Grading the neuroendocrine tumors of the lung: an evidence-based proposal

Guido Rindi(Università Cattolica del Sacro Cuore), Catherine Klersy(Policlinico San Matteo Fondazione), Frediano Inzani(Università Cattolica del Sacro Cuore), Giovanni Fellegara(Centro Diagnostico Italiano), Luca Ampollini(University of Parma), Andrea Ardizzoni(University of Parma), Nicoletta Campanini(University of Parma), Paolo Carbognani(University of Parma), Tommaso Martino De Pas(European Institute of Oncology), Domenico Galetta(European Institute of Oncology), Pierluigi Granone(Università Cattolica del Sacro Cuore), Luisella Righi(University of Turin), Michele Rusca(University of Parma), Lorenzo Spaggiari(University of Milan), Marcello Tiseo(University of Parma), Giuseppe Viale(European Institute of Oncology), Marco Volante(University of Turin), Mauro Papotti(University of Turin), Giuseppe Pelosi(Fondazione IRCCS Istituto Nazionale dei Tumori)
Endocrine Related Cancer
December 17, 2013
Cited by 211Open Access
Full Text

Abstract

Lung neuroendocrine tumors are catalogued in four categories by the World Health Organization (WHO 2004) classification. Its reproducibility and prognostic efficacy was disputed. The WHO 2010 classification of digestive neuroendocrine neoplasms is based on Ki67 proliferation assessment and proved prognostically effective. This study aims at comparing these two classifications and at defining a prognostic grading system for lung neuroendocrine tumors. The study included 399 patients who underwent surgery and with at least 1 year follow-up between 1989 and 2011. Data on 21 variables were collected, and performance of grading systems and their components was compared by Cox regression and multivariable analyses. All statistical tests were two-sided. At Cox analysis, WHO 2004 stratified patients into three major groups with statistically significant survival difference (typical carcinoid vs atypical carcinoid (AC), P=0.021; AC vs large-cell/small-cell lung neuroendocrine carcinomas, P<0.001). Optimal discrimination in three groups was observed by Ki67% (Ki67% cutoffs: G1 <4, G2 4-<25, G3 ≥25; G1 vs G2, P=0.021; and G2 vs G3, P≤0.001), mitotic count (G1 ≤2, G2 >2-47, G3 >47; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001), and presence of necrosis (G1 absent, G2 <10% of sample, G3 >10% of sample; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001) at uni and multivariable analyses. The combination of these three variables resulted in a simple and effective grading system. A three-tiers grading system based on Ki67 index, mitotic count, and necrosis with cutoffs specifically generated for lung neuroendocrine tumors is prognostically effective and accurate.


Related Papers

No related papers found

Powered by citation graph analysis