Anti-Tumor Efficacy of Anti-PD-1/PD-L1 Antibodies in Combination With Other Anticancer Drugs in Solid Tumors: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BackgroundThe clinical efficacy of immune checkpoint inhibitors (CPIs) has been proven; however, it is also known that their efficacy as monotherapy is limited, with a response rate of 20% or less in solid tumors. The combination of CPIs and anticancer agents has been actively attempted in solid tumors area. In this systematic review and meta-analysis, we aimed to find favorable combination therapies of programmed death 1 (PD-1) or programmed death ligand 1 (PD-L1) inhibitors in terms of anti-tumor efficacy in clinical settings.MethodsAn electronic database search was performed using ClinicalTrials.gov, PubMed, and ASCO/ESMO annual meeting libraries. We included randomized or non-randomized trials designed to evaluate the efficacy and safety of combination therapies of PD-1/PD-L1 inhibitors and other anticancer drug-containing therapies. All clinical studies selected were solid tumors with objective response rate (ORR) data. The quality of the evidence was assessed with the Cochrane risk of bias tool or the Newcastle-Ottawa Scale. Meta-analysis used random effects models to pool results.ResultsSixteen studies involving 3793 patients were included in the primary analysis. These studies have a monotherapy group with PD-1/PD-L1 inhibitors as the control group or the in-study arm/cohort (1863 patients in the combination group with PD-1/PD-L1 inhibitors and 1930 patients in PD-1/PD-L1 inhibitor monotherapy). The pooled results showed that the combination of PD-1/PD-L1 inhibitors and other anticancer drugs significantly improved the ORR (relative risk [RR] = 1.79, 95% confidence interval [CI] 1.46, 2.20). In the subgroup analysis, PD-1/PD-L1 inhibitor plus DNA-synthesis or microtubule inhibitor led to a statistically significant improvement in the ORR compared to PD-1/PD-L1 inhibitor alone.ConclusionsIt was suggested that combinations of PD-1/PD-L1 inhibitors and potential immunogenic cell death (ICD) inducers improve the clinical anti-tumor efficacy, although updated meta-analyses based on the results of ongoing clinical trials are further needed.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".