International perspectives on suboptimal patient‐reported outcome trial design and reporting in cancer clinical trials: A qualitative study
Bibliographic record
Abstract
PURPOSE: Evidence suggests that the patient-reported outcome (PRO) content of cancer trial protocols is frequently inadequate and non-reporting of PRO findings is widespread. This qualitative study examined the factors influencing suboptimal PRO protocol content, implementation, and reporting, and use of PRO data during clinical interactions. METHODS: Semi-structured interviews were conducted with four stakeholder groups: (1) trialists and chief investigators; (2) people with lived experience of cancer; (3) international experts in PRO cancer trial design; (4) journal editors, funding panelists, and regulatory agencies. Data were analyzed using directed thematic analysis with an iterative coding frame. RESULTS: Forty-four interviews were undertaken. Several factors were identified that could influenced effective integration of PROs into trials and subsequent findings. Participants described (1) late inclusion of PROs in trial design; (2) PROs being considered a lower priority outcome compared to survival; (3) trialists' reluctance to collect or report PROs due to participant burden, missing data, and perceived reticence of journals to publish; (4) lack of staff training. Strategies to address these included training research personnel and improved communication with site staff and patients regarding the value of PROs. Examples of good practice were identified. CONCLUSION: Misconceptions relating to PRO methodology and its use may undermine their planning, collection, and reporting. There is a role for funding, regulatory, methodological, and journalistic institutions to address perceptions around the value of PROs, their position within the trial outcomes hierarchy, that PRO training and guidance is available, signposted, and readily accessible, with accompanying measures to ensure compliance with international best practice guidelines.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".