health
problems to which a patient’s scale score can be compared.31 This makes the interpretation of a patient’s (or
groups of patients’) score(s) much easier.
The primary weakness of composite measures of pain
intensity and interference concerns the loss of information about the relative levels of each pain dimension
included in the composite score. Someone with high pain
intensity that he or she is not allowing to have an impact
on activities and someone with low pain intensity that is
interfering substantially with function could obtain the
same score on a measure that was an average of these 2
dimensions. Related to this, if a treatment is shown to
decrease a composite score of pain intensity and pain
interference and only the changes in the composite score
are reported in a research study, it is not possible to
determine whether the treatment had a greater (or primary) impact on pain interference or pain intensity. Of
course, investigators could analyze the pain intensity
and pain interference items that contributed to the composite score separately, but unless they do so and report
the findings on the individual ratings in their published
report, information concerning the impact of treatment
on each component dimension will be lost.
On the positive side, data support the validity and reliability of both the EOTC QLQ-C30 Pain and the SF-36
Bodily Pain composite scores. The findings indicate that
19
these scales generally have adequate to excellent internal consistencies across samples and cancer pain populations. Also, like measures of pain intensity, these measures of pain have shown appropriate associations with a
number of validity criteria, including measures of other
dimensions of quality of life, functional status, disease
stage, performance status, tumor stage, tumor size, survival, and treatment prognosis.
The finding that the QLQ-C30 Pain scale and the SF-36
Bodily Pain scale are very strongly associated with one
another (r ⫽ .83) also supports the conclusion that they
measure the same underlying dimension(s) of pain. Also,
both the QLQ-C30 and SF-36 Pain scales have shown sensitivity to changes in pain over time and with treatment,
although one study found that the SF-36 scale was not
sensitive to a treatment effect that was detected by
changes in a VAS rating of intensity (Holland et al, 1998),
suggesting the possibility that pain severity measures
may be more useful for providing global descriptions of
cancer pain than for assessing treatment outcome.
Proxy Measures of Cancer Pain
Several conclusions can be drawn from the line of research that has compared proxy with patient measures
of cancer pain. First, the strength of the associations between proxy measures and patient measures is quite
variable, with moderate associations being found more
often than either weak or strong associations. Second,
more often than not, physicians tend to underestimate
patient cancer pain and caregivers (including significant
others or family members) tend to overestimate patient
cancer pain, relative to what patients themselves are reporting. Nurses, perhaps because of their more frequent
contact with patients during treatment, are often (but
not always) more accurate than either physicians or caregivers when rating patient pain.
The findings from these groups of studies suggest that
proxy measures of patient cancer pain may carry some
valid variance and therefore might provide some indication of patient pain when patients are unable to provide
their own ratings of pain experience. However, care
must be taken to not conclude that a proxy’s estimate of
patient pain is necessarily accurate. In particular, health
care providers need to be careful to not assume that their
own judgments concerning a patient’s pain intensity will
necessarily reflect the patient’s own report; in fact, there
is a good chance that the health care provider may be
underestimating patient pain levels. There is a need,
therefore, to ensure that patients are provided every
opportunity to rate their own pain to ensure that accurate ratings are available when making treatment decisions.
Issues of Content Validity
As reviewed above, only 4 studies (2.4% of studies reviewed) addressed issues of content validity of cancer
pain measures. Evidence concerning measure reliability
and criterion validity were included much more often in
these studies. This finding may not be particularly sur-
20
prising, in that much of the research reviewed was not
specifically performed to address the psychometric properties of the measures. More often than not, findings
that spoke to the psychometric properties of the measures examined were presented in the context of a study
with other primary goals, such as a clinical trial or a descriptive study. However, the paucity of discussion of and
presentation of data that speak to the content validity of
cancer pain measures is a concern, given the importance
of content validity to measure development and evaluation.2
There is an important need for clinicians and researchers to consider content validity of cancer pain measures,
in particular, because of the multidimensional nature of
cancer pain. Although it is likely that pain intensity will
be one of the dimensions assessed, it is also important
that an assessment of pain quality as well as the impact
of pain on a person’s life (pain interference) be at least
considered as possible secondary measures. As is evident
from this review, other pain dimensions, including pain
relief, pain site, and the temporal aspects of pain, are
rarely considered in cancer pain research. It is possible
that these other dimensions are not considered because
they are unimportant to patients or to clinicians, and so
there is little need to assess these pain dimensions in
most situations. However, a more likely explanation for
the lack of research that uses measures of these other
components of cancer pain is that they are simply overlooked. It is difficult to imagine, for example, that the
presence and frequency of breakthrough pain (excruciating pain that occurs in the context of ongoing background pain) are of little importance to the patient experiencing this type of pain. In addition, the number and
distribution of pain sites could impact a patient’s quality
of life over and above the intensity of average pain. To
the extent that these dimensions of pain are not assessed, their associations with important functioning
variables will remain unknown, and their potential for
impacting quality of life will not be determined. Ultimately, the lack of assessment of these pain dimensions
may also contribute to a lack of focus on them as potential outcome variables, limiting the treatment options
for patients with cancer pain in multiple sites or with
specific temporal patterns.
Limitations of the Current Review
This review has several limitations. First, to provide focus for the review, studies were limited to those that
studied pain assessment among adults with cancer. Pediatric pain assessment requires consideration of many additional issues not addressed in this review, such as the
developmental stage of the person being assessed.19
Many of the conclusions drawn from this review of assessment of pain in adults with cancer therefore do not
necessarily apply to the assessment of pediatric cancer
pain. The reader is referred to the small, but growing,
literature on pediatric cancer pain assessment for information concerning the psychometric properties of available measures.4,5,10,11,17,32 Second, the majority of the
studies reviewed in this article were not specifically de-
Cancer Pain Assessment
signed to test the psychometric properties of cancer pain
measures. The fact that they contained data concerning
the reliability and validity of pain measures in persons
with cancer was not necessarily evident from their titles
or even abstracts. Thus, it is likely that additional articles
that provide such data were missed in the current review.
However, the generally consistent findings across the
studies that were reviewed do provide some support for
the conclusions drawn from this review. Third, there are
issues relevant to the assessment of pain that were not
considered in this review, such as the advantages and
disadvantages of assessing pain on a single occasion versus assessing pain on multiple occasions over time, cultural issues relating to pain assessment, and the advantages and disadvantages of using pain intensity cutoffs
as inclusion/exclusion criteria in pain treatment outcome
studies. Research concerning these issues was not discussed because the focus of the review was on cancer
pain assessment specifically and not pain assessment in
general. Finally, this review focused primarily on selfreport and proxy measures of cancer pain and did not
include discussion of research on observational measures
of pain behaviors in patients with cancer. This limitation
was due primarily to the fact that most, if not all, of the
research on behavioral measures of cancer pain has been
performed in pediatric samples.10,11 However, it is possible that behavioral observation measures of cancer pain
may prove to be useful for adults as well. Future research
is needed to determine the reliability, validity, and utility
of observational measures of cancer pain.
Summary and Conclusions
A great deal of research has been performed that provides data concerning the psychometric properties of
cancer pain measures. The findings from this research
support the multidimensional nature of cancer pain. The
results also support validity of a number of measures,
especially the most commonly used measures of cancer
pain intensity and pain interference. Measures of other
dimensions of cancer pain, such as pain site and the temporal and qualitative aspects of pain, are less often used
and studied. Yet measures of these and other cancer pain
dimensions may prove to be invaluable for assessing cancer pain and the efficacy of cancer pain treatment. Future research that develops, refines, and evaluates such
measures will provide important information that investigators and clinicians may then use to select specific
scales for their research and clinical work. By increasing
knowledge about and options for cancer pain assessment, investigators will ultimately contribute to a better
understanding and alleviation of cancer pain.
Acknowledgments
The author wishes to express his appreciation to Elena
Mihailova for her invaluable assistance in typing the
study summary tables and to Lisa C. Murphy for her helpful comments on an earlier version of this manuscript.
CRITICAL REVIEW/Jensen
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