Development and validation of a recursive partitioning analysis-based pretreatment decision-making tool identifying ideal candidates for spine stereotactic body radiation therapy.
Cancer
; 129(6): 956-965, 2023 03 15.
Article
em En
| MEDLINE
| ID: mdl-36571507
ABSTRACT
BACKGROUND:
This study was aimed at developing and validating a decision-making tool predictive of overall survival (OS) for patients receiving stereotactic body radiation therapy (SBRT) for spinal metastases.METHODS:
Three hundred sixty-one patients at one institution were used for the training set, and 182 at a second institution were used for external validation. Treatments most commonly involved one or three fractions of spine SBRT. Exclusion criteria included proton therapy and benign histologies.RESULTS:
The final model consisted of the following variables and scores Spinal Instability Neoplastic Score (SINS) ≥ 6 (1), time from primary diagnosis < 21 months (1), Eastern Cooperative Oncology Group (ECOG) performance status = 1 (1) or ECOG performance status > 1 (2), and >1 organ system involved (1). Each variable was an independent predictor of OS (p < .001), and each 1-point increase in the score was associated with a hazard ratio of 2.01 (95% confidence interval [CI], 1.79-2.25; p < .0001). The concordance value was 0.75 (95% CI, 0.71-0.78). The scores were discretized into three groups-favorable (score = 0-1), intermediate (score = 2), and poor survival (score = 3-5)-with 2-year OS rates of 84% (95% CI, 79%-90%), 46% (95% CI, 36%-59%), and 21% (95% CI, 14%-32%), respectively (p < .0001 for each). In the external validation set (182 patients), the score was also predictive of OS (p < .0001). Increasing SINSCONCLUSIONS:
This novel score is proposed as a decision-making tool to help to optimize patient selection for spine SBRT. SINS may be an independent predictor of OS.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Coluna Vertebral
/
Radiocirurgia
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article