Evidence map›Paper›PMID 41294651›Full record

ReviewCurrent oncology (Toronto, Ont.)2025

ctDNA in Pancreatic Adenocarcinoma: A Critical Appraisal.

Sujata Ojha, William Sessions, Yuhang Zhou, Kyaw L Aung

Abstract readReview
In one paragraph

Review in Current oncology (Toronto, Ont.), 2025. 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. Review
  4. Review
  5. 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.

Sujata OjhaDepartment of Internal Medicine, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.
William SessionsDivision of Hematology and Oncology, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.
Yuhang ZhouDivision of Hematology and Oncology, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.
Kyaw L AungDivision of Hematology and Oncology, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.

Funding

Cancer Prevention and Research Institute of Texas RP210234
6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies due to late diagnosis and limited treatment options. Circulating tumor DNA (ctDNA) is a promising, minimally invasive biomarker that could improve the clinical outcomes of patients with PDAC by enabling early disease detection, minimal residual disease (MRD) assessment, precise prognostication, and accurate treatment monitoring. CtDNA has prognostic as well as predictive value in both resectable and metastatic settings, with serial measurements enhancing risk stratification and recurrence prediction beyond CA19-9. However, despite the promise, the true potential of ctDNA has not yet been fulfilled in patients with PDAC. The current limitations include a low sensitivity of ctDNA assays in early stage PDAC, challenges in the assay interpretation due to the specific nature of ctDNA shedding in PDAC, inter-patient heterogeneity, and technical variability. As precision oncology advances, ctDNA will be a powerful tool for personalized care in PDAC, but rigorous validation of its use within specific clinical contexts is still needed before the true potential of ctDNA is realized for patients with PDAC.

Indexed as

AdenocarcinomaBiomarkers, TumorCarcinoma, Pancreatic DuctalCirculating Tumor DNAPancreatic NeoplasmsHumansPrognosisBiomarkers, TumorCirculating Tumor DNAcirculating tumor DNA (ctDNA)liquid biopsyminimal residual disease (MRD)pancreatic ductal adenocarcinoma (PDAC)precision oncology

Identifiers

PMID41294651
PMCPMC12650963

What Socratic holds

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LicenceCC BY
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 Socratic graph.