Development and validation of a nomogram for predicting the 6-months survival rate of patients undergoing incident hemodialysis in China

Background The all-cause mortality of patients undergoing hemodialysis (HD) is higher than in the general population. The first 6 months after dialysis are important for new patients. The aim of this study was to develop and validate a nomogram for predicting the 6-month survival rate of HD patients. Methods A prediction model was constructed using a training cohort of 679 HD patients. Multivariate Cox regression analyses were performed to identify predictive factors. The identified factors were used to establish a nomogram. The performance of the nomogram was assessed using the C-index and calibration plots. The nomogram was validated by performing discrimination and calibration tests on an additional cohort of 173 HD patients. Results During a follow-up period of six months, 47 and 16 deaths occurred in the training cohort and validation cohort, respectively, representing a mortality rate of 7.3% and 9.2%, respectively. The nomogram comprised five commonly available predictors: age, temporary dialysis catheter, intradialytic hypotension, use of ACEi or ARB, and use of loop diuretics. The nomogram showed good discrimination in the training cohort [C-index 0.775(0.693-0.857)] and validation cohort [C-index 0.758(0.677-0.836)], as well as good calibration, indicating that the performance of the nomogram was good. The total score point was then divided into two risk classifications: low risk (0-90 points) and high risk ([greater than or equai to] 91 points). Further analysis showed that all-cause mortality was significantly different between the high-risk group and the low-risk group. Conclusions The constructed nomogram accurately predicted the 6-month survival rate of HD patients, and thus it can be used in clinical decision-making. Keywords: Hemodialysis, Nomogram, Prediction model, Survival, All-cause mortality