Spirometric Predictors of Lung Function Decline and Mortality in Early Chronic ObstructivePulmonary Disease
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 185 2012
M. Bradley Drummond1, Nadia N. Hansel1, John E. Connett2, Paul D. Scanlon3, Donald P. Tashkin4, and Robert A. Wise1
1Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland; 2Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota; 3Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota; and 4Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
Rationale: The course of lung function decline for smokers with early airﬂow obstruction remains undeﬁned. It is also unclear which early spirometric characteristics identify individuals at risk for rapid decline and increased mortality. Objectives: Todetermine the association between spirometric measures and 5-year decline in FEV1 and 12-year mortality. Methods: WeanalyzedlongitudinaldatafromtheLungHealthStudy, a clinical trial of intensive smoking cessation intervention with or withoutbronchodilator therapy in 5,887 smokers with mild to moderate airﬂow obstruction. Participants were stratiﬁed into bins of baseline FEV1 to FVC ratio, using binsof 5%, and separately into bins of Z-score (difference between actual and predictedFEV1/FVC, normalized to SD of predicted FEV1/FVC). Associations between spirometric measures and FEV1 decline and mortality were determined afteradjustingforbaselinecharacteristicsandtime-varyingsmoking status. Measurements and Main Results: Thecohort was approximately twothirdsmale, predominantlyofwhiterace(96%),andwithmeanageof 49 6 7 years. In general, individuals with lower lung function by any metric had morerapid adjusted FEV1 decline.Athreshold fordifferential decline was present atFEV1/FVC less than 0.65 (P , 0.001) and Z-score less than 22 (2.3percentile) (P , 0.001). At year 12, 575 (7.2%) of the cohort had died. Lower thresholds of each spirometric metric were associated with increasing adjusted hazard of death. Conclusions:Smokers at risk or with mild to moderate chronic obstructive pulmonary disease have accelerated lung function decline. Individuals with lower baseline FEV1/FVC have more rapid decline and worse mortality.
Keywords: chronic obstructive pulmonary disease; spirometry; disease progression; prognosis; mortality
AT A GLANCE COMMENTARY
Scientiﬁc Knowledge on the Subject
The traditional model of accelerated decline in lung function in chronic obstructive pulmonary disease (COPD) has been recently challenged by several studies showing heterogeneity in lung function decline. It is important to identify earlyspirometric characteristics that can determine who is at risk for the most rapid rate of lung function decline and worse mortality.
What This Study Adds to the Field
In smokers at risk or with mild to moderate COPD, worse baseline lung function is associated with more rapid long-term FEV1 decline and higher risk of death. The threshold of FEV1/FVC that placed people at risk for excessive lung functiondecline and mortality was lower than current thresholds used to deﬁne COPD.
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality, recently becoming the third leading cause of death in the United States (1). Expiratory airﬂow limitation, the hallmark physiologic abnormality inCOPD, is determined by a reduction in the ratio of FEV1 to the FVC. The traditional model of COPD as deﬁned by Fletcher and Peto is one of accelerated decline in lung function, resulting in reduced FEV1 over many years (2). Recently, this notion hasbeen challenged by several clinical trials describing substantial heterogeneity in lung function decline, with normal or near-normal rates of decline in some individuals with established COPD (3–6). It is unclear if these observations reﬂect a plateauof lung function decline in those with moderate to severe COPD, the natural course of treated COPD, or that not all COPD patients experience the historically accepted trajectory of FEV1 decline.
As most clinical trials included patients with established and symptomatic COPD, the course of lung function decline for individuals with early airﬂow obstruction remains unclear. It is important to identify early spirometric characteristicsthat can identify those at risk for the most rapid rate of lung function decline as well as those with inconsequential disease. Moreover, current spirometric guidelines used to diagnose COPD have not been validated in terms of predicting long-termoutcomes (7–11). The Lung Health Study (LHS) was a longitudinal multicenter randomized clinical trial of an intensive smoking cessation intervention with or without inhaled bronchodilator therapy compared with usual care in smokers recruitedfrom the community with mild to moderate airﬂow obstruction (12). The longitudinal data from LHS offer a unique opportunity to explore how a range of baseline spirometric measures are associated with longitudinal FEV1 decline and mortality.In this analysis, we stratify the 5,885 LHS participants into bins of baseline FEV1/FVC and FEV1% predicted, determining the association between spirometric measures and the annual decline in FEV1 over 5 years and mortality at 12 years.
The design of LHS has been previously described (12–14). LHS I was a multicenter, randomized three-arm trial of smoking cessation intervention combined with inhaled ipratropium or placebo versus usual care (Clinialtrials.gov NCT00000568). The studyenrolled 5,887 active smokers from the community aged 35 to 60 years with prebronchodilator FEV1/FVC less than 0.70 and prebronchodilator FEV1 between 55 and 90% predicted who were not regularly using physician-prescribed bronchodilators. Lungfunction was measured annually over 5 years. LHS III extended the follow-up of 98.3% of LHS I participants to December 31, 2001 or 14.5 years (whichever was earlier), to determine long-term impact of the smoking cessation intervention (15, 16). Forthis analysis, all LHS I participants with post-bronchodilator FEV1/ FVC measurements (n ¼ 5885) were included. Because of the observed increase in FEV1 during the ﬁrst year of LHS (13), and potential bias related to deaths and loss to follow-up with LHSIII, analysis of rate of decline of FEV1 was limited to annual visit one through annual visit ﬁve. For mortality analyses, LHS III death status was used. Written informed consent was obtained from all participants originally enrolled in LHS. InstitutionalReview Board approval was waived as all data were previously collected and deidentiﬁed.
Deﬁning Spirometric Thresholds
The procedure for spirometry measurements has been described elsewhere (17). Spirometric values collected at the second screening visit were used in this analysis. Participants were stratiﬁed into bins of baseline post-bronchodilator FEV1/FVC as a percent,using bins of 5%. Separately, participants were stratiﬁed by baseline postbronchodilator FEV1/FVC into bins of Z-score, using reference formulas of Hankinson (18). The Z-score represents the difference between the actual FEV1/FVC and the predictedFEV1/FVC, normalized to the SD of the predicted FEV1/FVC. For example, a Z-score of 21.0 means that the measured FEV1/FVC is 1 SD below the mean of the reference population (the 16th percentile of the population). A Z-score of 21.645 representsthe 5th percentile of the population (the lower limit of normal [LLN] threshold) used to deﬁne COPD by some guidelines (8). Table E1 in the online supplement provides a summary of the correlation between Z-scores and normally distributed populationpercentiles. Participants were also stratiﬁed into bins of baseline FEV1% predicted.
TABLE 1. CHARACTERISTICS OF LUNG HEALTH STUDY COHORT (N ¼ 5,885)
|Baseline Age, yr||
|Male, n (%)||
|Race/ethnicity, n (%)|
|Cigarettes per day||
|FEV1/FVC ratio, post-BD||
|FVC, post-BD, L||
|Smoking status at last visit|
|Average annual change in post-BD FEV1,ml|
Definition of abbreviations:BD ¼ bronchodilator;BMI ¼ body massindex;LHS3 ¼ Lung Health Study III.
Values are presented as mean (SD) unless otherwise indicated.
Modeling of Longitudinal FEV1 Decline
To test for the association between bins of baseline spirometric measurements and mean annual FEV1 decline, generalized estimating equations (19) with a robust exchangeable variance-covariance matrix were used. Lung function decline was assessed viathe interaction of the spirometric measure and time. Predictors associated with FEV1 measurements and thus included in modeling were randomization group, race, sex, age, height, body mass index, and time-varying smoking patterns. Time-varyingsmoking pattern was modeled with three covariates: (1) average number of cigarettes smoked per day over the previous year at each annual visit, (2) subject’s smoking status for the current year, (3) and subject’s smoking status for the previous year(deﬁned as smoker or nonsmoker). Full details on predictors and model construction are available in the online supplement. Graphs of adjusted mean FEV1 change (expressed in milliliters per year) across bins of different spirometric measures weregenerated. Methacholine reactivity was deﬁned as previously described (20). To determine the association between different spirometric thresholds and the hazard of death at LHS III follow-up, adjusted Cox proportional hazard regression models weregenerated using duration of follow-up as the time metric. A P value of less than 0.05 was used to infer statistical significance. Stata version 10.0 (Stata Corp, College Station, TX), was used for statistical analyses.
Participant Characteristics at Baseline
A total of 5,885 LHS participants were included in this analysis, representing 99.9% of the original LHS cohort. (Table 1) Two individuals were excluded due to the lack of postbronchodilator spirometry. The cohort was predominantly of whiterace (96%), with mean age of 49 6 6.8 years. Approximately two-thirds were men. All participants were active smokers at the time of enrollment, with an average smoking history of 41 6 19 pack-years. The mean prebronchodilator FEV1/FVCwas 0.63 6 0.06, with post-bronchodilator FEV1/FVC increasing to 0.65 6 0.06. Although all participants had a prebronchodilator FEV1/FVC less than 0.70, 1,245 (21%) had a postbronchodilator FEV1/FVC greater than or equal to 0.70. Themean post-bronchodilator FEV1% predicted of the cohort was 78 6 9% predicted.
Five-Year and LHS III Outcomes
At 5-year follow-up, 147 (2.5%) of the cohort had died (Table 1). Of those still living, 3,890 (68%) were active smokers. At LHS III, 575 participants had died, representing 9.8% of the original LHS cohort. Data regarding cause of death havebeen previously reported (13, 15, 21). At the last visit before study completion, loss to follow-up, or death, 2,695 (46%) of the cohort were active smokers, whereas 915 (15.5%) were sustained quitters. The unadjusted annual decline in absoluteFEV1 for the entire cohort was 53.1 6 0.6 ml at year 5 and 53.9 6 0.5 ml at year 12.
Adjusted Mean FEV1 Decline Stratiﬁed by Bins of Baseline Spirometric Measures
In exploratory analyses, several participant baseline characteristics were identiﬁed to contribute to the longitudinal decline in absolute FEV1 and were incorporated in a multivariate model. The relative adjusted effect of these covariates on absolute FEV1 is summarized in Table E2. In general, individuals with lower lung function by any metric had more rapid adjustedFEV1 decline. When stratifying participants into bins of baseline absolute FEV1/FVC, all but the highest bin was associated with an adjusted mean FEV1 slope less than zero (Figure 1). There appeared to be a threshold of differential decline at the 0.60 to 0.65 bin, with a statistically greater FEV1 decline compared with participants in the next highest bin (P , 0.001). For the bins less than 0.65 to 0.70, there was a signiﬁcantly greater FEV1 decline for lower FEV1/FVC bins (see Figure 1 andTable E3). When stratifying participants into bins of Z-score, a similar pattern was observed with a threshold of differential decline occurring between the 22.5 to 22 Z-score bin and the 22 to 21.5 bin (P , 0.001) (Figure 2). There was no statistical difference in annual FEV1 decline between participants whose baseline FEV1/FVC Z-score includes the LLN 5th percentile threshold (22to 21.5 bin) compared with the next highest bin (P ¼0.52). Subsequently lower Z-score bins were associated with greater adjusted FEV1 slope of decline (Table E3). Individuals with baseline FEV1% predicted that ranged from 80 to 85% had a greater annual decline than participants in the 85 to 90%FEV1% predicted bin (P , 0.001) (Figure 3). Each subsequently lower bin of baseline FEV1% predicted was associated with a statistically greater decline in annual FEV1 (Table E3). The observed trends in FEV1 slope of decline across bins ofdifferent spirometric measures were not substantially altered when including methacholine reactivity or baseline FEV1 in the primary model (Figures E1–E5). When evaluating the usual care group separately (to completely remove any potentialimpact of smoking cessation intervention and ipratropium on the FEV1 slope) or including the 11-year follow-up data, similar trends were present (Figures E6–E11). When stratifying the study cohort by smoking pattern (sustained quitter,intermittent quitter, or continuous smoker), the association between lower baseline lung function and accelerated decline was present in all three groups, but attenuated in the sustained quitters. Intermittent smokers and continuous smokers hadsimilar trends when baseline lung function was normal or mildly impaired. At levels of more severe baseline lung impairments, intermittent smokers demonstrated less rapid lung function decline than continuous smokers (Figures E12–E14).
As seen in Figure 4 and Table E4, a consistent trend was seen with lower thresholds of spirometric measures being associated with increasing adjusted hazard of death. Speciﬁcally, lower FEV1/FVC ratios increased the hazard of death, withstatistical signiﬁcance being met when comparing an FEV1/FVC less than 0.55 to greater than 0.55 (hazard ratio [HR], 1.31; 95% conﬁdence interval [CI], 1.01–1.70; P ¼ 0.04). When evaluating different Z-score thresholds, the hazard of death began increasing at the 23.0 threshold (HR, 1.19; 95% CI, 0.99–1.43; P ¼0.06) and reached statistical signiﬁcance at the 23.5 threshold (HR, 1.31; 95% CI, 1.06–1.62; P ¼ 0.014). Progressively lower Z-score thresholds were associated with an increasing hazard of death. An increased hazard of death was seen acrossthe range of baseline FEV1% predicted thresholds, with the greatest risk observed when comparing those with a baseline FEV1% predicted less than 65% to those greater than 65% predicted (HR, 1.36; 95% CI, 1.08–1.72; P ¼ 0.01). Whenstratifying by cause of death, no clear spirometric thresholds existed to identify an increased risk of death. (Table E5).
We have demonstrated that spirometry testing in a population at risk or with mild to moderate lung disease provides important prognostic information. Some smokers with mild to moderate airﬂow limitation do have an increased rate of lungfunction decline. In smokers at risk or with mild to moderate COPD, worse lung function at baseline is associated with more rapid long-term decline in FEV1 and higher risk of death. In our analysis, excessive lung function decline occurred belowFEV1/FVC of 0.65 or Z-score of 22.0 (2.3 percentile). The risk of death did not increase until even lower thresholds (FEV1/FVC of 0.55 or Z-score of 23.5 [0.023 percentile]). The thresholds we observed that placed people at risk for excessive lung function decline and mortality were lower than current thresholds used to deﬁne COPD (FEV1/FVC , 0.70 or ﬁfth percentile LLN). These ﬁndings highlight the usefulness of screening spirometry in at-risk groups, allowing for risk stratiﬁcation of at-risk individuals to avoid overtreatment of those not at risk for accelerated lung function decline or death. Moreover, these data can inform screening criteria for guideline development.
Understanding the predictors and signiﬁcance of the rate of decline in lung function in individuals with COPD has been the focus of several recent studies (3–6, 22–24). When examining individuals with established COPD, it was observed thatlung function decline is heterogeneous (5). A recent report observed that only 18% of patients with COPD experienced a statistically signiﬁcant FEV1 decline assessed by linear regression (6). It is unclear if the observation of less than anticipatedFEV1 decline in those studies was attributable to alterations in disease pathobiology or response to medical therapy. By analyzing a group of individuals with mild to moderate disease relatively free of treatment, we have expanded theunderstanding of lung function decline in smokers. Our results demonstrate that some smokers with minimal to moderate lung function impairment do have an accelerated decline of lung function. Both the baseline FEV1/FVC ratio and the FEV1%predicted were informative in this regard. These ﬁndings were present even after accounting for longitudinal smoking habits of the LHS cohort. Although the most accelerated lung function decline was seen in continuous smokers, the associationbetween lower baseline lung function and more rapid FEV1 decline was also present in intermittent quitters and sustained quitters. Our ﬁndings conﬁrm the previously described “horse racing effect” in established COPD, whereby those with themost severe FEV1 impairment, on average, have the most accelerated future FEV1 decline (25). Our ﬁndings also complement the reported observation that lower lung function at young age is highly predictive of low lung function in middle age(23). We have now expanded this observation by including at-risk individuals as well. We observed that at thresholds of FEV1% predicted above 60%, those below that level had a higher risk of death than those above. These observations can helppractitioners identify those individuals who are at greatest risk for future lung impairment and death.
Consistent with recent reports describing the heterogeneity of FEV1 decline in COPD, in addition to identifying a subset of individuals with accelerated lung function decline we also observed that many smokers did not have a rapid decline inlung function over time. We observed that differential FEV1 decline did not occur unless the baseline FEV1/FVC was below 0.65 or Z-score less than 22.0, and the mean rate of decline of FEV1 increased with further reduction in the baseline ratio. As identiﬁed by the writing committees of the major pulmonary organizations, the currently selected spirometric thresholdslack clinical validation (7, 8). These data suggest that the current thresholds to deﬁne COPD may be identifying individuals who are not at risk of accelerated FEV1 decline and thus may not warrant pharmacotherapy. The use of a diagnosticthreshold that identiﬁes individuals who may not be at risk of accelerated decline could lead to potential overdiagnosis of nonsigniﬁcant disease.
Current guidelines recommend against spirometric screening of asymptomatic individuals, regardless of COPD risk factors (26). Such recommendations are based on the lack of evidence for beneﬁcial pharmacotherapy to treat asymptomaticpersons with or without airﬂow obstruction. Our analysis shows that spirometry can inform the prognosis of smokers. Albeit limited by post hoc subgroup analysis, reports demonstrate that pharmacotherapies can improve symptoms,exacerbation frequency, rate of FEV1 decline, and mortality in individuals with mild and moderate COPD (27–29). It remains unclear if therapies for mild COPD will deﬁnitely improve outcomes, and thus the ﬁndings presented here do notcontradict current screening guidelines. If pharmacotherapy that reduces rate of decline in more advanced disease is found to be useful in milder disease, there may be therapeutic beneﬁt of screening. This is not the case currently. Smokingcessation should be recommended to all individuals regardless of lung function status. However, if resources for high intensity smoking cessation are limited, those with the greatest risk for lung function decline would be highest priority.
In our analysis, we did not observe a statistically signiﬁcant increase in the risk of death for participants with a baseline FEV1/FVC less than 0.70 or LLN encompassing the ﬁfth percentile compared with those above that threshold. Themajority of studies evaluating the relationship between spirometry and mortality focus on comparing the ﬁxed ratio and LLN criteria (30–33). Few have explored different thresholds above and below the current criteria (34, 35). Moreover, allLHS participants were active smokers at baseline with careful follow-up of biochemically validated smoking status, allowing us to account for the confounding effect of smoking on mortality. Vaz Fragoso and colleagues examined the associationbetween different thresholds of LLN criteria (ranging from 5th to 25th percentile) and 12-year mortality in 3,502 participants of the Third National Health and Nutrition Examination Survey (NHANES III) (34). They observed an increase in theadjusted hazard of death only for those below the 5th percentile compared with those above the 25th percentile. The authors did not evaluate thresholds below the ﬁfth percentile. Mannino and colleagues evaluated the association betweenFEV1/FVC less than 0.70 and LLN ﬁfth percentile criteria with 11-year mortality in an elderly community-based cohort (35). These authors observed a 40% increase in the hazard of death (HR, 1.40; 95% CI, 1.1–1.7) comparing individuals withFEV1/FVC less than 0.70 and below LLN to individuals with normal spirometry. In a recent analysis of the Lung Health Study cohort, increased 15-year mortality was seen only in those with modiﬁed GOLD stage three or four lung disease (36).Our ﬁndings support and reﬁne these observations by demonstrating that a better threshold to determine mortality risk may exist, speciﬁcally an FEV1/FVC , 0.55 or Z-score less than 23.5.
Our analysis has limitations. The data for this analysis are collected in the setting of a clinical trial, and thus the characteristics of participants in this cohort may not reﬂect the general population. Even though evaluation of the usual care groupalone was similar to the overall ﬁndings, the data presented here may reﬂect changes related to trial interventions rather than the natural course of COPD. LHS did not collect radiographic or pulmonary function measures of emphysema, which hasbeen shown to be important in determining prognosis in patients with COPD (24). Because the LHS did not enroll subjects with severe airﬂow limitation, these analyses do not exclude the possibility that individuals with severe airﬂowobstruction experience a slower rate of decline in lung function than those with moderate obstruction, resulting in a sigmoid curve with mild and severe obstruction showing the slowest rates of decline. The participants of LHS were predominantlywhite, limiting generalizability to other demographic groups. LHS had relatively few deaths and relatively mild airﬂow obstruction, potentially leading to an underpowering for detection of a consistent association between lower spirometric valuesand mortality, particularly when stratifying by cause of death. This analysis did not evaluate other endpoints important in the conceptual deﬁnition of disease, speciﬁcally the association between baseline FEV1 and respiratory symptoms andquality of life.
In summary, we have demonstrated that smokers at risk or with mild to moderate COPD have accelerated lung function decline. Individuals with lower FEV1/FVC have more rapid decline and worse mortality. The current spirometricthresholds used to deﬁne COPD, either an FEV1/FVC less than 0.70 or below the ﬁfth percentile, are above a level that predicts more rapid lung function decline and increased risk of death. In a group of active smokers, it may be necessary tolower the threshold to an FEV1/FVC less than 0.65 or Z-score less than 22.0 to identify those at increased risk for more rapid fall in FEV1, with even lower thresholds potentially necessary to identify those at increased risk of mortality. In addition to demonstrating the value of screening spirometry in smokers topredict long-term outcomes, we have provided information allowing for risk stratiﬁcation of at-risk individuals.
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(Received in original form February 8, 2012; accepted in ﬁnal form April 26, 2012)
Supported by National Institutes of Health–National Heart, Lung, and Blood Institute grant K23HL103192 (M.B.D.).
Author Contributions: M.B.D. was responsible for manuscript concept, data analysis, drafting of the manuscript, and revisions. N.N.H. was responsible for study design, data analysis, and revisions for intellectual content. J.E.C., P.D.S., D.P.T., and R.A.W. were responsible for data collection, study design, data analysis, and revisions for intellectual content. All authors approved the ﬁnal manuscript.
Correspondence and requests for reprints should be addressed to M. Bradley Drummond,M.D., M.H.S.,DivisionofPulmonary/CriticalCareMedicine, 5501Hopkins Bayview Circle, JHAAC 3B.53, Baltimore, MD 21224. E-mail: email@example.com
This article has an online supplement, which is accessible from this issue’s table of contents at www.atsjournals.org
Am J Respir Crit Care Med Vol 185, Iss. 12, pp 1301–1306, Jun 15, 2012 Copyright ª 2012 by the American Thoracic Society Originally Published in Press as DOI: 10.1164/rccm.201202-0223OC on May 3, 2012 Internet address: www.atsjournals.org
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