Literature DB >> 24879473

Do Sociodemographic Factors Influence Outcome in Prostate Cancer Patients Treated With External Beam Radiation Therapy?

Avielle Movsas1, Ramy Ibrahim, Mohamed A Elshaikh, Lois Lamerato, Mei Lu, Alexandra Sitarik, Deepak Pradhan, Eleanor M Walker, Hans Stricker, Svend O Freytag, Indrin J Chetty, Benjamin Movsas, Farzan Siddiqui.   

Abstract

OBJECTIVES: The purpose of this study was to analyze the prognostic significance of sociodemographic factors on biochemical control (bNED) and overall survival (OS) in patients with prostate cancer.
METHODS: Prostate cancer patients treated with definitive external beam radiation therapy (EBRT)±hormone therapy from 1997 to 2006 were analyzed in this IRB-approved study. Patient demographics, treatment (Tx), and clinical outcome were obtained from electronic medical records. Median household income (mHHI) at the census block group level was obtained from the 2000 census data. Data on disease and Tx parameters included Gleason score, pre-Tx prostate-specific antigen (PSA), T stage, year of Tx, EBRT dose, and use of hormone therapy. Patients were categorized as having low-risk, intermediate-risk, or high-risk disease. Sociodemographic factors included age, race, marital status, and mHHI. Biochemical failure was defined as nadir PSA+2 ng/mL. OS was based on death from any cause.
RESULTS: A total of 788 consecutive patients were studied with a median follow-up of 7 years (range, 0.4 to 15 y). African Americans comprised 48% of the patients, whereas 46% of patients were white and 6% were other races. Whites had an average mHHI of $60,190 compared with $36,917 for African Americans (P<0.001). After multivariable modeling, only radiation dose was predictive for bNED (P=0.004) or OS (P=0.008). No sociodemographic factors were predictive for either outcome. Higher radiation dose predicted for better biochemical control and OS.
CONCLUSIONS: This analysis suggests that sociodemographic factors are not important prognostic factors in determining outcome after EBRT for prostate cancer.

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Year:  2016        PMID: 24879473     DOI: 10.1097/COC.0000000000000093

Source DB:  PubMed          Journal:  Am J Clin Oncol        ISSN: 0277-3732            Impact factor:   2.339


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2.  Accurate training of the Cox proportional hazards model on vertically-partitioned data while preserving privacy.

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  2 in total

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