Impact of mental health illness (MHI) prior to prostate cancer (PC) diagnosis (Dx) on treatment (Tx) received and PC outcomes.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».