Investigating the association (assoc) between mental health illness (MHI) and development of prostate cancer (PC) in a nationwide matched cohort of >5,000,000 US Veterans.
Notice bibliographique
Résumé
e17113 Background: Previous reports suggest that men with MHI who subsequently develop PC have worse outcomes. However, it has not been established whether a history of MHI is associated with a PC diagnosis (dx) or more aggressive PC. The objective of this study was to (i) investigate the assoc between MHI and development of PC, and (ii) in a subset of men with available Gleason Score (GS) data, assess the assoc between MHI and aggressive PC as measured by GS ≥7 PC at dx. Methods: This was a retrospective matched-cohort analysis to assess the assoc between MHI and time to PC dx in the Veterans Affairs (VA) Health Care System. Men with an ICD code for MHI dx between 2000-2020 were matched 1:1 to men with no MHI dx in the same time frame. The MHI dx date of the exposed (exp) male was assigned as the index date of the unexp male. Variables matched on included race, age at MHI exp (+/- 3 years), census region, and median household income. Uni- and multivariable competing risks models were used to test the assoc between MHI and time to PC using death from other causes as competing risk. In a subset of men with GS data available, logistic regression was used to test the assoc between MHI and GS ≥7 at PC dx. All multivariable models were adjusted for age, race, census region, income, Charlson Comorbidity Index, year of MHI index, and year of VA entry. Results: There were 2,597,810 MHI-exp men matched 1:1 to unexp men. During a median (Q1, Q3) follow up of 128 (65, 192) months, 390,977 PC diagnoses were observed (172,442 MHI-exp vs. 218,535 unexp). MHI-exp men were significantly less likely to be diagnosed with PC than unexp men in both uni- (HR: 0.798, 95% CI: 0.793-0.803) and multivariable (HR: 0.763, 95% CI: 0.758-0.768) analysis. Cumulative incidence estimates at 3, 5, 10, and 20 years were 2.1%, 3.1%, 5.2%, and 8.5%, respectively, for MHI-exp men vs 2.9%, 4.2%, 6.9%, and 11.7%, respectively, for unexp men. Among men with PC and available GS data (n = 51,404), 32,645 had GS ≥7 PC, of which 20,749 were MHI-exp vs 11,896 unexp. MHI-exp men had significantly higher odds of GS ≥7 PC in both uni- (OR: 2.38, 95% CI: 2.32-2.43) and multivariable (OR: 1.97, 95% CI: 1.92-2.02) analysis. Conclusions: Men with MHI are 20% less likely to be diagnosed with PC, however when diagnosed, are nearly 2 times more likely to have aggressive PC compared to non-MHI men. Although speculative based on the nature of the study, this may be due to poorer access to preventative health services resulting in delayed diagnoses.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 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 | 0,000 |
| 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 ».