Ronsini Carlo, Restaino Stefano, Vizzielli Giuseppe, Di Donna Mariano Catello, Cucinella Giuseppe, Solazzo Maria Cristina, Scaffa Cono, De Franciscis Pasquale, Chiantera Vito
Unit of Gynecologic Oncology, National Cancer Institute, IRCCS, Fondazione "G. Pascale", 80131 Naples, Italy.
Unit of Obstetrics and Gynecology, "Santa Maria Della Misericordia" University Hospital, Azienda Sanitaria Universitaria Friuli Centrale, 33100 Udine, Italy.
Medicina (Kaunas). 2025 Apr 22;61(5):777. doi: 10.3390/medicina61050777.
: This study aimed to evaluate the diagnostic potential of systemic inflammatory indices such as Systemic Inflammation Response Index (SIRI) and Systemic Inflammatory Response (SIR). These were assessed in combination with CA 125 to distinguish ovarian carcinoma (OC) from borderline ovarian tumors (BOT) in patients with suspicious adnexal masses. : A retrospective multicenter observational study including patients undergoing surgery for suspected ovarian neoplasms was conducted. Inclusion criteria required preoperative blood sampling for inflammatory markers and CA 125. SIR-125 and SIRI-125 were developed by combining SIR and SIRI with CA 125 levels. Diagnostic performance was assessed using ROC curve analysis and linear regression models. : A total of 63 patients (42 BOT, 21 OC) were analyzed. OC patients exhibited significantly higher SIR-125 and SIRI-125 values ( < 0.001). ROC analysis demonstrated good diagnostic accuracy, with AUCs of 0.83 (SIR-125) and 0.82 (SIRI-125). SIR-125 showed higher specificity (0.83), while SIRI-125 had superior sensitivity (0.86). : SIR-125 and SIRI-125 enhance diagnostic differentiation between OC and BOT, providing a simple, cost-effective preoperative tool. Future prospective studies are needed to validate these findings in broader patient populations.
本研究旨在评估全身炎症指标如全身炎症反应指数（SIRI）和全身炎症反应（SIR）的诊断潜力。将这些指标与CA 125联合评估，以区分附件包块可疑患者的卵巢癌（OC）与卵巢交界性肿瘤（BOT）。
开展了一项回顾性多中心观察性研究，纳入因疑似卵巢肿瘤接受手术的患者。纳入标准要求术前采集血液检测炎症标志物和CA 125。通过将SIR和SIRI与CA 125水平相结合得出SIR-125和SIRI-125。使用受试者工作特征（ROC）曲线分析和线性回归模型评估诊断性能。
共分析了63例患者（42例BOT，21例OC）。OC患者的SIR-125和SIRI-125值显著更高（<0.001）。ROC分析显示诊断准确性良好，SIR-125的曲线下面积（AUC）为0.83，SIRI-125的AUC为0.82。SIR-125显示出更高的特异性（0.83），而SIRI-125具有更高的敏感性（0.86）。
SIR-125和SIRI-125增强了OC与BOT之间的诊断区分能力，提供了一种简单、经济高效的术前工具。未来需要进行前瞻性研究，在更广泛的患者群体中验证这些发现。
