Abstract 2528: Rurality and neighborhood socioeconomic deprivation associated with patient-reported outcomes andsurvivalin men with prostate cancer in NRG RTOG 0415
Notice bibliographique
Résumé
Abstract Background: Prostate cancer is the most common cancer among men. Monitoring of patient-reported outcomes (PROs) can enhance provider-patient communication, promote better decision-making, and improve survival. Geospatial factors, namely rurality and neighborhood socioeconomic deprivation, could influence the experience across cancer treatment, thus impacting PROs and survival. This study examined associations of rurality, neighborhood socioeconomic deprivation (Area Deprivation Index [ADI]) with cancer treatment-related PROs and survival in men with prostate cancer. Methods: Data from men with prostate cancer in the trial NRG Oncology/RTOG 0415 were analyzed. In this trial, 1092 men were randomized to receive conventional radiotherapy (RT) or hypofractionated RT. Patients had Gleason scores of 2-6 and prostate-specific antigen of <10 ng/mL. Rurality was categorized as urban vs rural using Rural-Urban Continuum Codes via patient zip codes. Neighborhood socioeconomic deprivation was assessed by the ADI calculated via the American Community Survey by patient zip codes. The Expanded Prostate Cancer Index Composite (EPIC) measures cancer-specific quality of life (QOL); Hopkins Symptom Checklist measures anxiety and depression; EuroQoL-5 Dimension (EQ-5D) VAS and Index scores assess general health. All PROs were measured at baseline before and 6, 12, 24 and 60 months after RT. Overall survival (OS) and disease-free survival (DFS) were assessed using Cox proportional hazards models. Mixed effects models and generalized estimating equations were used to analyze PROs. Results: We analyzed 751 patients with complete data. Patients from the ADI 25% most deprived neighborhoods (vs. the other 75% of neighborhoods) were more likely to be non-white, unmarried and from rural areas. At baseline, patients from the most deprived areas had worse EPIC bowel score (P=0.011), worse sexual score (P=0.042) and worse hormonal score (P=0.015); patients from the most deprived areas had worse self-care (P=0.04) and more pain (P=0.047). Patients from rural areas had worse EPIC urinary score (P=0.03) and sexual score (P=0.003). Longitudinal analyses showed that ADI 25% most deprived areas (β=4.05, P=0.001) and rural areas (β=-5.70, P=0.003) were associated with worse EQ-5D VAS score. Compared to the 75% less deprived neighborhoods and urban, the ADI 25% most deprived neighborhoods and rural areas respectively had 47% (HR=1.466, P=0.033) and 93% (HR=1.925, P=0.026) relative increase in risk of recurrence or death (DFS). No differences were seen in OS. Conclusions: Patients with prostate cancer from the most deprived neighborhoods and rural areas had low QOL at baseline, poor general health and DFS. Interventions should target populations from socioeconomic deprived neighborhoods and rural areas to improve patient access to supportive care services and DFS. Citation Format: Jinbing Bai, Stephanie L. Pugh, Ronald Eldridge, Katherine Yeager, Qi Zhang, W Robert Lee, Amit B. Shah, Ian S. Dayes, David P. D'Souza, Jeff M. Michalski, Jason A. Efstathiou, John M. Longo, Thomas M. Pisansky, Jordan M. Maier, Sergio L. Faria, Anand B. Desai, Samantha A. Seaward, Howard M. Sandler, Mary E. Cooley, Deborah W. Bruner. Rurality and neighborhood socioeconomic deprivation associated with patient-reported outcomes andsurvivalin men with prostate cancer in NRG RTOG 0415 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2528.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».