Impact of methodological variability on the prognostic performance of circulating tumor DNA in colorectal cancer: A systematic review and meta-analysis.

Monyse Nobrega, Nivedita Kaorey, Luani Godoy, Kyle Dickinson, Dylan Wu, Aaron Tanchingco, Ramana-Kumar Agnihotram, Julia V Burnier

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In one paragraph

Review in The journal of liquid biopsy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Monyse NobregaCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Nivedita KaoreyCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Luani GodoyCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Kyle DickinsonCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Dylan WuCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Aaron TanchingcoCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Ramana-Kumar AgnihotramBiostatistics Consulting Unit, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Julia V BurnierCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating tumor DNA (ctDNA) has demonstrated utility for treatment monitoring, risk stratification, and prognostication in colorectal cancer (CRC). However, substantial methodological heterogeneity across studies may influence its reported prognostic performance. Here, we systematically searched four databases up to October 2025. Eligible studies included patients with CRC who underwent mutation-based plasma ctDNA analysis reported as a binary variable (positive/negative) and provided hazard ratios (HRs) with 95% confidence intervals (95%CIs) for recurrence-free survival (RFS), disease-free survival (DFS), progression-free survival (PFS), or overall survival (OS). Pooled HRs were synthesized using random-effects meta-analysis. Thirty-seven studies met the inclusion criteria. ctDNA positivity was consistently associated with inferior outcomes across all survival endpoints, including OS (HR 3.52; 95%CI 2.42-5.13; p < 0.001; I

Indexed as

Colorectal cancerctDNActDNA standardizationLiquid biopsyMeta-analysis

Identifiers

PMID42668443

DOI10.1016/j.jlb.2026.100487

PMCPMC13524542

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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.