Norwegian Cervical Cancer Prevention
Supplementary Appendix
SUPPLEMENTARY APPENDIX
Accompanying the manuscript:
Cost-effectiveness of cervical cancer screening with primary human papillomavirus (HPV)
testing in Norway
Emily A. Burger, MPhil
Jesse D. Ortendahl, BS
Stephen Sy, BS
Ivar Sonbo Kristiansen, MD, MPH, PhD
Jane J. Kim, PhD
Part I: Model and parameterization
Part II: Cost assumptions
Part III: Strategies and assumptions
Part IV: Additional Results
Part V: References
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Supplementary Appendix
Part I: Model and parameterization
The first-order Monte Carlo simulation model (i.e., stochastic) of cervical cancer has been
previously described (1-3). The model, comprising of mutually exclusive, collectively exhaustive
health states, follows individual women throughout their lives, calculates lifetime cervical cancer
risk, cancer incidence and mortality, and life expectancy. The model also tracks costs associated
with events such as vaccination, screening, diagnostic follow-up, treatment of precancer, and
cancer treatment and care. By simulating a large number of individual women, expected health
benefits and costs of alternative prevention policies that may include screening, vaccination or
both, can be assessed. Baseline transition parameter values describing the natural history of
disease were based on the best available empirical data, have been previously published and
assume that the underlying mechanism of cervical carcinogenesis does not vary across
epidemiological settings (1-3). Risk factors, such as sexual behaviour, and cervical cancer
incidence rates differ between countries; therefore, country-specific data are needed to adjust
baseline inputs to account for variations in progression and regression rates. We leveraged
empirical data from Norway and used a likelihood-based algorithm to identify candidate sets of
parameter values that achieve good-fit to epidemiological outcomes observed in the Norwegian
population.
Defining calibration targets
In total, 37 calibration targets were defined. The Norway-specific targets included age-specific
prevalence of HPV-16, -18 in women, age-specific prevalence of CIN23, HPV-16, -18 and other
high-risk HPV distributions in high-grade CIN, HPV-16 and -18 distributions in cervical cancer
and age-specific cancer incidence. For each calibration target, we determined a point estimate and
confidence interval, using population-based sources.
Calibration target data was used to inform multipliers of the initial model inputs. All prevalence
and HPV type distribution targets were calculated using 95% confidence intervals of the binomial
distribution in STAT/SE 11.0, and cancer incidence bounds were informed by taking the
minimum and maximum age-specific annual incidence from 1953-1969.
Calibration target data sources and model fitting
Age-specific prevalence of HPV-16,-18
There are limited number of HPV prevalence studies which have been published in Norway and
even fewer which inform the prevalence of HPV among younger women. Three published studies
(4-7) were identified by a literature search; however, we were not able to extract the pertinent
data to inform our model. For one study (6;7), the reported estimates pooled the prevalence from
only five high-risk HPV types or did not separate high-risk types from low-risk types, and the
second study did not separate HPV-16, -18, -6,-11 from each other. The third study (4), reported
the prevalence of HPV-16 and -18 among younger women, though we could not simultaneously
stratify the age groups and attribute multiple HPV infections hierarchically from the published
manuscript. The best available data came from a study affiliated with the Norwegian Cancer
Registry (Personal communication: Mari Nygaard, MD, PhD, March 2011). They gave us
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Supplementary Appendix
preliminary insight to results from a study they conducted in a large city in Norway (Appendix
Table and Figure 1). The study selected a random sample of Norwegian women in 18-45 yrs of
age, who attended to screening in 2007 in S. Olav hospital, in Trondheim, Norway. HPV DNA
positivity was detected by PCR G5+/6+ for 30+ HPV types. We assumed participants to be
sexually active and used a weighted average from two sexual behavior studies conducted in
Norway (8;9) to adjust for sexual debut in the younger age groups. The adjustment factor for
women aged 18-19 and 20-24 years was 80% and 95%, respectively.
Appendix Table 1: Age-specific prevalence of HPV-16,-18 in women (adjusted for non-sexually
active women) with 95% confidence intervals
AGE GROUP
N
X
PREV HPV16/18
LB
UB
15-17
18-19
20-24
25-29
30-34
35-39
40-44
45-49
77
689
296
213
235
234
57
16
151
46
11
10
1
2
0.2085
0.2190
0.1554
0.0516
0.0426
0.0043
0.0351
0.1254
0.1826
0.1183
0.0281
0.0223
0.0001
0.0027
0.3192
0.2440
0.2013
0.0911
0.0775
0.0263
0.1261
Appendix Figure 1: Model output from 50 good-fitting sets and the upper and lower bound from
the empirical data (bold). 5 best fitting sets in red.
Prevalence of high-grade cervical lesions by age
We used a published study (6;7) in which Pap smears were taken for a cytological analysis from
4419 women (Appendix Table and Figure 2). These women visited selected specialist
gynecological clinics in Oslo, and the samples were taken consecutively in the period from
February to June 2001. The gynecologists performed the Pap smears, which were then screened
by experienced cyto-technologists at two different laboratories. The cytology was evaluated
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Supplementary Appendix
independently of the HPV testing. Distribution of lesions was reported by for women ≤29 and by
10-year age groups, thereafter.
Appendix Table 2: Age-specific prevalence of CIN23 in women
(1)
AGE GROUP
N
X
Prev
PREV CIN2-3
(X*1.4)(1)
LB(X)
UB(X*1.4)
≤29
30-39
40-49
50-59
60+
283
1023
1211
1208
694
0
14
6
4
1
0
0.0140
0.0050
0.0030
0.0010
0.0000
0.0196
0.0070
0.0042
0.0014
0.0000
0.0075
0.0018
0.0009
0.0000
0.0130
0.0300
0.0130
0.0096
0.0080
Prevalence was corrected by 40% false negatives in all age-groups.
Appendix Figure 2: Model output from 50 good-fitting sets and the upper and lower bound from
the empirical data (bold). 5 best fitting sets in red.
Distribution of HPV-16, -18 and other high-risk types among CIN and distribution of HPV-16, 18 among cervical cancer
We reported the proportion of HPV-16,-18 and other high-risk HPV in CIN23 from a Norwegian
epidemiological study (working paper) of HPV type distribution in high-grade cervical precancer using standardized HPV DNA detection and typing on archived, formalin-fixed, paraffinembedded cervical and excision specimens (personal communication: Steinar Thoresen)
(Appendix Table and Figure 3). The upper and lower bounds from this study were consistent with
a study identified in the literature search (10), but was not utilized because we could not attribute
other high-risk types hierarchically to estimate the distribution of other high-risk HPV types
among CIN. We identified two publications during our literature search which reported HPV type
distributions within cervical cancer, however, one (11) used invasive cervical cancer specimens
from the late 80’s which may no longer be representative of current HPV distributions and we
could not separate CIN3 from invasive cancer from the other (12). We estimated HPV-16, -18
type distribution among invasive cancer from the same working paper as above (personal
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Norwegian Cervical Cancer Prevention
Supplementary Appendix
communication: Steinar Thoresen, PhD, February 2011). Women were aged 18 or above at the
time of collection of cervical/excision specimens, and had been diagnosed with invasive cervical
cancer from 2001 onwards. HPV type distribution targets were calculated using 95% confidence
intervals of the binomial distribution in STAT/SE 11.0.
Appendix Table 3: Distribution of HPV-16,-18 and other high-risk types in high-grade CIN and
HPV-16,-18 types in cervical cancer with 95% confidence intervals
Lesion & HPV-type
CIN 23 HR_16
CIN 23 HR_18
CIN 23 HR_Other
CANCER HR_16
CANCER HR_18
N
255
255
255
342
342
X
121
17
103
163
66
PREV TYPE
0.4745
0.0667
0.4039
0.4766
0.1930
LB
0.4119
0.0393
0.3432
0.4226
0.1525
UB
0.5377
0.1046
0.4669
0.5310
0.2389
Appendix Figure 3: Model output from 50 good-fitting sets and the upper and lower bound from
the empirical data (bold). 5 best fitting sets in red.
Cervical cancer incidence
To evaluate model outcomes on the natural history of disease in the absence of screening, targets
on the age-specific incidence of invasive cervical cancer were defined based on the minimum and
maximum annual incidence from Norwegian Cancer Registry data, 1953-1969 (Contact: Gry
Skare, Cancer Registry of Norway) (Appendix Table and Figure 4). The registry is based on a
modified version of International Classification of Disease, version 7 or version O (ICD-7/ICDO). Staging is done according to Federation Internationale Gynecologie et d’Obstetrique (FIGO).
The registration of invasive cervical cancer is nearly 100% complete in Norway (13). The 50
good-fitting sets in relation to the empirical cancer incidence bounds are shown in Appendix
Figure 5.
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Supplementary Appendix
Appendix Table 4: Incidence per 100,000 womann-years, by year and age (Cumulative from stages I-IV and unknown).
0.00
LB
(min)
0.00
UB
(max)
0.00
0.00
1.31
6.72
23.22
34.23
57.93
50.05
50.12
31.72
29.18
26.24
34.43
25.50
0.00
0.00
0.00
10.46
22.26
30.70
28.79
24.27
28.86
22.57
11.22
9.76
11.56
0.68
2.06
13.38
23.99
46.35
58.65
50.05
50.12
49.10
47.03
43.50
34.43
29.18
AGE GROUP
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
10-14
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75+
0.00
0.96
6.88
21.78
26.81
39.36
37.16
36.51
47.19
33.25
18.47
33.93
23.78
0.00
0.00
11.53
23.99
22.26
31.78
44.49
44.47
49.10
33.47
33.32
9.76
27.38
0.00
0.00
3.60
17.94
33.91
36.46
37.05
34.96
41.97
32.48
26.64
26.42
21.61
0.00
2.06
6.49
20.24
36.46
30.70
37.50
38.39
38.43
32.59
27.40
25.74
11.87
0.00
1.04
6.59
21.82
39.44
41.78
36.88
32.66
38.82
22.57
35.27
30.50
15.52
0.00
1.02
2.92
23.46
46.35
41.44
40.64
34.25
28.86
47.03
30.13
29.73
29.18
0.00
0.00
6.99
23.30
31.14
39.29
43.77
37.27
37.12
26.68
38.52
27.56
12.37
0.00
0.97
13.38
22.86
38.89
34.91
28.79
44.75
42.49
32.39
28.35
23.48
27.80
0.00
0.95
0.00
17.81
43.27
48.24
40.88
24.27
43.10
44.20
11.22
29.42
26.04
0.00
0.92
3.15
10.46
32.12
38.24
40.64
34.93
34.42
26.28
43.50
28.85
11.56
0.00
0.00
9.27
20.60
35.82
43.63
39.46
39.62
35.08
38.08
23.42
24.92
19.44
0.00
0.00
7.05
19.08
40.53
55.02
48.56
33.55
41.80
29.71
29.73
22.62
20.20
0.00
0.78
4.90
22.69
40.36
40.71
43.07
48.40
35.91
32.41
37.99
33.59
22.88
0.00
0.00
8.71
15.75
34.85
50.88
44.86
46.45
30.99
34.01
25.11
26.49
21.94
0.00
0.00
4.67
17.95
31.53
58.65
49.37
42.02
33.98
41.42
43.07
28.35
15.09
0.68
1.98
8.04
22.78
42.35
36.91
47.84
39.21
33.58
29.64
30.81
31.41
17.52
Cancer incidence: Norway (1953-1969)
Appendix Figure 4: Annual agespecific incidence of invasive
cervical cancer in Norway in the 50’s
(dark blue) and 60’s (pink) used to
inform the minimum and maximum
bounds for model fitting.
70.000
60.000
50.000
40.000
30.000
20.000
10.000
0.000
10-14
15-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75+
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Supplementary Appendix
Appendix Figure 5: Model output from 50 good-fitting sets (light grey) and the upper and lower
bound from the empirical data (bold).
Part II: Cost assumptions
Direct medical and non-medical costs of screening, diagnosis and treatment, were based on a
combination of primary data and expert opinion. There are evidence gaps in Norway with respect
to detailed costing estimates for cervical cancer screening and treatment; therefore, we present
details of our estimation and rationales below. Input values and ranges used in this analysis are
presented in the Main Manuscript Table 1.
Estimation of costs
Direct medical costs of screening included the test, supplies, specimen transport, laboratory
processing of the screening sample, staff time, and the office visit. Diagnostic costs included
colposcopy, biopsy, supplies, equipment, laboratory processing, staff time, and the office visit.
Pre-cancer treatment costs included the procedure, which included pharmaceuticals and supplies,
complications, and hospitalization, and the facility visit. Direct medical costs of cancer care
included staging of cancer severity, work-up, hospitalization, stage-appropriate treatment, and
follow-up visits for five years (discounted). Direct non-medical costs and time costs associated
with screening, diagnosis, and treatment for precancerous lesions and invasive cancer included all
patient time in transport, waiting, receiving treatment, and in hospitalization as well as actual
transport costs. Invasive cervical cancer stages Ia-IIa were classified as local cancer, stages IIbIIIb as regional cancer, and stages IVa-IVb as distant cancer, based on FIGO staging system.
To estimate costs associated screening, diagnosis and treatment, we based costs on official
national tariffs (outpatient care) (14;15) and hospital-based DRG reimbursement rates (inpatient
care) (16) using official treatment guidelines (17) and expert opinion from Norwegian
gynaecologists to quantify resource use. See Appendix Table 5 for descriptive estimates of the
direct medical and non-medical costs associated with screening, treatment and vaccination.
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Appendix Table 5: Description of estimates used in base case analysis
2010 ($)
CATEGORY
DESCRIPTION
Office costs
Weighted average of GP based visit (80%) and gynecologist-based visit (20%). Cost of staff,
facilities for a common "office" visit in a primary clinic -- exam plus a basic clinic room with an
exam bed, sending of sample to laboratory and letter/results
$81
Patient time for
office visit
Cost of patient time (2 way travel (60min), waiting(15min), receiving care (15min)) for a primary
clinic + the cost of 2 way patient transport to and from the primary clinic
$87
Conventional Pap
test
Cost of pap collection materials, rubber gloves, disinfectant, glass slide of tube, speculum, other
disposable supplies, includes all laboratory transport, equipment, supplies, facilities, staff
(Independent/adjusted analysis) (material fee of $3 added to estimated lab costs, explained
below).
$49
Liquid-based
cytology
Cost of pap collection materials, rubber gloves, disinfectant, tube, speculum, other disposable
supplies, includes all laboratory transport, equipment, supplies, facilities, staff
(Independent/adjusted analysis)
$50
HPV DNA test
Cost of HPV collection kit, rubber gloves, disinfectant, speculum, other disposable supplies,
includes all laboratory transport, equipment, supplies, facilities, staff (Independent/adjusted
analysis) Includes co-collection fee for LBC (assumed $8), regardless if LBC is conducted)
$62
Patient time for
colposcopy
Cost of patient time for 2-way travel, waiting, and receiving services at a district/regional hospital
+ cost of patient transport
Colposcopy
procedure
CIN1 treatment
CIN23 treatment
Local cancer
treatment
Cost of the facilities, staff time to perform colposcopy. Cost of supplies and equipment to do
colposcopy (speculum, colposcope, rubber gloves, disinfectant, etc), Including taking and
analyzing biopsy.
Cost of treating a person who has true CIN1. This is a weighted average of LEEP, conisation, and
simple hysterectomy for people with this true lesion status and includes the treatment specific
staff time, supplies, equipment, hospitalization, and follow-up visits and procedures as well as
patient time receiving services, hospitalization, and follow-up and patient transport for the same
Cost of treating a person who has true CIN23. This is a weighted average of LEEP, conisation,
and simple hysterectomy for people with this true lesion status and includes the treatment specific
staff time, supplies, equipment, hospitalization, and follow-up visits and procedures as well as
patient time receiving services, hospitalization, and follow-up and patient transport for the same
Diagnosis, conisation (19%), simple (19%) and radical hysterectomy (41%), radiotherapy and/or
adjuvant chemo (19%), fertility preserving (2%), complications (10%), relapse/retreat (20%),
recommended follow-up for 5 years conditioned on survival, transport, productivity loss for direct
treatment time and f/u procedures
(Stages Ia-IIa)
$138
$199
$1,024
$2,162
$25,770
Regional cancer
treatment
Diagnosis, radical hysterectomy (6%), 25 visits radiotherapy with adjuvant chemo (92%), 10
visits simplified external radiotherapy (2%), complications (10%), relapse/retreat (20%),
recommended follow-up for 5 years conditioned on survival, productivity loss for treatment time
and f/u procedures
(Stages IIb-IIIb)
$51,589
Distant cancer
treatment
Diagnosis, 25 visit radiotherapy with adjuvant chemo (27%), 30 visits radiotherapy with boost
and adjuvant chemo (50%), simplified external radiotherapy (8%), complications (90%),
relapse/retreat (50%), recommended follow-up for 5 years conditioned on survival, productivity
loss for treatment time and f/u procedures
(Stages IVa-IVb)
$59,635
Vaccine dose 1
Vaccine dose 2
$163
Vaccine costs (excluding VAT), wastage, supplies. Not including patient time and transport,
because the vaccine is assumed to be administered through a school-based program.
Vaccine dose 3
$163
$163
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Women’s Time and Transport Cost Estimates
Time and transportation cost estimates for two-way travel to clinical services, including followup visits and hospitalization, were based on two data sources. The time spent travelling and the
costs associated with transport to and from screening were approximated from a prospective
study which determined the time and transportation costs for colorectal screening in Norway
(18). We applied 100 Kroner for roundtrip transportation costs and 60 minutes travelling time for
the screening office visit. The time spent travelling to a hospital to receive cervical cancer
treatment was estimated from a health survey conducted by Statistics Norway for the World
Health Organization, estimated to be 44 minutes one-way (19). The transportation cost for
women seeking cancer treatment was estimated using the published deductible for roundtrip
transportation for hospital-treated patients (260 Kroner) (20). We assumed a four-hour production
loss for each radiotherapy or chemotherapy treatment. As a proxy for production loss, we used
the 2010 average gross monthly income of Norwegian women obtained from Statistics Norway
(33,500 Kroner) and adjusted the wage to include social benefits (40%) paid by employers (21).
Estimation of laboratory costs
Published reimbursement rates for the laboratory analysis of cervical screening tests (22) are
thought to be underestimated. The Norwegian health care system is funded by taxes and patient
co-payments, approximately 80% and 20%, respectively. Screening tests are mainly taken by
general practitioners (GPs), but some are taken by private practicing gynaecologists and in
hospital out-patient clinics. Hospitals are publicly funded and the great majority of them are also
publicly owned. GPs are funded by patient co-payments, per capita payments from the
municipalities and service fees from the Norwegian Welfare and Labour Administration (in
Norwegian: “NAV”) while private practicing gynaecologists are funded by patient co-payments,
block grants from the Regional Health Authorities and service fees from the Norwegian Welfare
and Labor Administration. For both these physician groups we used co-payments, service-fees
and per-capita payments to estimate the cost of their services. Hospitals’ in-patient and outpatient services are funded in part by the DRG system and in part by block grants. The former is
supposed to represent 60% of the total costs. The DRG cost weights are based on costing in a
sample of Norwegian hospitals.
Conventional cytology, liquid based cytology tests (LBC) and HPV tests are analyzed in
microbiology and pathology laboratories whether they are taken by GPs, private practicing
physicians or at out-patient hospital clinics. For in-patients, laboratory costs are included when
estimating DRG weights, and the hospitals do not receive any additional reimbursement for
laboratory tests. For all the others (i.e. the overwhelming majority of tests in the cervical cancer
screening program), the laboratories are funded by means of service fees from The Norwegian
Health Economics Administration (in Norwegian: ”HELFO”). In principle these service fees
shall represent 40% of the total costs. For various political reasons, (see below) laboratory fees
are much lower than the costs would indicate. Since the 1960s, Norway has had several private
laboratories (clinical chemistry, pathology, microbiology) run by physicians working in public
hospitals (mainly professors in the respective disciplines). The physicians worked in these private
laboratories, presumably during their leisure time. The tests performed, however, were paid in
full (fee-for-service) by the national health insurance (tax paid). Public hospitals which
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Supplementary Appendix
performed the same tests for outpatients, received the same fees as private laboratories. The
profits in these private laboratories increased over the years, and different governments
considered the system, which subsidized private business, unreasonable. To squeeze out the
private laboratories, fees were gradually reduced – for private as well as public laboratories.
Although laboratories in public hospitals disliked this squeeze, they survived because hospitals’
main revenue is block grants paid by the government. The process, however, implied that fees
paid to public laboratories far from covered the real costs when taking into account that 40% of
the real costs should be covered by the fees and 60% by the block grants. Because the laboratory
costs represent a small proportion of the total hospital costs, the situation has been financially
viable. The service fees for out-patient laboratory services, however, cannot be used as proxies
for the societal costs of laboratory services.
We therefore used four experts involved in managing microbiology and pathology laboratories to
estimate the real costs of the different tests (Pap smear, LBC, HPV). For each of the tests we
assumed a medium sized laboratory. The need for physicians, laboratory technicians, office space
and capital equipment was based on judgment from the laboratory experts. The cost of cleaning,
heating, clothing and managerial overhead was based on the accounts in two hospitals. The cost
of laboratory equipment and office/laboratory space was based on market prices. It was assumed
that capital equipment has a life of 10 years, and 4% discounting was employed in accordance
with guidelines from the Ministry of Finance. The number of tests was based on expert judgment.
The estimated costs were 277 NOK, 305 NOK and 324 NOK for conventional cytology, LBC
and HPV, respectively (Appendix Table 6). In contrast, Appendix Table 7 lists the published
reimbursement costs used for sensitivity analysis.
Appendix Table 6: Cost of analyzing one conventional smear, one liquid based cytology test,
and one HPV test
Conventional (NOK)
LBC (NOK)
HPV (NOK)
Office space
150 000
150 000
75 000
Electricity and heating
25 000
25 000
12 500
Cleaning
40 000
40 000
20 000
Laboratory personnel
5 740 000
5 180 000
2 492 000
Administrative overhead
130 500
116 000
60 900
Laboratory clothes
45 000
40 000
21 000
Consumables
1 500 000
2 880 000
3 500 000
IT services
90 000
80 000
42 000
Service of laboratory equipment
100 000
100 000
100 000
Capital costs
493 164
540 000
150 000
Total
8 313 664
9 151 000
6 473 400
Estimated number of tests per year
30 000
30 000
20 000
Unit cost of tests
277
305
324
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Supplementary Appendix
Appendix Table 7: Published reimbursement costs for a conventional smear, liquid based
cytology, and HPV test used in sensitivity analysis
Test
Reimbursement rate
Conventional
cytologya
23 NOK
Liquid-based
cytologyb
70 NOK
HPV-DNA
testingc
277 NOK
a Reimbursement
code: 705e (34)
b Reimbursement code: 705f (34)
c Reimbursement code: 701k (34)
Part III: Strategies and assumptions
Each cervical cancer prevention strategy considered in the cost-effectiveness analysis has
multiple attributes: 1) the age at which screening starts; 2) the frequency with which screening is
performed (e.g., the screening interval); 3) the screening tests used as primary screening tests and
triage tests for younger women; 4) the screening tests used as primary screening tests and triage
tests for older women; 5) the age at which the screening tests used for younger women are
replaced by those used for older women; 6) the use of prophylactic vaccination for preadolescent
girls. Screening strategies included for consideration in this analysis were chosen based upon
plausibility – those recommended by current guidelines and those under consideration by policymaking organizations. For example, we do not consider strategies that use primary HPV DNA
testing with cytology triage for all ages. We considered strategies most likely to be accepted by
Norway in our primary analysis, and a wider range of potential strategies in a secondary analysis.
We made the following assumptions for all analyses: (1) the current strategy utilises conventional
cytology while the proposed strategies utilise LBC; (2) among women with underlying CIN23 or
worse, colposcopy directed biopsy determines the actual histology of the cervix; (3) all women
with CIN23 or worse are treated according to standard guidelines (The Norwegian Medical
Association, 2010); (4) women with any confirmed abnormality, even if treated successfully for
CIN, are screened annually until three consecutive negative results; (5) women with CIN1 are not
treated, but monitored at an increased intensity (i.e., annually) until three consecutive negative
results; (6) within the proposed strategy for older women who have not had CIN, one negative
HPV test, regardless of previous test history, will return women to regular screening at the
predefined interval; and (7) if at any point, a woman returns an HPV-positive, cytology-positive
result, she will be referred directly to colposcopy/biopsy (Appendix Table 8).
Vaccine coverage with the 3-dose vaccine course was assumed to be 100% in the base case for
pre-adolescent girls at age 12. Vaccination was assumed to provide complete life-long protection
against vaccinated types, though duration of protection was also explored in a sensitivity analysis
where we repeated the base case analysis with a vaccine that provides 15 years of protection for
pre-adolescent vaccinated girls. Vaccine-induced immunity is modelled in a similar way to
immunity derived from clearing an HPV infection. The probability of infection with the
vaccinated type is reduced – in the base case, this reduction was 100% though alternative
assumptions were explored in sensitivity analyses (for example, we repeated the base case
analysis with a vaccine that reduced the HPV type-specific infection probability by 75% for each
HPV type targeted by the vaccine). The reduction in the infection risk of other closely-related
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Norwegian Cervical Cancer Prevention
Supplementary Appendix
Appendix Figure 6: Current screening algorithm for Norwegian women
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Supplementary Appendix
Appendix Figure 7: Proposed screening algorithm for older women
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Supplementary Appendix
Appendix Table 8: Strategy attributes and assumptions*
Strategy Attributes
Screening start age
Screening frequency for younger women
Screening frequency for older women
Screening strategy for younger women
Screening strategy for older women
# of additional HPV+/Cytology- results
needed before being referred to colposcopy
(older women only)
Follow up wait time for HPV+/Cytologyresults (older women only)
Screening switch age
Age at vaccination
Strategy Assumptions
Screening coverage
Alternatives
25 years old
Never
Every 3 years
Never
Every 3 years
Every 4 years
Every 5 years
Every 6 years
Cervical cytology followed by combination HPV-DNA/cytology testing for ASCUS/LSIL
Cervical cytology followed by combination HPV-DNA/cytology testing for ASCUS (secondary
analysis only)
Cervical cytology followed by combination HPV-DNA/cytology testing for ASCUS/LSIL
Cervical cytology followed by combination HPV-DNA/cytology testing for ASCUS (secondary
analysis only)
HPV-DNA testing followed by cervical cytology for all positive results
One
Two
Three
6 months
12 months
31 years old (secondary analysis only)
34 years old
12 years old
Base case: 100%
Scenario analysis
Diagnostic work-up for HSIL
Diagnostic work-up for LSIL (for current
strategy and younger women)
Diagnostic work-up for ASCUS (for current
strategy and younger women)
Verification of CIN2/3
Treatment of CIN2/3 or worse
Management of CIN1 or negative results
Duration of vaccine efficacy
Vaccine efficacy
Girls receiving all 3 courses of vaccine
Cross-protection with non-vaccination types
Herd immunity from mass vaccination
Colposcopy/biopsy
Triage with combination HPV-DNA and cytology(see ASCUS below for management)
Colposcopy/biopsy (secondary analysis only)
Triage with combination HPV-DNA and cytology:
-High-risk HPV positive and positive cytology: colposcopy/biopsy
-High-risk HPV positive and negative cytology: repeat combo test (if persistent HPVDNA test, refer to colposcopy/biopsy)
-High-risk HPV negative: return to regular screening
Colposcopy directed biopsy
Standard guidelines
Monitored every 12 months until 3 consecutive negative results
Base case: Lifelong
Wanes after 15 years
Base case: 100%
75%
100%
None
Base case: None
10% (80% vaccinated population)
20% (80% vaccinated population)
*HPV: Human papillomavirus; LSIL: Low-grade squamous intraepithelial lesion; ASCUS: Atypical squamous cells
of undetermined significance; CIN: Cervical intraepithelial neoplasia; DNA: Deoxyribonucleic acid
HPV types not covered by the vaccine’s targeted HPV types for vaccinated women was assumed
to remain unchanged (i.e., no cross-protection effects). No indirect effects of vaccination (i.e.,
herd immunity) are assumed in the base case. In sensitivity analysis, the implications of this
assumption were explored, as unvaccinated women (at vaccine coverage levels of 80%) have
their HPV type-specific probabilities of infection reduced by 10 or 20% for HPV types targeted
by the vaccine.
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Norwegian Cervical Cancer Prevention
Supplementary Appendix
Part IV: Additional Results
Additional results from sensitivity analyses
The optimal strategy, given a cost-effectiveness threshold of $83,000 per year of life saved
(YLS), under each assumption varied in the sensitivity analyses is shown in Appendix Table 9.
For unvaccinated women, the primary screening interval for older women was extended beyond
four years when: 1) office costs were doubled; 2) the sensitivity of cytology was below 50%; and
3) when the underlying risk of infection with both HPV-16, -18 was reduced by 20% in
unvaccinated women (herd immunity). When we explored a distribution of screening compliance,
(see distribution used for the scenario analysis in Appendix Table 10), the optimal strategies
under base case assumptions remained constant. In all cases of our sensitivity analyses, only the
follow-up management of HPV+/Cyt- women was influenced when we varied our base case
assumptions. For vaccinated women, there were two situations where a vaccination-only strategy
was the only intervention below the cost-effectiveness threshold. This pertained to: 1) doubling
office visit costs; and 2) when the sensitivity of cytology was below 40%.
Appendix Table 9: Summary of optimal strategies under a range of assumptions
Unvaccinated women
Cancer Treatment Costs
(including time/transport)
Base case
4yrs+3 persis+12mo
($76,000/YLS)
50%
4yrs+3 persis+12mo
($78,000)
200%
4yrs+3 persis+12mo
($72,000)
BC on
Frontier?
50%, 200%
No
Yes, Yes
No
Yes
Published Screening Costs
4yrs+3 persis+12mo
($76,000/YLS)
Colposcopy Costs
(including time/transport)
4yrs+3 persis+12mo
($76,000/YLS)
4yrs+1 persis+12mo
($81,000)
4yrs+3 persis+12mo
($76,000)
A little
No, Yes
Office Costs
(including time/transport)
4yrs+3 persis+12mo
($76,000/YLS)
4yrs+3 persis+6mo
($73,000)
6yrs+3 persis+12mo
($50,000)
Yes
Yes, No
CIN Treatment Costs
(including time/transport)
4yrs+3 persis+12mo
($76,000/YLS)
4yrs+3 persis+12mo
($76,000)
4yrs+3 persis+12mo
($77,000)
No
Yes, Yes
Optimal
Changed
from BC?
BC on
Frontier?
40%, 50%
Yes
No, No
Optimal
Changed
from BC?
BC on
Frontier?
10%, 20%
Yes
Yes, Yes
Optimal
Changed
from BC?
BC on
Frontier?
15%, 20%
No
Yes, Yes
Cytology Sensitivity
Herd Immunity
(80% vaccine coverage)
Scenario Analysis
Base case
4yrs+3 persis+12mo
($76,000/YLS)
Base case
4yrs+3 persis+12mo
($76,000/YLS)
Base case
4yrs+3 persis+12mo
($76,000/YLS)
4yrs+3 persis+12mo
($72,000)
Optimal
Changed
from BC?
40%
5yrs+1persis+6mo
($20,000)
10%
4yrs+3 persis+12mo
($80,000)
Scenario 1
4yrs+3 persis+12mo
($75,000)
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50%
5yrs+1persis+6mo
($62,000)
20%
5yrs+2persis+12mo
($74,000)
Scenario 2
4yrs+3persis+12mo
($76,000)
Norwegian Cervical Cancer Prevention
Supplementary Appendix
Vaccinated women
Base case
6yrs+2persis+12mo
($80,000/YLS)
Cancer Treatment Costs
(including time/transport)
50%
6yrs+2persis+12mo
($82,000)
200%
6yrs+2persis+12mo
($76,000)
BC on
Frontier?
20%, 200%
No
Yes, Yes
A little
Yes
Published Screening Costs
6yrs+2persis+12mo
($80,000/YLS)
Colposcopy Costs
(including time/transport)
6yrs+2persis+12mo
($80,000/YLS)
6yrs+1persis+12mo
($79,000)
6yrs+3persis+12mo
($81,000)
A little
No, Yes
Office Costs
(including time/transport)
6yrs+2persis+12mo
($80,000/YLS)
6yrs+1persis+12mo
($68,000)
Vaccinate only§
($17,000)
Yes
Yes, Yes
CIN Treatment Costs
(including time/transport)
6yrs+2persis+12mo
($80,000/YLS)
6yrs+2persis+12mo
($79,000)
6yrs+2persis+12mo
($81,000)
No
Yes, Yes
Optimal
Changed
from BC?
BC on
Frontier?
40%, 50%
Yes
No, No
Optimal
Changed
from BC?
BC on
Frontier?
75%, 15yrs
A little
Yes, Yes
Optimal
Changed
from BC?
BC on
Frontier?
15%, 20%
No
Yes, Yes
Base case
6yrs+2persis+12mo
($80,000/YLS)
Cytology Sensitivity
Base case
6yrs+2persis+12mo
($80,000/YLS)
Efficacy/Duration
Base case
6yrs+2persis+12mo
($80,000/YLS)
Scenario Analysis
6yrs+3persis+6mo
($81,000)
Optimal
Changed
from BC?
40%
Vaccinate only ฿
($17,000)
50%
6yrs+1persis+6mo
($83,000)
75% efficacy
6yrs+2persis+12mo
($63,000)
15yrs
6yrs+3persis+6mo
($72,000)
Scenario 1
6yrs+2persis+12mo
($81,000)
Scenario 2
6yrs+2persis+12mo
($83,000)
Optimal strategy given $83,000/YLS threshold where all optimal strategies involve switching at age 31, triage younger women with
ASCUS/LSIL using HPV testing unless otherwise indicated. ICERs rounded to the nearest 1000's. BC on Frontier: Base case on
efficiency frontier; Xyrs+Xpersis+Xmo: screening interval for older women + number of additional persistent HPV-positive,
cytology-negative results prior to colposcopy/biopsy referral + number of months prior to follow-up screening for HPV-positive,
cytology-negative women.
§ Next most efficient strategy was screening 6yrs+2persis+12mo at $137,000/YLS
฿ Next most efficient strategy was screening 6yrs+1persis+6mo at $84,000/YLS
Appendix Table 10: Distribution of screening compliance used in scenario analysis
Scenario 1:
Screening interval
Never participate
Comply with
recommendation (n)
Less frequently (n+1)
Scenario 2:
Distribution
15%
70%
15%
Screening interval
Never participate
Comply with
recommendation (n)
Less frequently (n+1)
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Distribution
20%
70%
10%
Norwegian Cervical Cancer Prevention
Supplementary Appendix
Part V: References
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