A systematic review of immune-related adverse event (irAE) reporting in clinical trials of immune checkpoint inhibitors (ICIs).
Bibliographic record
Abstract
3057 Background: ICIs are active in various solid tumors. irAEs are associated with ICI therapy that can affect multiple organ systems. Limited data exist regarding the quality of irAE reporting in ICI clinical trial publications. Methods: A systematic search of citations from MEDLINE, EMBASE and Cochrane databases identified prospective clinical trials involving ICIs in advanced solid tumors from 2003-2013. A 21-point (pt) (title, abstract, introduction 3 pts; methods 6 pts; results 9 pts and discussion 3 pts) quality score (QS) was adapted from the CONSORT harms extension statement. Items included in the 21-pt QS addressed: methods of irAE assessment; duration of irAE evaluation; time of onset, management, and resolution of irAEs; and consistency of safety reporting with authors’ conclusion. Two reviewers independently scored all trials and differences were resolved by consensus. Linear regression was used to identify factors associated with quality reporting. Results: After review of 2628 articles, 50 trial reports were included (50% phase I, 38% phase II, 6% phase III, and 6% not specified) with ICIs as monotherapy (52%) or combination treatments (48%). The median QS was 11.25 pts (range 3.5-17.5 pts). The median grade 3/4 toxicity rate reported was 20.5% (range 0-66%) and 29/50 (58%) of trials concluded that irAEs were tolerable. Of these 29 studies, 5 had grade 3/4 toxicity rates that exceeded 33%. Thirteen (26%) studies did not report any details on the outcome of irAEs and 22% did not provide information on how irAEs were managed. Six trials concluded that the ICI tested had reversible or manageable irAEs without presenting any data on irAE treatment or resolution. Multivariate regression analysis revealed that year of publication (within last 5 years) and journal impact factor >15 were significantly associated with a higher QS (p=0.002 for both). Conclusions: The reporting of irAEs due to ICIs is often incomplete. A standardized reporting method of irAEs that accounts for tolerability, management and reversibility is needed to ensure completeness and transparency of published trial data. This would enable a more precise evaluation of the therapeutic risk benefit ratio of ICIs.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Reporting · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Metaresearch Domain: Reporting · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.377 | 0.360 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.051 | 0.034 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".