Silva cumulative score and its relationship with prognosis in Endocervical adenocarcinoma

BACKGROUND: The Silva system has been demonstrated to have a good predictive value of lymph node metastasis (LNM) in endocervical adenocarcinoma (EAC). Tumours were classified based on the highest identified pattern of invasion in this system, this may not exactly reflect the true situation when it presents with a “mixed pattern” in some cases. Recent study has shown that patients with lymphovascular invasion (LVI) have worse prognosis in EAC. Here we design a Silva cumulative score (SCS) system which also combined the LVI status to explore its prognostic role in EAC patients. METHODS: A total of 120 patients with EAC were included in this study. Clinicopathological characteristics were retrospectively retrieved from the medical records and follow-up data were obtained. The clinicopathological information included age at diagnosis, depth of invasion (DOI), LNM, LVI, Silva classification, and SCS. SCS is a classification system based on the sum score of different Silva pattern which is founded on morphological phenomena. The relationships between the pathological characteristics and prognoses were analyzed. RESULTS: According to the Silva system, 11 (9.2%), 22 (18.3%) and 87 (72.5%) patients had patterns A, B, and C, respectively. Patients with pattern C had the highest incidence of LVI and LNM (p < 0.05). Although the Kaplan-Meier curves demonstrated that survival decreased with increasing Silva classification for A-C cancers, there was no statistically significant difference [disease-free survival (DFS): p = 0.181; overall survival (OS): p = 0.205]. There were 45 cases presented as mixed-type of Silva patterns. According to the SCS, 23 cases (19.2%) were rated as grade I, 31 cases (25.8%) as grade II and 66 (55.0%) cases as grade III. Patients with SCS grade III had the highest incidence of LVI and LNM (p < 0.05). Kaplan–Meier analysis revealed that patients with higher SCS had significantly shorter DFS and OS than those with lower SCS (p < 0.05). High SCS was an independent predictor of poorer OS and DFS (p < 0.05) in patients with EAC. CONCLUSIONS: The application of the Silva system could effectively predict the LNM of patients and may be helpful in selecting an appropriate surgical procedure. The SCS system we designed showed a good predictive value for DFS and OS in EAC.