Incidence, outcomes, and risk factors of acute immune checkpoint inhibitor (ICI) pneumonitis post-chemoradiation with durvalumab for patients with locally advanced non-small cell lung cancer (LA-NSCLC): A population-based multicenter study.
Bibliographic record
Abstract
8561 Background: The PACIFIC trial has drastically changed the LA-NSCLC treatment paradigm and improved survival outcomes with consolidation durvalumab post-chemoradiotherapy. Despite these promising results, real-world practice has demonstrated that ICI pneumonitis can have significant clinical complications and terminate consolidation therapy prematurely. This study aimed to identify clinical predictors, outcomes, and healthcare utilization in ICI pneumonitis in LA-NSCLC patients who received consolidation durvalumab in real-world practice. Methods: Using the Alberta Immunotherapy Database, we retrospectively evaluated all NSCLC patients who received durvalumab in Alberta, Canada from January 2018 to December 2021. Pneumonitis cases were identified based on radiographic changes and oncologists’ clinical assessments. We examined incidence and predictive values of severe pneumonitis (≥grade 3), with secondary outcomes of overall survival (OS) and time-to-treatment failure (TTF). Exploratory multivariate analyses were performed to identify predictive values to developing severe pneumonitis and worse OS/TTF. Results: Of 189 total patients, most were ECOG 0-1 (91%) and had partial response from chemoradiation (85%) prior to durvalumab. 49% received full year of therapy (n = 93). Median TTF was 11.2 months, and median OS of 19.7 months with 1-year OS 64% (n = 121). 26% (n = 49) developed any grade of pneumonitis. 9% (n = 17) had severe pneumonitis. Corticosteroids were administered to 86% of the pneumonitis patients (n = 42); 53% (n = 26) required admission. 13% (n = 9) of deaths were attributed to pneumonitis. Male gender and pre-existing autoimmune condition were associated with severe pneumonitis whereas V20 (percentage of irradiated lung volume ≥20Gy) was associated with developing any grade pneumonitis. In multivariable analysis, male gender and V20 was significantly associated with worse OS whereas older age, smoking status, pneumonitis, and male gender with lower TTF. Pneumonitis development was found to be an independent risk factor for worse OS (p = 0.038) and TTF (p = 0.007). Conclusions: We report a pneumonitis incidence comparable to prior retrospective studies and higher rate of severe pneumonitis compared to PACIFIC trial. Our results corroborate that V20, a previously established risk factor for durvalumab associated pneumonitis, is a significant predictor for developing pneumonitis and worse OS. In contrast to smaller retrospective studies, we observed male gender and pre-existing autoimmune conditions appear to predict severe durvalumab associated ICI pneumonitis. These results affirm the importance of careful patient selection for safe completion of consolidation durvalumab in real-world LA-NSCLC population.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".