Bibliographic record
Abstract
INTRODUCTION: Currently marketed epidermal growth factor receptor inhibitors (egfris) have been associated with high rates of dermatologic toxicity. METHODS: We formally reviewed the literature at medline and embase. Additional searches were conducted using Internet search engines. Studies were eligible if they were randomized controlled clinical trials of egfris, specifically cetuximab and panitumumab, in which at least one arm consisted of a non-egfri treatment and rash safety data were reported. The random effects method was used to pool differences in incident rash rates. Results are summarized as differences in incident rash (egfri therapy rate minus the non-egfri therapy rate) with corresponding 95% confidence intervals (cis) for all severity grades of rash and for grades 3 and 4 rash. RESULTS: Sixteen studies met the initial inclusion criteria of randomized controlled trials comparing egfri with non-egfri therapy. Seven publications that provided information on all severity grades of rash were found to have an overall difference in incident rash rate of 0.74 (95% ci: 0.68 to 0.81; p < 0.01). Thirteen studies that reported the incidence of grades 3 and 4 rash showed an overall difference in the incident rash rate of 0.12 (95% ci: 0.09 to 0.14; p < 0.01) between egfri and non-egfri therapy. Sensitivity analyses showed that the results were generally robust, but sensitive to small samples. CONCLUSIONS: Results quantify the difference in rash rates between egfri and non-egfri therapy.
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 | 0.036 | 0.057 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.091 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".