A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients
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 predicti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/2/286 |
| _version_ | 1797396867909156864 |
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| author | Jia-Feng Chang Po-Cheng Chen Chih-Yu Hsieh Jian-Chiun Liou |
| author_facet | Jia-Feng Chang Po-Cheng Chen Chih-Yu Hsieh Jian-Chiun Liou |
| author_sort | Jia-Feng Chang |
| collection | DOAJ |
| description | 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), <i>p</i> < 0.05) and CV mortality (aHRs: 3.11 (95% CI: 1.02–9.50), <i>p</i> < 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. |
| first_indexed | 2024-03-09T00:57:42Z |
| format | Article |
| id | doaj.art-7225f4ef1d0b4a1bbc3c31649a8a0baf |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T00:57:42Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-7225f4ef1d0b4a1bbc3c31649a8a0baf2023-12-11T16:47:12ZengMDPI AGDiagnostics2075-44182021-02-0111228610.3390/diagnostics11020286A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis PatientsJia-Feng Chang0Po-Cheng Chen1Chih-Yu Hsieh2Jian-Chiun Liou3Division of Nephrology, Department of Internal Medicine, En Chu Kong Hospital, New Taipei City 237, TaiwanDepartment of Urology, En Chu Kong Hospital, New Taipei City 237, TaiwanDivision of Nephrology, Department of Internal Medicine, En Chu Kong Hospital, New Taipei City 237, TaiwanSchool of Biomedical Engineering, Taipei Medical University, Taipei 110, TaiwanBackground: 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), <i>p</i> < 0.05) and CV mortality (aHRs: 3.11 (95% CI: 1.02–9.50), <i>p</i> < 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.https://www.mdpi.com/2075-4418/11/2/286growth differentiation factor 15death prediction modelhemodialysis |
| spellingShingle | Jia-Feng Chang Po-Cheng Chen Chih-Yu Hsieh Jian-Chiun Liou A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients Diagnostics growth differentiation factor 15 death prediction model hemodialysis |
| title | A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients |
| title_full | A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients |
| title_fullStr | A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients |
| title_full_unstemmed | A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients |
| title_short | A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients |
| title_sort | growth differentiation factor 15 based risk score model to predict mortality in hemodialysis patients |
| topic | growth differentiation factor 15 death prediction model hemodialysis |
| url | https://www.mdpi.com/2075-4418/11/2/286 |
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