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. 2021 Dec 14;326(22):2287-2298.
doi: 10.1001/jama.2021.20939.

Association Between Preserved Ratio Impaired Spirometry and Clinical Outcomes in US Adults

Affiliations

Association Between Preserved Ratio Impaired Spirometry and Clinical Outcomes in US Adults

Emily S Wan et al. JAMA. .

Erratum in

  • Incorrect Surname for Author.
    [No authors listed] [No authors listed] JAMA. 2022 Jan 18;327(3):286. doi: 10.1001/jama.2021.23883. JAMA. 2022. PMID: 35040903 Free PMC article. No abstract available.

Abstract

Importance: Chronic lung diseases are a leading cause of morbidity and mortality. Unlike chronic obstructive pulmonary disease, clinical outcomes associated with proportional reductions in expiratory lung volumes without obstruction, otherwise known as preserved ratio impaired spirometry (PRISm), are poorly understood.

Objective: To examine the prevalence, correlates, and clinical outcomes associated with PRISm in US adults.

Design, setting, and participants: The National Heart, Lung, and Blood Institute (NHLBI) Pooled Cohorts Study was a retrospective study with harmonized pooled data from 9 US general population-based cohorts (enrollment, 65 251 participants aged 18 to 102 years of whom 53 701 participants had valid baseline lung function) conducted from 1971-2011 (final follow-up, December 2018).

Exposures: Participants were categorized into mutually exclusive groups by baseline lung function. PRISm was defined as the ratio of forced expiratory volume in the first second to forced vital capacity (FEV1:FVC) greater than or equal to 0.70 and FEV1 less than 80% predicted; obstructive spirometry FEV1:FVC ratio of less than 0.70; and normal spirometry FEV1:FVC ratio greater than or equal to 0.7 and FEV1 greater than or equal to 80% predicted.

Main outcomes and measures: Main outcomes were all-cause mortality, respiratory-related mortality, coronary heart disease (CHD)-related mortality, respiratory-related events (hospitalizations and mortality), and CHD-related events (hospitalizations and mortality) classified by adjudication or validated administrative criteria. Absolute risks were adjusted for age and smoking status. Poisson and Cox proportional hazards models comparing PRISm vs normal spirometry were adjusted for age, sex, race and ethnicity, education, body mass index, smoking status, cohort, and comorbidities.

Results: Among all participants (mean [SD] age, 53.2 [15.8] years, 56.4% women, 48.5% never-smokers), 4582 (8.5%) had PRISm. The presence of PRISm relative to normal spirometry was significantly associated with obesity (prevalence, 48.3% vs 31.4%; prevalence ratio [PR], 1.68 [95% CI, 1.55-1.82]), underweight (prevalence, 1.4% vs 1.0%; PR, 2.20 [95% CI, 1.72-2.82]), female sex (prevalence, 60.3% vs 59.0%; PR, 1.07 [95% CI, 1.01-1.13]), and current smoking (prevalence, 25.2% vs 17.5%; PR, 1.33 [95% CI, 1.22-1.45]). PRISm, compared with normal spirometry, was significantly associated with greater all-cause mortality (29.6/1000 person-years vs 18.0/1000 person-years; difference, 11.6/1000 person-years [95% CI, 10.0-13.1]; adjusted hazard ratio [HR], 1.50 [95% CI, 1.42-1.59]), respiratory-related mortality (2.1/1000 person-years vs 1.0/1000 person-years; difference, 1.1/1000 person-years [95% CI, 0.7-1.6]; adjusted HR, 1.95 [95% CI, 1.54-2.48]), CHD-related mortality (5.4/1000 person-years vs 2.6/1000 person-years; difference, 2.7/1000 person-years [95% CI, 2.1-3.4]; adjusted HR, 1.55 [95% CI, 1.36-1.77]), respiratory-related events (12.2/1000 person-years vs 6.0/1000 person-years; difference, 6.2/1000 person-years [95% CI, 4.9-7.5]; adjusted HR, 1.90 [95% CI, 1.69-2.14]), and CHD-related events (11.7/1000 person-years vs 7.0/1000 person-years; difference, 4.7/1000 person-years [95% CI, 3.7-5.8]; adjusted HR, 1.30 [95% CI, 1.18-1.42]).

Conclusions and relevance: In a large, population-based sample of US adults, baseline PRISm, compared with normal spirometry, was associated with a small but statistically significant increased risk for mortality and adverse cardiovascular and respiratory outcomes. Further research is needed to explore whether this association is causal.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Wan reported receipt of personal fees for serving as faculty and expert content provider for chronic obstructive pulmonary disease (COPD) continuing medical education for PriMed. Dr Balte reported funding from the National Institutes of Health (NIH). Dr Bhatt reported grants from NIH; personal fees from Sanofi (consulting), Boehringer Ingelheim (consulting), GlaxoSmithKline (advisory board), and Sunovion (advisory board) outside the submitted work. Dr Couper reported grants from the National Heart, Lunb, and Blood Institute (NHLBI) and from the COPD Foundation during the conduct of the study. Dr Daviglus reported grants from NIH during the conduct of the study. Dr Dransfield reported grants from NIH during the conduct of the study; personal fees from AstraZeneca, GlaxoSmithKline, Mereo, Quark, and Teva (consulting fees); personal fees for travel from Pulmonx; contracted clinical trial support from AstraZeneca, Boehringer Ingelheim, Boston Scientific, Gala, GlaxoSmithKline, Nuvaira, PneumRx/BTG, and Pulmonx; and grants from NIH, the US Department of Defense, and the American Lung Association outside the submitted work. Dr Kalhan reported grants from NHLBI during the conduct of the study; grants and personal fees from Boehringer Ingelheim, AstraZeneca, and GlaxoSmithKline; personal fees from CVS Caremark, Aptus Health, Boston Scientific, and the Boston Consulting Group; and grants from PneumRx (BTG) and Spiration outside the submitted work. Dr Navas-Acien reported grants from NIH during the conduct of the study and grants from NIH outside the submitted work. Dr O'Connor reported grants from NIH during the conduct of the study. Dr Sanders reported other from Vertex Pharmaceuticals (employment at the time of publication). Dr Smith reported grants from NIH (R01-HL130506) during the conduct of the study; and grants from Canadian Institutes of Health Research outside the submitted work. Dr Oelsner reported grants from NHLBI during the conduct of the study. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Associations Between Lung Function Category, Mortality, and Hospitalizations
Cox proportional hazards models were adjusted for age, sex, race and ethnicity, education, body mass index, smoking status, and medical comorbidities (hypertension, diabetes, coronary heart disease, heart failure, stroke, and chronic kidney disease); cohort was treated as a stratum variable. Lung function category definitions: preserved ratio impaired spirometry (PRISm) (ratio of forced expired volume in the first second to forced vital capacity [FEV1:FVC] ≥0.7 and FEV1<80%), obstructive spirometry (FEV1:FVC ratio <0.7), and normal spirometry (FEV1:FVC ratio ≥0.7 and FEV1 ≥80%). See footnote a in Table 1 for expanded names of study cohorts. Cohorts included in analysis of all-cause mortality, CHD-related mortality, and CHD-related events (hospitalizations and mortality): ARIC, CARDIA, CHS, FOC, Health ABC, JHS, MESA, and SHS. Cohorts included in analysis of respiratory-related mortality: ARIC, CHS, CARDIA, Health ABC, MESA, and SHS. Cohorts included in analysis of respiratory-related events (hospitalizations and mortality): ARIC, CHS, Health ABC, and MESA. HR indicates hazard ratio.
Figure 2.
Figure 2.. Age-Adjusted Absolute Incidence Density Rates by Lung Function Category
Data were stratified by smoking status for all-cause mortality, respiratory-related mortality, coronary heart disease (CHD)-related mortality, respiratory-related events (hospitalizations and mortality), and CHD-related events (hospitalizations and mortality). Lung function category definitions: preserved ratio impaired spirometry (PRISm) (ratio of forced expired volume in the first second to forced vital capacity [FEV1:FVC] ≥0.7 and FEV1<80%), obstructive spirometry (FEV1:FVC ratio <0.7), and normal spirometry (FEV1:FVC ratio ≥0.7 and FEV1 ≥80%). Using the direct method and the observed age distribution across all 9 cohorts, age-adjusted absolute incidence density rates and their differences were calculated per 1000 person-years for each combination of baseline smoking status and lung function category.

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