ArticleFrontiers in oncology2021
Adenosquamous Carcinoma of the Cervix: A Population-Based Analysis.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- Adenosquamous carcinoma of the cervix: a case report from a resource-limited setting.International journal of surgery case reports · 2026Article
- Development and validation of the competing risk nomogram and risk classification system for predicting cancer-specific mortality in patients with cervical adenosquamous carcinoma treated via radical hysterectomy.Biomolecules & biomedicine · 2025Article
- Genetic Variants of Interleukin-8 and Interleukin-16 and Their Association with Cervical Cancer Risk.Life (Basel, Switzerland) · 2025Article
- L1CAM is not prognostic factor in HPV-associated adenocarcinoma and adenosquamous cell carcinoma of the uterine cervix.Cancer biomarkers : section A of Disease markers · 2024Article
- Analysis of clinicopathological characteristics and prognosis on primary gastric adenosquamous carcinoma.Scientific reports · 2024Article
- Article
- Pre-treatment inflammatory and immune system parameters predicting cervical cancer metastasis.Turkish journal of obstetrics and gynecology · 2023Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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