Publication and Reporting Conduct for Pharmacodynamic Analyses of Tumor Tissue in Early-Phase Oncology Trials
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
PURPOSE: In principle, nondiagnostic biopsies for pharmacodynamic (PD) studies are carried out to inform decision-making in drug development. Because such procedures have no therapeutic value, their ethical justification requires that results be published. We aimed to assess the frequency of nonpublication of PD data in early phase cancer trials and to identify factors that prevent full publication of data. METHODS: We identified a sample of early-phase cancer trials containing invasive nondiagnostic tissue procurement for PD analysis from American Society of Clinical Oncology and American Association for Cancer Research meeting abstracts published between 1995 and 2005. These trials were followed to publication to determine frequency of nonpublication of PD data. Corresponding authors on early-phase cancer trials using invasive nondiagnostic research procedures were also surveyed to identify factors preventing full publication of PD data. RESULTS: In a sample of 90 trials, 22.2% (20 trials) resulted in no trial publication. Of published trials expected to contain PD reports, 16 (17.8%) did not include any PD data, and 21 (23.3%) reported incomplete PD data. We surveyed 92 authors; nonpublication was regarded as a frequent occurrence, and the most commonly cited barrier to full publication of PD data was strategic considerations in publication (58.8% of responding authors). CONCLUSIONS: Our results suggest ways that investigators, study planners, and reviewers can improve the burden/knowledge value balance in PD studies.
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.
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 | 0.179 | 0.806 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it