Factors influencing survival time of hemodialysis patients; time to event analysis using parametric models: a cohort study

Abstract

Background Survival analysis of patients on maintenance hemodialysis (HD) has been the subject of many studies. No study has evaluated the effect of different factors on the survival time of these patients. In this study, by using parametric survival models, we aimed to find the factors affecting survival and discover the effect of them on the survival time. Methods As a retrospective cohort study, we evaluated the data of 1408 HD patients. We considered the data of patients who had at least 3 months of HD and started HD from December 2011 to February 2016. The data were extracted from Shiraz University of Medical Sciences (SUMS) Special Diseases database. Primary event was death. We applied Cox-adjusted PH to find the variables with significant effect on risk of death. The effect of various parameters on the survival time was evaluated by a parametric survival model, the one found to have the best fit by Akaike Information Criterion (AIC). Results Of 428 HD patients eligible for the analysis, 221 (52%) experienced death. With the mean ± SD age of 60 ± 16 years and BMI of 23 ± 4.6 Kg/m, they comprised of 250 men (58%). The median of the survival time (95% CI) was 624 days (550 to 716). The overall 1, 2, 3, and 4-year survival rates for the patients undergoing HD were 74, 42, 25, and 17%; respectively. By using AIC, AFT log-normal model was recognized as the best functional form of the survival time. Cox-adjusted PH results showed that the amount of ultrafiltration volume (UF) (HR = 1.146, P = 0.049), WBC count (HR = 1.039, P = 0.001), RBC count (HR = 0.817, P = 0.044), MCHC (HR = 0.887, P = 0.001), and serum albumin (HR = 0.616, P < 0.001) had significant effects on mortality. AFT log-normal model indicated that WBC (ETR = 0.982, P = 0.018), RBC (ETR = 1.131, P = 0.023), MCHC (ETR = 1.067, P = 0.001), and serum albumin (ETR = 1.232, 0.002) had significant influence on the survival time. Conclusion Considering Cox and three parametric event-time models, the parametric AFT log-normal had the best efficiency in determining factors influencing HD patients survival. Resulting from this model, WBC and RBC count, MCHC and serum albumin are factors significantly affecting survival time of HD patients.

Survival and analysis of predictors of mortality in patients undergoing replacement renal therapy: a 20-year cohort

“…In the analysis of the patient’s blood count, only the leukocyte was an independent prognostic factor for patient survival and its normal to high values (5.81–7.70 and ≥ 7.71) had an HR of, respectively 2.665 (95% CI 1.387–5.119) and 1.435 (95% CI 0.687–2.997). The study by Ebrahimi et al (2019) [ 4 ], confirmed our findings by indicating that as the level of leukocyte count increases, the survival time of patients undergoing HD decreases. A study carried out in Taiwan, showed that the total leukocyte count predicts all causes and cardiovascular mortality in just one year [ 35 ], while in another study carried out in the United States, the reduction in the lymphocyte count are risk factors for mortality [ 36 ].…”

“…The median survival time was 6.79 ± 0.37 years (mean ± standard deviation), and 254 (60.2%) patients died. In the study by Nyuyen et al (2017) [ 23 ] the survival time was 5.27 ± 0.31 years (mean ± standard deviation), in the study by Browne et al (2014) [ 1 ] the death rate was 60%, in the study by Ebhahimi et al (2019) [ 4 ] of 52% and in the study by Chandrashekar et al (2014) [ 24 ] 19.8% over 2 years. These periods are relatively short when compared to US rapporteurs [ 24 , 25 ].…”

“…Chronic Kidney Disease (CKD) and its evolution to end-stage renal disease (ESRD) is increasingly recognized as a serious risk factor for mortality, being considered an unquestionable global public priority [ 1 – 4 ]. In 2016 CKD was the 13th in the list of causes of death, with projection that in 2040 it will be the 5th leading cause of death worldwide [ 2 , 5 ].…”

“…HD is the major treatment modality for RRT worldwide, and it is also the one with the highest mortality rates, followed by kidney transplantation and peritoneal dialysis [ 4 , 10 , 11 ]. For these reasons, one of the most worrying outcomes of CKD is ESRD, in which there is a need for RRT.…”

“…Identifying the prognostic factors that are associated to and worsen ESRD certainly helps to reduce morbidity and mortality, especially in the first year of patients undergoing HD [ 4 , 12 ]. For this, it is necessary to analyze the dynamics of biochemical parameter and different factors in the survival time of patients at baseline and for a long follow-up period, which few studies focus on doing [ 13 ].…”