Overall survival of patients with chronic obstructive pulmonary disease receiving immunotherapy for non-small cell lung cancer: A population-based analysis in Ontario, Canada.
Bibliographic record
Abstract
e21172 Background: Outside of clinical trial eligibility criteria, there is limited data to guide the selection of patients with non-small cell lung cancer (NSCLC) for immune checkpoint inhibitor (ICI) therapy. Chronic obstructive pulmonary disease (COPD) and lung cancer are associated, independent of smoking history, with a common background of chronic inflammation. Previous studies have demonstrated that COPD is a negative prognostic marker for NSCLC, but the clinical benefit of ICI in patients with NSCLC and COPD is unknown. Methods: A population-level administrative data analysis of Ontario patients was performed through the Institute of Clinical Evaluative Sciences (ICES) Data Analytic Services. All patients with NSCLC diagnosed between Jan 2010 and Dec 2020 and treated with immune-checkpoint inhibitors (pembrolizumab, nivolumab, atezolizumab) were included. Demographics, comorbidity and marginalization scores, and COPD status were extracted along with outcome information. Overall survival (OS) was estimated using the Kaplan-Meier method, and compared between patients with or without COPD using Cox proportional hazards regression. The frequency of patients requiring hospitalization and duration of treatment was also estimated and compared using the chi-square and Wilcoxon rank-sum test. Results: 73331 NSCLC patients were identified, of which 4.5% (n = 3285) patients received ICI. COPD patients were less likely to receive immunotherapy (3.8% vs. 5.1%, p < 0.001). Among those receiving an ICI, 41% (n = 1362) of patients had a diagnosis of COPD prior to NSCLC diagnosis. Median (95% CI) OS was 17.3 (16.6 to 18.2) months for patients with COPD and 16.9 (16.2 to 17.8) for patients with no known COPD, which was not significantly different in univariate (hazard ratio = 0.96, 95% CI = 0.89 to 1.04, p = 0.35) or multivariate analysis (HR = 0.96, 95% CI = 0.89 to 1.05, p = 0.40). The 5-year survival was also similar between both groups (6.7% vs. 6.5%). The rate of hospitalization within 6 months (18.4% vs 18.0%, p = 0.82) and the duration of immunotherapy treatment (median = 80 vs 71 days p = 0.23) did not differ for the COPD vs. non-COPD groups. Conclusions: Despite an expectation of frailty, our data suggest that NSCLC patients with COPD receiving ICI maintained similar durations of treatment and similar rates of hospitalization, with no significant difference in survival time, compared with those without COPD. While a treatment selection bias cannot be excluded in this non-randomized dataset, our data suggest that a diagnosis of COPD itself should not be considered a contraindication to immune checkpoint inhibitor use in NSCLC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".