Implementation of a disease specific survivorship program for men with prostate cancer and their partners.
Bibliographic record
Abstract
e21569 Background: Treatment for localized prostate cancer (PC) can adversely impact the quality of life for the patient (pt) and his partner. Addition of androgen deprivation therapy (ADT) when indicated can result in further symptoms. We hypothesized that PC pts and partners would benefit from a clinical, educational, research-based approach that would focus on their specific needs. Methods: A multi-disciplinary survivorship program, the Prostate Cancer Supportive Care (PCSC) Program, was established in the Vancouver Prostate Centre with funding from government agencies and philanthropic sources in January 2013. The program was originally organized around 5 thematic modules: information about PC and primary treatment options (TX); sexual health and intimacy (SH); lifestyle changes in diet and exercise (DE); managing the side effects of ADT; incontinence and pelvic floor physiotherapy (PT). In late 2015, a psycho-oncology (PO) module was initiated to address emotional needs of patients and their partners. Group educational sessions for each module are held 1-2 times monthly and individual clinic appointments with SH, PT, PO and DE clinicians are also available. Urologists, radiation oncologists, primary care physicians, nurses and pharmacists refer pts to PCSC. Results: Of 917 pts who enrolled (167 in 2013; 369 in 2014; 281 in 2015), 741 (81%) chose to participate in at least one module (TX, 28%; SH, 65%; DE, 20%; ADT, 15%; PT, 37%). Median age at enrollment was 66 yrs (range 42 to 92); 51.6% enrolled within 12 months of diagnosis. 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 pts for research projects and training opportunities for young MDs. Conclusions: The results demonstrate that implementation of a PC specific survivorship program is feasible, well received and has other unanticipated benefits. SH and PT are the most commonly utilized services. Newly obtained funding will extend PC supportive care services to additional sites in BC. Since SH and PT expertise are not widely available across BC, training programs that focus in these areas for PC are in development.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".