Evidence map›Paper›PMID 40129529›Full record

ArticleOpen medicine (Warsaw, Poland)2025

Perform tumor-specific survival analysis for Merkel cell carcinoma patients undergoing surgical resection based on the SEER database by constructing a nomogram chart.

Jingxuan Zhou, Hai Yu, Xichun Xia, Yanan Chen, Wai-Kit Ming, Yuzhen Jiang, Yau Sun Lak, Chongchong Ip, Chaodi Huang, Qiqi Zhao and 6 more

Abstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Jingxuan ZhouDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Hai YuDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Xichun XiaInstitute of Biomedical Transformation, Jinan University, Guangzhou, China.
Yanan ChenInstitute of Dermatology and Venereal Diseases, Dermatology Hospital, Southern Medical University, Guangzhou, 510091, China.
Wai-Kit MingDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
Yuzhen JiangDepartment of Ophthalmology, Royal Free Hospital & University College London, London, United Kingdom.
Yau Sun LakDepartment of Dermatology, Centro de Hospitalar Conde de Januario, Macau, China.
Chongchong IpDepartment of Dermatology, University Hospital Macau, Macau, China.
Chaodi HuangDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Qiqi ZhaoDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Suzheng ZhengDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Liming XiaGuangzhou Jnumeso Bio-technology Co., Ltd., Guangzhou, China.
Xinkai ZhengDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Shi WuDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Jun LyuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.
Liehua DengDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the postoperative risk factors of Merkel cell carcinoma patients who have undergone surgical resection, and to construct a survival prognosis column chart. Method: Patients diagnosed with Merkel cell carcinoma and underwent surgical resection from 2000 to 2019 were selected from the surveillance, epidemiology, and end results database. COX regression analysis was used to screen for independent prognostic factors, and a column chart was constructed. The predictive performance of the column chart was evaluated using consistency index, receiver operating characteristic curve, and calibration curve. Results: The results of multi-factor COX regression showed that T stage and N stage were independent prognostic factors affecting cancer-specific survival (CSS) in patients after Merkel cell carcinoma resection. Construct a column chart based on the above two factors. The C-index of the column chart in the modeling group is 0.732 [95% CI (0.649, 0.814)], and the area under the curve (AUC) for the first and second years are 0.816 [95% CI (0.728, 0.904)] and 0.693 [95% CI (0.593, 0.792)], respectively. The C-index in the validation group was 0.724 [95% CI (0.569, 0.879)], and the AUC in the first and second years were 0.739 [95% CI (0.644, 0.833)] and 0.658 [95% CI (0.556, 0.759)], respectively. Conclusion: The predictive model constructed based on two factors, T stage and N stage, has good prognostic diagnostic accuracy and is helpful for clinical decision-making and personalized treatment.

Indexed as

column chartMerkel cell carcinomasurgical resectionsurvival analysis

Identifiers

PMID40129529
PMCPMC11931659

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