AbstractBackgroundInsulin resistance (IR) and systemic inflammation are common in patients with cancer and are associated with poor prognosis. Few studies have reported IR in female reproductive system malignancies. This study investigated the prognostic value of IR and systemic inflammation in this population.MethodsA prospective multicenter real‐world cohort study involving 571 patients diagnosed with female reproductive system malignancies was conducted. Lipid ratios (low‐density lipoprotein‐cholesterol/high‐density lipoprotein‐cholesterol [LHR], total cholesterol/HDL‐cholesterol [TCHR], triglyceride/HDL‐cholesterol [TGHR], fasting triglyceride/glucose [TyG]) were used to reflect IR. Optimal cut‐off values were determined using maximally selected rank statistics. The Kaplan–Meier and Cox regression were used to calculate the hazard ratios for overall survival.ResultsOver half (55.90%) of the 571 patients with female reproductive system malignancies (mean age: 52 years) had cervical cancer. Both IR and inflammation were negatively correlated with overall survival in female reproductive system cancer patients. Multivariate survival analysis showed that patients with high LHR (hazard ratio [HR]: 1.51, 95% confidence interval [CI]: 1.01–2.25, p = .046), high TCHR (HR: 1.90, 95% CI:1.22–2.95, p = .005), high TGHR (HR: 1.66, 95% CI:1.17–2.36, p = .004), high TyG (HR: 1.64, 95% CI:1.13–2.40, p = .010), high neutrophil lymphocyte ratio (NLR, HR: 2.03, 95% CI:1.44–2.86, p = .004) were significantly associated with worse prognosis. By calculating the concordance index of the four IR surrogate indicators, TyG was the most valuable indicator for the prognosis of patients with malignant tumors of the female reproductive system. High TyG combined with high NLR had improved prognostic value (HR: 3.22, 95% CI: 1.97–5.26, p < .001).ConclusionsIR can be used as an independent predictor of prognosis in the female reproductive system malignancy population regardless of the IR substitution index. The combination of TyG and NLR could better predict the prognostic outcomes of women with breast cancer.