Evidence map›Paper›PMID 27666740›Full record

ArticleCancer medicine2016

Evaluating IPMN and pancreatic carcinoma utilizing quantitative histopathology.

Evan S Glazer, Hao Helen Zhang, Kimberly A Hill, Charmi Patel, Stephanie T Kha, Michael L Yozwiak, Hubert Bartels, Nellie N Nafissi, Joseph C Watkins, David S Alberts and 1 more

Abstract read
In one paragraph

Article in Cancer medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Evan S GlazerUniversity of Tennessee Health Sciences Center, Memphis, Tennessee.
Hao Helen ZhangThe University of Arizona, Tucson, Arizona.
Kimberly A HillUniversity of Colorado, Denver, Colorado.
Charmi PatelThe University of Arizona, Tucson, Arizona.
Stephanie T KhaThe University of Arizona, Tucson, Arizona.
Michael L YozwiakThe University of Arizona, Tucson, Arizona.
Hubert BartelsThe University of Arizona, Tucson, Arizona.
Nellie N NafissiThe University of Arizona, Tucson, Arizona.
Joseph C WatkinsThe University of Arizona, Tucson, Arizona.
David S AlbertsThe University of Arizona, Tucson, Arizona.
Robert S KrouseCMC Veterans Affairs Medical Center, Philadelphia, Pennsylvania. robert.krouse@va.gov.

Funding

VITAMIN AP30CA023074 · NCI · UNIVERSITY OF ARIZONA · PI Dan Theodorescu · 1985 to 2026
$110.2M
SHORT-TERM TRAINING STUDENTS IN HEALTH PROFESSIONAL SCHOT35HL007479 · NHLBI · UNIVERSITY OF ARIZONA · PI GEOFFREY C GURTNER, JAMES Kuang-Jan LIAO · 1985 to 2026
$4.4M
NCI NIH HHS P30 CA023074NHLBI NIH HHS T35 HL007479
6 · The paper itself

Abstract

Intraductal papillary mucinous neoplasms (IPMN) are pancreatic lesions with uncertain biologic behavior. This study sought objective, accurate prediction tools, through the use of quantitative histopathological signatures of nuclear images, for classifying lesions as chronic pancreatitis (CP), IPMN, or pancreatic carcinoma (PC). Forty-four pancreatic resection patients were retrospectively identified for this study (12 CP; 16 IPMN; 16 PC). Regularized multinomial regression quantitatively classified each specimen as CP, IPMN, or PC in an automated, blinded fashion. Classification certainty was determined by subtracting the smallest classification probability from the largest probability (of the three groups). The certainty function varied from 1.0 (perfectly classified) to 0.0 (random). From each lesion, 180 ± 22 nuclei were imaged. Overall classification accuracy was 89.6% with six unique nuclear features. No CP cases were misclassified, 1/16 IPMN cases were misclassified, and 4/16 PC cases were misclassified. Certainty function was 0.75 ± 0.16 for correctly classified lesions and 0.47 ± 0.10 for incorrectly classified lesions (P = 0.0005). Uncertainty was identified in four of the five misclassified lesions. Quantitative histopathology provides a robust, novel method to distinguish among CP, IPMN, and PC with a quantitative measure of uncertainty. This may be useful when there is uncertainty in diagnosis.

Indexed as

Adenocarcinoma, MucinousAdultAgedAged, 80 and overCarcinoma, Pancreatic DuctalCarcinoma, PapillaryDiagnosis, DifferentialFemaleHumansMaleMiddle AgedPancreatic NeoplasmsIntraductal papillary mucinous neoplasmskaryometrynuclear chromatin patternpancreatic carcinomaquantitative histopathology

Identifiers

PMID27666740
PMCPMC5083737

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.