Recursive Partitioning Analysis of Systemic Therapy after Radiotherapy in Patients with Brain Metastases.
Oncol Res Treat
; 44(3): 86-92, 2021.
Article
en En
| MEDLINE
| ID: mdl-33477159
ABSTRACT
PURPOSE:
The purpose of this study was to identify factors associated with the initiation or continuation of systemic treatment after brain irradiation. The outcome of interest was a utilization rate of at least 75%, given that active extracranial disease is common in patients with brain metastases. If left untreated, extracranial disease limits survival, regardless of successful local treatment of the brain metastases. In this context, systemic therapy has been shown to improve survival, e.g., after whole-brain radiotherapy. PATIENTS ANDMETHODS:
The study included 185 patients with active extracranial disease, 60% of whom received systemic therapy.RESULTS:
Survival from the start of brain irradiation was longest in patients who received additional immune checkpoint inhibitors, endocrine treatment, or anti-HER-2 drugs. After uni- and multivariate analyses, Eastern Cooperative Oncology Group performance status (PS) was selected as the first prediction criterion in the recursive partitioning analysis (RPA) decision tree analysis. RPA was successful for patients with PS 0-1, but patients with PS 2 had lower treatment utilization rates (maximum 60-70%, with a disease-dependent impact of age and LabBM score [blood test results]). The highest utilization rates were observed in (1) patients with PS 0 and (2) those with breast cancer, small-cell lung cancer, or lung adenocarcinoma with PS 1.CONCLUSIONS:
These results inform the multidisciplinary discussion and treatment planning for the common scenario of simultaneous intra- and extracranial metastases.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Neoplasias Encefálicas
/
Neoplasias Pulmonares
Tipo de estudio:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Oncol Res Treat
Año:
2021
Tipo del documento:
Article