Evidence map›Paper›PMID 36457649›Full record

ArticleEClinicalMedicine2023

Diagnostic accuracy and added value of blood-based protein biomarkers for pancreatic cancer: A meta-analysis of aggregate and individual participant data.

Lenka N C Boyd, Mahsoem Ali, Mariska M G Leeflang, Giorgio Treglia, Ralph de Vries, Tessa Y S Le Large, Marc G Besselink, Elisa Giovannetti, Hanneke W M van Laarhoven, Geert Kazemier

Abstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Challenges of early detection of pancreatic cancer.The Journal of clinical investigation · 2025
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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

10 authors.

Lenka N C BoydAmsterdam UMC, Location Vrije Universiteit, Department of Surgery, Amsterdam, the Netherlands.
Mahsoem AliAmsterdam UMC, Location Vrije Universiteit, Department of Surgery, Amsterdam, the Netherlands.
Mariska M G LeeflangAmsterdam UMC, Location University of Amsterdam, Department of Epidemiology and Data Science, Amsterdam, the Netherlands.
Giorgio TregliaClinic of Nuclear Medicine, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
Ralph de VriesAmsterdam UMC, Location Vrije Universiteit, Medical Library, Amsterdam, the Netherlands.
Tessa Y S Le LargeDepartment of Surgery, Dijklander Ziekenhuis Location Hoorn, Hoorn, the Netherlands.
Marc G BesselinkCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands.
Elisa GiovannettiAmsterdam UMC, Location Vrije Universiteit, Department of Medical Oncology, Lab of Medical Oncology, Amsterdam, the Netherlands.
Hanneke W M van LaarhovenCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, the Netherlands.
Geert KazemierAmsterdam UMC, Location Vrije Universiteit, Department of Surgery, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Novel blood-based protein biomarkers may be of value for efficient, accurate, and non-invasive diagnosis of pancreatic cancer. This study assesses the diagnostic accuracy of newly recognized blood-based protein biomarkers for detecting pancreatic cancer, and investigates their added value to CA19-9, the common blood-based biomarker in clinical use for pancreatic cancer. Methods: PubMed, Embase, Web of Science, and the Wiley/Cochrane Library were systematically searched from inception until June 2022. A meta-analysis of aggregate and individual participant data was conducted using frequentist and Bayesian hierarchical random-effects models. The added clinical utility of protein biomarkers was investigated using bootstrap bias-corrected decision curve analyses. Findings: Aggregate data from 28 primary studies (6127 participants) were included, of which 8 studies (1790 participants) provided individual participant data. CA19-9 was significantly more accurate than MIC-1 for distinguishing pancreatic cancer from benign disease (AUC, 0.83 Interpretation: Novel protein biomarkers have moderate diagnostic accuracy, do not outperform CA19-9 in differentiating pancreatic cancer from benign disease, and show limited added clinical value to CA19-9. We propose recommendations to aid the development of minimally invasive diagnostic tests with sufficient clinical utility to improve the management of patients with suspected pancreatic cancer. Funding: Bennink Foundation, Dutch Cancer Foundation (KWF Kankerbestrijding), and AIRC.

Identifiers

PMID36457649
PMCPMC9706531

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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.