Prognostic Differences and Survival Predictive Models for Mucinous Versus Usual‐Type Adenocarcinoma of the Uterine Cervix DOI Creative Commons

Yaxin Kang,

Lele Chang, Jing Liu

et al.

Cancer Medicine, Journal Year: 2025, Volume and Issue: 14(9)

Published: May 1, 2025

ABSTRACT Background There is significant histological heterogeneity between the endocervical adenocarcinoma (EA) subtypes. Usual‐type carcinoma (adenocarcinoma) and mucinous (mucinous adenocarcinoma, MA) are most common types of EA. Methods Demographic clinical variables were collected from SEER database for selected patients 2004 2021. The effect confounding was reduced by propensity score matching (PSM). Survival data analyzed using Kaplan–Meier method Cox regression models. A risk prediction model nomogram MA developed validated. Results median age 46 years compared to 45 ( p = 0.021). 1‐, 3‐, 5‐year overall survival (OS) rates 88.2%, 74.5%, 68.4%, respectively, significantly lower than those (89.0%, 79.0%, 74.9%, < 0.0001). Cancer‐specific (CSS) showed a similar trend Seven variables, including age, primary site, T, N, combined stage, surgery, chemotherapy, create nomograms predicting OS, while tumor size, surgery CSS. validations all predictive models satisfactory. Conclusion This study revealed MA's poorer prognosis database. It OS CSS MA, offering more accurate assessment tool practice.

Language: Английский

Prognostic Differences and Survival Predictive Models for Mucinous Versus Usual‐Type Adenocarcinoma of the Uterine Cervix DOI Creative Commons

Yaxin Kang,

Lele Chang, Jing Liu

et al.

Cancer Medicine, Journal Year: 2025, Volume and Issue: 14(9)

Published: May 1, 2025

ABSTRACT Background There is significant histological heterogeneity between the endocervical adenocarcinoma (EA) subtypes. Usual‐type carcinoma (adenocarcinoma) and mucinous (mucinous adenocarcinoma, MA) are most common types of EA. Methods Demographic clinical variables were collected from SEER database for selected patients 2004 2021. The effect confounding was reduced by propensity score matching (PSM). Survival data analyzed using Kaplan–Meier method Cox regression models. A risk prediction model nomogram MA developed validated. Results median age 46 years compared to 45 ( p = 0.021). 1‐, 3‐, 5‐year overall survival (OS) rates 88.2%, 74.5%, 68.4%, respectively, significantly lower than those (89.0%, 79.0%, 74.9%, < 0.0001). Cancer‐specific (CSS) showed a similar trend Seven variables, including age, primary site, T, N, combined stage, surgery, chemotherapy, create nomograms predicting OS, while tumor size, surgery CSS. validations all predictive models satisfactory. Conclusion This study revealed MA's poorer prognosis database. It OS CSS MA, offering more accurate assessment tool practice.

Language: Английский

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