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Impact of body mass index on survival of patients with surgically treated renal cell carcinoma.

Donat SM, Salzhauer EW, Mitra N, Yanke BV, Snyder ME, Russo P

Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. donats@mskcc.org

PURPOSE: Population studies link increased BMI with an increased risk of cancer and cancer mortality and in particular a greater risk of RCC. We evaluated the impact of BMI and other clinical/pathological characteristics on survival in patients with RCC treated with radical or partial nephrectomy. MATERIALS AND METHODS: Between 1995 and 2003 patients undergoing radical (760) or partial (399) nephrectomy for RCC were entered into a database. BMI data were available on 1,137 of 1,159 (98%). Demographic and clinical/pathological parameters were analyzed. World Health Organization BMI definitions (normal-less than 25 kg/m(2), overweight-25 to 29.9 kg/m(2), obese-30 kg/m(2) or more) were used. RESULTS: A total of 75% of patients had greater than normal BMI with 472 (41.5%) overweight and 387 (34.0%) obese. Median followup was 33 months with a median overall survival of 110 months and a 5-year overall survival probability of 0.79. BMI categories were similar in age, gender, smoking status, presenting symptoms, tumor size, stage, and type of surgery. Significant increases in blood loss and operative time (p <0.05) were seen with increasing BMI. Although BMI 30 kg/m(2) or greater was associated with a higher proportion of clear cell histology (p = 0.002), it did not translate into an increased pathological stage, or incidence of metastasis. Multivariate analysis revealed age older than 65 years, systemic symptoms, surgery type, and pathological stage impacted overall survival (p <0.05). CONCLUSIONS: Although an increased BMI was associated with a greater proportion of clear cell histology, comorbidity, and surgical morbidity, BMI did not adversely impact overall or progression-free survival.

Published 12 January 2006 in J Urol, 175(1): 46-52.
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Biostatistics Books

Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)

Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)