• Ann Transl Med · May 2021

    Developing a predictive risk score for perioperative blood transfusion: a retrospective study in patients with oral and oropharyngeal squamous cell carcinoma undergoing free flap reconstruction surgery.

    • Jun-Qi Su, Shang Xie, Zhi-Gang Cai, and Xiao-Ying Wang.
    • Department of Clinical Laboratory, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing, China.
    • Ann Transl Med. 2021 May 1; 9 (10): 854.

    BackgroundA simple and accurate scoring system to predict risk of blood transfusion in patients having surgical tumor resection with immediate free flap reconstruction primary surgery for oral and oropharyngeal squamous cell carcinoma (OOSCC) is lacking. Anticipating the blood transfusion requirements in patients with oral cancer is of great clinical importance. This research aimed to propose a valid model to predict transfusion requirements in patients undergoing surgery with free flap reconstruction for an OOSCC.MethodsThis retrospective study consisted of 385 patients who underwent oncologic surgery with immediate free flap reconstruction for locally advanced OOSCC from 2012 to 2019. The primary outcome measured was the exposure of patients to perioperative allogeneic blood transfusion. Based on a multivariate model of independent risk variables and their odds ratio, a blood transfusion risk score (TRS) was developed to predict the likelihood of the perioperative blood transfusion. The discriminatory accuracy of the model was evaluated using the area under the receiver operating characteristic (ROC) curve, and Youden index was used to identify the optimal cut-point.ResultsLogistic regression analyses identified lymph node status, preoperative hemoglobin (Hb) levels, bone resection, osseous free tissue transfer, and operative duration were identified as independent predictors of blood transfusion. A TRS integrating these variables was separated into three categories. The TRS assessed the transfusion risk with good predictive ability, with an overall area under the ROC curve (AUC) was 0.826. At the optimal cut-point of 5.5, the TRS had a sensitivity of 72.3% and a specificity of 78.2%. The ROC analysis showed that patients with a TRS of 5.5 or more had a greater requirement for perioperative transfusion.ConclusionsThe use of the integer-based TRS allowed the identification of high-risk patients who may require perioperative transfusion undergoing tumor resection surgery for the treatment of OOSCC.2021 Annals of Translational Medicine. All rights reserved.

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