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<p>The triglyceride-glucose (TyG) index is a simple surrogate marker for insulin resistance (IR), but its longitudinal stability and clinical predictive value in patients with cancer remain poorly understood. To evaluate whether cancer and anti-tumor therapies affect the longitudinal stability of the TyG index over 24 months and to identify its core influencing factors. This retrospective study analyzed 538 cancer patients from a single-center database (2015–2020) who completed five TyG index measurements over 24 months. Longitudinal stability was quantified using repeated measures analysis of variance (RM-ANOVA) and intraclass correlation coefficients (ICC). Binary logistic regression models were employed to explore factors associated with different TyG levels. A longitudinal K-means clustering algorithm was used to identify trajectory differences, and multivariable logistic regression models determined the independent predictive factors. The TyG index demonstrated excellent longitudinal stability over 24 months (F = 5.38, <i>P</i> &lt; 0.001; average ICC = 0.890; Pearson <i>r</i> = 0.54–0.71). Binary logistic regression analysis showed that body mass index (BMI) was the core factor independently associated with a high TyG index (Q4 &gt; 8.79). K-means clustering identified three parallel longitudinal trajectories (Stable-Low, Stable-Medium, and Stable-High risk). Multivariable logistic regression models indicated that the high-risk trajectory was significantly associated with BMI (OR = 1.25, 95% CI 1.10–1.41, <i>P</i> &lt; 0.001) and diabetes mellitus, whereas advanced cancer stage (OR = 0.95, 95% CI 0.53–1.70, <i>P</i> = 0.862) and cachexia (OR = 0.90, 95% CI 0.45–1.80, <i>P</i> = 0.767) showed no significant effect. The TyG index in cancer patients exhibited a long-term stable trend over 24 months. Severe IR may represent a metabolic phenotype closely associated with fat accumulation, and it may be independent of catabolic states such as cancer stage and cachexia.</p>

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Long-term stability of the triglyceride-glucose index in cancer patient Cohort

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月28日

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  • Xie Yulei,
  • Chen Xin,
  • Xie Liang,
  • Wang Yinxu

摘要

The triglyceride-glucose (TyG) index is a simple surrogate marker for insulin resistance (IR), but its longitudinal stability and clinical predictive value in patients with cancer remain poorly understood. To evaluate whether cancer and anti-tumor therapies affect the longitudinal stability of the TyG index over 24 months and to identify its core influencing factors. This retrospective study analyzed 538 cancer patients from a single-center database (2015–2020) who completed five TyG index measurements over 24 months. Longitudinal stability was quantified using repeated measures analysis of variance (RM-ANOVA) and intraclass correlation coefficients (ICC). Binary logistic regression models were employed to explore factors associated with different TyG levels. A longitudinal K-means clustering algorithm was used to identify trajectory differences, and multivariable logistic regression models determined the independent predictive factors. The TyG index demonstrated excellent longitudinal stability over 24 months (F = 5.38, P < 0.001; average ICC = 0.890; Pearson r = 0.54–0.71). Binary logistic regression analysis showed that body mass index (BMI) was the core factor independently associated with a high TyG index (Q4 > 8.79). K-means clustering identified three parallel longitudinal trajectories (Stable-Low, Stable-Medium, and Stable-High risk). Multivariable logistic regression models indicated that the high-risk trajectory was significantly associated with BMI (OR = 1.25, 95% CI 1.10–1.41, P < 0.001) and diabetes mellitus, whereas advanced cancer stage (OR = 0.95, 95% CI 0.53–1.70, P = 0.862) and cachexia (OR = 0.90, 95% CI 0.45–1.80, P = 0.767) showed no significant effect. The TyG index in cancer patients exhibited a long-term stable trend over 24 months. Severe IR may represent a metabolic phenotype closely associated with fat accumulation, and it may be independent of catabolic states such as cancer stage and cachexia.