Related Experiment Video
Updated: Nov 15, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients
Jia-Feng Chang1,2,3,4,5, Po-Cheng Chen6, Chih-Yu Hsieh1,7
1Division of Nephrology, Department of Internal Medicine, En Chu Kong Hospital, New Taipei City 237, Taiwan.
Insights
A new risk score using growth differentiation factor 15 (GDF15), age, and albumin effectively predicts cardiovascular and all-cause death in maintenance hemodialysis patients. This GDF15-based model offers improved accuracy for risk stratification and intervention planning.
Area of Science:
- Nephrology
- Cardiology
- Biomarker Discovery
Background:
- Patients on maintenance hemodialysis (MHD) face high risks of cardiovascular (CV) and fatal events.
- Growth differentiation factor 15 (GDF15) is a recognized biomarker for risk stratification in MHD patients.
Purpose of the Study:
- To develop and validate a GDF15-based risk score for predicting mortality in MHD patients.
- To assess the predictive accuracy of the GDF15 score for all-cause and CV death.
Main Methods:
- Cox regression analysis was used to identify prognostic factors for mortality.
- A risk score model was constructed incorporating age, GDF15, and clinical predictors.
- Receiver operating characteristic (ROC) curve analysis evaluated the predictive accuracy of the model.
Main Results:
- Age, GDF15, and albumin levels were significantly associated with increased all-cause and CV mortality risk.
- The highest GDF15 tertile showed significant associations with both all-cause and CV mortality.
- The GDF15-based prediction model demonstrated robust predictive accuracy for all-cause (0.75) and CV mortality (0.72).
Conclusions:
- A combination scoring system including age, GDF15, and hypoalbuminemia provides superior prediction of all-cause and CV death in MHD patients.
- An elevated GDF15-based risk score can guide clinicians in timely interventions.
- The GDF15-based death prediction model holds potential for development within AI-driven precision medicine.
Background:
The risk of cardiovascular (CV) and fatal events remains extremely high in patients with maintenance hemodialysis (MHD), and the growth differentiation factor 15 (GDF15) has emerged as a valid risk stratification biomarker. We aimed to develop a GDF15-based risk score as a death prediction model for MHD patients.
Methods:
Age, biomarker levels, and clinical parameters were evaluated at study entry. One hundred and seventy patients with complete information were finally included for data analysis. We performed the Cox regression analysis of various prognostic factors for mortality. Then, age, GDF15, and robust clinical predictors were included as a risk score model to assess the predictive accuracy for all-cause and CV death in the receiver operating characteristic (ROC) curve analysis.
Results:
Age, GDF15, and albumin were significantly associated with higher all-cause and CV mortality risk that were combined as a risk score model. The highest tertile of GDF-15 (>1707.1 pg/mL) was associated with all-cause mortality (adjusted hazard ratios (aHRs): 3.06 (95% confidence interval (CI): 1.20-7.82), p < 0.05) and CV mortality (aHRs: 3.11 (95% CI: 1.02-9.50), p < 0.05). The ROC analysis of GDF-15 tertiles for all-cause and CV mortality showed 0.68 (95% CI = 0.59 to 0.77) and 0.68 (95% CI = 0.58 to 0.79), respectively. By contrast, the GDF15-based prediction model for all-cause and CV mortality showed 0.75 (95% CI: 0.67-0.82) and 0.72 (95% CI: 0.63-0.81), respectively.
Conclusion:
Age, GDF15, and hypoalbuminemia predict all-cause and CV death in MHD patients, yet a combination scoring system provides more robust predictive powers. An elevated GDF15-based risk score warns clinicians to determine an appropriate intervention in advance. In light of this, the GDF15-based death prediction model could be developed in the artificial intelligence-based precision medicine.
Related Concept Videos
01:28Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration
01:25Hemodialysis III: Nursing Management
01:11Renal Failure: Dose Adjustments
Reduced renal clearance and elimination rate are common outcomes of renal impairment. These alterations lead to a prolonged elimination half-life and an altered apparent volume of distribution for drugs. As a result, dosage adjustments are typically necessary to maintain optimal drug levels in the body.
However, dosage adjustments...
01:25Hemodialysis I: Introduction
01:18Pharmacokinetics in Geriatric Patients: Effect of Age on Drug Excretion
01:24Hemodialysis II: Procedure and Complications