Related Experiment Video
Updated: Jan 23, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Factors influencing survival time of hemodialysis patients; time to event analysis using parametric models: a cohort
Vahid Ebrahimi1,2, Mohammad Hossein Khademian3, Seyed Jalil Masoumi4,5,6
1Shiraz Nephro-Urology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
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.
More Related Videos
03:05Influence of Emotional Factors on the Efficacy of Acupuncture Treatment for Overweight Complicated with Hyperlipidemia: A Retrospective Cohort Study
Published on: November 21, 2025
05:18Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions
Published on: July 22, 2016
Related Concept Videos
01:14Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
01:22Bioavailability: Influencing Factors
01:05Noncompartmental Analysis: Mean Residence Time
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
01:29Factors Influencing Microbial Growth: pH
01:22Factors Influencing Attraction I: Proximity
01:30Factors Influencing Heart Rate
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...