Virchows Archiv, May, 2013, Vol.462(5), p.507(7)
Byline: Arne Warth (1), Ludger Fink (2), Annette Fisseler-Eckhoff (3), Danny Jonigk (4), Marius Keller (1), German Ott (5), Ralf J. Rieker (6), Peter Sinn (1), Stephan Soder (6), Alex Soltermann (7), Klaus Willenbrock (3), Wilko Weichert (1) Keywords: Pulmonary carcinoids; Proliferation; Prognosis; Mitosis; Interobserver agreement; Ki-67 Abstract: Evaluation of proliferative activity is a cornerstone in the classification of endocrine tumors in pulmonary carcinoids, the mitotic count delineates typical carcinoid (TC) from atypical carcinoid (AC). Data on the reproducibility of manual mitotic counting and other methods of proliferation index evaluation in this tumor entity are sparse. Nine experienced pulmonary pathologists evaluated 20 carcinoid tumors for mitotic count (hematoxylin and eosin) and Ki-67 index. In addition, Ki-67 index was automatically evaluated with a software-based algorithm. Results were compared with respect to correlation coefficients (CC) and kappa values for clinically relevant grouping algorithms. Evaluation of mitotic activity resulted in a low interobserver agreement with a median CC of 0.196 and a median kappa of 0.213 for the delineation of TC from AC. The median CC for hotspot (0.658) and overall (0.746) Ki-67 evaluation was considerably higher. However, kappa values for grouped comparisons of overall Ki-67 were only fair (median 0.323). The agreement of manual and automated Ki-67 evaluation was good (median CC 0.851, median kappa 0.805) and was further increased when more than one participant evaluated a given case. Ki-67 staining clearly outperforms mitotic count with respect to interobserver agreement in pulmonary carcinoids, with the latter having an unacceptable low performance status. Manual evaluation of Ki-67 is reliable, and consistency further increases with more than one evaluator per case. Although the prognostic value needs further validation, Ki-67 might perspectively be considered a helpful diagnostic parameter to optimize the separation of TC from AC. Author Affiliation: (1) Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 224, 69120, Heidelberg, Germany (2) Institute of Pathology and Cytology, Wetzlar, Germany (3) Institute of Pathology and Cytology, Horst-Schmidt Hospital, Wiesbaden, Germany (4) Institute for Pathology, University Hospital Hannover, Hannover, Germany (5) Department of Clinical Pathology, Robert-Bosch Hospital and Dr. Margarete Fischer-Bosch Institute for Clinical Pharmacology, Stuttgart, Germany (6) Institute for Pathology, University Hospital Erlangen-Nurnberg, Erlangen, Germany (7) Institute of Surgical Pathology, University Hospital Zurich, Zurich, Switzerland Article History: Registration Date: 27/03/2013 Received Date: 04/02/2013 Accepted Date: 26/03/2013 Online Date: 05/04/2013 Article note: Electronic supplementary material The online version of this article (doi: 10.1007/s00428-013-1408-2) contains supplementary material, which is available to authorized users.
Tumors ; Algorithms
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