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Abstract

Background The selection of radiation therapy dose fractionation schedules for bone metastases is often based on the estimation of life expectancy. Therefore, accurate prognosis prediction is an important issue. It is reported that the Katagiri scoring system can be used to predict the survival of patients with bone metastases. We aimed to assess prognostic factors and validate the Katagiri scoring system in patients who were treated with radiation therapy for bone metastases. Materials/Methods We retrospectively reviewed data of all patients who were treated with radiation therapy for bone metastases between 2004 and 2013. Age, sex, Karnofsky performance status (KPS), Eastern Cooperative Oncology Group performance status (ECOG PS), primary site (lesions and characteristics), visceral metastases, laboratory data, previous chemotherapy, and multiple bone metastases were analyzed for associations with overall survival (OS). Katagiri scores were calculated for each patient and were used to compare OS. Results Out of the 616 patients included in this analysis, 574 had died and 42 remained alive. The median follow-up time for survivors was 42 months. Univariate analysis revealed that age (P = 0.604) and multiple bone metastases (P = 0.691) were not significantly associated with OS. Multivariate analysis revealed that sex, ECOG PS, KPS, primary characteristics, visceral metastases, laboratory data, and previous chemotherapy were significantly associated with OS. The survival rates at 3, 6, 12, and 24 months, categorized by Katagiri score, were as follows: score 0–3, 94.4, 77.8, and 61.1%, respectively; score 4–6, 67.7, 48.7, and 31.2%, respectively; and score 7–10, 39.1, 22.1, and 9.0%, respectively (P < 0.001). Conclusion Sex, ECOG PS, KPS, primary characteristics, visceral metastases, laboratory data, and previous chemotherapy were significant predictors of survival in patients with bone metastases. The Katagiri scoring system was significantly correlated with OS and can help us select the optimal dose-fractionation.

Journal

  • Radiation Oncology

    Radiation Oncology (14), 13, 2019-01-18

    BMC

Codes

  • NII Article ID (NAID)
    120006552886
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    1748-717X
  • Data Source
    IR 
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