Successful implementation of a disease-specific survivorship program for men with prostate cancer (PC) and their partners.
Bibliographic record
Abstract
31 Background: Treatment for localized PC can adversely impact the quality of life for the patient (pts) and his partner. Addition of androgen deprivation therapy (ADT) to treat biochemical relapse or metastatic disease can result in further symptoms. We hypothesized that PC pts and partners would benefit from a clinical, educational, research-based approach to care that would focus on their specific needs. Methods: Funding from government agencies and philanthropic sources were used to establish a survivorship program in the urology clinic at the Vancouver Prostate Centre. A multi-disciplinary management team was formed to oversee the program. The Prostate Cancer Supportive Care (PCSC) Program is organized around 5 thematic modules 1) information about PC and primary treatment options (TX), 2) sexual health and intimacy (SH), 3) lifestyle changes in diet and exercise (DE), 4) managing the side effects of ADT, 5) incontinence and pelvic floor physiotherapy (PT). Group educational sessions (ED) are held 1-2 times monthly. Individual clinic appointments with SH and PT clinicians are also available. A program manager, clinic coordinator, and research assistant run PCSC on a day-to-day basis. Results: PCSC was initiated in January 2013. Urologists, nurses, pharmacists, and radiation oncologists referred patients to PCSC. Of 802 pts who enrolled (167 in 2013, 369 in 2014, and 266 in 2015 to date), to receive the quarterly newsletter, 626 (78%) chose to actively participate in at least one module (summarized in table). Feedback from couples, participating clinicians, and allied health personnel has been overwhelmingly positive. In addition, the PCSC population is proving to be a rich source of patients for research projects and training opportunities for young MDs. Conclusions: The results demonstrate that implementation of a disease specific survivorship program is feasible, well received and has other unanticipated benefits. Outcomes research and intervention protocols are in progress to address our hypothesis. [Table: see text]
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".