Practice patterns and perceptions of survivorship care in Canadian genitourinary oncology: A multidisciplinary perspective
Bibliographic record
Abstract
INTRODUCTION: There is little knowledge of survivorship care specific to genitourinary (GU) cancers. To improve care delivery to this patient population, we need to clearly define physician perceptions of survivorship care. We therefore conducted a study to determine the challenges to GU cancer survivorship care in Canada. METHODS: A web-based questionnaire was e-mailed to physicians treating GU cancers in Canada, including urologists, radiation oncologists, and medical oncologists. Five domains were assessed: demography, current post-cancer treatment care, perspectives on barriers to survivorship care, accessibility to survivorship resources, and perspectives about advocacy groups. RESULTS: There were 306 responses, with 260 eligible for study. A total of 82% of physicians involve primary care practitioners (PCPs) at some point in survivorship care. Most physicians provide some form of written follow-up plan to PCPs. However, only 25% provided lifestyle recommendations and 53% included persistent and late effects of therapy. Lack of time or resources dedicated to survivorship care was the most commonly reported barrier. There was variation in accessibility to survivorship support programs among different subspecialties and regions. Advocacy groups generally were underutilized, particularly in testis cancer. Low response rate and the potential response bias are the main limitations of this survey. CONCLUSION: To our knowledge this is the first study to address the challenges of GU cancer survivorship care in Canada. The barriers and accessibility of survivorship care quoted in this survey may be used to improve care for this group of patients. Underutilization of advocacy groups may stimulate the advocacy groups and institutions to address its causes and solutions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".