机构：[1]Zhongtai Securities Institute for Financial Studies, Shandong University, Jinan, Shandong, China.[2]School of Statistics, Shandong University of Finance and Economics, Jinan, Shandong, China.[3]School of Science, Guangxi University of Science and Technology, Liuzhou, Guangxi, China.[4]Linyi People's Hospital, Shandong, China.[5]School of Mathematics and Statistics, Yunnan University, Kunming, Yunnan, China.[6]Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.[7]Chengdu Medical College, Chengdu, Sichuan, China.[8]Chengdu First People's Hospital, Chengdu, China.
Personalized medicine has gained much attention in the past decades, and identifying the effects of factors is essential for personalized preventions and treatments. Hypertension is a major modifiable risk factor for cardiovascular disease and is influenced by complex factors. In order to decrease the incidence of hypertension effectively, the subjects should be divided into subgroups according to their characteristics. In this study, we proposed to use a heterogeneous logistic regression combined with a concave fusion penalty to analyze the population-based survey data, including common influencing factors of hypertension. The analytic steps include: (1) identifying the most important predictor; (2) estimating subgroup-based heterogeneous effects. In the present context of primary hypertension data, the modeling results showed that the calculated prediction accuracy under our method was greater than 99%, while zero under the classical logistic regression. The findings could provide a practical guide for further individualized measures implementation.
基金：
This study was equally supported by the National Natural Science Foundation of China [grant number 11901352], the
Social Science Foundation of Ministry of Education of China [grant number:18XJC910001], the Natural Science
Foundation of Shandong Province [grant number ZR2019BA017], the Social Science Foundation of Shandong
Province [grant number 19DTJJ03] and the Young Scholars Program of Shandong University [YSPSDU:
11020088964008]. Xinglin Scholar Academic Backbone Project of Chengdu University of TCM [XSGG2020006].
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2022]版：
大类|4 区医学
小类|3 区统计学与概率论4 区药学
最新[2023]版：
大类|4 区医学
小类|4 区药学4 区统计学与概率论
第一作者：
第一作者机构：[1]Zhongtai Securities Institute for Financial Studies, Shandong University, Jinan, Shandong, China.
共同第一作者：
通讯作者：
通讯机构：[5]School of Mathematics and Statistics, Yunnan University, Kunming, Yunnan, China.[6]Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.[7]Chengdu Medical College, Chengdu, Sichuan, China.[8]Chengdu First People's Hospital, Chengdu, China.[*1]School of Mathematics and Statistics Yunnan University, Kunming China[*2]Chengdu University of Traditional Chinese Medicine, Chengdu, China[*3]Chengdu Medical College, Chengdu, China[*4]Chengdu First People’s Hospital
推荐引用方式(GB/T 7714)：
Yan Xiaodong,Wang Hongni,Zhou Yanqiu,et al.Heterogeneous logistic regression for estimation of subgroup effects on hypertension[J].Journal of biopharmaceutical statistics.2022,1-17.doi:10.1080/10543406.2022.2058528.
APA：
Yan Xiaodong,Wang Hongni,Zhou Yanqiu,Yan Jingxin,Wang Ying...&Chen Xinyun.(2022).Heterogeneous logistic regression for estimation of subgroup effects on hypertension.Journal of biopharmaceutical statistics,,
MLA：
Yan Xiaodong,et al."Heterogeneous logistic regression for estimation of subgroup effects on hypertension".Journal of biopharmaceutical statistics .(2022):1-17
