Financial toxicity, quality of life, symptom burden, and access to resources in early-phase clinical trial (EP-CT) participants.
Notice bibliographique
Résumé
103 Background: EP-CTs are an important therapeutic option for patients, and financial toxicity represents an increasing concern in oncology. Little is known about the financial toxicity of EP-CT participants. We sought to describe baseline financial toxicity in EP-CT participants and assess associations of this factor with patient characteristics, quality of life (QOL), symptom burden, and access to resources. Methods: We prospectively enrolled consecutive adults participating in EP-CTs at Massachusetts General Hospital from 04/2021 – 01/2023. Participants completed surveys at time of treatment initiation that assessed financial toxicity (Comprehensive Score for Financial Toxicity [COST tool], higher scores indicate greater financial wellbeing). We adapted a financial toxicity grading scale proposed by the creators of the COST tool to define levels: low (COST ≥26) and high (COST 0–25). We surveyed QOL (Functional Assessment of Cancer Therapy-General) and symptom burden (psychological: Patient Health Questionaire-4; physical: Edmonton Symptom Assessment System). Patients were asked their concerns regarding access to resources. We explored associations of financial toxicity with patient characteristics, QOL, symptom burden, and access to resources. Results: Of 221 eligible patients, we enrolled 196 (median age = 62.3 years [range 31.8-88.6], 57.1% female). Most common tumors were gastrointestinal (33.2%) and breast (20.4%); most (93.7%) had metastatic disease. Patients had an average COST score of 28.4 (SD 9.0), with 33.7% reporting high financial toxicity. Patients with high financial toxicity were more likely to be <65 years (70.0% vs 47.7%, p=0.003), unemployed (44.6% vs 17.7%, p<0.001), lack a college degree (52.3% vs 25.6%, p<0.001), and have income <$60,000 (60.6% vs 25.4%, p<0.001) compared to those with low financial toxicity. Compared to those with low toxicity, patients with high financial toxicity also had lower QOL scores (69.9 vs 77.3, p<0.001) and increased psychological (1.3 vs 0.9, p=0.02) and physical (19.3 vs 15.9, p=0.091) symptom burden, although increased physical symptoms did not reach statistical significance. Those with high financial toxicity were more likely to report concerns regarding access to several resources (housing [10.6% vs 2.3%, p=0.033], bill paying [31.8% vs 3.8% 3.8%, p<0.001], food [9.0% vs 0.7%, p<0.006], employment [21.2% vs 1.5%, p<0.001]; there was no significant difference in transportation [22.7% vs 16.1%, p=0.3]). Conclusions: We found that one third of EP-CT participants report high financial toxicity and identified factors associated with higher toxicity. We demonstrated novel associations between high financial toxicity and lower QOL, greater depression, and increased concerns regarding access to resources. Findings highlight the need to address financial toxicity among this population.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».