Normal Spirometric
Reference Equations – When
the Best Fit May Not be the
Best Solution
Allan Coates, B Eng (Elect) MDCM
University of Toronto
Hospital for Sick Children, Toronto
2011 Canadian Respiratory Conference
The “Holy Grail” of Reference
Equations
 Representative of the population of interest
 One equation for all ages for each sex
 Simple to program into the spirometers
 Sufficient numbers to give confidence to the lower
limit of normal (LLN)
Definitions of “Normal” Values
 American Association of Clinical Chemistry
 Based on “healthy” individuals
 Plus/minus 2 standard deviations or 95% of the
populations
 Clearly the variability of a value in the general population
whether or not associated with a “disease” will impact the
range of values within 2 SD
 How does this fit with our spirometry reference values?
Health vs Disease
 If 1000 perfectly healthy individuals had
spirometry preformed, 2.5% would be below 2 SD
and 2.5% above
 By definition, none would have disease
 Hence any clinical decision based on spirometric
values would depend on pre test probability
Pre Test Probability
 Definition
 Pretest Probability is defined as the probability of
the target disorder before a diagnostic test result is
known
 In respiratory medicine, only extreme
deviations from the reference values are
pathognomonic for disease
 Hence pretest probability is an essential part of
diagnosis
Who is Healthy?
 NHANES III rejection criteria
 Smoking (cigarettes, cigars, pipe)
 MD dx of asthma, chronic bronchitis, emphysema
 Whistling or wheezing in chest (last 12 months and
apart from colds)
 Persistent cough for phlegm
 Moderate shortness of breath
 Of the 15,000 plus acceptable spirometry
tracings where did this leave us?
Hankinson et al Am J Resp Crit Care Med 1999
15,503 Acceptable Adult Tests
 Smokers
 MD Dx asthma, COPD
 Whistling or wheezing in chest
 Persistent cough and/or phlegm
 Moderate shortness of breath
 Over 80 (too few observations)
7115 Remaining
6465 Remaining
5934 Remaining
5651 Remaining
4803 Remaining
4634 Remaining
 In adults, the rejection rate was > 2/3
Hankinson et al Am J Resp Crit Care Med 1999
What about Children?
 There were 3917 good test in 8-16 year olds
 Rejection criteria
 Smoking
3580 Remaining
 Asthma, chronic bronchitis
3170 Remaining
 Wheezing, cough, phlegm
2796 Remaining
 In pediatric sample, the rejection rate was > 1/4
Lower Limit of Normal - Definition
200
FEV1 values
less than LLN
are considered
to be below
normal
-
Number of Subjects
This is a plot of the FEV1
measured from a group of normal,
non-smoking men who were all 60
years old and 180 cm tall.
150
The predicted value for FEV1 for
someone in this group is 3.5L.
-
100
The shaded area represents 5% of
normal men, age 60, height 180
cm, with the lowest FEV1.
95 %
5%
-
This defines the Lower Limit of
Normal (LLN).
50-
LLN for FEV1 for this group is 2.6L
-
0-
1
2
3
Predicted
Lower
Limit ofValue
Normal
Ref: MR Miller –
www.millermr.com
4
5
6
FEV1 in Liters
5% of the population with normal
lungs have FEV1 below LLN
95% of the population with normal
lungs have FEV1 above LLN
Controversies over LLN
 Most of us were trained on percent predicted and
the concept that FEV1 and FVC ≥ 80% was normal
 In other words, we had our own concept of LLN
 In fact, for NHANES III, for FVC, LLN is 84%
predicted for a tall young male and 75% for a short
elderly female
 All of us use ± 2 SD for electrolytes with normal
(95% of healthy) being inside 2 SD
 We have better PFT data – Why not use it?
LLN for the FEV1/FVC ratio
NHANES III
Hankinson, 1999
While the ratio clearly decreases with age,
these data showed that the variance was not
affected by age or height. ie, homoscedastic.
Thanks to Bruce Culver
Concept of Homoscedasticity
 For any given value of x (eg
height) the standard deviation of
y (eg FEV1) is the same
 The standard deviation depends
on both variability and n
 Reference values from small
samples may not meet this
requirement
NHANES III Approach
 Using a polynomial analysis for height and age,
attempted to have one equation for FEV1 and FVC
 Had to settle for separate equations that joined at
18 for females and 20 for males
 Also included values for FEV1/FVC, PEF, FEV6 and
FEF25-75 and LLN for all parameters
 Reference values for Caucasian, Mexican
Americans and African Americans between 8 and
80 years
Problems with NHANES III
 Numbers small at either extremes of the ages
giving rise to inhomoscedasticity
 Extrapolation to ages less than 8 gave rise to
significant over estimation in males
 While the curves met at the 18 (♀s) and 20
years (♂s), the curves were discontinuous
DESPITE THESE CONCERNS, IT WAS
WIDELY ACCEPTED AND EASILY
PROGRAMMED INTO SPIROMETRIC
SOFTWARE
Solutions
 The values from pediatric series down to age
5 (Corey et al, Lebeques et al and Rosenthal
et al were found to over lap where ages
overlapped with NHANES and added to the
series
 New data analysis by the LMS method
 Resulting curves were “continuous”
LMS: lambda, mu, sigma Method
.
The distribution of the normal population at each
point along the continuum is described by:
mu
the median
sigma
the coefficient of variance
lambda
an index of skewness.
The result is a series of equations linked by
“splines” with coefficients from a set of look up
tables, read by computer.
The method creates a smooth continuous
predicted value (given by the median, mu )
Stanojevic et al Am J Resp Care Med 2008
The sigma and lambda terms allow for the 5th
percentile LLN to be independently determined
throughout the age-height spectrum
M
F
FEV1/FVC ratio
LLN
Stanojevic
2008
Stanojevic compared to NHANES III
Stanojevic vs NHANES
 Mores sophisticated statistical approach (Coles et
al 2008) with somewhat better “accuracy” overall
 Solved the problem of age limitation of NHANES
 Smoothed the 18 and 20 year transition points
 NHANES uses simple polynomial equation, easy
to program into a computer or hand calculator
 The complex mathematical approach of
Stanojevic has not been adapted (to date) in any
commercial spirometric software
Reference Sources - Spirometry
NHANES III v Knudson, Crapo,
Glindmeyer
Does One Set Over Another Really
Make a Difference?
 The difference between NNANES, Stanojevic and
older series in adults is too small to result is
serious clinical errors
 This is not the case in children
Differences Depending on Equations
Hankinson breaks down when out of range
Knudson equations just do not apply to young
Subbarao et al Pediatr Pulmonol 2004
ERS Task Force – Global Lungs Initiative
Project to collate available international lung function
data to develop new reference equations.
Unlike the 1983-93 ECSC compilation which merged
equations, the current effort has collected raw data
and is using the LMS method to analyze it.
Data from 150,000 individuals from 71 countries.
Co-chairs: Janet Stocks – UK, Xvar Baur – Germany
Graham Hall – ANZRS, Bruce Culver – ATS
Steering Comm includes: Phil Quanjer, Sonja Stanojevik,
John Hankinson, Paul Enright.
ERS
Global
Lungs
Initiative
Problems and Challenges
 NHANES III is from one data set gathered on the
same equipment under the same conditions
 The Stanojevic data is a composite of 4 sets from
different countries and different equipment
 The ERS Task Force will have the same problems
with multi site challenges
 The challenge is enough numbers to have
confidence in the LLN but have identical
methodology and homogeneous sample
What to Do?
 NHANES III is the largest data set to date and
while the polynomial approach may not be as
scientific as the LMU approach, few if any clinical
errors would occur for patients ≥ 8 years
 The Stanojevic analysis is the best available and
while cumbersome, can be used for ≥ 5 years
 New Canadian data is being analyzed and should
be available in the next 18 months
Conclusions
 We do not have a perfect data set yet so reference
equations are less than absolute ESPECIALLY FOR
NON CAUCASIANS
 We have much more confidence and better data on
the LLN
 There will always be a certain inaccuracy in the
application of the results of any pulmonary
function test, especially near the LLN