Post-Treatment Adverse Health Correlates among Prostate Cancer Survivors in a Sample of Men Residing in Atlantic Canada
Bibliographic record
Abstract
BACKGROUND: Recent large population-based studies have shed light on an association between prostate cancer (PCa) survivorship and mental health, which emerged when the comparison group was either men without a history of cancer or those with any other type of cancer except prostate. Here we examine the role of surgery alone, compared to other types of treatment modalities in this association in a population-based sample of men with prostate or other types of cancer. METHODS: A cross-sectional analysis was conducted on a subsample of 632 male participants aged 36-69 from the 2009-2015 survey cycle of the Atlantic PATH cohort study. The primary outcomes were the presence of mild, moderate or severe depression or anxiety indicators and were assessed using the seven-item generalized anxiety disorder (GAD-7) scale and the nine-item Patient Health Questionnaire (PHQ-9), respectively. The presence of a lifetime history of PCa or other form of cancer (except PCa) was the main predictor variable and was assessed in cancer treatment modality (surgery or other types of treatment modalities) stratified analyses. Covariates included age, marital status, household income, comorbidity, and survivorship time. RESULTS: The presence of depression in this sample was prevalent among 17.7% of men, and of anxiety among 9.3% of men. Survivors who were treated with surgery for their PCa diagnosis had 7.55 statistically significantly higher odds of screening positive for current depression symptoms compared with those of other forms of cancer in controlled analyses. These differences were not observed for anxiety. CONCLUSIONS: These findings emphasize the need for multidisciplinary survivorship care plans among PCa patients, especially those who undergo surgery. Targeted programming aimed at prioritizing and delivering comprehensive mental health support to PCa survivors early in the survivorship journey is justified.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".