Assessment of the Clinical Trials Safety Profile of PD-1/PD-L1 Inhibitors Among Patients With Cancer: An Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Understanding the safety and adverse event profiles of PD-1/PD-L1 inhibitors is important in guiding cancer immunotherapy. Consequently, we designed this meta-analysis to evaluate the safety of PD-1/PD-L1 inhibitors in clinical trials involving cancer patients. METHODS: Four safety indicators comprising treatment-related adverse events, death, discontinuation of therapy and grades 3-5 adverse events were evaluated using the random effect model. The quality of enrolled trials was assessed using the Newcastle Ottawa Scale (NOS). RESULTS: = 0%, Z = 2.52 (P = 0.01)). Similar observations were apparent regarding the other three indicators of safety and also when the use of PD-1/PD-L1 inhibitors alone is compared with the combined use of PD-1/PD-L1 and CTLA-4. When used together with chemotherapy, PD-1/PD-L1 inhibitors increased the incidence of the adverse events as compared to the use of chemotherapy alone. Increased risks for adverse events were also noticed with the use of PD-1/PD-L1 inhibitors over the use of a placebo. CONCLUSION: The use of PD-1/PD-L1 inhibitors alone is associated with a better safety profile compared to either the use of chemotherapy or the use of PD-1/PD-L1 inhibitors with other anticancer regimens.
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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 | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 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".