Applying Data Mining Technology on Risk Analysis for Transitional Cell Carcinoma on End-Stage Renal Disease Patients with Maintenance Hemodialysis
Keywords:Hemodialysis, transitional cell carcinoma, insurance data, urinary tract disease, data mining, Cox regression
AbstractThe purpose of this study was application the general insurance claims data to investigate the risk of transitional cell carcinoma (TCC) for patients with hemodialysis (HD). This study surveyed 4577 patients with end-stage renal disease undergoing maintenance HD and 970339 patients without HD identified from claims data of National Health Insurance from 1997 to 2010. Incidence densities of TCC in upper urinary tract (UUT) and bladder only were estimated for these two cohorts. Hazard ratios (HRs) of TCC were measured in association with HD, covariates and comorbidities. Based on the result, the risk rate of TCC and UUT of patients with HD was higher than patients without HD. The risk of female was lower than male. The risk in TCC of female was .63 times of male. The age was positive with the risk of TCC an UUT. One more unit of age of patients, and the risk of TCC increase 1.04 times. One more unit of age of patients, and the risk of UUT increase 1.04 times.
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