Evidence map›Paper›PMID 40590061›Full record

ArticleStatistical methods in medical research2025

Using circulating tumor DNA as a novel biomarker of efficacy for dose-finding designs in oncology.

Xijin Chen, Pavel Mozgunov, Richard D Baird, Thomas Jaki

Abstract read
In one paragraph

Article in Statistical methods in medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Xijin ChenMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0001-5591-4828
Pavel MozgunovMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0001-6810-0284
Richard D BairdCancer Research UK, Cambridge Centre, University of Cambridge, Cambridge, UK.ORCID 0000-0001-7071-6483
Thomas JakiMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-1096-188X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dose-finding trials are designed to identify a safe and potentially effective drug dose and schedule during the early phase of clinical trials. Historically, Bayesian adaptive dose-escalation methods in Phase I trials in cancer have mainly focussed on toxicity endpoints rather than efficacy endpoints. This is partly because efficacy readouts are often not available soon enough for dose escalation decisions. In the last decade, 'liquid biopsy' technologies have been developed, which may provide a readout of treatment response much earlier than conventional endpoints. This paper develops a novel design that uses a biomarker, circulating tumour DNA (ctDNA), with toxicity and activity outcomes in dose-finding studies. We compare the proposed approach based on repeated ctDNA measurement with existing Bayesian adaptive approaches under various scenarios of dose-toxicity, dose-efficacy relationship, and trajectories of regular ctDNA values over time. Simulation results show that the proposed approach can yield significantly shorter trial duration and may improve identification of the target dose. In addition, this approach has the potential to minimise the time individual patients spend on potentially inactive trial therapies. Using two different dose-finding designs, we demonstrate that the way we incorporate biomarker information is broadly applicable across different dose-finding designs and yields notable benefit in both cases.

Indexed as

Biomarkers, TumorCirculating Tumor DNAMedical OncologyNeoplasmsAntineoplastic AgentsBayes TheoremClinical Trials, Phase I as TopicComputer SimulationDose-Response Relationship, DrugHumansResearch DesignAntineoplastic AgentsBiomarkers, TumorCirculating Tumor DNABayesian adaptive trial designbiomarkercirculating tumour DNAdose-finding studies

Identifiers

PMID40590061
PMCPMC12365363

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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.