The Risk of Diarrhea and Colitis in Patients With Advanced Melanoma Undergoing Immune Checkpoint Inhibitor Therapy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Checkpoint inhibitors are a first-line therapy for advanced melanoma, though their use is limited by diarrhea and colitis. The aim of our study was to determine the risk of these toxicities associated with immunotherapy in advanced melanoma. Electronic databases were searched through June 2017 for prospective studies reporting the risk of diarrhea and colitis in advanced melanoma treated with anti-programmed death-1 (PD-1) or anti-cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors. Standardized definitions assessed the grade of diarrhea and colitis. Pooled incidence and weighted relative risk estimates with 95% confidence intervals (CI) were estimated using random effects model. Eighteen studies were included: 6 studies (1537 patients) with PD-1 inhibitors and 15 studies (3116 patients) with CTLA-4 inhibitors. The incidence of all-grade diarrhea was 13.7% (95% CI, 10.1%-17.2%) for anti-PD-1 and 35.4% (95% CI, 30.4%-40.5%) for anti-CTLA-4. The incidence of all-grade colitis was 1.6% (95% CI, 0.7%-2.4%) for anti-PD-1, and 8.8% (95% CI, 6.1%-11.5%) for anti-CTLA-4. When PD-1 inhibitors were compared directly with CTLA-4 inhibitors, the relative risk of all-grade diarrhea was 0.58 (95% CI, 0.43-0.77), and the relative risk of all-grade colitis was 0.16 (95% CI, 0.05-0.51). The rate of therapy discontinuation was numerically higher for anti-CTLA-4 therapy compared with anti-PD-1 therapy. Finally, 2 studies compared combination immunotherapy with anti-CTLA-4 therapy alone. The relative risk of developing all-grade diarrhea and colitis with combination therapy was 1.31 (95% CI, 1.09-1.57) and 1.21 (95% CI, 0.73-1.99), respectively. Diarrhea and colitis are frequent toxicities associated with checkpoint inhibitors, and seem to be most common with CTLA-4 inhibitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".