The PROTEUS-Trials Consortium: Optimizing the use of patient-reported outcomes in clinical trials
Bibliographic record
Abstract
BACKGROUND: The assessment of patient-reported outcomes in clinical trials has enormous potential to promote patient-centred care, but for this potential to be realized, the patient-reported outcomes must be captured effectively and communicated clearly. Over the past decade, methodologic tools have been developed to inform the design, analysis, reporting, and interpretation of patient-reported outcome data from clinical trials. We formed the PROTEUS-Trials Consortium (Patient-Reported Outcomes Tools: Engaging Users and Stakeholders) to disseminate and implement these methodologic tools. METHODS: PROTEUS-Trials are engaging with patient, clinician, research, and regulatory stakeholders from 27 organizations in the United States, Canada, Australia, the United Kingdom, and Europe to develop both organization-specific and cross-cutting strategies for implementing and disseminating the methodologic tools. Guided by the Knowledge-to-Action framework, we conducted consortium-wide webinars and meetings, as well as individual calls with participating organizations, to develop a workplan, which we are currently executing. RESULTS: Six methodologic tools serve as the foundation for PROTEUS-Trials dissemination and implementation efforts: the Standard Protocol Items: Recommendations for Interventional Trials-patient-reported outcome extension for writing protocols with patient-reported outcomes, the International Society for Quality of Life Research Minimum Standards for selecting a patient-reported outcome measure, Setting International Standards in Analysing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium recommendations for patient-reported outcome data analysis, the Consolidated Standards for Reporting of Trials-patient-reported outcome extension for reporting clinical trials with patient-reported outcomes, recommendations for the graphic display of patient-reported outcome data, and a Clinician's Checklist for reading and using an article about patient-reported outcomes. The PROTEUS-Trials website (www.TheProteusConsortium.org) serves as a central repository for the methodologic tools and associated resources. To date, we have developed (1) a roadmap to visually display where each of the six methodologic tools applies along the clinical trial trajectory, (2) web tutorials that provide guidance on the methodologic tools at different levels of detail, (3) checklists to provide brief summaries of each tool's recommendations, (4) a handbook to provide a self-guided approach to learning about the tools and recommendations, and (5) publications that address key topics related to patient-reported outcomes in clinical trials. We are also conducting organization-specific activities, including meetings, presentations, workshops, and webinars to publicize the existence of the methodologic tools and the PROTEUS-Trials resources. Work to develop communications strategies to ensure that PROTEUS-Trials reach key audiences with relevant information about patient-reported outcomes in clinical trials and PROTEUS-Trials is ongoing. DISCUSSION: The PROTEUS-Trials Consortium aims to help researchers generate patient-reported outcome data from clinical trials to (1) enable investigators, regulators, and policy-makers to take the patient perspective into account when conducting research and making decisions; (2) help patients understand treatment options and make treatment decisions; and (3) inform clinicians' discussions with patients regarding treatment options. In these ways, the PROTEUS Consortium promotes patient-centred research and care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.948 | 0.947 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.024 | 0.039 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.048 | 0.030 |
| Open science | 0.021 | 0.054 |
| Research integrity | 0.014 | 0.025 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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; the direct Gemma label and the distilled Codex classifier 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".