Predicting Values Of Lipids And White Blood Cell Count For All-Site Cancer In Type 2 Diabetes

Type 2 diabetic patients have increased cancer risk. We developed and validated an all-site cancer risk score in a prospective cohort of 7374 Chinese type 2 diabetic patients free of known history of cancer at enrolment, using split-half validation. Spline Cox model was used to detect common risk factors of cancer and to guide linear transformation of non-linear risk factors. After a median follow-up period of 5.45 years, 365 patients (4.95%) developed cancer. Body mass index (BMI; <24.0 or >= 27.6 kg/m(2)), triglyceride (>= 0.81 to < 1.41 mmol/l), high-density lipoprotein cholesterol (< 0.9 or >= 1.8 mmol/l), total cholesterol (<4.3 mmol/l) and white blood cell (WBC) count (<5.8 x 10(9) count per litre) were associated with increased cancer risks and exhibited non-linear relationships. We further linear transformed these terms for selection using backward Cox regression (P<0.05forstay) in the training dataset. In the test dataset, calibration was checked using Hosmer-Lemeshow test and discrimination checked using area under receiver operating characteristic curve. In addition to age and current smoking, only linear-transformed total cholesterol and WBC count were selected. The risk score was 0.0488 x age (years) -0.5810 x total cholesterol (mmol/l, coded to 4.3 if >4.3)-0.3596 x WBC count (10(9) counts/l, 5.8 if >5.8)+0.639OXcurrent smoking status (1 if yes). The 5-year probability of cancer was 1 - 0.9590(EXP(0.9382x(RISK SCORE+ 1.5903))). The predicted cancer probability was not significantly different from the observed cancer probability during the 5-year follow-up. The adjusted area under receiver operating characteristic curve was 0.712. In conclusion, BMI, lipids and WBC count have predicting values for cancer.