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  3. COMPETITIVE TESTING THE WHO 2010 VS THE WHO 2017 GRADING OF PANCREAS NEUROENDOCRINE NEOPLASIA: DATA FROM A LARGE INTERNATIONAL COHORT STUDY.
 

COMPETITIVE TESTING THE WHO 2010 VS THE WHO 2017 GRADING OF PANCREAS NEUROENDOCRINE NEOPLASIA: DATA FROM A LARGE INTERNATIONAL COHORT STUDY.

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BORIS DOI
10.48350/120582
Publisher DOI
10.1159/000494355
PubMed ID
30300897
Description
<br>Background: the World Health Organization (WHO) and the American Joint Cancer Committee (AJCC) modified the grading of pancreatic neuroendocrine neoplasms from a three-tiers (WHO-AJCC 2010) to a four-tiers system by introducing the novel category of NET G3 (WHO-AJCC 2017).

OBJECTIVES

This study aims at validating the WHO-AJCC 2017 and identifying the most effective grading system.

METHOD

2102 patients were enrolled; entry criteria were i) performed surgery; ii) at least two years of follow-up; iii) observation time up to 2015. Data from 34 variables were collected; grading was assessed and compared for efficacy by statistical means including Kaplan Meier method, Cox regression analysis, Harrell's C statistics and Royston's explained variation in univariable and multivariable analyses.

RESULTS

At descriptive analysis, the two grading systems demonstrated statistically significant differences for the major category sex but not for age groups. At Cox regression analysis, both grading systems showed statistically significant differences between grades for OS and EFS, however no statistically significant difference was observed between the two G3 classes of WHO-AJCC 2017. At multivariable analysis for the two models fitted to compare efficacy, the two grading systems performed equally well with substantially similar optimal discrimination and well-explained variation for both OS and EFS. The WHO-AJCC 2017 grading system retained statistically significant difference between the two G3 classes for OS but not for EFS.

CONCLUSIONS

the WHO-AJCC 2017 grading is at least equally performing as the WHO-AJCC 2010 but allows the successful identification of the most aggressive PanNET subgroup. Grading is confirmed as probably the most powerful tool for patient survival prediction. <br>.
Date of Publication
2018-10-09
Publication Type
Article
Subject(s)
500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
Language(s)
en
Contributor(s)
Rindi, Guido
Klersy, Catherine
Albarello, Luca
Baudin, Eric
Bianchi, Antonio
Büchler, Markus W
Caplin, Martyn
Couvelard, Anne
Cros, Jérôme
de Herder, Wouter W
Delle Fave, Gianfranco
Doglioni, Claudio
Federspiel, Birgitte
Fischer, Lars
Fusai, Giuseppe
Gavazzi, Francesca
Hansen, Carsten
Inzani, Frediano
Jann, Henning
Komminoth, Paul
Knigge, Ulrich
Landoni, Luca
La Rosa, Stefano
Lawlor, Rita
Luong, Tu
Marinoni, Ilaria
Institut für Pathologie
Panzuto, F
Pape, Ulrich-Frank
Partelli, Stefano
Perren, Aurelorcid-logo
Institut für Pathologie
Rinzivillo, Maria
Rubini, Corrado
Ruszniewski, Philippe
Scarpa, Aldo
Schmitt Kurrer, Anja
Institut für Pathologie
Schinzari, Giovanni
Scoazec, Jean-Yves
Sessa, Fausto
Solcia, Enrico
Spaggiari, Paola
Toumpanakis, Christos
Vanoli, Alessandro
Wiedenmann, Bertram
Zamboni, Giuseppe
Zandee, Wouter
Zerbi, Alessandro
Falconi, Massimo
Additional Credits
Institut für Pathologie
Series
Neuroendocrinology
Publisher
Karger
ISSN
0028-3835
Access(Rights)
restricted
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