Evidence map›Paper›PMID 38896084›Full record

ArticleHepatology communications2024

Development and validation of a biomarker index for HCC treatment response.

Jeff Liang, Po-Yi Li, Joshua Norman, Marie Lauzon, Yee Hui Yeo, Hirsh Trivedi, Walid S Ayoub, Alexander Kuo, Marc L Friedman, Kamya Sankar and 15 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Hepatology communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. 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

25 authors.

Jeff LiangDepartment of Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Po-Yi LiDepartment of Medicine, Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA.
Joshua NormanDepartment of Internal Medicine, Stanford University, Palo Alto, California, USA.
Marie LauzonBiostatistics and Bioinformatics Research Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Yee Hui YeoDepartment of Internal Medicine, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Hirsh TrivediDepartment of Internal Medicine, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Walid S AyoubDepartment of Internal Medicine, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Alexander KuoDepartment of Internal Medicine, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Marc L FriedmanDepartment of Radiology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Kamya SankarSamuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Jun GongSamuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Arsen OsipovSamuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Andrew HendifarSamuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Tsuyoshi TodoComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Irene KimComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Georgios VoidonikolasComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Todd V BrennanComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Steven A WiselComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Justin SteggardaComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Kambiz KosariComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Rola SaouafDepartment of Radiology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Nicholas NissenComprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Francis YaoDepartment of Medicine, Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA.
Neil MehtaDepartment of Medicine, Division of Gastroenterology, University of California, San Francisco, San Francisco, California, USA.
Ju Dong YangDepartment of Internal Medicine, Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Funding

Novel circulating biomarker digital scores for assessing treatment response in liver cancerK08CA259534 · NCI · CEDARS-SINAI MEDICAL CENTER · PI YANG, JU DONG · 2022 to 2024
$807k
Novel circulating biomarker digital scores for assessing treatment response in liver cancerR21CA280444 · NCI · CEDARS-SINAI MEDICAL CENTER · PI YANG, JU DONG, ZHU, YAZHEN · 2023 to 2023
$436k
NCI NIH HHS K08 CA259534NCI NIH HHS R21 CA280444
6 · The paper itself

Abstract

backgroundSerum AFP-L3%, AFP, and DCP are useful biomarkers for HCC detection, but their utility in assessing treatment response remains unknown. We aim to evaluate the accuracy of a biomarker model in the detection of posttreatment viable tumors.

methodsFor model derivation, recipients with HCC undergoing liver transplant from 2018 to 2022 who had biomarkers collected within 3 months before transplant were included. We developed a generalized linear model for detecting posttreatment viable tumors with the 3 biomarkers as covariates, which we termed the "LAD Score." An independent cohort of 117 patients with HCC was used for external validation.

resultsAmong 205 recipients of transplant, 70.2% had evidence of viable tumor on explant. The median LAD score was higher among patients with viable versus nonviable tumors (1.06 vs. 0.465, p < 0.001). The LAD score had a sensitivity of 55.6% and a specificity of 85.1% at the cutoff of 0.927, which was more accurate than imaging for detecting posttreatment viable tumors (AUROC 0.736 vs. 0.643, respectively; p = 0.045). The superior performance of the LAD score over imaging is primarily driven by its greater accuracy in detecting tumors <2 cm in diameter (AUROC of the LAD score 0.721 vs. imaging 0.595, p = 0.02). In the validation data set, the LAD score had an AUROC of 0.832 (95% CI: 0.753, 0.911) with a sensitivity of 72.5% and a specificity of 89.4% at the cutoff of 0.927.

conclusionsOur findings suggest the utility of LAD score in treatment response assessment after locoregional therapy for HCC, particularly in detecting small tumors. A larger prospective study is in progress to validate its accuracy and evaluate its performance in recurrence monitoring.

Indexed as

alpha-FetoproteinsBiomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsLiver TransplantationAgedFemaleHumansMaleMiddle AgedRetrospective StudiesSensitivity and SpecificityTreatment Outcomealpha-FetoproteinsBiomarkers, Tumor

Identifiers

PMID38896084
PMCPMC11186807

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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.