Impact of mental health illness (MHI) prior to prostate cancer (PC) diagnosis (Dx) on treatment (Tx) received and PC outcomes.
Bibliographic record
Abstract
5030 Background: We previously showed that men with MHI are 20% less likely to be diagnosed with PC, but when diagnosed, are nearly 2 times more likely to have aggressive PC compared to non-MHI men (Klaassen et al. ASCO 2023). It is unknown whether men with MHI and PC receive definitive Tx (DTx) and have comparable post-Tx outcomes to non-MHI men with PC. This study assessed (i) receipt of DTx, (ii) adherence to surveillance (surv) after Tx, and (iii) biochemical recurrence (BCR) rates among MHI vs non-MHI men. Methods: This national, retrospective study used a matched cohort of male veterans who were diagnosed with PC following recent MHI Dx (within 3 yrs prior to PC Dx) or diagnosed with PC in the absence of MHI from 2000-2020. Men were included if they were active users of the VA system (≥2 encounters with a VA provider within a 5-yr period from 2000-2020), their age at Dx was 40> and <80 yrs, and they had no prior malignancy. Competing risks (CR) models and cumulative incidence estimates were used to assess the association (assoc) between MHI and time from PC Dx to receipt of DTx (radical prostatectomy (RP) or radiotherapy (RT)), with death treated as a CR. Logistic regression models were used to test the assoc between MHI and adherence to surv (≥3 PSAs within the first yr following DTx, and at least 1 PSA in each yr to follow for the next 4 consecutive yrs) among treated men. CR models were used to assess the assoc between MHI and time from DTx to BCR (1 PSA >0.2 ng/mL, 2 PSA ≥0.2 ng/mL, or secondary Tx for elevated PSA for RP patients (pts), and a rise of ≥2 ng/mL or more above nadir after RT) among treated men. Results: 52,407 men diagnosed with PC (n=19,976 with MHI) were included. The cumulative incidence of DTx was higher for MHI vs non-MHI men (36% vs. 27% after 10 yrs). Men with pre-existing MHI were significantly more likely to receive DTx for PC than men without MHI in both univariable (UVA) (HR: 1.37, 95% CI: 1.32-1.41) and multivariable (MVA) (HR: 1.34, 95% CI: 1.30-1.39) analysis. Among men treated for PC (n=10,086), a similar proportion of MHI men met criteria for adhering to surv as non-MHI men (45% vs. 46%). The odds of adhering to surv did not differ significantly between MHI vs non-MHI men in UVA (OR: 0.96, 95% CI: 0.89-1.04); however, in MVA, the odds of adhering were lower in MHI vs non-MHI men (OR: 0.92, 95% CI: 0.85-1.00, p=0.049). The cumulative incidence of BCR following DTx was higher in MHI vs non-MHI men (31% vs. 28% after 15 yrs). The risk of BCR was significantly higher in MHI vs. non-MHI men in both UVA (HR: 1.08, 95% CI: 1.01, 1.15) and MVA (HR:1.07, 95% CI: 1.00-1.14). Conclusions: Men with MHI prior to PC Dx are more likely to receive DTx compared to non-MHI men with PC. Given that men with MHI and PC have more aggressive disease than non-MHI men with PC, more DTx is encouraging, however poorer post-Tx surv adherence and increased risk of BCR presents an opportunity for intervention to improve outcomes in these pts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".