Evidence map›Paper›PMID 33280269›Full record

ArticleCancer medicine2021

A practical nomogram and risk stratification system predicting the cancer-specific survival for patients with early hepatocellular carcinoma.

Bing Yan, Bing-Bing Su, Dou-Sheng Bai, Jian-Jun Qian, Chi Zhang, Sheng-Jie Jin, Guo-Qing Jiang

Abstract read
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Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

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30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Construction of webZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023
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  8. Competing risk analysis of surgical resectionTranslational cancer research · 2025
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Bing YanDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Bing-Bing SuDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Dou-Sheng BaiDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Jian-Jun QianDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Chi ZhangDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Sheng-Jie JinDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.
Guo-Qing JiangDepartment of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, China.ORCID 0000-0002-8699-6624

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur purpose was to establish and validate a nomogram model in early hepatocellular carcinoma (HCC) patients for predicting the cancer-specific survival (CSS).

methodsWe extracted eligible data of relevant patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Further, we divided all patients into two groups (training and validation cohorts) at random (7:3). Nomogram was established using effective risk factors based on univariate and multivariate analysis. The effective performance of nomogram was evaluated using concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic curve (ROC).

resultsWe selected 3620 patients with early HCC including the training cohort (70%, 2536) and the validation cohort (30%, 1084). The nomogram-related C-indexes were 0.755 (95% CI: 0.739-0.771) and 0.737 (95% CI: 0.712-0.762), in the training and validation cohorts, respectively. The calibration plots showed good consistency of 3-and 5-year CSS between the actual observation and the nomogram prediction. The 3-, 5-year DCA curves also indicated that the nomogram has excellent clinical utility. The 3-, 5-year area under curve (AUC) of ROC in the training cohort were 0.783, 0.779, respectively, and 0.767, 0.766 in the validation cohort, respectively. With the establishment of nomogram, a risk stratification system was also established that could divide all patients into three risk groups, and the CSS in different groups (i.e., low risk, intermediate risk, and high risk) had a good regional division.

conclusionsWe developed a practical nomogram in early HCC patients for predicting the CSS, and a risk stratification system follow arisen, which provided an applicable tool for clinical management.

Indexed as

NomogramsAgedCarcinoma, HepatocellularCombined Modality TherapyFemaleFollow-Up StudiesHumansLiver NeoplasmsMalePrognosisRetrospective StudiesRisk AssessmentRisk FactorsROC CurveSEER ProgramSurvival Ratecancer-specific survivalhepatocellular carcinomanomogrampredictrisk stratification

Identifiers

PMID33280269
PMCPMC7877377

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.