Additional file 1 of Are immune-related adverse events associated with the efficacy of immune checkpoint inhibitors in patients with cancer? A systematic review and meta-analysis
Bibliographic record
Abstract
Contains additional information about the methods, literature search and data analyses. Table S1. Additional characteristics of the eligible studies. Table S2. The Newcastle-Ottawa Scale (NOS) quality assessment of the enrolled studies. Figure S1. Subgroup analysis stratified by class of immune checkpoint inhibitors in the melanoma cohort. Figure S2. Forest plot (fixed effects model) of the association between immune-related adverse event development and progression-free survival. Figure S3. Subgroup analyses of the association between immune-related adverse event development and progression-free survival. Figure S4. Sensitivity analysis of the impact of each individual study on the pooled effect. A) Overall survival; B) Progression-free survival. Figure S5. Funnel plots of the overall survival results. (A) Without trim and fill; (B) With trim and fill. Figure S6. Funnel plots of the overall survival results in large sample size studies. Figure S7. Funnel plots of the progression-free survival results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.739 | 0.027 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".