Abstract
BackgroundDue to the rarity of adenosquamous carcinoma of the cervix (ASCC), studies on the incidence, prognostic factors, and treatment outcomes of ASCC remain scarce. Therefore, we performed a retrospective population-based study to systematically investigate the characteristics of ASCC patients.MethodsPatients 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. Selected variables were integrated to establish a predictive nomogram and the predictive performance of the nomogram was estimated using Harrell’s concordance index (C-index), calibration curve, and decision curve analysis (DCA).ResultsA total of 1142 ASCC patients were identified and included in this study and were further randomized into the training and validation cohorts in a 7:3 ratio. 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 actual observation in both the training and testing cohorts. The C-index was 0.7916 (95% CI: 0.7990-0.8042) and 0.8148 (95% CI: 0.7954-0.8342) for the training and testing cohorts, respectively, indicating an excellent discrimination ability of the nomogram. The DCA showed that the nomogram exhibited more clinical benefits than the FIGO staging system.ConclusionsWe established and validated an accurate predictive nomogram for ASCC patients based on several clinical characteristics. This model might serve as a useful tool for clinicians to estimate the prognosis of ASCC patients.
Highlights
Cervical cancer was the fourth most frequent malignancy and the leading cause of gynecologic cancer-associated mortality worldwide in 2018 [1]
17,339 (75%) patients had squamous cell carcinoma of the cervix (SCCC), 3,012 (13%) had adenocarcinoma of the cervix (ADCC), 1,142 (5%) had Adenosquamous carcinoma of the cervix (ASCC), and 1,722 (7%) patients presented with other histological subtypes (Figure 1B)
Kaplan-Meier analysis showed marked differences in the Cancer-specific survival (CSS) of these three risk groups, and the 3year CSS rate was found to be 91% for the low-risk group, 58% for the medium-risk group, and 13% for the high-risk group (Figure 5). These results suggested that the novel riskstratification system exhibited a strong ability to identify high-risk ASCC patients, which was further tested in the validation and total cohorts (Figure 5)
Summary
Cervical cancer was the fourth most frequent malignancy and the leading cause of gynecologic cancer-associated mortality worldwide in 2018 [1]. The introduction of the human papillomavirus (HPV) vaccine and effective cervical cancer screening strategies have resulted in a significant decline in the incidence and morbidity of cervical cancer, it continues to be the most prevalent gynecological malignancy in 28 countries and the leading cause of cancer-related deaths in 42 countries [1, 2]. Squamous cell carcinoma of the cervix (SCCC) represents the most common subtype of cervical cancer, accounting for approximately 75% of all cervical cancers, followed by adenocarcinoma of the cervix (ADCC) with a proportion of approximately 15% [4]. Unusual histological subtypes such as adenosquamous carcinoma and neuroendocrine tumors are rare. We performed a retrospective population-based study to systematically investigate the characteristics of ASCC patients
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