Quality of Life Determinants in Patients with Metastatic Prostate Cancer: Insights from a Cross-Sectional Questionnaire-Based Study
Bibliographic record
Abstract
Introduction: Prostate cancer is one of the most prevalent malignancies affecting men globally, with a significant impact on health-related quality of life (HRQOL). With the recent therapeutic advancements and improvements in survival, there is a need to understand the determinants of HRQOL in metastatic prostate cancer patients to optimize treatment strategies for quality of life as the number of survivors increases. The aim of this study was to identify clinical variables that affect HRQOL and its domains in patients with metastatic prostate cancer. Methods: We conducted a cross-sectional questionnaire-based study in patients diagnosed with metastatic prostate cancer at a tertiary cancer center in India. Baseline clinical features, treatment details, and completed Functional Assessment of Cancer Therapy—Prostate (FACT-P), composed of FACT-general (FACT-G) and prostate cancer-specific concerns subscale (PCS) and FACT-P Trial Outcome Index (FACT-P TOI) questionnaires, were collected. The mean total, as well as individual domain scores, were calculated. Additionally, these were stratified by the current treatment being received by patients. Linear regression was used to identify independent factors affecting HRQOL in these patients. Results: Of the 106 enrolled patients, 84 completed the FACT-P questionnaire and were included in the analysis. The median age was 66 years, and at the time of assessment, 3 patients (3.6%) were receiving androgen deprivation therapy only, 53 patients (63.1%) were on ADT + androgen receptor-targeted agents (ARTAs), and 18 patients (21.4%) patients received ADT + chemotherapy. The mean (±standard deviation) of the FACT-P TOI score was 70.33 (±15.16); the PCS subscale was the most affected, followed by functional well-being. Patients on chemotherapy scored significantly higher on PCS, but the composite scores were not significantly different. Univariable regression identified obesity (body mass index > 25 kg/m2) and duration of first-line treatment as significant predictors of better HRQOL; however, obesity was the only independent predictor in multivariable analysis (β = 8.2; 95% confidence interval, 1.2 to 15.0; p = 0.022). Obesity also independently predicted a better FACT-P and its physical well-being domain score and PCS. Conclusion: Prostate cancer patients experience impaired QoL, especially in the prostate cancer-specific and functional well-being domains. Lower BMI is an independent predictor of poor QoL, and this requires efforts to assess the impact of strategies to manage the nutritional status of patients with metastatic disease on QoL outcomes.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".