L’incohérence de l’incohérence. Les rapports troubles du révélé et du rationnel textuel
Bibliographic record
Abstract
Immune checkpoint blockade (ICB) therapies are one of the greatest advances in the history of cancer care and are now commonly used in the management of many different malignancies. However, much remains unknown about the factors that affect the efficacy and side effect profile of these agents. This review delves into the published literature that evaluates the intricate interplay between race, age, gender, and social determinants in shaping outcomes following ICB across solid tumors and hematologic malignancies. We examine the pivotal phase 2 and 3 trials to evaluate the demographics of participants and outcomes based on these variables, if reported. Most, but not all, trials reported some basic demographic information like age, sex, race, ethnicity, and/or geographic area for enrollment. Clinically relevant biological markers that could affect ICB outcomes such as obesity or markers of social determinants of health were largely not reported. Trials were generally representative for men and women based on expected prevalence for a given malignancy, but often under-represented non-white participants and rarely enrolled patients from the global south. Subgroup analyses were conducted in many ICB trials for solid malignancies, but rarely conducted for hematologic malignancies. These analyses largely showed similar qualitative benefit across subgroups, but adverse events were rarely reported by subgroup. This review adds to our understanding of the populations that these clinical trials have studied and highlight the urgent need to redouble our efforts at increasing the diversity of the population in future ICB trials.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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; both teacher heads 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".