Identifying Influential Prognostic Factors of Death Hazard Rates in Patients with Chronic Kidney Disease (CKD) Using Weibull Model with Non-Constant Shape Parameter

Abstract

Introduction: Chronic Kidney Disease (CKD) is a disease in which damaged kidneys could not remove waste material from the blood which could result in other health problems. The aim of this analysis was to identify significant laboratory prognostic factors on death hazard due to CKD. Methods: There were 109 patients with end-stage renal disease (ESRD) treated at Helal pharmaceutical and clinical complex. The survival time was set as the time interval from starting dialysis until death due to CKD. Age, gender and factors such as creatinine, cholesterol, uric acid, SGOT, SGPT, bilirubin, hemoglobin, potassium, ALP, HbA1C, ferritin, calcium, phosphorus, PTH and albumin were employed in this study. Weibull Distribution with non-Constant Shape Parameter versus constant Shape Parameter for the analysis were used. Results: Death due to CKD occurred in 29 (26.6%) of the patients. Sixty-seven (61.5%) had uric acid higher than 6.8 (mg/dl) and 39(35%) had phosphorus higher than 4.7 (mg/dl) which were poor prognoses. The incidence of death was 48.4%. Calcium 9.5 (mg/dl) (p=0.003), Albumin 4-6.3 (g/dl) (p=0.034), Phosphorus (p=0.022), hemoglobin12.5 (g/dl) (p=0.006) and iPTH (p<0.001) were significant variables which had an effect on death hazard rates. Conclusion: The Weibull model with Non-Constant shape parameter was suggested to be more accurate for identifying risk factors, leading to more precise results, compared to constant shape parameter. Investigators mostly emphasize on the importance of Calcium, Albumin, Phosphorus, hemoglobin and iPTH for reducing hazard rates in CKD patients.

Keywords

• Chronic Kidney Disease
• Survival Data
• Hazard modeling
• Shape parameter