Social determinants of health (SDOH) and survival among patients with metastatic prostate cancer (mPC): A systematic literature review (SLR).
Notice bibliographique
Résumé
25 Background: Population level data show strong associations between race and other SDOH including income, education, and geographic region of residence. The relationship between SDOH and clinical outcomes has become increasingly recognized. This review examines the impact of SDOH on survival in patients with mPC in real-world (RW) settings. Methods: A systematic literature search in accordance with Cochrane guidelines was conducted on July 7, 2022, searching for RW studies published as full-text (Jan 2012-July 2022) and conferences (Jan 2019-July 2022) using Ovid MEDLINE, Embase, and Cochrane. A manual search of key congress websites for conference abstracts was also conducted. Studies which assessed the impact of SDOHs on survival, treatment access, and other clinical outcomes in patients with mPC were included in the overall SLR. Here, we present results from studies which assessed the impact of SDOH on overall survival (OS) and prostate cancer specific mortality (PCSM). Clinical trials were excluded. Results: Of 3,228 records screened, 86 studies were included, with findings reported in 67 full-text publications (60 US and 7 ex-US) and 28 conference abstracts (22 US and 6 ex-US). The impact of race on survival was reported in 54 studies. While most studies showed no difference between Black vs White for both OS (n=22) and PCSM (n=8), for patients on specific mPC treatments, there was an association between Black race and improved OS (n=5). Asian patients had improved OS vs White patients (n=4), and reduced PCSM vs White (n=6) and Black patients (n=1). Higher income was generally associated with improved OS (n=7), but no difference in PCSM (n=3). Although the regions compared differed, most studies found disparities in OS among US geographic regions (n=5). Education level was generally not associated with OS (n=2) or PCSM (n=3). Most studies showed that married patients had improved OS (n=4) and reduced PCSM (n=3) compared to unmarried patients. Conclusions: This SLR demonstrated that various SDOH are associated with disparities in survival among mPC patients. Asian race, which is generally associated with higher frequency of better SDOH risk factors, was linked with better OS. In contrast, Black race, which is generally associated with higher frequency of worse SDOH risk factors, was associated with similar or better OS. Having lower income and being unmarried were both associated with reduced OS, while disparities in OS were reported across geographic regions of the US. More studies are needed to understand why SDOH are linked with poor outcomes, including their connection with access to care.
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 | 0,009 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,010 |
| Bibliométrie | 0,013 | 0,013 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».