Guido Rindi1, Catherine Klersy2, Luca Albarello3, Eric Baudin4, Antonio Bianchi5, Markus W Buchler6, Martyn Caplin7, Anne Couvelard8, Jérôme Cros8, Wouter W de Herder9, Gianfranco Delle Fave10, Claudio Doglioni3, Birgitte Federspiel11, Lars Fischer6, Giuseppe Fusai12, Francesca Gavazzi13, Carsten P Hansen14, Frediano Inzani15, Henning Jann16, Paul Komminoth17, Ulrich P Knigge14, Luca Landoni18, Stefano La Rosa19, Rita T Lawlor20, Tu V Luong21, Ilaria Marinoni22, F Panzuto10, Ulrich-Frank Pape16, Stefano Partelli23, Aurel Perren22, Maria Rinzivillo10, Corrado Rubini24, Philippe Ruszniewski25, Aldo Scarpa20, Anja Schmitt22, Giovanni Schinzari26, Jean-Yves Scoazec27, Fausto Sessa19, Enrico Solcia28, Paola Spaggiari29, Christos Toumpanakis6, Alessandro Vanoli28, Bertram Wiedenmann16, Giuseppe Zamboni30, Wouter T Zandee9, Alessandro Zerbi13, Massimo Falconi23. 1. Institute of Pathology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma-Università Cattolica del Sacro Cuore, Roma ENETS Center of Excellence, Rome, Italyguido.rindi@unicatt.it. 2. Service of Biometry and Clinical Epidemiology, Research Department, and IRCCS Fondazione Policlinico San Matteo, Pavia, Italy. 3. Pathology Unit, San Raffaele Scientific Institute, Milan, Italy. 4. Department of Oncology, Cancer Campus, Villejuif, France. 5. Department of Endocrinology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma-Università Cattolica del Sacro Cuore, Roma ENETS Center of Excellence, Rome, Italy. 6. Department of Surgery, University Hospital Heidelberg, Neu Heidelberg, Germany. 7. Neuroendocrine Tumour Unit, Centre for Gastroenterology, London, United Kingdom. 8. Department of Pathology, Hopital Beaujon, Paris ENETS Center of Excellence, Clichy, France. 9. Section Endocrinology, Department of Internal Medicine, Erasmus University Medical Center and and Erasmus MC Cancer Institute Rotterdam, Rotterdam ENETS Center of Excellence, Rotterdam, The Netherlands. 10. Digestive and Liver Disease Unit, Sant'Andrea University Hospital, Roma ENETS Center of Excellence, Rome, Italy. 11. Department of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen ENETS Center of Excellence, Copenhagen, Denmark. 12. Department of Surgery, University College, Royal Free Hospital, London ENETS Center of Excellence, London, United Kingdom. 13. Pancreatic Surgery, Humanitas Clinical and Research Center, Humanitas Milan ENETS Center of Excellence, Milan, Italy. 14. Department of Surgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen ENETS Center of Excellence, Copenhagen, Denmark. 15. Institute of Pathology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma-Università Cattolica del Sacro Cuore, Roma ENETS Center of Excellence, Rome, Italy. 16. Department of Hepatology and Gastroenterology, Charité, Campus Virchow Klinikum and Charite Mitte, University Medicine Berlin, Berlin ENETS Center of Excellence, Berlin, Germany. 17. Institute of Pathology, Stadtspital Triemli, Zurich, Switzerland. 18. Department of Surgery and Oncology, General and Pancreatic Surgery, The Pancreas Institute, Verona ENETS Center of Excellence, Verona, Italy. 19. Department of Pathology, Ospedale di Circolo, Università dell'Insubria, Varese, Italy. 20. Section of Pathology and ARC-Net Research Centre, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona ENETS Center of Excellence, Verona, Italy. 21. Department of Pathology, University College, Royal Free Hospital, London ENETS Center of Excellence, London, United Kingdom. 22. Institute of Pathology, University of Bern, Bern, Switzerland. 23. Pancreatic Surgery Unit, San Raffaele Scientific Institute, Milan, Italy. 24. Department of Pathology, Marche Polytechnic University, Ancona, Italy. 25. Department of Gastroenterology and Pancreatology, Hopital Beaujon, Paris ENETS Center of Excellence, Clichy, France. 26. Department of Medical Oncology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma-Università Cattolica del Sacro Cuore, Roma ENETS Center of Excellence, Rome, Italy. 27. Department of Medical Biology and Pathology, Cancer Campus, Villejuif, France. 28. Department of Molecular Medicine, University of Pavia, Pavia, Italy. 29. Pathology Department, Humanitas Clinical and Research Center, Humanitas Milan ENETS Center of Excellence, Milan, Italy. 30. Department of Pathology, Sacro Cuore-Don Calabria Hospital, Negrar, Italy.
Abstract
BACKGROUND: The World Health Organization (WHO) and the American Joint Cancer Committee (AJCC) modified the grading of pancreatic neuroendocrine neoplasms from a three-tier (WHO-AJCC 2010) to a four-tier 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: A total of 2,102 patients were enrolled; entry criteria were: (i) patient underwent surgery; (ii) at least 2 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: In descriptive analysis, the two grading systems demonstrated statistically significant differences for the major category sex but not for age groups. In 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. In 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 system 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 predicting patient survival.
BACKGROUND: The World Health Organization (WHO) and the American Joint Cancer Committee (AJCC) modified the grading of pancreatic neuroendocrine neoplasms from a three-tier (WHO-AJCC 2010) to a four-tier 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: A total of 2,102 patients were enrolled; entry criteria were: (i) patient underwent surgery; (ii) at least 2 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: In descriptive analysis, the two grading systems demonstrated statistically significant differences for the major category sex but not for age groups. In 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. In 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 system 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 predicting patient survival.
Authors: Amit Tirosh; Jonathan Keith Killian; David Petersen; Yuelin Jack Zhu; Robert L Walker; Jenny E Blau; Naris Nilubol; Dhaval Patel; Sunita K Agarwal; Lee Scott Weinstein; Paul Meltzer; Electron Kebebew Journal: J Clin Endocrinol Metab Date: 2020-10-01 Impact factor: 5.958