Data from: Evaluating lipid-driven insulin resistance via TyG index in breast cancer patients: Toward effective secondary prevention

Breast cancer is the most commonly diagnosed malignancy worldwide. Insulin
resistance (IR) plays a key role in its progression by activating
oncogenic signaling pathways. The triglyceride-glucose (TyG) index is a
validated, cost-effective surrogate marker for IR. This study aims to
evaluate the prevalence of IR in female breast cancer patients using the
TyG index and to identify lipid parameters associated with increased IR,
thereby supporting strategies for secondary prevention. A cross-sectional
study was conducted among non-diabetic, histopathologically confirmed
female breast cancer patients. Demographic data, lipid profiles, and
fasting glucose levels were collected. Participants were stratified into
high-risk (TyG ≥ 8.87) and low-risk (TyG < 8.87) groups based on
their TyG index. Logistic regression analysis was performed to identify
significant predictors of elevated TyG index. Among 122 patients, 44.3%
demonstrated elevated insulin resistance. Triglycerides (TG), total
cholesterol (TC), VLDL-C, and the TC/HDL-C ratio were significantly higher
in the high-risk group. Logistic regression identified TC, TC/HDL-C ratio,
and LDL-C as significant predictors of elevated IR (p < 0.05). The
model is represented as: Logit(P) = −13.941 + 0.145X₁ + 1.558X₂ − 0.178X₃,
where X₁, X₂, and X₃ correspond to TC, TC/HDL-C ratio, and LDL-C,
respectively. The predictive model achieved 90.2% accuracy with an area
under the ROC curve (AUROC) of 0.927. Monitoring lipid parameters and
managing insulin resistance are crucial for enhancing breast cancer
prognosis and potentially reducing progression.