Evidence map›Paper›PMID 36439435›Full record

ArticleFrontiers in oncology2022

Development and Validation of a nomogram for forecasting survival of alcohol related hepatocellular carcinoma patients.

Tao Yan, Chenyang Huang, Jin Lei, Qian Guo, Guodong Su, Tong Wu, Xueyuan Jin, Caiyun Peng, Jiamin Cheng, Linzhi Zhang and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 3 countries.

Tao YanComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Chenyang HuangComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Jin LeiThe First Affiliated Hospital, Guizhou Medical University, Guiyang, China.
Qian GuoThe First Affiliated Hospital, Guizhou Medical University, Guiyang, China.
Guodong SuComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Tong WuComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Xueyuan JinMedical Quality Control Department, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Caiyun PengComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Jiamin ChengComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Linzhi ZhangComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Zherui LiuComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Terence KinDepartment of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Fan YingDepartment of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Suthat LiangpunsakulDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.
Yinyin LiComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Yinying LuComprehensive Liver Cancer Center, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Chinese PLA General Hospital · CNHong Kong Polytechnic University · HKAffiliated Hospital of Guizhou Medical University · CNGuiyang Medical University · CNIndiana University – Purdue University Indianapolis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the increasing incidence and prevalence of alcoholic liver disease, alcohol-related hepatocellular carcinoma has become a serious public health problem worthy of attention in China. However, there is currently no prognostic prediction model for alcohol-related hepatocellular carcinoma. Methods: The retrospective analysis research of alcohol related hepatocellular carcinoma patients was conducted from January 2010 to December 2014. Independent prognostic factors of alcohol related hepatocellular carcinoma were identified by Lasso regression and multivariate COX proportional model analysis, and the nomogram model was constructed. The reliability and accuracy of the model were assessed using the concordance index(C-Index), receiver operating characteristic (ROC) curve and calibration curve. Evaluate the clinical benefit and application value of the model through clinical decision curve analysis (DCA). The prognosis was assessed by the Kaplan-Meier (KM) survival curve. Results: In sum, 383 patients were included in our study. Patients were stochastically assigned to training cohort (n=271) and validation cohort (n=112) according to 7:3 ratio. The predictors included in the nomogram were splenectomy, platelet count (PLT), creatinine (CRE), Prealbumin (PA), mean erythrocyte hemoglobin concentration (MCHC), red blood cell distribution width (RDW) and TNM. Our nomogram demonstrated excellent discriminatory power ( Conclusion: The nomogram model we established can precisely forcasting the prognosis of alcohol related hepatocellular carcinoma patients, which would be helpful for the early warning of alcohol related hepatocellular carcinoma and predict prognosis in patients with alcoholic hepatocellular carcinoma.

Indexed as

alcoholhepatocellular carcinomanomogramoverall survivalprognosis

Identifiers

PMID36439435
PMCPMC9692070
OpenAlexW4308935607

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.