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. 2005 Sep 1;23(25):6072-82.
doi: 10.1200/JCO.2005.08.104.

Survival in patients operated on for pathologic fracture: implications for end-of-life orthopedic care

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Survival in patients operated on for pathologic fracture: implications for end-of-life orthopedic care

Saminathan S Nathan et al. J Clin Oncol. .

Abstract

Purpose: Life expectancy is routinely used as part of the decision-making process in deciding the value of surgery for the treatment of bone metastases. We sought to investigate the validity of frequently used indices in the prognostication of survival in patients with metastatic bone disease.

Methods: The study prospectively assessed 191 patients who underwent surgery for metastatic bone disease. Diagnostic, staging, nutritional, and hematologic parameters cited to be related to life expectancy were evaluated. Preoperatively, the surgeon recorded an estimate of projected life expectancy for each patient. The time until death was recorded.

Results: Kaplan-Meier survival analyses indicated that the survival estimate, primary diagnosis, use of systemic therapy, Eastern Cooperative Oncology Group (ECOG) performance status, number of bone metastases, presence of visceral metastases, and serum hemoglobin, albumin, and lymphocyte counts were significant for predicting survival (P < .004). Cox regression analysis indicated that the independently significant predictors of survival were diagnosis (P < .006), ECOG performance status (P < .04), number of bone metastases (P < .008), presence of visceral metastases (P < .03), hemoglobin count (P < .009), and survival estimate (P < .00005). Diagnosis, ECOG performance status, and visceral metastases covaried with surgeon survival estimate. Linear regression and receiver-operator characteristic assessment confirmed that clinician estimation was the most accurate predictor of survival, followed by hemoglobin count, number of visceral metastases, ECOG performance status, primary diagnosis, and number of bone metastases. Nevertheless, survival estimate was accurate in predicting actual survival in only 33 (18%) of 181 patients.

Conclusion: A better means of prognostication is needed. In this article, we present a sliding scale for this purpose.

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