Frontiers in Cellular Neuroscience (Feb 2022)
Cancer Related Subarachnoid Hemorrhage: A Multicenter Retrospective Study Using Propensity Score Matching Analysis
Abstract
ObjectiveTo investigate the clinical features, risk factors and underlying pathogenesis of cancer related subarachnoid hemorrhage (SAH).MethodsClinical data of SAH in patients with active cancer from January 2010 to December 2020 at four centers were retrospectively reviewed. Patients with active cancer without SAH were matched to SAH patients with active cancer group. Logistic regression was applied to investigate the independent risk factors of SAH in patients with active cancer, after a 1:1 propensity score matching (PSM). A receiver operator characteristic curve was configured to calculate the optimal cut-off value of the joint predictive factor for cancer related SAH.ResultsA total of 82 SAH patients with active cancer and 309 patients with active cancer alone were included. Most SAH patients with cancer had poor outcomes, with 30-day mortality of 41.5%, and with 90-day mortality of 52.0%. The PSM yielded 75 pairs of study participants. Logistic regression revealed that a decrease in platelet and prolonged prothrombin time were the independent risk factors of cancer related SAH. In addition, receiver operator characteristic curve of the joint predictive factor showed the largest AUC of 0.8131, with cut-off value equaling to 11.719, with a sensitivity of 65.3% and specificity of 89.3%.ConclusionPatients with cancer related SAH often have poor outcomes. The decrease in platelet and prolonged prothrombin time are the independent risk factors of cancer related SAH, and the joint predictive factor with cutoff value equal to 11.719 should hence serve as a novel biomarker of cancer related SAH.
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