Evidence map›Paper›PMID 36969760›Full record

ArticleFrontiers in surgery2023

Development and validation of a prognostic nomogram for neuroendocrine prostate cancer, based on the SEER database.

Siming Chen, Kangping Xiong, Jiageng Shi, Shijie Yao, Gang Wang, Kaiyu Qian, Xinghuan Wang

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Article in Frontiers in surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Siming ChenDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Kangping XiongDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Jiageng ShiDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Shijie YaoDepartment of Gynecological Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China.
Gang WangDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Kaiyu QianDepartment of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xinghuan WangDepartment of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The tumor biology of neuroendocrine prostate cancer (NEPC) is different from that of ordinary prostate cancer, herefore, existing clinical prognosis models for prostate cancer patients are unsuitable for NEPC. The specialized individual situation assessment and clinical decision-making tools for NEPC patients are urgently needed. This study aimed to develop a valid NEPC prognostic nomogram and risk stratification model to predict risk associated with patient outcomes. Methods: We collected 340 de-novo NEPC patients from the SEER database, and randomly selected 240 of them as the training set and the remaining 100 as the validation set. Cox regression model was used to screen for risk factors affecting overall survival (OS) and cancer-specific survival (CSS) and construct a corresponding nomogram. The receiver operating characteristic (ROC) curves, calibration curves, C-indexes, and decision curve analysis (DCA) curves are used to verify and calibrate nomograms. Results: NEPC prognosis nomograms were constructed by integrating independent risk factors. The C-indexes, ROC curves, calibration curves, and DCA curves revealed excellent prediction accuracy of the prognostic nomogram. Furthermore, we demonstrated that NEPC patients in the high-risk group had significantly lower OS and CSS than those in the low-risk group with risk scores calculated from nomograms. Conclusions: The nomogram established in this research has the potential to be applied to the clinic to evaluate the prognosis of NEPC patients and support corresponding clinical decision-making.

Indexed as

cancer-specific survivalneuroendocrine prostate cancernomogramoverall survivalprognosisSEER

Identifiers

PMID36969760
PMCPMC10036588

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