Evidence map›Paper›PMID 39894511›Full record

ArticleEndocrine journal2025

Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.

Shih-Peng Mao, Chen-Yu Wang, Chi-Hao Liu, Chung-Bao Hsieh, Dee Pei, Ta-Wei Chu, Yao-Jen Liang

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Article in Endocrine journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Shih-Peng MaoDepartment of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei City 235, Taiwan, R.O.C.
Chen-Yu WangDepartment of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan, R.O.C.
Chi-Hao LiuDivision of Nephrology, Department of Medicine, Kaohsiung Armed Forces General Hospital, Kaohsiung 802, Taiwan, R.O.C.
Chung-Bao HsiehDepartment of Surgery, Kaohsiung Armed Forces General Hospital, Kaohsiung 802, Taiwan, R.O.C.
Dee PeiDivision of Endocrinology and Metabolism, Department of Internal Medicine, Fu Jen Catholic University Hospital, School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei City 242, Taiwan, R.O.C.
Ta-Wei ChuDepartment of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan, R.O.C.
Yao-Jen LiangGraduate Institute of Applied Science and Engineering, Fu Jen Catholic University, New Taipei City 242, Taiwan, R.O.C.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical tool for quantifying insulin resistance (HOMA-IR). Multiple adaptive regression spline (MARS) is a machine learning method used in many research fields but has yet to be applied to estimating HOMA-IR. This study uses MARS to build an equation to estimate HOMA-IR in pre-menopausal Chinese women based on a sample of 4,071 healthy women aged 20-50 with no major diseases and no medication use for blood pressure, blood glucose or blood lipids. Thirty variables were applied to build the HOMA-IR model, including demographic, laboratory, and lifestyle factors. MARS results in smaller prediction errors than traditional multiple linear regression (MLR) methods, and is thus more accurate. The model was established based on key impact factors including waist-hip ratio (WHR), C reactive protein (CRP), uric acid (UA), total bilirubin (TBIL), leukocyte (WBC), serum glutamic oxaloacetic transaminase (GOT), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), serum glutamic pyruvic transaminase (GPT), and triglycerides (TG). The equation is as following:HOMA-IR = 6.634 - 1.448MAX(0, 0.833 - WHR) + 10.152MAX(0, WHR - 0.833) - 1.351MAX(0, 0.7 - CRP) - 0.449MAX(0, CRP - 0.7) + 1.062MAX(0, UA - 8.5) + +1.047(MAX(0, 0.83 - TBIL) + 0.681MAX(0, WBC - 11.53) - 0.071MAX(0, 11.53 - WBC) + 0.043MAX(0, 24 - GOT) - 0.017MAX(0, GOT - 24) + 0.021MAX(0, 59 - HDL) - 0.005MAX(0, HDL - 59) - 0.013MAX(0, 141 - SBP) - 0.033MAX(0, 100 - GPT) + 0.013MAX(0, GPT - 100) - 0.004MAX(303 - TG)Results indicate that MARS is a more precise tool than fasting plasma insulin (FPI) levels, and could be used in the daily practice, and further longitudinal studies are warranted.

Indexed as

Insulin ResistanceAdultBilirubinBlood GlucoseBlood PressureChinaCholesterol, HDLC-Reactive ProteinEast Asian PeopleFemaleHumansMachine LearningMiddle AgedTriglyceridesUric AcidWaist-Hip RatioBilirubinBlood GlucoseCholesterol, HDLC-Reactive ProteinTriglyceridesUric AcidHomeostasis assessment modelInsulin resistanceMultiple adaptive regression spline

Identifiers

PMID39894511
PMCPMC11997268

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.