Disparities in diabetes-related outcomes in prostate cancer patients - role of social determinants of health and race
Notice bibliographique
Résumé
Abstract Background Prostate cancer (PC) patients on androgen deprivation therapy (ADT) with diabetes mellitus (DM) are at increased risk of cardiovascular events (CVE) and all-cause mortality (ACM), with metformin use linked to lower ACM. Purpose To analyze the impact of low socioeconomic status (SES), low educational levels, and Non-Hispanic Black (NHB) race on the relationship between DM, and its treatments, and CVE, cardiovascular mortality (CVm), prostate cancer-specific mortality (PCsm), and ACM within 2 years of PC diagnosis in patients ± ADT. Methods We utilized SEER-Medicare (national database for individuals 65 or older covered under US federal health insurance program merged with multiple state cancer registries with ~50% US cancers covered) to study a cohort of PC patients diagnosed from 2009 to 2017, identifying PC cases with ICD-10 - C61 and DM via the Medicare chronic condition file. CVE included Afib, AMI, peripheral artery disease, ischemic stroke, and heart failure. Two patient cohorts were analyzed: those enrolled in Medicare Parts A and B with PC (cohort 1), and those exclusively on ADT (± diabetic medications) and enrolled in Medicare Part D (cohort 2). Outcomes were evaluated using Fine-Gray and Cox models, with further analysis by subgroups: NHB, SES, and education. Results We analyzed 74,052 PC patients, with 6,682 having comprehensive Part D data. Of these, 35% in cohort 1 and 16% in cohort 2 had DM, with median ages of 73 and 72, respectively. Diabetes was more prevalent among NHB men than Non-Hispanic White (NHW), 49% vs 33% in cohort 1 and 25% vs 15% in cohort 2. In cohort 1, 9% and 8.5% of overall and DM individuals were on ADT. Risk factor details are in Table 1, and CVE, CVm, PCsm, and ACM are included in Table 2, showing higher risks of various cardiovascular outcomes for DM patients, particularly for those with low-education levels. In cohort 1, we demonstrated a higher risk of all outcomes across all subgroups with DM (p<0.001). No significant interaction with race was present except in those with lower education levels, where NHW men with lower education showed an increased risk of CVE (sHR 1.15, 95%CI 1.10-1.21, P<0.001). In cohort 2, compared to metformin, the use of all other DM medications was associated with higher ACM. Additionally, those on other DM medications with lower education levels had higher CVE rates. Non-DM individuals with low SES had lower CVE rates, while NHB non-DM individuals had higher PCsm. Conclusion Our study highlights disparities in PC patients with DM in relation to cardiovascular and ACM, with NHB men and those with lower SES and educational status having worse outcomes. Metformin use in patients with low education levels was associated with reduced ACM and CVE risk, indicating its potential protective effect. These findings emphasize the need for further research on the disparities in PC and effects of diabetes medications across different subpopulations.
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 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 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) | 0,003 | 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 ».