Examining the prevalence and predictors of anxiety and depression across treatment stages in prostate cancer: a systematic review
Bibliographic record
Abstract
Anxiety and depression are common in prostate cancer (PCa) patients and negatively impact the quality of life, treatment outcome, survival and overall well-being, thus, requiring interventions to meet the psychosocial needs of PCa patients across treatment stages. However, there is not enough information to guide the design of these interventions, as there are still areas of lack of clarity regarding the prevalence and predictors of anxiety and depression in PCa patients. Therefore, this review was conducted to examine the literature to identify the overall prevalence of anxiety and depression across treatment stages in PCa patients and to identify the predictors of anxiety and depression in this population. A literature search was conducted from the Cochrane library, Ovid Medline and APA PsycINFO databases. Eighteen eligible studies were included in the final review. The findings were analysed using a narrative synthesis. The study quality was assessed using the Joanna Briggs Institute critical appraisal checklist. The prevalence of anxiety and depression was found to be between 6% to 44.8% and 10% to 48%, respectively. Notably, the prevalence of depression was higher in the post-treatment phase than in the treatment phase. Finally, the result demonstrates that socio-economic/demographic, clinical and lifestyle factors determine patients' predisposition to anxiety and depression. These demonstrate that the prevalence of anxiety and depression is high across the PCa disease trajectory and that some patients are more likely to experience anxiety and depression than others. Therefore, we recommend periodic assessment to identify at risk patients and those with clinically significant or worsening levels of anxiety and depression for timely interventions to mitigate the risks or ameliorate the symptoms of anxiety and depression.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".