Current Mental Distress Among Men With a History of Radical Prostatectomy and Related Adverse Correlates
Bibliographic record
Abstract
Recent reviews and observational studies have reported that patients with prostate cancer (PCa) are at increased risk of mental health issues, which in turn negatively affects oncological outcomes. Here, we examine possible explanatory variables of mental distress in a population-based cohort of men who have undergone radical prostatectomy (RP). Data were derived from a Maritimes-Canada online survey assessing patient-reported quality of life outcomes between 2017 and 2019 administered to 136 men (47–88 years old, currently in a relationship) who have undergone RP for their PCa diagnosis. The primary outcome was a validated assessment of mental distress, the Kessler Psychological Distress Scale (K10). Urinary function was assessed using the International Prostate Symptom Score, and relationship satisfaction was assessed using the Dyadic Assessment Scale. A multivariate logistic regression assessed the contribution of urinary function, relationship satisfaction, age, multimorbidity, additional treatments, medication for depression and/or anxiety, and survivorship time. A total of 16.2% men in this sample screened positive for mental distress. The severity of urinary problems was positively associated with increased mental distress ( OR = 4.79, 95% CI [1.04, 22.03]), while increased age ( OR = 0.87, 95% CI [0.78, 0.97]), relationship satisfaction ( OR = 0.14, 95% CI [0.3, .077]), and current medication for anxiety, depression, or both ( OR = 0.09, 95% CI [0.02, 0.62]) were protective factors. Survivorship time, the presence of additional comorbidities, or PCa treatments were not identified to be statistically significant contributions to the fitted model. Here, we report that RP survivors are prone to presenting with increased mental distress long after treatment. Screening for mental distress during RP survivorship is recommended.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".