Four-year overview of enrollment and participation in research studies conducted at the Prostate Cancer Supportive Care (PCSC) Program.
Bibliographic record
Abstract
39 Background: The mission of the Prostate Cancer Supportive Care (PCSC) Program at the Vancouver Prostate Centre (VPC) is to provide clinical care focused on the needs of prostate cancer patients and partners. It is comprised of six modules that are administered by medical professionals in urology, radiation oncology, sexual health nurses, registered dieticians, certified exercise physiologist, male pelvic floor physiotherapists, and couples’ counselling. Incorporation of research into daily care provides evidence for these practices, identifies areas for improvement, and tests new approaches. In order to evaluate the interface between the clinical and research programs, we reviewed the metrics of our PCSC program. Methods: Research studies were grouped by type. Screening and enrollment logs were reviewed to tally the total number of patients approached versus enrolled. Reasons for non-participation based on data in our enrollment logs were categorized. Results: Between Feb 2015 and Mar 2019, PCSC Program participated in 22 research studies: 9 therapeutic or lifestyle intervention studies (3 RCTs), 3 observational studies, 2 registries, 1 survey, 1 genetic study, 1 databank , 2 collaborative programmatic studies, 3 “permission to contact” studies (referral to the study team only). 8 of the 22 studies included recruitment of dyads (both patient and their partner or caregiver). Of 1080 consenting patients, 760 (70.4%) enrolled in 1 study, 210 (19.4%) in 2 studies, and 110 (10.2%) in > 3 studies. 583 patients did not consent due to lack of interest (43.7%), not available (21.1%), time constraints (10.3%), travel distance (6.7%). Conclusions: Our data show that a subspecialty supportive care program can provide a rich environment in which to conduct clinical research. We believe that the integration of the research program and personnel into the clinical setting is key to our success. Current on-going studies are evaluating the impact of and patient satisfaction with all PCSC modules.
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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 | 0.040 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".