The potential role of frailty in modifying quality-of-life related outcomes in metastatic castration-resistant prostate cancer (mCRPC) patients receiving docetaxel, abiraterone, enzalutamine, and radium 223.
Notice bibliographique
Résumé
63 Background: As the arsenal of therapeutic agents for mCRPC expands, frailty-informed care is emerging as a strategy for tailoring management decisions. Yet, data to guide this approach and to ascertain its impact on the mood, fatigue, pain, and quality of life (QoL) experienced by older men with mCRPC remain lacking. We examined patient-reported outcomes, stratified by a validated frailty index (FI), for mCRPC treatment with docetaxel chemotherapy (CHEMO), abiraterone (ABI), enzalutamide (ENZA), or radium 223 (RAD). Methods: Older (aged 65+) men starting one of four approved therapies for mCRPC were enrolled in a multicenter prospective cohort study. Assessing their mood, fatigue, pain, and QoL with PHQ-9, ESAS tiredness, ESAS pain, and FACT-G total as well as subscale scores, we used linear mixed effect models to determine change in each outcome over time (0, 3, 6 months). At end of treatment, we administered the Decisional Regret Scale. We then constructed a FI from 34 variables that span laboratory abnormalities, geriatric syndromes, instrumental activities of daily living, social support, as well as emotional, cognitive, and physical deficits. Following established cut-offs, we categorized patients as non-, pre-, and frail, then performed stratified linear mixed effects regression analyses to identify differences in outcomes by frailty status. Results: A total of 198 men (mean age 75.1) starting CHEMO (n = 70), ABI (n = 38), ENZA (n = 67), and RAD (n = 29) were included, of which 9.6%, 1.5%, 5.6%, and 2.5%, respectively, were determined frail. Frailty correlated only modestly with age (Pearson r = 0.27). Independent of frailty status, patients across treatment cohorts were similar in terms of baseline QoL-related measures, with the exceptions of mood (p = 0.033) and pain (p = 0.034). Over time, no significant change in QoL was reported, although all four therapies resulted in generally low levels of decisional regret and similar trends of improved pain but worsened mood (p = 0.006 and 0.02, respectively). At baseline, frailty status correlated with worse FACT-G total (p < 0.001) and functional well-being (p < 0.001), as well as worse depression scores (p < 0.001). According to FI-stratified analysis, frail patients experienced similar QoL-related outcomes to fit patients for all measures aside from mood (p < 0.001). Contrary to our hypotheses, frailty was not associated with significant worsening in emotional well-being or functional well-being in response to mCRPC treatment. Conclusions: Of the older men receiving care for mCRPC, frail patients may experience generally similar trends in QoL as fit patients. Interestingly, frailty status, rather than treatment modality, may play more of a contributory role to changes in QoL-related outcomes over time.
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 | 0,000 |
| 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) | 0,001 | 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 ».