A novel Silva pattern-based model for precisely predicting recurrence in intermediate-risk cervical adenocarcinoma patients

• DOI: 10.1186/s12905-022-01971-z
• Publication Date: 2022-09-16T14:02:48Z
• Authors: Chenyan Guo; Xiang Tao; Lihong Zhang; Ying Zhang; Keqin Hua; Junjun Qiu
• Keywords: Research; Cervical adenocarcinoma; Uterine Cervical Neoplasms; Silva; Gynecology and obstetrics; Adenocarcinoma; Prognosis; 3. Good health; 03 medical and health sciences; 0302 clinical medicine; Recurrence; Prediction model; RG1-991; Carcinoma, Squamous Cell; Humans; Female; Public aspects of medicine; RA1-1270; Neoplasm Recurrence, Local

Abstract Background Considering the unique biological behavior of cervical adenocarcinoma (AC) compared to squamous cell carcinoma, we now lack a distinct method assess prognosis for AC patients, especially intermediate-risk patients. Thus, sought establish Silva-based model predict recurrence specific patients and guide adjuvant therapy. Methods 345 were classified according Silva pattern, their clinicopathological data survival outcomes assessed. Among them, 254 with only factors identified. The significant cutoff values four (tumor size, lymphovascular space invasion (LVSI), depth stromal (DSI) pattern) determined by univariate multivariate Cox analyses. Subsequently, series four-, three- two-factor models developed via various combinations above factors. Results (1) We confirmed prognostic value pattern using cohort (2) established potential prediction in including 12 four-factor models, 30 three-factor 16 models. (3) Notably, model, which includes any three (Silva C, ≥ 3 cm, DSI > 2/3, mild LVSI), exhibited best performance surpassed Sedlis criteria. Conclusions Our study has superior than criteria may better postoperative