Evidence map›Paper›PMID 33387587›Full record

ReviewHuman pathology2021

Hepatocellular carcinoma: making sense of morphological heterogeneity, growth patterns, and subtypes.

Michael S Torbenson

Abstract readReview
In one paragraph

Review in Human pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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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

1 author.

Michael S TorbensonDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA. Electronic address: Torbenson.Michael@mayo.edu.

Funding

Project 4: ImmunovirotherapyP50CA210964 · NCI · MAYO CLINIC ROCHESTER · PI Rory Smoot · 2018 to 2026
$20.5M
NCI NIH HHS P50 CA210964
6 · The paper itself

Abstract

Hepatocellular carcinomas are not a homogenous group of tumors but have multiple layers of heterogeneity. This heterogeneity has been studied for many years with the goal to individualize care for patients and has led to the identification of numerous hepatocellular carcinoma subtypes, defined by morphology and or molecular methods. This article reviews both gross and histological levels of heterogeneity within hepatocellular carcinoma, with a focus on histological findings, reviewing how different levels of histological heterogeneity are used as building blocks to construct morphological hepatocellular carcinoma subtypes. The current best practice for defining a morphological subtype is outlined. Then, the definition for thirteen distinct hepatocellular carcinoma subtypes is reviewed. For each of these subtypes, unresolved issues regarding their definitions are highlighted, including recommendations for these problematic areas. Finally, three methods for improving the research on hepatocellular carcinoma subtypes are proposed: (1) Use a systemic, rigorous approach for defining hepatocellular carcinoma subtypes (four-point model); (2) Once definitions for a subtype are established, it should be followed in research studies, as this common denominator enhances the ability to compare results between studies; and (3) Studies of subtypes will be more effective when morphological and molecular results are used in synergistic and iterative study designs where the results of one approach are used to refine and sharpen the results of the other. These and related efforts to better understand heterogeneity within hepatocellular carcinoma are the most promising avenue for improving patient care by individualizing patient care.

Indexed as

Carcinoma, HepatocellularHumansLiver NeoplasmsClear cellFibrolamellarGrowth patternsHepatocellular carcinomaHeterogeneitySteatohepatiticSubtypes

Identifiers

PMID33387587
PMCPMC9258523

What OpenQuestion holds

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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.