Incidence, Prevalence, and Mortality of Interstitial Lung Diseases in Alberta, Canada: A Population-Based Study
Bibliographic record
Abstract
Abstract Rationale The epidemiology of adult interstitial lung disease (ILD) is uncertain, given heterogeneous estimates from prior studies. Objective We sought to define the incidence, prevalence, and mortality of ILD over a 10-year period using population-based data. Methods We created an administrative ILD cohort in Alberta, Canada between 2010 and 2019 using population-based administrative data (inpatient, ambulatory, and outpatient physician billing databases) for a repeat cross-sectional study. Case definitions were developed from an established ILD cohort and applied to the general population, with performance characteristics tested using a nested case-control design. Age- and sex-standardized annual incidence and point prevalence rates were estimated for ILD overall and within diagnostic subgroups, with trends over time, per 100,000 at-risk adults and to permit comparisons with other studies, per 100,000 total population. Cox models estimated risk of death or lung transplantation. Results Between 2010 and 2019, 31,492 incident and 42,549 prevalent adult ILD cases were identified. The case definition for ILD performed well with 96.8% sensitivity, 98.5% specificity, and a positive predictive value of 94.3% in the population cohort. Mean age-standardized ILD incidence was 107.9/100,000 at-risk adults, 90.9/100,000 for females and 129.1/100,000 for males. Age-standardized ILD point prevalence increased from 416.5/100,000 at-risk adults in 2010 to 789.7/100,000 in 2019, higher in males versus females, and in rural versus urban areas. Age-standardized mean idiopathic pulmonary fibrosis (IPF) incidence was 36.9/100,000 at-risk adults, and point prevalence was 205.3/100,000 at-risk adults in 2019. Mean age-standardized ILD incidence and prevalence was 84 and 516.9/100,000 total population, respectively. One-year all-cause mortality for ILD patients decreased from 14.5% in 2011 to 11.7% in 2018 (for 2018 vs. 2011, adjusted rate ratio = 0.76; 95% confidence interval = 0.67–0.86). One-year all-cause mortality for IPF similarly decreased from 20.9% in 2011 to 14.7% in 2018 (for 2018 vs. 2011, adjusted rate ratio = 0.71; 95% confidence interval = 0.59–0.85), representing improved survival. Conclusions In this population-based cohort, claims-based case definitions derived from an established ILD cohort performed well to develop an administrative cohort. Incidence remained stable over time, whereas prevalence increased and mortality decreased, for ILD overall and within the IPF subgroup. These estimates are higher than most prior reports, suggesting an overall underestimate of ILD burden.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".