Assessment of clinical trial protocols for pathology content using the <scp>SPIRIT‐Path</scp> guidelines highlights areas for improvement
Bibliographic record
Abstract
The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013 Statement provides evidence-based recommendations for the minimum content of clinical trial protocols. The Cellular Molecular Pathology Initiative, hosted by the UK National Cancer Research Institute, developed an extension, SPIRIT-Path, describing how to effectively incorporate pathology support into clinical trial protocols. The current study assessed the inclusion of SPIRIT-Path items in protocols of active clinical trials. Publicly available clinical trial protocols were identified for assessment against the new guidelines using a single UK hospital as the 'test site'. One hundred and ninety interventional clinical trials were identified as receiving support from the pathology department. However, only 38 had publicly available full trial protocols (20%) and following application of the inclusion/exclusion criteria, 19 were assessed against the SPIRIT-Path guidelines. The reviewed clinical trial protocols showed some areas of compliance and highlighted other items that were inadequately described. The latter lacked information about the individuals responsible for the pathology content of the trial protocol, how pathology activities and roles were organised in the trial, where the laboratory work would be carried out, and the accreditation status of the laboratory. Only one trial had information specific to digital pathology, a technology certain to become more prevalent in the future. Adoption of the SPIRIT-Path checklist will facilitate comprehensive trial protocols that address all the key cellular and molecular pathology aspects of interventional clinical trials. This study highlights once again the lack of public availability of trial protocols. Full trial protocols should be available for scrutiny by the scientific community and the public who participate in the studies, increasing the transparency of clinical trial activity and improving quality.
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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 | 0.359 | 0.379 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.011 |
| 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; both teacher heads 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".