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. 2025 Jul 22.
doi: 10.1007/s40618-025-02629-x. Online ahead of print.

Development of a nomogram based on METS-IR and SPISE index for predicting mild cognitive impairment in type 2 diabetes mellitus

Niu Tong  1   2 , Liu Kunyu  1   2 , Zhou Xueling  1   2 , Sun Ruoyu  1   2 , Niu Diejing  1   2 , Wang Shaohua  1   2 , Yuan Yang  3   4
Affiliations

Development of a nomogram based on METS-IR and SPISE index for predicting mild cognitive impairment in type 2 diabetes mellitus

Niu Tong et al. J Endocrinol Invest. .

Abstract

Background: Insulin resistance (IR) is central to metabolic syndrome and contributes to the development of type 2 diabetes mellitus (T2DM) as well as mild cognitive impairment (MCI). Several low-cost surrogate markers have been proposed to assess IR, such as the triglyceride-glucose (TyG) index, TyG-BMI, TG/HDL-C, metabolic score for insulin resistance (METS-IR), and single-point insulin sensitivity estimator (SPISE). This study aimed to develop nomogram models integrating these indices with clinical data to predict MCI in patients with T2DM.

Methods: A total of 600 patients diagnosed with T2DM were recruited. Demographic, clinical, and biochemical parameters were documented, and cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). Logistic regression analyses identified predictors of MCI, and receiver operating characteristic (ROC) curves evaluated their predictive accuracy. Two nomogram models were constructed: Model 1 included METS-IR, age, sex, education level, and hypertension; Model 2 substituted SPISE for METS-IR, retaining other clinical variables.

Results: All IR surrogate indices were significantly associated with MCI and reduced MMSE scores (P < 0.001). METS-IR and SPISE exhibited higher predictive accuracy (AUC: METS-IR = 0.809, SPISE = 0.805) compared to TyG, TyG-BMI, and TG/HDL-C, particularly among female participants. Nomogram models demonstrated robust predictive performance (AUC: Model 1 = 0.846; Model 2 = 0.838).

Conclusions: Nomogram models incorporating METS-IR or SPISE alongside key clinical parameters effectively predicted the risk of MCI among patients with T2DM. These indices notably outperformed other surrogate markers, highlighting their clinical value for early assessment of cognitive risk.

Keywords: Insulin resistance; Metabolic score for insulin resistance index; Mild cognitive impairment; Nomogram; Single-point insulin sensitivity estimator index; Type 2 diabetes mellitus.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Consent for publication: All authors have reviewed and approved the final version of the manuscript. Ethics approval and consent to participate: This cohort study was approved by the Research Ethics Committee, Affiliated ZhongDa Hospital of Southeast University (approval no. of ethics committee: 2023ZDSYLL435-P01), and follows the ethical guidelines outlined in the Declaration of Helsinki. Informed consent: Informed consent was obtained from all individual participants included in the study.

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