Cantatore Francesco, Agrillo Nadia, Camussi Alessandro, Colella Lucrezia, Origoni Massimo
Department of Gynecology & Obstetrics, Vita Salute San Raffaele University School of Medicine, IRCCS Ospedale San Raffaele, Via Olgettina 60, 20132 Milan, Italy.
Diagnostics (Basel). 2025 Jun 23;15(13):1585. doi: 10.3390/diagnostics15131585.
Cervical Intraepithelial Neoplasia (CIN) is a significant risk factor for the development of invasive cancer, and the histological detection of High-Grade CIN (CIN2+) during screening generally indicates the need for surgical removal of the lesion; cervical conization is the current gold standard of treatment. The recurrence risk for disease is reported to be up to 30%, based on data in the literature. Follow-up protocols mainly rely on High-Risk Human Papillomavirus (hrHPV) detection at six months post-treatment; if negative, this is considered the test of cure. This approach assumes that all patients have an equal risk of disease recurrence, regardless of individual characteristics. The objective of this study was to evaluate the individual recurrence risk using a mathematical model, analyzing the weight of various parameters and their associations in terms of recurrence development. We retrospectively examined 428 patients treated for CIN2+ at San Raffaele Hospital in Milan between January 2010 and April 2019. Clinical and pathological data were recorded and correlated with disease recurrence; three different variables, known to behave as significant prognostic factors, were analyzed: hrHPV persistence, the surgical margin status, Neutrophil-Lymphocyte Ratio (NLR), along with their relative associations. Data were used to engineer a mathematical model for the identification of different risk classes, allowing for the risk stratification of cases. Surgical margins status, hrHPV persistence, and a high NLR index were demonstrated to act as independent and significant risk factors for disease recurrence, and their different associations significantly correlated with different recurrence rates. The mathematical model identified eight classes of recurrence probability, with Odds Ratios (ORs) ranging from 7.48% to 69.4%. The developed mathematical model may allow risk stratification for recurrence in a hierarchical fashion, potentially supporting the tailored management of follow-up, and improving the current protocols. This study represents the first attempt to integrate these factors into a mathematical model for post-treatment risk stratification.
宫颈上皮内瘤变（CIN）是浸润性癌发生的一个重要危险因素，在筛查过程中对高级别CIN（CIN2+）进行组织学检测通常表明需要手术切除病变；宫颈锥切术是目前的治疗金标准。根据文献数据，该病的复发风险据报道高达30%。随访方案主要依赖于治疗后六个月的高危型人乳头瘤病毒（hrHPV）检测；如果检测结果为阴性，则视为治愈检测。这种方法假定所有患者的疾病复发风险均等，而不考虑个体特征。本研究的目的是使用数学模型评估个体复发风险，分析各种参数的权重及其在复发发展方面的关联。我们回顾性研究了2010年1月至2019年4月期间在米兰圣拉斐尔医院接受CIN2+治疗的428例患者。记录临床和病理数据，并将其与疾病复发相关联；分析了三个已知为重要预后因素的不同变量：hrHPV持续存在、手术切缘状态、中性粒细胞与淋巴细胞比值（NLR）及其相对关联。数据被用于构建一个数学模型，以识别不同的风险类别，从而对病例进行风险分层。手术切缘状态、hrHPV持续存在和高NLR指数被证明是疾病复发的独立且重要的危险因素，它们的不同关联与不同的复发率显著相关。该数学模型确定了八类复发概率，优势比（OR）范围为7.48%至69.4%。所开发的数学模型可能允许以分层方式对复发进行风险分层，潜在地支持后续的个性化管理，并改进当前的方案。本研究是首次尝试将这些因素整合到一个用于治疗后风险分层的数学模型中。
