Association of Patient Sex With Efficacy of Immune Checkpoint Inhibitors and Overall Survival in Advanced Cancers
Bibliographic record
Abstract
IMPORTANCE: Sex-associated differences in immune response are known, but a meta-analysis suggested men, compared with women, derive greater value from immunotherapy for advanced solid-organ malignant neoplasms. However, methodologic concerns and subsequent trials have placed these results in doubt. OBJECTIVE: To perform an updated, comprehensive meta-analysis that assesses the efficacy of immunotherapy in advanced cancers according to patient sex. DESIGN, SETTING, AND PARTICIPANTS: A systematic review of studies (n = 23) indexed in MEDLINE (PubMed), Embase, and Scopus from inception of these databases to October 2, 2018, was conducted. Randomized clinical trials that compared immunotherapy with standard of care in the treatment of advanced solid-organ malignant neoplasms were included if overall survival was reported as an outcome and if data stratified by patient sex were available. Observational studies, editorials, commentaries, review articles, non-peer-reviewed publications, studies that compared various immunotherapy regimens, studies that reported other measures of oncologic response, and studies that reported subgroup analyses for 1 sex only were excluded. MAIN OUTCOMES AND MEASURES: Overall survival, with a test for heterogeneity between women and men, to assess the null hypothesis that no difference in the survival advantage of immunotherapy exists by patient sex. RESULTS: This meta-analysis included 23 randomized clinical trials that reported on 9322 men (67.9%) and 4399 women (32.1%); the age of most patients was in the 70s. An overall survival benefit of immunotherapy was found for both men (hazard ratio [HR], 0.75; 95% CI, 0.69-0.81; P < .001) and women (HR, 0.77; 95% CI, 0.67-0.88; P = .002). Random-effects meta-analysis of study-level differences in response to immunotherapy demonstrated no statistically significant difference between the sexes (I2 = 38%; P = .60). Subgroup analyses according to disease site, line of therapy, class of immunotherapy, study methodology, and representation of women recapitulated these findings. CONCLUSIONS AND RELEVANCE: Stratified analyses demonstrated no statistically significant association of patient sex with the efficacy of immunotherapy in the treatment of advanced cancers using overall survival as the outcome.
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.021 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".