Toxicity-benefit analysis of advanced prostate cancer trials using weighted toxicity scoring
Bibliographic record
Abstract
OBJECTIVE: The weighted toxicity score (WTS) is a metric suitable for comparing the toxicity burden in experimental versus control arms of randomized controlled trials (RCTs). When paired with clinical endpoints, the WTS offers a framework to evaluate the toxicity-benefit profile of anti-cancer agents. This study applied the WTS to phase III advanced prostate cancer (PC) clinical trials. DESIGN: Select phase III PC RCTs with adverse event (AE) data were compiled. The WTS was calculated for each trial arm using 2 approaches: (1) all AEs (A-WTS) and (2) symptomatic AEs (S-WTS). Percent change in WTS between trial arms quantified the toxicity burden, while hazard ratios (HRs) for overall survival (OS) and progression-free survival (PFS) were used to assess efficacy. RESULTS: Seventeen RCTs were analyzed (investigational agents: androgen-receptor signaling inhibitors [ARSi, n = 4], poly (ADP-ribose) polymerase inhibitor monotherapy [PARPi, n = 2], ARSi + PARPi [n = 3], ARSi + ARSi [n = 3], triplet therapy [n = 3], and docetaxel as well as Lutetium-177 (177Lu)-PSMA-617) [n = 1 each]). Overall, toxicity and efficacy were greater among experimental than control arms (median A-WTS 6.62 vs. 4.10; median S-WTS 3.91 vs. 3.08; median HR for OS 0.75, median HR for PFS 0.61). ARSi + PARPi studies observed the highest average A-WTS increase (78%), whereas ARSi + ARSi and triplet therapy trials noted the lowest average A-WTS increases (31% and 32%, respectively) with favorable clinical outcomes. CONCLUSIONS AND RELEVANCE: RCTs demonstrated increased toxicity in experimental arms relative to controls, with both toxicity and survival outcomes varying across therapeutic strategies.
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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 | 0.012 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".