Why the FEV1/FVC ratio LLN as a percent of the predicted FEV1/FVC ratio is important

My medical director and I had a discussion today about where the cutoff for a normal FEV1/FVC ratio would be for a 93 year old patient of his. Part of the problem is that there are almost no reference equations for patients this age and the best you can usually do is to extrapolate. Another part is that anybody in their 90’s is a survivor and must have had good lung function throughout their life to reach that age, which means that they aren’t average so it’s not clear how well extrapolation actually works in this population. The final part is that the guidelines for PFT interpretation that are used by my lab were put into place about 40 years ago and reflect the thoughts at that time. I updated part of the guidelines with the 2005 ATS/ERS interpretation algorithm about 10 years ago, but the thresholds for normalcy (as well as the reference equations we use) still haven’t changed all that much. I’ve brought this issue up a number of times over the years (usually every time I get a new medical director) but haven’t gotten a consensus from the pulmonary physicians on either the need for change or for what threshold values should be used.

Anyway, both my medical director and I felt felt that the LLN for the FEV1/FVC ratio (when viewed as a percent of the predicted FEV1/FVC ratio) is probably lower for a 75 year old (and certainly for a 93 year old) than it is for a 25 year old, and that the current lab guidelines for interpretation were probably diagnosing airway obstruction in the elderly more often than they should. My lab currently uses the NHANESIII reference equations for spirometry however, and I wasn’t sure they showed this particularly well since the equations for the FEV1/FVC ratio and its LLN are quite simplistic compared to those for FVC and FEV1.

The NHANESIII reference equations were published in 1999 and at that time they were derived from the largest population that had ever been studied (7428 subjects, 40.9% male, 59.1% female) and with the most sophisticated statistical analysis that had been used up until that time. In 2012 however, the Global Lung Function Initiative (GLI) released a set of reference equations using data obtained from 73 centers world-wide on 97,759 subjects (44.7% male, 55.3% female). Statistical analysis of the GLI data was performed using the Lambda, Mu, Sigma (LMS) approach and a set of equations were derived that covered ages 3 to 95.

I have some reservations about how well the GLI equations match the population served by my lab but it’s a moot point whether I like them or not since even now, 5 years after the GLI equations were published, my lab’s software has not been updated to include them. The reason for this is that the GLI spirometry equations use what are called “splines” to generate the spirometry reference values and these are taken from a look-up table. My lab’s software does have an equation editor but it will not accommodate lookup tables so the GLI equations can’t be added. I’m sure our equipment manufacturer could get around this if they really wanted to, but so far it hasn’t happened.

I do have a lot of respect for the GLI equations however, and think that the overall view they give of the normal distribution of FVC, FEV1 and the FEV1/FVC ratio is far more correct than those of any prior studies. Using a spreadsheet tool downloaded from the GLI that lets me generate the GLI spirometry predicted values and the NHANESIII reference equations I decided to take a closer look at their predicted FEV1/FVC ratios and their LLNs.

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What’s normal about the GLI DLCO reference values?

The Global Lung Initiative (GLI) has been working for several years to develop a universal reference equation for DLCO. Although this endeavor is not necessarily complete, an article describing the GLI DLCO reference equation for Caucasians was published in the September issue of the European Respiratory Journal as an open access article and can be downloaded by anyone. The Global Lung Initiative in general and the authors of the article more particularly are to be commended for this monumental work and for the insight it brings to understanding the normal distribution of DLCO.

The data used to develop the GLI reference equations was originally derived from 19 studies the GLI identified to have been performed on lifetime nonsmoking populations. 85% of the results came from Caucasian populations and the remaining from two Asian sources. The authors felt that there weren’t a sufficient number of non-Caucasians to accurately describe any ethnicity-based differences in DLCO and for this reason only the Caucasian data was used.

From this data some results were excluded because of:

  • FEV1 > 5 Z-scores or < 5 Z scores
  • Height (children only, >5 or <5 Z scores)
  • VA less than VC
  • Elevated BMI (>30 kg/m2 in adults, >85% centile in children)
  • Missing demographic information

After these exclusions 9710 results remained of which 4859 were male and 4851 were female. DLCO values were corrected for altitude and FiO2 and uncorrected for hemoglobin. Reference equations were derived using the LMS (Lambda, Mu, Sigma) method.

Note: The study population consisted of individuals from 4.5 to 91 years of age and GLI reference equations are valid across this entire span. The majority of the existing DLCO reference equations available to me are for an adult population and for this reason this discussion of the GLI DLCO reference equations will be limited to this portion of the age range. The GLI article also includes reference values for KCO and VA but these subjects will also be saved for a separate discussion.

Not surprisingly, DLCO is highest in tall and young individuals, and lower in short and elderly ones.

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