Evidence map›Paper›PMID 36516200›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2023

Blood-Based Diagnosis and Risk Stratification of Patients with Pancreatic Intraductal Papillary Mucinous Neoplasm (IPMN).

Chaoyang Zhang, Fawaz N Al-Shaheri, Mohamed Saiel Saeed Alhamdani, Andrea S Bauer, Jörg D Hoheisel, Miriam Schenk, Ulf Hinz, Philipp Goedecke, Karam Al-Halabi, Markus W Büchler and 3 more

Open access · hybridAbstract readEditorialComment
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 22 citations in OpenAlex.

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  10. Non-Contrasted CT Radiomics for SAH Prognosis Prediction.Bioengineering (Basel, Switzerland) · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 2 countries.

Chaoyang ZhangDivision of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0001-6816-3840
Fawaz N Al-ShaheriDivision of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0002-6857-2596
Mohamed Saiel Saeed AlhamdaniDivision of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0001-9168-3895
Andrea S BauerDivision of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0002-7919-0497
Jörg D HoheiselDivision of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.ORCID 0000-0002-1583-5049
Miriam SchenkDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0003-0208-7958
Ulf HinzDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0001-8227-968X
Philipp GoedeckeDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0002-8753-6224
Karam Al-HalabiDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0001-5269-783X
Markus W BüchlerDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0002-3666-5675
Nathalia A GieseDepartment of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0001-5920-3142
Thilo Hackert *Department of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0002-7012-1196
Susanne Roth *Department of General Surgery, University Hospital Heidelberg, Heidelberg, Germany.ORCID 0000-0002-5136-4686
Heidelberg University · DEGerman Cancer Research Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIntraductal papillary mucinous neoplasm (IPMN) is a precursor of pancreatic ductal adenocarcinoma. Low-grade dysplasia has a relatively good prognosis, whereas high-grade dysplasia and IPMN invasive carcinoma require surgical intervention. However, diagnostic distinction is difficult. We aimed to identify biomarkers in peripheral blood for accurate discrimination. EXPERIMENTAL

designSera were obtained from 302 patients with IPMNs and 88 healthy donors. For protein biomarkers, serum samples were analyzed on microarrays made of 2,977 antibodies. A support vector machine (SVM) algorithm was applied to define classifiers, which were validated on a separate sample set. For microRNA biomarkers, a PCR-based screen was performed for discovery. Biomarker candidates confirmed by quantitative PCR were used to train SVM classifiers, followed by validation in a different sample set. Finally, a combined SVM classifier was established entirely independent of the earlier analyses, again using different samples for training and validation.

resultsPanels of 26 proteins or seven microRNAs could distinguish high- and low-risk IPMN with an AUC value of 95% and 94%, respectively. Upon combination, a panel of five proteins and three miRNAs yielded an AUC of 97%. These values were much better than those obtained in the same patient cohort by using the guideline criteria for discrimination. In addition, accurate discrimination was achieved between other patient subgroups.

conclusionsProtein and microRNA biomarkers in blood allow precise diagnosis and risk stratification of IPMN cases, which should improve patient management and thus the prognosis of IPMN patients. See related commentary by Löhr and Pantel, p. 1387.

Indexed as

Adenocarcinoma, MucinousCarcinoma, Pancreatic DuctalMicroRNAsPancreatic Intraductal NeoplasmsPancreatic NeoplasmsBiomarkersHumansHyperplasiaPancreasRisk AssessmentBiomarkersMicroRNAs

Identifiers

PMID36516200
PMCPMC10102846
OpenAlexW4311438967

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.