Evidence map›Paper›PMID 28376184›Full record

ArticleJournal of the National Cancer Institute2017

A Plasma Biomarker Panel to Identify Surgically Resectable Early-Stage Pancreatic Cancer.

Seetharaman Balasenthil, Ying Huang, Suyu Liu, Tracey Marsh, Jinyun Chen, Sanford A Stass, Debra KuKuruga, Randall Brand, Nanyue Chen, Marsha L Frazier and 4 more

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Journal of the National Cancer Institute, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

43 citing papers in PubMed, 71 citations in OpenAlex.

  1. Pancreatic Cancer Detection Consortium Biomarker Bakeoff: A Phase II Blinded Biomarker Validation and Panel Discovery Study.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 1 country.

Seetharaman BalasenthilDepartment of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Ying HuangFred Hutchison Cancer Research Center, Seattle, WA, USA.
Suyu LiuDepartment of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Tracey MarshFred Hutchison Cancer Research Center, Seattle, WA, USA.
Jinyun ChenDepartment of Epidemiology, University of Maryland Medical Center , Baltimore, MD, USA.
Sanford A StassUniversity of Maryland Medical Center , Baltimore, MD, USA.
Debra KuKurugaUniversity of Maryland Medical Center , Baltimore, MD, USA.
Randall BrandUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Nanyue ChenDepartment of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Marsha L FrazierDepartment of Epidemiology, University of Maryland Medical Center , Baltimore, MD, USA.
J Jack LeeDepartment of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Sudhir SrivastavaNational Cancer Institute, Rockville, MD, USA.
Subrata SenDepartment of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
Ann McNeill KillaryDepartment of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
The University of Texas MD Anderson Cancer Center · USUniversity of Maryland, Baltimore · USFred Hutch Cancer Center · USNational Cancer Institute · USUniversity of Pittsburgh Medical Center · USCancer Research Center · USUniversity of Maryland Medical Center · US

Funding

Biomarkers for the Early Detection of Pancreatic CancerU01CA111302 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KILLARY, ANN M, SEN, SUBRATA · 2004 to 2015
$6.6M
Digital Nanoplasmonic Quantification of Tumor-derived Extracellular Vesicles in Plasma MicrosamplesU01CA252965 · NCI · TULANE UNIVERSITY OF LOUISIANA · PI HU, TONY Y., LU, HUA · 2020 to 2024
$3.0M
NCI NIH HHS U01 CA111302NCI NIH HHS U01 CA252965
6 · The paper itself

Abstract

Background: Blood-based biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are urgently needed. Current biomarkers lack high sensitivity and specificity for population screening. The gold-standard biomarker, CA 19-9, also fails to demonstrate the predictive value necessary for early detection. Methods: To validate a functional genomics-based plasma migration signature biomarker panel, plasma tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FN III-C), and CA 19-9 levels were measured by enzyme-linked immunosorbent assays in three early-stage PDAC plasma cohorts, including two independent blinded validation cohorts containing a total of 43 stage I, 163 stage II, 86 chronic pancreatitis, 31 acute biliary obstruction, and 108 controls. Logistic regression models developed classification rules combining TFPI and/or TNC-FN III-C with CA 19-9 for patient cases and control subjects, with or without adjustment for age and diabetes status. Model classification performance was evaluated and analyses repeated among subpopulations without diabetes and pancreatitis history. Two-sided P values were calculated using bootstrap method. Results: The TFPI/TNC-FN III-C/CA 19-9 panel improved CA 19-9 performance in all early-stage cohorts, including discriminating stage IA/IB/IIA, stage IIB, and all early-stage cancer from healthy controls. Statistical significance was reached for a number of subcohorts, including for all early-stage cancer vs healthy controls (cohort 1 AUC = 0.92, 95% CI = 0.86 to 0.96, P  = .04; cohort 3 AUC = 0.83, 95% CI = 0.76 to 0.89, P  = .045). Among subcohorts without diabetes and pancreatitis history, the panel approaches potential clinical utility for early detection to discriminate early-stage PDAC from healthy controls including an area under the curve (AUC) of 0.87 (95% CI = 0.77 to 0.95) for stage I/IIA, an AUC of 0.93 (95% CI = 0.87 to 0.98) for stage IIB, and a statistically significant AUC of 0.89 (95% CI = 0.82 to 0.95) for all early-stage cancer ( P  = .03). Conclusions: TFPI/TNC-FN III-C migration signature adds statistically significantly to CA 19-9's predictive power to detect early-stage PDAC and may have clinical utility for early detection of surgically resectable PDAC, as well as for enhanced survival from this routinely lethal cancer.

Indexed as

Acute DiseaseAgedAged, 80 and overAge FactorsArea Under CurveCA-19-9 AntigenCarcinoma, Pancreatic DuctalCase-Control StudiesCholestasisCohort StudiesDiabetes MellitusEarly Detection of CancerFemaleHumansLipoproteinsMaleCA-19-9 Antigenlipoprotein-associated coagulation inhibitorLipoproteinsTenascin

Identifiers

PMID28376184
PMCPMC6059209
OpenAlexW2610732926

What OpenQuestion holds

Textmetadata
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.