Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study

Abstract Background Chronic kidney disease (CKD) is a growing public health challenges worldwide. Various studies have investigated risk factors of incident CKD; however, a very few studies examined interaction between these risk factors. In an attempt to clarify the potential interactions between r...

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Main Authors: Azra Ramezankhani, Maryam Tohidi, Fereidoun Azizi, Farzad Hadaegh
Format: Article
Language:English
Published: BMC 2017-11-01
Series:Journal of Translational Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12967-017-1346-x
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spelling doaj-6be82248de284eb4bfe6f2e087baa5832020-11-24T20:59:04ZengBMCJournal of Translational Medicine1479-58762017-11-0115111710.1186/s12967-017-1346-xApplication of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up studyAzra Ramezankhani0Maryam Tohidi1Fereidoun Azizi2Farzad Hadaegh3Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesEndocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesPrevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesAbstract Background Chronic kidney disease (CKD) is a growing public health challenges worldwide. Various studies have investigated risk factors of incident CKD; however, a very few studies examined interaction between these risk factors. In an attempt to clarify the potential interactions between risk factors of CKD, we performed survival tree analysis. Methods A total of 8238 participants (46.1% men) aged > 20 years without CKD at baseline [(1999–2001) and (2002–2005)], were followed until 2014. The first occurrence of CKD, defined as the estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2, was set as the main outcome. Multivariable Cox proportional hazard (Cox PH) regression was used to identify significant independent predictors of CKD; moreover, survival tree analysis was performed to gain further insight into the potential interactions between predictors. Results The crude incidence rates of CKD were 20.2 and 35.2 per 1000 person-years in men and women, respectively. The Cox PH identified the main effect of significant predictors of CKD incidence in men and women. In addition, using a limited number of predictors, survival trees identified 12 and 10 subgroups among men and women, respectively, with different survival probability. Accordingly, a group of men with eGFR > 74 ml/min/1.73 m2, age ≤ 46 years, low level of physical activity, waist circumference ≤ 100 cm and FPG ≤ 4.7 mmol/l had the lowest risk of CKD incidence; while men with eGFR ≤ 63.4 ml/min/1.73 m2, age > 50 years had the highest risk for CKD compared to men in the lowest risk group [hazard ratio (HR), 70.68 (34.57–144.52)]. Also, a group of women aged ≤ 45 years and eGFR > 83.5 ml/min/1.73 m2 had the lowest risk; while women with age > 48 years and eGFR ≤ 69 ml/min/1.73 m2 had the highest risk compared to low risk group [HR 27.25 (19.88–37.34)]. Conclusion In this post hoc analysis, we found the independent predictors of CKD using Cox PH; furthermore, by applying survival tree analysis we identified several numbers of homogeneous subgroups with different risk for incidence of CKD. Our study suggests that two methods can be used simultaneously to provide new insights for intervention programs and improve clinical decision making.http://link.springer.com/article/10.1186/s12967-017-1346-xChronic kidney diseaseRisk factorsEpidemiologySurvival tree analysisInteraction
collection DOAJ
language English
format Article
sources DOAJ
author Azra Ramezankhani
Maryam Tohidi
Fereidoun Azizi
Farzad Hadaegh
spellingShingle Azra Ramezankhani
Maryam Tohidi
Fereidoun Azizi
Farzad Hadaegh
Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
Journal of Translational Medicine
Chronic kidney disease
Risk factors
Epidemiology
Survival tree analysis
Interaction
author_facet Azra Ramezankhani
Maryam Tohidi
Fereidoun Azizi
Farzad Hadaegh
author_sort Azra Ramezankhani
title Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
title_short Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
title_full Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
title_fullStr Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
title_full_unstemmed Application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
title_sort application of survival tree analysis for exploration of potential interactions between predictors of incident chronic kidney disease: a 15-year follow-up study
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2017-11-01
description Abstract Background Chronic kidney disease (CKD) is a growing public health challenges worldwide. Various studies have investigated risk factors of incident CKD; however, a very few studies examined interaction between these risk factors. In an attempt to clarify the potential interactions between risk factors of CKD, we performed survival tree analysis. Methods A total of 8238 participants (46.1% men) aged > 20 years without CKD at baseline [(1999–2001) and (2002–2005)], were followed until 2014. The first occurrence of CKD, defined as the estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2, was set as the main outcome. Multivariable Cox proportional hazard (Cox PH) regression was used to identify significant independent predictors of CKD; moreover, survival tree analysis was performed to gain further insight into the potential interactions between predictors. Results The crude incidence rates of CKD were 20.2 and 35.2 per 1000 person-years in men and women, respectively. The Cox PH identified the main effect of significant predictors of CKD incidence in men and women. In addition, using a limited number of predictors, survival trees identified 12 and 10 subgroups among men and women, respectively, with different survival probability. Accordingly, a group of men with eGFR > 74 ml/min/1.73 m2, age ≤ 46 years, low level of physical activity, waist circumference ≤ 100 cm and FPG ≤ 4.7 mmol/l had the lowest risk of CKD incidence; while men with eGFR ≤ 63.4 ml/min/1.73 m2, age > 50 years had the highest risk for CKD compared to men in the lowest risk group [hazard ratio (HR), 70.68 (34.57–144.52)]. Also, a group of women aged ≤ 45 years and eGFR > 83.5 ml/min/1.73 m2 had the lowest risk; while women with age > 48 years and eGFR ≤ 69 ml/min/1.73 m2 had the highest risk compared to low risk group [HR 27.25 (19.88–37.34)]. Conclusion In this post hoc analysis, we found the independent predictors of CKD using Cox PH; furthermore, by applying survival tree analysis we identified several numbers of homogeneous subgroups with different risk for incidence of CKD. Our study suggests that two methods can be used simultaneously to provide new insights for intervention programs and improve clinical decision making.
topic Chronic kidney disease
Risk factors
Epidemiology
Survival tree analysis
Interaction
url http://link.springer.com/article/10.1186/s12967-017-1346-x
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