Use of the Toxicity Index in Evaluating Adverse Events in Anal Cancer Trials
Bibliographic record
Abstract
Novel toxicity metrics that account for all adverse event (AE) grades and the frequency of may enhance toxicity reporting in clinical trials. The Toxicity Index (TI) accounts for all AE grades and frequencies for categories of interest. We evaluate the feasibility of using the TI methodology in 2 prospective anal cancer trials and to evaluate whether more conformal radiation (using Intensity Modulated Radiation Therapy) results in improved toxicity as measured by the TI. Patients enrolled on NRG/RTOG 0529 or nonconformal RT enrolled on the 5-Fluorouracil/Mitomycin arm of NRG/RTOG 9811 were compared using the TI. Patients treated on NRG/RTOG 0529 had lower median TI compared with patients treated with nonconformal RT on NRG/RTOG 9811 for combined GI/GU/Heme/Derm events (3.935 vs 3.996, P=0.014). The TI methodology is a feasible method to assess all AEs of interest and may be useful as a composite metric for future efforts aimed at treatment de-escalation or escalation.
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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 | 0.408 | 0.309 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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; 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".