Evidence map›Paper›PMID 32931023›Full record

ArticleHepatology (Baltimore, Md.)2021

HepatoScore-14: Measures of Biological Heterogeneity Significantly Improve Prediction of Hepatocellular Carcinoma Risk.

Jeffrey S Morris, Manal M Hassan, Ye Emma Zohner, Zeya Wang, Lianchun Xiao, Asif Rashid, Abedul Haque, Reham Abdel-Wahab, Yehia I Mohamed, Karri L Ballard and 11 more

Abstract readValidation Study
In one paragraph

Article in Hepatology (Baltimore, Md.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Circulating Galectin-3: A Prognostic Biomarker in Hepatocellular Carcinoma.Journal of immunotherapy and precision oncology · 2024
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors.

Jeffrey S MorrisDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.ORCID 0000-0002-8520-6088
Manal M HassanDepartment of Epidemiology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Ye Emma ZohnerDepartment of Statistics, Rice University, Houston, TX.
Zeya WangDepartment of Statistics, Rice University, Houston, TX.
Lianchun XiaoDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
Asif RashidDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Abedul HaqueDepartment of Hematopathology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Reham Abdel-WahabDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-5432-5068
Yehia I MohamedDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Karri L BallardMyriad RBM Inc., Austin, TX.
Robert A WolffDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Bhawana GeorgeDepartment of Hematopathology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Liang LiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX.
Genevera AllenDepartment of Statistics, Rice University, Houston, TX.
Michael WeylandtDepartment of Statistics, Rice University, Houston, TX.
Donghui LiDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Wenyi WangDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0003-0617-9438
Kanwal RaghavDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.
James YaoDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.ORCID 0000-0002-1875-3962
Hesham M AminDepartment of Hematopathology, the University of Texas MD Anderson Cancer Center, Houston, TX.
Ahmed Omar KasebDepartment of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Genome-Wide Association Study (GWAS) in Hepatocellular Carcinoma (HCC)R01CA186566 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AMOS, CHRISTOPHER I., HASSAN, MANAL METWALLY · 2015 to 2019
$3.6M
Bayesian Network-Based Integrative Genomics Methods for Precision MedicineR01CA244845 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BALADANDAYUTHAPANI, VEERABHADRAN, MORRIS, JEFFREY S · 2021 to 2024
$1.8M
Statistical methods for genomic analysis of heterogeneous tumorsR01CA183793 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WANG, WENYI · 2014 to 2018
$1.7M
Bayesian methods for complex, high-dimensional functional data in cancer researchR01CA178744 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MORRIS, JEFFREY S · 2015 to 2019
$1.7M
Role of IGF-IR tyrosine kinase in NPM-ALK-expressing T-cell lymphomaR01CA151533 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AMIN, HESHAM M · 2011 to 2015
$1.6M
Molecular Epidemiology of Chronic Liver DiseasesK07CA106458 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI HASSAN, MANAL METWALLY · 2005 to 2009
$681k
Novel Point-of-Care Tool to Predict Response to Sorafenib in Hepatocellular CarcinomaR21CA190945 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KASEB, AHMED · 2016 to 2017
$383k
Integrating plasma IGF-1 into novel classification of hepatocellular carcinomaR21CA170035 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KASEB, AHMED · 2012 to 2013
$366k
Hepatitis Virus, Alcohol Exposure and Oxidative StressR03ES011481 · NIEHS · UNIVERSITY OF TEXAS MD ANDERSON CAN CTR · PI HASSAN, MANAL M · 2001 to 2002
$150k
NCI NIH HHS K07 CA106458NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA151533NCI NIH HHS R01 CA178744NCI NIH HHS R01 CA183793NCI NIH HHS R01 CA186566NCI NIH HHS R01 CA244845NCI NIH HHS R21 CA170035NCI NIH HHS R21 CA190945NIEHS NIH HHS R03 ES011481
6 · The paper itself

Abstract

BACKGROUND AND

aimsTherapeutic, clinical trial entry and stratification decisions for hepatocellular carcinoma (HCC) are made based on prognostic assessments, using clinical staging systems based on small numbers of empirically selected variables that insufficiently account for differences in biological characteristics of individual patients' disease. APPROACH AND

resultsWe propose an approach for constructing risk scores from circulating biomarkers that produce a global biological characterization of individual patient's disease. Plasma samples were collected prospectively from 767 patients with HCC and 200 controls, and 317 proteins were quantified in a Clinical Laboratory Improvement Amendments-certified biomarker testing laboratory. We constructed a circulating biomarker aberration score for each patient, a score between 0 and 1 that measures the degree of aberration of his or her biomarker panel relative to normal, which we call HepatoScore. We used log-rank tests to assess its ability to substratify patients within existing staging systems/prognostic factors. To enhance clinical application, we constructed a single-sample score, HepatoScore-14, which requires only a subset of 14 representative proteins encompassing the global biological effects. Patients with HCC were split into three distinct groups (low, medium, and high HepatoScore) with vastly different prognoses (medial overall survival 38.2/18.3/7.1 months; P < 0.0001). Furthermore, HepatoScore accurately substratified patients within levels of existing prognostic factors and staging systems (P < 0.0001 for nearly all), providing substantial and sometimes dramatic refinement of expected patient outcomes with strong therapeutic implications. These results were recapitulated by HepatoScore-14, rigorously validated in repeated training/test splits, concordant across Myriad RBM (Austin, TX) and enzyme-linked immunosorbent assay kits, and established as an independent prognostic factor.

conclusionsHepatoScore-14 augments existing HCC staging systems, dramatically refining patient prognostic assessments and therapeutic decision making and enrollment in clinical trials. The underlying strategy provides a global biological characterization of disease, and can be applied broadly to other disease settings and biological media.

Indexed as

Severity of Illness IndexBiomarkers, TumorCarcinoma, HepatocellularCase-Control StudiesFemaleHumansLiver NeoplasmsMalePredictive Value of TestsPrognosisProportional Hazards ModelsRisk FactorsBiomarkers, Tumor

Identifiers

PMID32931023
PMCPMC7956911

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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.