Evidence map›Paper›PMID 34785539›Full record

ReviewCancer discovery2021

Detecting Liquid Remnants of Solid Tumors: Circulating Tumor DNA Minimal Residual Disease.

Everett J Moding, Barzin Y Nabet, Ash A Alizadeh, Maximilian Diehn

Open access · bronzeAbstract readReview
In one paragraph

Review in Cancer discovery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 211 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
211citing papers in PubMed, 9 pooled it
18.0field-weighted citation impact, top 1% 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

211 citing papers in PubMed, 9 syntheses or guidelines pooled it, 292 citations in OpenAlex.

  1. Circulating tumor DNA as a predictive biomarker for colorectal cancer postsurgical recurrence: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  11. Minimal Residual Disease Enhances Prognostic Stratification beyond Pathologic Response in Resectable Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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  14. Analysis of Circulating Tumor DNA Predicts Outcomes of Short-Course Consolidation Immunotherapy in Unresectable Stage III NSCLC.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2024
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151 more citing papers are in PubMed but not listed here.

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

4 authors at 2 institutions in 2 countries.

Everett J ModingStanford Cancer Institute, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-7913-5351
Barzin Y NabetStanford Cancer Institute, Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-4824-3533
Ash A AlizadehStanford Cancer Institute, Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-5153-5625
Maximilian DiehnStanford Cancer Institute, Stanford University School of Medicine, Stanford, California.ORCID 0000-0003-2032-0581
California Institute for Regenerative Medicine · USStanford Medicine · US

Funding

Circulating Genomic Determinants of Treatment Failure in Hodgkin LymphomaR01CA257655 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2021 to 2025
$3.2M
Molecularly-based outcome and toxicity prediction after radiotherapy for lung cancerR01CA254179 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2020 to 2024
$3.1M
Analysis of urine tumor nucleic acids for detection and personalized surveillance of bladder cancerR01CA244526 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2020 to 2024
$3.0M
A Genomic Framework for Molecular Risk Prediction & Individualized Lymphoma TherapyR01CA233975 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2019 to 2023
$2.8M
Imaging and circulating DNA markers to assess early response and predict treatment failure patterns in lung cancerR01CA233578 · NCI · STANFORD UNIVERSITY · PI DIEHN, MAXIMILIAN, LI, RUIJIANG · 2019 to 2023
$2.7M
Cancer Systems Biology Scholars ProgramR25CA180993 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2014 to 2018
$2.2M
Noninvasive monitoring of lung cancer patients treated with radiotherapyR01CA188298 · NCI · STANFORD UNIVERSITY · PI ALIZADEH, ASH ARASH, DIEHN, MAXIMILIAN · 2015 to 2019
$1.8M
NCI NIH HHS R01 CA188298NCI NIH HHS R01 CA233578NCI NIH HHS R01 CA233975NCI NIH HHS R01 CA244526NCI NIH HHS R01 CA254179NCI NIH HHS R01 CA257655NCI NIH HHS R25 CA180993
6 · The paper itself

Abstract

Growing evidence demonstrates that circulating tumor DNA (ctDNA) minimal residual disease (MRD) following treatment for solid tumors predicts relapse. These results suggest that ctDNA MRD could identify candidates for adjuvant therapy and measure response to such treatment. Importantly, factors such as assay type, amount of ctDNA release, and technical and biological background can affect ctDNA MRD results. Furthermore, the clinical utility of ctDNA MRD for treatment personalization remains to be fully established. Here, we review the evidence supporting the value of ctDNA MRD in solid cancers and highlight key considerations in the application of this potentially transformative biomarker. SIGNIFICANCE: ctDNA analysis enables detection of MRD and predicts relapse after definitive treatment for solid cancers, thereby promising to revolutionize personalization of adjuvant and consolidation therapies.

Indexed as

Circulating Tumor DNABiomarkers, TumorHumansNeoplasm Recurrence, LocalNeoplasm, ResidualBiomarkers, TumorCirculating Tumor DNA

Identifiers

PMID34785539
PMCPMC8976700
OpenAlexW3214322235

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.