Abstract 785P
Background
Due to the rarity of adenosquamous carcinoma of the cervix (ASCC), studies on incidence, prognostic factors, and treatment outcomes of ASCC remains scarce. Therefore, we performed a retrospective population-based study to investigate ASCC patients’ characteristics systematically.
Methods
Patients with a histopathologically confirmed diagnosis of ASCC were enrolled from the Surveillance, Epidemiology, and End Results database between 1975 and 2016. Univariate and multivariate Cox regression analyses were performed to identify the potential predictors of cancer-specific survival (CSS) in patients with ASCC. The selected variables were integrated to establish a predictive nomogram. The predictive performance of the nomogram was estimated by Harrell’s concordance index (C-index), calibration curve, and decision curve analysis (DCA).
Results
A total of 1142 ASCC patients were identified and included in this study and were further randomly divided into the training and validation cohort with a ratio of 7:3. The age-adjusted incidence of ASCC declined from 0.19 to 0.09 cases per 100,000 person-years between 2000 and 2017, with an annual percentage change of -4.05% (P<0.05). We identified age, tumor grade, FIGO stage, tumor size, and surgical procedure as independent predictors for CSS in ASCC patients and constructed a nomogram to predict the 3- and 5-year CSS using these prognostic factors. The calibration curve indicated an outstanding consistency between the nomogram prediction and the actual observation in both the training and testing cohort. The C-index was 0.7916 (95% CI: 0.7990-0.8042) and 0.8148 (95% CI: 0.7954-0.8342) for the training cohort and testing cohort, respectively, indicating an excellent discrimination ability of the nomogram. The DCA showed that the nomogram exhibited more clinical benefits than the FIGO staging system.
Conclusions
We established and validated an accurate predictive nomogram for ASCC patients based on several clinical characteristics, and the model might serve as a useful tool for the clinician to estimate the prognosis of ASCC patients.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.