Comparison of spirometry criteria for the diagnosis of COPD: results from the BOLD study

Although chronic obstructive pulmonary disease (COPD) is recognised as a major public health problem worldwide, estimates of its prevalence vary widely 1. Much of this variation probably reflects differences in the populations studied, spirometry methods and data quality control, and the rules used to define COPD. For example, self-reported physician diagnosis of COPD typically results in estimated prevalences well below those obtained based on spirometry 1, 2.

Although no gold standard definition of COPD exists, published guidelines recommend use of spirometry to define it 3, 4. However, even spirometry-based COPD prevalence estimates can vary by two-fold or more, depending on the definition used to classify mild disease 5, 6. The most widely used definition comes from the Global Initiative for Chronic Obstructive Lung Disease (GOLD), which recommends using a post-bronchodilator forced expiratory volume in 1 s (FEV₁) to forced vital capacity (FVC) ratio <0.7 to define irreversible airflow limitation, and the FEV₁ to stage disease 3. This “fixed ratio” approach, while easy to apply, appears to overestimate COPD in older individuals 2, 7–10 and to underestimate it in young adults 9, 11. Alternative definitions that account for normal ageing can alleviate this bias 9, 12 but, in turn, this raises questions about which reference equations are appropriate for which populations. In addition, if pre- (rather than post-) bronchodilator spirometry is used, COPD prevalence may be overestimated by as much as 30% 8, 10, 13, 14.

The Burden of Obstructive Lung Disease (BOLD) study is an international effort to collect population-based estimates of the prevalence and economic burden of COPD using standardised methods 15, 16. Using BOLD study data, we examined the impact on prevalence estimates of using the fixed ratio criterion versus various other spirometry-based definitions of COPD. We also compare the effects of using central versus site-specific prediction equations and of using the FEV₁/FEV₆ ratio in place of FEV₁/FVC.

METHODS AND MATERIALS

The design of the BOLD study is described in detail elsewhere 15, 16 and only summarised here. Participating entities in the BOLD Collaborative Research Group are listed in the online supplement.

Analysis

To provide comparability with earlier reports 16, the site-specific prevalences presented in figure 1⇓ are population-based estimates reflecting sampling designs used at each site. For all other analyses, data are pooled across sites and presented as unweighted prevalences with standard errors accounting only for correlations within the site and, where applicable, for clustering in the sampling plan. Comparisons of the prevalence estimates in figures 1⇓–⇓3⇓ and in table 3⇓ were computed using McNemar's test.

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Fig. 1—

Comparison of chronic obstructive pulmonary disease (COPD) prevalence for various alternative definitions of COPD for participants in the Burden of Obstructive Lung Disease (BOLD) study. a) Contrasting prevalences for each definition within site. ▪: fixed ratio; ▓: lower limit of normal (LLN) (ratio); □: Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2–4; ▒: LLN (ratio) and forced expiratory volume in 1 s (FEV₁) <80% predicted; ░: LLN (ratio) and LLN (FEV₁). b) Contrasting site differences within each definition. Significant site-to-site variability persisted for each of the estimates even after adjusting for age, sex, cigarette smoking (pack-yrs), body mass index, years worked in a dusty job and interactions of sex with both age and smoking history in logistic regression models (Wald statistics ranging from 7.1 to 8.6, all p-values <0.0001). Prevalences based on the fixed ratio are significantly higher than for all other estimators at each site (all p-values <0.001). ▪: Guangzhou, China; ▨: Adana, Turkey; ▧: Salzburg, Austria; ▦: Reykjavik, Iceland; ▒: Cape Town, South Africa; □: Krakow, Poland; ▓: Hanover, Germany; ▪: Bergen, Norway; ░: Vancouver, BC, Canada; : Manila, Philippines; : Lexington, KY, USA; : Sydney, Australia; ▣: London, UK; ▩: Uppsala, Sweden.

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Fig. 2—

Prevalence of “chronic obstructive pulmonary disease” among healthy never-smokers in the Burden of Obstructive Lung Disease (BOLD) study (data from all sites combined). Wald statistics for comparing the four age groups (and adjusted for site, sex, body mass index and years worked in a dusty job) ranged from 62.6 for the fixed ratio criterion, to 24.5 for Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2–4, to ∼6.6 for the two analogues of these criteria in which the forced expiratory volume in 1 s (FEV₁) to forced vital capacity (FVC) ratio <0.7 is replaced by FEV₁/FVC<LLN (lower limit of normal), to 3.4 for the “LLN (FEV₁/FVC) and LLN (FEV₁)” criteria. All were statistically significant. Significant sex–age interactions were observed only for the fixed ratio criterion. Except for the LLN (ratio) criterion for the lowest age group (p = 0.14), the fixed ratio prevalence estimates were all significantly greater than those for each of the other estimators (p<0.0001). ▪: fixed ratio; □: LLN (ratio); ▵: GOLD stages 2–4; ▾: LLN (ratio) and FEV₁ <80% predicted; •: LLN (ratio) and LLN (FEV₁).

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Fig. 3—

Prevalence of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2–4 chronic obstructive pulmonary disease in the Burden of Obstructive Lung Disease (BOLD) study using the Third US National Health and Nutrition Examination Survey (NHANES-III) and site-specific prediction equations (data from all sites combined). Site differences were greater when using the NHANES-III equations (Wald statistic 9.5, p<0.0001) or Hordaland county equations (Wald statistic 8.4, p<0.0001) than when using the site-specific equations (Wald statistic 4.7, p<0.0001). The estimated prevalences were significantly higher (p<0.0001 for all age groups) when using common reference equations for all sites (NHANES-III and Hordaland County) than when using local prediction equations. The NHANES-III and Hordaland County prevalence estimates differed significantly overall and for the oldest age group. ♦: NHANES-III; □: Hordaland County; ▵: local equations.

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Table 3—

Prevalence of chronic obstructive pulmonary disease(COPD) computed using FEV₁/FEV₆ in place of FEV₁/FVC

A desired characteristic of any prevalence estimator is that it gives comparable estimates in different populations after adjusting for known confounders. In order to compare the residual site-to-site variability associated with our various prevalence estimators, we report the Wald statistic for the “site” effect, as derived from logistic regression models that adjusted for age (40–49, 50–59, 60–69 and ≥70 yrs), sex, cigarette smoking history (never-smokers, 0–9, 10–19 and ≥20 pack-yrs), BMI (<20, 20–25, 25–30, 30–35 and >35 kg·m⁻²), years worked in a dusty job (0, 1–9 and ≥10 yrs) and interactions of sex with both age and smoking history. We also report Wald statistics for testing the significance of age in selected regression models. Where appropriate, we tested heterogeneity of age effects across strata using appropriate interaction terms. Under the null hypothesis of no effect, the Wald statistic will have an F-distribution with an expected value equal to one, and higher values indicate greater heterogeneity across subgroups. All Wald tests are adjusted for clustering in the sampling plan.

All analyses were conducted using Stata version 9.2 (Stata Corp., College Station, TX, USA).

RESULTS

Participants exhibited marked differences in smoking patterns across sites and between sexes within sites (table 4⇓). BOLD sites also differ markedly in prevalences of occupational and other potential COPD risk factors 16.

Use of the fixed ratio criterion (GOLD stage 1 and higher) produced overall population prevalence estimates that, for each site, were significantly greater than those for each of the other estimators (all but one p<0.0001). The fixed ratio estimates were generally 5–11 percentage points higher than those for GOLD stages 2–4 (fig. 1a⇑). The LLN (FEV₁/FVC) criterion produced estimates that tended to be intermediate to these two GOLD-based definitions, although generally closer to the GOLD stages 2–4 criterion than to the fixed ratio criterion. The added requirement of an FEV₁ <80% pred and an FEV₁/FVC ratio below the LLN resulted in estimates that were 1–3 percentage points lower than estimates for GOLD stages 2–4. Finally, use of FEV₁<LLN in place of FEV₁ <80% pred in this latter definition further reduced estimates (although generally by less than one percentage point). These patterns were generally consistent across sites.

Regardless of the definition used, we observed sizable site-to-site variation in prevalence estimates (fig. 1b⇑). After adjusting for potential confounders, site-to-site variance in COPD prevalence (as measured by the Wald statistic) ranged from 7.1 to 8.6 and was lowest (7.1 and 7.3, respectively) using the “LLN (FEV₁/FVC) and LLN (FEV₁)” and “LLN (FEV₁/FVC) and FEV₁ <80% pred” criteria, respectively. These Wald statistics all indicated highly statistically significant (p<0.0001) residual site-to-site variability in prevalence estimates.

All prevalences reported in figure 1⇑ were lower than they would have been had we based them on pre-bronchodilator measurements (see online supplementary material). For the fixed ratio criterion, absolute declines between pre- and post-bronchodilator values ranged from 1 to 11 percentage points across centres, while using GOLD stages 2–4 instead of the fixed ratio criterion led to a decline in prevalence ranging from 1 to 6 percentage points across centres. On a relative basis, prevalence estimates declined between 25% to 29% (depending on the definition used) across the five measures in going from pre- to post-bronchodilator measurements.

The prevalence of “COPD” per the fixed ratio criterion increased sharply with age even among healthy never-smokers (fig. 2⇑), a population in which COPD is expected to be rare. By contrast, for the other measures we observed much more muted increases with age and, except for the LLN (ratio) criterion for the lowest age group (p = 0.14), the fixed ratio prevalence estimates were all significantly greater than those for each of the other estimators (p<0.0001). These age-related increases in prevalence were lowest for the “LLN (FEV₁/FVC) and LLN (FEV₁)” and “LLN (FEV₁/FVC) and FEV₁ <80% pred” criteria, for which the age-specific prevalence estimates varied from 2% among 40 yr olds, to 4–5% among those aged ≥70 yrs. We observed the same general patterns within each site (data not shown).

The Wald statistic for testing for age effects in figure 2⇑ dropped from a high of 62.6 for the fixed ratio criterion to 24.5 for GOLD stages 2–4, to ∼6.6 for the two analogues of these criteria in which FEV₁/FVC <0.7 is replaced by FEV₁/FVC<LLN, and to 3.4 for the “LLN (FEV₁/FVC) and LLN (FEV₁)” criteria. All were statistically significant. We found modest evidence of a statistically significant sex-age interaction using the fixed ratio criterion (Wald statistic 3.1, p = 0.027) and no evidence of statistically significant sex-age interactions in these healthy never-smokers using any of the other prevalence estimators.

When we assessed site differences in the group of healthy, never-smoking individuals, we observed smaller site differences for the GOLD stages 2–4 criterion (Wald statistic 1.6) than for the LLN (FEV₁/FVC) criterion (Wald statistic 2.9), although once again the smallest site differences were seen for the “LLN (FEV₁/FVC) and LLN (FEV₁)” and “LLN (FEV₁/FVC) and FEV₁ <80% pred” criteria (Wald statistic 0.9–1.1). Indeed, for both of these latter criteria, the site differences did not come close to reaching statistical significance (p>0.35), whereas for the other three criteria the p-values were all less than 0.07.

Figure 3⇑ illustrates the impact on prevalence of using a single common prediction equation (the US NHANES-III Caucasian equations or the Hordaland County Respiratory Health Study equations) versus site-specific prediction equations. For both males and females, the estimated GOLD stage 2–4 prevalences were higher (by 2–3 percentage points overall; p<0.0001) when using common reference equations for all sites (NHANES-III and Hordaland County) than when using local prediction equations. The NHANES-III and Hordaland County prevalence estimates were generally similar, although they differed significantly overall and for the oldest age group. The Wald statistic for site differences computed from the site-specific equations (4.7) was less than the Wald statistic for the NHANES (9.5) and Hordaland County (8.4) equations, although all were highly statistically significant (p<0.0001). We observed similar patterns when we replaced the GOLD stage 2–4 criterion with the LLN (ratio) and FEV₁ <80% pred criterion (data not shown), although the Wald statistics were closer (6.5 versus 7.3 and 8.9).

Finally, the use of the FEV₁/FEV₆ in place of the FEV₁/FVC when using the “LLN (FEV₁/FVC) and FEV₁ <80% pred” criterion had little clinically relevant impact on prevalence estimates, whether computed overall, by age or smoking history categories, or by site (table 3⇑). When we did observe statistically significant differences, the prevalences were generally smaller for the FEV₁/FEV₆-based criterion.

DISCUSSION

This analysis of data from the BOLD study confirmed previously reported limitations associated with the use of the fixed ratio criterion to define COPD. Adjusting the FEV₁/FVC for normative ageing effects appears to reduce the rate of false-positive diagnoses that has been reported for older individuals 2, 7–10, and the added requirement of a low FEV₁ further reduced the age-related increases in COPD prevalence seen among healthy never-smokers.

A strength of this analysis is that data were gathered using a standardised approach from a wide range of populations, with close attention paid to spirometry quality control. The qualitative similarity of results across sites (fig. 1a⇑) provides strong evidence for the robustness of our findings. The wide variation in characteristics of BOLD sites enabled us to use site-to-site variation in prevalence (assessed using the Wald statistic) as a convenient metric for comparing alternative measures of COPD prevalence, since a desired characteristic of any prevalence estimate is that it yields comparable estimates in different populations after adjusting for known risk factors.

An obvious limitation of this analysis is the lack of a gold standard against which to assess our putative definitions of COPD (indeed, a more accurate descriptor of what we are measuring may simply be chronic airflow limitation). Nonetheless, it is possible to evaluate how alternative definitions perform in individuals who have a low a priori probability of disease. Our results confirm previous reports that the fixed ratio criterion lacks specificity and that, as age increases, increasingly misclassifies apparently healthy never-smokers as having COPD 2, 7–10, 12. This pattern of (apparent) misclassification with increasing age was greatly muted by adding the requirement that the FEV₁ % pred be below a defined threshold, or by replacing the fixed ratio criterion with a criterion that the FEV₁/FVC be below the LLN (fig. 2⇑). However, only the method requiring both an FEV₁/FVC below the LLN and a low FEV₁ (measured as either FEV₁<LLN or FEV₁ <80% pred) largely eliminated this age-related increase.

The upward trend that still persists in figure 2⇑ even with our “best” definitions of COPD may reflect the fact that our “healthy” never-smokers did include some individuals with symptoms. As noted below, this was a pragmatic decision due to the limited number of never-smokers at some sites. The fact that the NHANES-III prediction equations were fit to a cohort whose upper age limit was 80 yrs also may create an upward bias for very old individuals that helps explain the upward drift in figure 2⇑. However, <4% of the BOLD cohort were aged ≥80 yrs; in addition, the NHANES-III prediction equations for FEV₁ include an age-squared term and so allow for accelerated ageing effects.

Notably, the recent ATS/ERS statement recommends using the LLN of the FEV₁/FVC in place of the fixed ratio criterion to diagnose airflow obstruction 21; a recent paper by Swanney et al. 12, albeit using pre-bronchodilator spirometry, also supports this recommendation. Use of both an FEV₁/FVC below the LLN and a low FEV₁ was consistently associated with low site-to-site and age-related variation relative to other measures, after adjusting for known risk factors. Assuming that variability about the prediction equations is stable, using the LLN as a threshold for defining low FEV₁ should produce less misclassification 22, although in practice these two measures performed similarly.

The results of our study also add to the evidence suggesting that, without both a low FEV₁/FVC and a low FEV₁, confidence is low that a true lung function abnormality (or airway disease) exists. The current GOLD stage 1 classification was based solely on expert opinion, not on evidence of airway disease or subsequent rapid loss of lung function. Patients with GOLD stage 1 do not have reduced exercise capacity 23. Among Lung Health Study participants, a rapid fall in FEV₁ was not seen when baseline FEV₁ was >70% pred 24.

Apart from the fixed ratio criterion, the competing measures we evaluated all require use of prediction equations. One of the purported benefits of the fixed ratio criterion is that it does not rely on such equations. However, as Swanney et al. 12 note, this easy-to-apply definition is only valid at age ∼50 yrs. In addition, the fixed ratio criterion is not necessarily easier to use in practice, since even inexpensive pocket spirometers include a microprocessor that calculates the appropriate LLN for FEV₁/FVC, FEV₁/FEV₆ and FEV₁. Lastly, even GOLD relies on prediction equations to stage disease, so any advantage of the fixed ratio in terms of its simplicity disappears as soon as one looks at clinically relevant impairment (nominally GOLD stage 2 or higher). The only way to overcome the limitations of the current fixed ratio criterion while still avoiding the need for prediction equations would be to establish a series of separate fixed ratio cut points for different ages.

The question then arises, what is a suitable prediction equation for any given population, and what if normative prediction equations do not exist for that population? While the documented variability in lung function that exists among “healthy” never-smokers in different racial groups may reflect, at least in part, true genetic differences in these populations, it also may represent the cumulative effect of environmental exposures, including childhood factors. For this reason, BOLD chose to use a single set of sex-specific prediction equations for all subjects in all sites. We chose the US NHANES-III equations for Caucasian adults because they were derived from a large study conducted in a diverse population with rigorous attention to quality control. We observed similar prevalence estimates using equations derived from Norway's Hordaland County Respiratory Health Study 20 in place of the NHANES-III equations.

The PLATINO study (Latin American Project for the Investigation of Obstructive Lung Disease), conducted in five Latin American countries using methods similar to those of the BOLD study, used site-specific prediction equations 25. In BOLD, the use of local prediction equations led to prevalence estimates 2–3 percentage points lower, on average, than those based on a single, common equation. Whether this means that the BOLD prevalence estimates overestimate the “true” estimate, or the local equations underestimate it, we cannot say, but on balance we prefer to maintain the site-to-site variation and see if it can be explained by other risk factors. Because our local equations were fitted to individuals aged ≥40 yrs, while the NHANES-III equations were fitted to adults aged ≥18 yrs, the former may better describe the accelerated ageing that is known to occur in healthy adults. Also, we included symptomatic individuals in our prediction equations as long as they did not report diagnosed disease, whereas the NHANES-III equations required individuals to be asymptomatic. Since there can be large discrepancies between prediction equations based on individuals with and without major respiratory symptoms 26, this may also help to explain the somewhat lower prevalence estimates between the two approaches. One final consideration relating to the use of site-specific prediction equations, particularly if reliable normative equations for that population do not exist, is that the resulting estimates may be highly variable owing to limited sample sizes. For instance, despite relatively large sample sizes from each site, the number of healthy never-smokers available to build our prediction equations was very limited in some sites due to extremely high rates of ever having smoked.

Considerable attention is now being paid to the use of the FEV₁/FEV₆ as an alternative to the FEV₁/FVC, particularly in older, less healthy populations for whom achievement of a high quality, reproducible FVC may be problematic 27. Several studies have shown that the FEV₁/FEV₆, for which reliable reference equations exist 19, is a more reproducible measure than is the FEV₁/FVC 28, 29, and predicts subsequent lung function decline about as well as the FEV₁/FVC 30. Our results (table 3⇑) show that using the FEV₁/FEV₆ in place of the FEV₁/FVC in our definition of “LLN (FEV₁/FVC) and FEV₁ <80% pred” yields very similar prevalence estimates, thus further supporting the use of this alternative measure in future studies of COPD prevalence. Once an obstructive lung disease has been diagnosed, however, changes in FEV₁ should be used to follow disease progression or treatment responses.

Finally, our observation that use of pre-bronchodilator spirometry results in consistently inflated estimates of chronic airflow obstruction, regardless of the definition used, further emphasises the need for using post-bronchodilator spirometry to classify COPD 14. Our finding that prevalence estimates dropped, on average, ∼25% when using post-bronchodilator spirometry is generally consistent with other reports 8, 10, 13. Although we recognise that well-assessed, normal pre-bronchodilator spirometry has high negative predictive value even in the absence of post-bronchodilator testing, its use is associated with the more serious risk of increased false-positive diagnoses.

In summary, data from the BOLD study confirm previous reports of misclassification using the fixed ratio criterion to measure COPD. As an alternative, we recommend a definition based on an FEV₁/FVC ratio less than the LLN, and an FEV₁ either <80% pred, or below the LLN. This modification of the current GOLD stage 2 severity threshold appears to better account for known ageing effects in healthy never-smokers. While this new definition will likely miss many individuals with mild COPD, it should capture most individuals with clinically significant disease, while minimising the risk of false-positive diagnoses. Finally, substitution of the FEV₁/FEV₆ in place of the FEV₁/FVC in this definition appears to yield similar prevalence estimates and, based on previous reports, may be a more reproducible and practical measure.

Statement of interest

Statements of interest for W.M. Vollmer and P.L. Enright can be found at www.erj.ersjournals.com/misc/statements.dtl The BOLD initiative has been funded in part by unrestricted educational grants to the Operations Center. For full details see the online supplementary material available from www.erj.ersjournals.com