Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology
Author(s) -
Johnny Kao,
Kenneth D. Gold,
Gina Zarrili,
Emily Copel,
Andrew J. Silverman,
Shanata S. Ramsaran,
David Yens,
Samuel Ryu
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0124329
Subject(s) - medicine , proportional hazards model , univariate analysis , oncology , radiation therapy , stage (stratigraphy) , cancer , prognostic variable , survival analysis , kidney cancer , prostate cancer , multivariate analysis , paleontology , biology
Background There is an urgent need for a robust, clinically useful predictive model for survival in a heterogeneous group of patients with metastatic cancer referred to radiation oncology. Methods From May 2012 to August 2013, 143 consecutive patients with stage IV cancer were prospectively evaluated by a single radiation oncologist. We retrospectively analyzed the effect of 29 patient, laboratory and tumor-related prognostic factors on overall survival using univariate analysis. Variables that were statistically significant on univariate analysis were entered into a multivariable Cox regression to identify independent predictors of overall survival. Results The median overall survival was 5.5 months. Four prognostic factors significantly predicted survival on multivariable analysis including ECOG performance status (0–1 vs. 2 vs. 3–4), number of active tumors (1 to 5 vs. ≥6), albumin levels (≥3.4 vs. 2.4 to 3.3 vs. <2.4 and primary tumor site (Breast, Kidney or Prostate vs. Other). Risk group stratification was performed by assigning points for adverse prognostic factors resulting in very low, low, intermediate and high risk groups. The median survival was >31.4 months for very low risk patients compared to 14.5 months for low risk, 4.1 months for intermediate risk and 1.2 months for high risk (p<0.001). Conclusions These data suggest that a model that considers performance status, extent of disease, primary tumor site and serum albumin represents a simple model to accurately predict survival for patients with stage IV cancer who are potential candidates for radiation therapy.
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