Yaxin Kang, Lele Chang, Jing Liu, Haizhou Ji, Qin Xu
{"title":"宫颈黏液型与普通型腺癌的预后差异及生存预测模型","authors":"Yaxin Kang, Lele Chang, Jing Liu, Haizhou Ji, Qin Xu","doi":"10.1002/cam4.70927","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>There is significant histological heterogeneity between the endocervical adenocarcinoma (EA) subtypes. Usual-type carcinoma (adenocarcinoma) and mucinous carcinoma (mucinous adenocarcinoma, MA) are the most common types of EA.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Demographic and clinical variables were collected from the SEER database for selected patients between 2004 and 2021. The effect of confounding variables was reduced by propensity score matching (PSM). Survival data were analyzed using the Kaplan–Meier method and Cox regression models. A risk prediction model nomogram for MA was developed and validated.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The median age for MA patients was 46 years compared to 45 years for adenocarcinoma (<i>p</i> = 0.021). The 1-, 3-, and 5-year overall survival (OS) rates for MA were 88.2%, 74.5%, and 68.4%, respectively, significantly lower than those for adenocarcinoma (89.0%, 79.0%, and 74.9%, <i>p</i> < 0.0001). Cancer-specific survival (CSS) showed a similar trend (<i>p</i> < 0.0001). Seven variables, including age, primary site, T, N, combined stage, surgery, and chemotherapy, were selected to create the nomograms for predicting OS, while age, primary site, tumor size, T, N, combined stage, and surgery were selected for CSS. The validations of all predictive models were satisfactory.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This study revealed MA's poorer prognosis compared to adenocarcinoma using the SEER database. It developed predictive models for OS and CSS of MA, offering a more accurate prognosis assessment tool for clinical practice.</p>\n </section>\n </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"14 9","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.70927","citationCount":"0","resultStr":"{\"title\":\"Prognostic Differences and Survival Predictive Models for Mucinous Versus Usual-Type Adenocarcinoma of the Uterine Cervix\",\"authors\":\"Yaxin Kang, Lele Chang, Jing Liu, Haizhou Ji, Qin Xu\",\"doi\":\"10.1002/cam4.70927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>There is significant histological heterogeneity between the endocervical adenocarcinoma (EA) subtypes. Usual-type carcinoma (adenocarcinoma) and mucinous carcinoma (mucinous adenocarcinoma, MA) are the most common types of EA.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Demographic and clinical variables were collected from the SEER database for selected patients between 2004 and 2021. The effect of confounding variables was reduced by propensity score matching (PSM). Survival data were analyzed using the Kaplan–Meier method and Cox regression models. A risk prediction model nomogram for MA was developed and validated.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The median age for MA patients was 46 years compared to 45 years for adenocarcinoma (<i>p</i> = 0.021). The 1-, 3-, and 5-year overall survival (OS) rates for MA were 88.2%, 74.5%, and 68.4%, respectively, significantly lower than those for adenocarcinoma (89.0%, 79.0%, and 74.9%, <i>p</i> < 0.0001). Cancer-specific survival (CSS) showed a similar trend (<i>p</i> < 0.0001). Seven variables, including age, primary site, T, N, combined stage, surgery, and chemotherapy, were selected to create the nomograms for predicting OS, while age, primary site, tumor size, T, N, combined stage, and surgery were selected for CSS. The validations of all predictive models were satisfactory.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>This study revealed MA's poorer prognosis compared to adenocarcinoma using the SEER database. 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Prognostic Differences and Survival Predictive Models for Mucinous Versus Usual-Type Adenocarcinoma of the Uterine Cervix
Background
There is significant histological heterogeneity between the endocervical adenocarcinoma (EA) subtypes. Usual-type carcinoma (adenocarcinoma) and mucinous carcinoma (mucinous adenocarcinoma, MA) are the most common types of EA.
Methods
Demographic and clinical variables were collected from the SEER database for selected patients between 2004 and 2021. The effect of confounding variables was reduced by propensity score matching (PSM). Survival data were analyzed using the Kaplan–Meier method and Cox regression models. A risk prediction model nomogram for MA was developed and validated.
Results
The median age for MA patients was 46 years compared to 45 years for adenocarcinoma (p = 0.021). The 1-, 3-, and 5-year overall survival (OS) rates for MA were 88.2%, 74.5%, and 68.4%, respectively, significantly lower than those for adenocarcinoma (89.0%, 79.0%, and 74.9%, p < 0.0001). Cancer-specific survival (CSS) showed a similar trend (p < 0.0001). Seven variables, including age, primary site, T, N, combined stage, surgery, and chemotherapy, were selected to create the nomograms for predicting OS, while age, primary site, tumor size, T, N, combined stage, and surgery were selected for CSS. The validations of all predictive models were satisfactory.
Conclusion
This study revealed MA's poorer prognosis compared to adenocarcinoma using the SEER database. It developed predictive models for OS and CSS of MA, offering a more accurate prognosis assessment tool for clinical practice.
期刊介绍:
Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas:
Clinical Cancer Research
Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations
Cancer Biology:
Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery.
Cancer Prevention:
Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach.
Bioinformatics:
Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers.
Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.