Evidence map›Paper›PMID 30913869›Full record

ArticleCancer research and treatment2019

Novel Prognostic Nomograms Based on Inflammation-Related Markers for Patients with Hepatocellular Carcinoma Underwent Hepatectomy.

Yifei Wang, Kaiyu Sun, Jingxian Shen, Bin Li, Ming Kuang, Qinghua Cao, Sui Peng

Open access · diamondAbstract read
In one paragraph

Article in Cancer research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. [Establishment of a predictive nomogram model for predicting the death of very preterm infants during hospitalization].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2022
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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

7 authors at 2 institutions in 1 country.

Yifei WangDepartment of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Kaiyu SunDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jingxian ShenDepartment of Medical Imaging, Sun Yat-sen University Cancer Center, Guangzhou, China.
Bin LiClinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Ming KuangDepartment of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Qinghua CaoDepartment of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Sui PengClinical Trials Unit, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Sun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

China National Funds for Distinguished Young Scientists 81825013Natural Science Foundation of Guizhou Province 81770608Natural Science Foundation of Guizhou Province 81771958
6 · The paper itself

Abstract

purposeHepatocellular carcinoma (HCC) is an aggressive disease with high recurrence rate. However, current staging systems were lack of predictive capacity for HCC recurrence. We aimed to develop prognostic nomograms based on inflammation-related markers for HCC patients underwent hepatectomy. MATERIALS AND

methodsWe recruited 889 surgically treated patients from two medical centers. Independent prognostic factors were identified by cox regression analyses. Nomograms for recurrence-free survival (RFS) and overall survival (OS) were established, and validated internally and externally. The performance, discrimination, and calibration of nomograms were assessed, and compared with existed staging systems.

resultsNeutrophil to lymphocyte ratio (NLR) and gamma-glutamyl transpeptidase to platelet ratio (GPR) were the two inflammation-related factor that independently correlated with survival. NLR, GPR, international normalized ratio (INR), microvascular invasion, satellite lesions, tumour number, tumour diameter, and macrovascular invasion were used to construct nomogram for RFS while GPR, total bilirubin, INR, α-fetoprotein, microvascular invasion, satellite lesions, tumour diameter, and macrovascular invasion were for OS. In the training cohort, the C-index of nomogram was 0.701 (95% confidence interval [CI], 0.669 to 0.732) for RFS and 0.761 (95% CI, 0.728 to 0.795) for OS. These results received both internal and external validation with C-index of 0.701 (95% CI, 0.647 to 0.755) and 0.707 (95% CI, 0.657 to 0.756) for RFS, and 0.706 (95% CI, 0.640 to 0.772) and 0.708 (95% CI, 0.646 to 0.771) for OS, respectively. The nomograms showed superior accuracy to conventional staging systems (p<0.001).

conclusionThe nomograms based on inflammation-related markers are of high efficacy in predicting survival of HCC patients after hepatectomy, which will be valuable in guiding postoperative interventions and follow-ups.

Indexed as

NomogramsAdultalpha-FetoproteinsBiomarkers, TumorCarcinoma, HepatocellularChinaFemalegamma-GlutamyltransferaseHepatectomyHumansLiver NeoplasmsLymphocyte CountMaleMiddle AgedNeutrophilsPlatelet CountAFP protein, humanalpha-FetoproteinsBiomarkers, Tumorgamma-GlutamyltransferaseHepatocellular carcinomaInflammationNomogramsResectionSurvival

Identifiers

PMID30913869
PMCPMC6790828
OpenAlexW2921170114

What OpenQuestion holds

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LicenceCC BY-NC
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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.