Prognostic value of international normalized ratio in cancer patients with sepsis: A retrospective cohort study and secondary analysis

Sepsis is a life-threatening condition with high mortality, particularly in vulnerable populations such as cancer patients. While complex scoring systems exist, there is a need for simple, widely available biomarkers for early risk stratification in emergency settings. The international normalized ratio (INR), a standard measure of coagulation, has been associated with poor outcomes in sepsis, but its specific prognostic value in septic cancer patients is not well-defined. This study aimed to determine the prognostic value and optimal cutoff point of INR for predicting 72-hour mortality in this specific patient cohort. This retrospective cohort study was a secondary analysis of data from a publicly available dataset in the Dryad Digital Repository, which included 225 patients with sepsis (122 of whom had cancer). We employed multivariable logistic regression models to assess the association between admission INR and 72-hour mortality, adjusting for potential confounders. Receiver operating characteristic curve analysis was used to evaluate the predictive performance of INR, and the Youden index was calculated to determine the optimal cutoff value. A higher admission INR was significantly associated with 72-hour mortality in cancer patients with sepsis. After adjusting for confounding factors, INR remained an independent risk factor for 72-hour mortality (odds ratio = 4.16, 95% confidence interval = 1.28–13.51, P  = .0177). The receiver operating characteristic analysis for INR yielded an area under the curve of 0.7509 (95% confidence interval = 0.6385–0.8632). The optimal cutoff value was identified as 1.6, which provided a sensitivity of 58.33% and a specificity of 80.61%. Admission INR is an independent predictor of 72-hour mortality in cancer patients with sepsis. With an optimal cutoff of 1.6, this readily available biomarker can serve as a valuable and inexpensive tool for early risk stratification in the emergency care of this high-risk population.