Risk of Pneumonitis and Pneumonia Associated With Immune Checkpoint Inhibitors for Solid Tumors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: We performed a systematic review and meta-analysis to evaluate the risk of pneumonitis and pneumonia associated with immune checkpoint inhibitors (ICIs) for solid tumors. Methods: The following keywords were used in searching the Embase and PubMed database: pneumonitis, pneumonia, and immune checkpoint inhibitors. The data was analyzed by using the R software and Metafor package. Results: Among 3436 studies, 23 randomized clinical trials (RCTs) met our selection criteria which included data from 12876 patients. Compared with chemotherapy, PD-1 inhibitors showed significant increase in grade 1-5 and grade 3-5 pneumonitis (RR, 5.17, 95% CI: 2.82-9.47, p<0.001; RR, 4.14, 95% CI: 1.82-9.42, p<0.001), but not in pneumonia. PD-L1 inhibitors showed significant increase in grade 1-5 pneumonitis and pneumonia (RR, 3.25, 95% CI: 1.61-6.57, p<0.001; RR, 2.11, 95% CI: 1.20-3.70, p<0.001). There was no significant difference in any grade pneumonitis and pneumonia in cytotoxic T lymphocyte-associated protein 4 (CTLA4) inhibitors subgroup. Programmed cell death protein 1 (PD-1) inhibitor (nivolumab and pembrolizumab) showed significant increase in grade 1-5 pneumonitis, but only pembrolizumab showed significant increase in grade 3-5 pneumonitis. (RR, 5.64 95% CI: 1.94-16.38, p<0.001). Compared with PD-1 inhibitor (nivolumab) or CTLA-4 inhibitor (ipilimumab) monotherapy, PD-1 inhibitor and CTLA-4 inhibitor (nivolumab plus ipilimumab) combination therapies showed significant increase in grade 1-5 and grade 3-5 pneumonitis (RR 3.47, 95%CI:1.76-6.83, p<0.001; RR 3.48, 95%CI:1.10-11.02, p<0.001) Conclusions: PD-1/ PD-L1 inhibitors treatment could increase the risk of all-grade pneumonitis. CTLA4 inhibitor ipilimumab treatment alone could not increase the risk of pneumonitis but could augment the risk of pneumonitis in PD-1/ PD-L1 inhibitor treated patients. There was no significant increase in the risk of pneumonia after either PD-1/PDL-1inhibitor or CTLA4 inhibitor treatment alone or in combination.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.048 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".