A tailored phase I-specific patient-reported outcome (PRO) survey to capture the patient experience of symptomatic adverse events
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Patient perspectives are fundamental to defining tolerability of investigational anti-neoplastic therapies in clinical trials. Phase I trials present a unique challenge in designing tools for efficiently collecting patient-reported outcomes (PROs) given the difficulty of anticipating adverse events of relevance. However, phase I trials also offer an opportunity for investigators to optimize drug dosing based on tolerability for future larger-scale trials and in eventual clinical practice. Existing tools for comprehensively capturing PROs are generally cumbersome and are not routinely used in phase I trials. METHODS: Here, we describe the creation of a tailored survey based on the National Cancer Institute's PRO-CTCAE for collecting patients' perspectives on symptomatic adverse events in phase I trials in oncology. RESULTS: We describe our stepwise approach to condensing the original 78-symptom library into a modified 30 term core list of symptoms which can be efficiently applied. We further show that our tailored survey aligns with phase I trialists' perspectives on symptoms of relevance. CONCLUSIONS: This tailored survey represents the first PRO tool developed specifically for assessing tolerability in the phase I oncology population. We provide recommendations for future work aimed at integrating this survey into clinical practice.
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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 | 0.003 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it