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Interobserver agreement of proliferation index (Ki-67) outperforms mitotic count in pulmonary carcinoids

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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.

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References

  1. Zahel T, Krysa S, Herpel E et al (2012) Phenotyping of pulmonary carcinoids and a Ki-67-based grading approach. Virchows Arch 460:299–308

    Article  PubMed  CAS  Google Scholar 

  2. Warth A, Krysa S, Zahel T et al (2010) S100 protein positive sustentacular cells in pulmonary carcinoids and thoracic paragangliomas: differential diagnostic and prognostic evaluation. Pathologe 31:379–384

    Article  PubMed  CAS  Google Scholar 

  3. Warth A, Herpel E, Krysa S et al (2009) Chromosomal instability is more frequent in metastasized than in non-metastasized pulmonary carcinoids but is not a reliable predictor of metastatic potential. Exp Mol Med 41:349–353

    Article  PubMed  CAS  Google Scholar 

  4. Rekhtman N (2010) Neuroendocrine tumors of the lung: an update. Arch Pathol Lab Med 134:1628–1638

    PubMed  Google Scholar 

  5. Warren WH, Gould VE, Faber LP et al (1985) Neuroendocrine neoplasms of the bronchopulmonary tract. A classification of the spectrum of carcinoid to small cell carcinoma and intervening variants. J Thorac Cardiovasc Surg 89:819–825

    PubMed  CAS  Google Scholar 

  6. Ducrocq X, Thomas P, Massard G et al (1998) Operative risk and prognostic factors of typical bronchial carcinoid tumors. Ann Thorac Surg 65:1410–1414

    Article  PubMed  CAS  Google Scholar 

  7. Fink G, Krelbaum T, Yellin A et al (2001) Pulmonary carcinoid: presentation, diagnosis, and outcome in 142 cases in Israel and review of 640 cases from the literature. Chest 119:1647–1651

    Article  PubMed  CAS  Google Scholar 

  8. Travis WD (2010) Advances in neuroendocrine lung tumors. Ann Oncol 21(Suppl 7):vii65–vii71

    Article  PubMed  Google Scholar 

  9. Hage R, de la Riviere AB, Seldenrijk CA et al (2003) Update in pulmonary carcinoid tumors: a review article. Ann Surg Oncol 10:697–704

    Article  PubMed  CAS  Google Scholar 

  10. Skov BG, Holm B, Erreboe A et al (2010) ERCC1 and Ki67 in small cell lung carcinoma and other neuroendocrine tumors of the lung: distribution and impact on survival. J Thorac Oncol 5:453–459

    Article  PubMed  Google Scholar 

  11. Rindi G, Falconi M, Klersy C et al (2012) TNM staging of neoplasms of the endocrine pancreas: results from a large international cohort study. J Natl Cancer Inst 104:764–777

    Article  PubMed  CAS  Google Scholar 

  12. Rindi G, Kloppel G, Alhman H et al (2006) TNM staging of foregut (neuro)endocrine tumors: a consensus proposal including a grading system. Virchows Arch 449:395–401

    Article  PubMed  CAS  Google Scholar 

  13. Santinelli A, Ranaldi R, Baccarini M et al (1999) Ploidy, proliferative activity, p53 and bcl-2 expression in bronchopulmonary carcinoids: relationship with prognosis. Pathol Res Pract 195:467–474

    Article  PubMed  CAS  Google Scholar 

  14. Bohm J, Koch S, Gais P et al (1996) Prognostic value of MIB-1 in neuroendocrine tumours of the lung. J Pathol 178:402–409

    Article  PubMed  CAS  Google Scholar 

  15. Granberg D, Wilander E, Oberg K et al (2000) Prognostic markers in patients with typical bronchial carcinoid tumors. J Clin Endocrinol Metab 85:3425–3430

    Article  PubMed  CAS  Google Scholar 

  16. Das-Neves-Pereira JC, Bagan P, Milanez-de-Campos JR, et al. (2008) Individual risk prediction of nodal and distant metastasis for patients with typical bronchial carcinoid tumors. Eur J Cardiothorac Surg 34:473–7; discussion 477–8

    Google Scholar 

  17. Grimaldi F, Muser D, Beltrami CA, et al. (2011) Partitioning of bronchopulmonary carcinoids in two different prognostic categories by ki-67 score. Front Endocrinol (Lausanne) 2:20

    Google Scholar 

  18. Walts AE, Ines D, Marchevsky AM (2012) Limited role of Ki-67 proliferative index in predicting overall short-term survival in patients with typical and atypical pulmonary carcinoid tumors. Mod Pathol 25:1258–1264

    Article  PubMed  Google Scholar 

  19. Hasegawa T, Yamamoto S, Nojima T et al (2002) Validity and reproducibility of histologic diagnosis and grading for adult soft-tissue sarcomas. Hum Pathol 33:111–115

    Article  PubMed  Google Scholar 

  20. Gunia S, Kakies C, Erbersdobler A et al (2012) Scoring the percentage of Ki67 positive nuclei is superior to mitotic count and the mitosis marker phosphohistone H3 (PHH3) in terms of differentiating flat lesions of the bladder mucosa. J Clin Pathol 65:715–720

    Article  PubMed  Google Scholar 

  21. Ladekarl M (1998) Objective malignancy grading: a review emphasizing unbiased stereology applied to breast tumors. APMIS Suppl 79:1–34

    PubMed  CAS  Google Scholar 

  22. Barry M, Sinha SK, Leader MB et al (2001) Poor agreement in recognition of abnormal mitoses: requirement for standardized and robust definitions. Histopathology 38:68–72

    Article  PubMed  CAS  Google Scholar 

  23. Coindre JM, Trojani M, Contesso G et al (1986) Reproducibility of a histopathologic grading system for adult soft tissue sarcoma. Cancer 58:306–309

    Article  PubMed  CAS  Google Scholar 

  24. Silverberg SG (1976) Reproducibility of the mitosis count in the histologic diagnosis of smooth muscle tumors of the uterus. Hum Pathol 7:451–454

    Article  PubMed  CAS  Google Scholar 

  25. Montironi R, Collan Y, Scarpelli M et al (1988) Reproducibility of mitotic counts and identification of mitotic figures in malignant glial tumors. Appl Pathol 6:258–265

    PubMed  CAS  Google Scholar 

  26. Gilles FH, Tavare CJ, Becker LE et al (2008) Pathologist interobserver variability of histologic features in childhood brain tumors: results from the CCG-945 study. Pediatr Dev Pathol 11:108–117

    Article  PubMed  Google Scholar 

  27. Svanholm H, Starklint H, Barlebo H et al (1990) Histological evaluation of prostatic cancer. (II): reproducibility of a histological grading system. APMIS 98:229–236

    Article  PubMed  CAS  Google Scholar 

  28. Tsuda H, Akiyama F, Kurosumi M et al (2000) Evaluation of the interobserver agreement in the number of mitotic figures of breast carcinoma as simulation of quality monitoring in the Japan National Surgical Adjuvant Study of Breast Cancer (NSAS-BC) protocol. Jpn J Cancer Res 91:451–457

    Article  PubMed  CAS  Google Scholar 

  29. van Diest PJ, Baak JP, Matze-Cok P et al (1992) Reproducibility of mitosis counting in 2,469 breast cancer specimens: results from the Multicenter Morphometric Mammary Carcinoma Project. Hum Pathol 23:603–607

    Article  PubMed  Google Scholar 

  30. Biesterfeld S (1997) Methodologic aspects of a standardized evaluation of mitotic activity in tumor tissues. Pathologe 18:439–444

    Article  PubMed  CAS  Google Scholar 

  31. Yadav KS, Gonuguntla S, Ealla KK et al (2012) Assessment of interobserver variability in mitotic figure counting in different histological grades of oral squamous cell carcinoma. J Contemp Dent Pract 13:339–344

    Article  PubMed  Google Scholar 

  32. Tapia C, Kutzner H, Mentzel T et al (2006) Two mitosis-specific antibodies, MPM-2 and phospho-histone H3 (Ser28), allow rapid and precise determination of mitotic activity. Am J Surg Pathol 30:83–89

    Article  PubMed  Google Scholar 

  33. Schimming TT, Grabellus F, Roner M et al (2012) pHH3 immunostaining improves interobserver agreement of mitotic index in thin melanomas. Am J Dermatopathol 34:266–269

    Article  PubMed  Google Scholar 

  34. Yamaguchi U, Hasegawa T, Sakurai S et al (2006) Interobserver variability in histologic recognition, interpretation of KIT immunostaining, and determining MIB-1 labeling indices in gastrointestinal stromal tumors and other spindle cell tumors of the gastrointestinal tract. Appl Immunohistochem Mol Morphol 14:46–51

    Article  PubMed  Google Scholar 

  35. Mengel M, von Wasielewski R, Wiese B et al (2002) Inter-laboratory and inter-observer reproducibility of immunohistochemical assessment of the Ki-67 labelling index in a large multi-centre trial. J Pathol 198:292–299

    Article  PubMed  Google Scholar 

  36. Hsu CY, Ho DM, Yang CF et al (2003) Interobserver reproducibility of MIB-1 labeling index in astrocytic tumors using different counting methods. Mod Pathol 16:951–957

    Article  PubMed  Google Scholar 

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Acknowledgments

Iver Petersen, Philipp A. Schnabel, Klaus Junker, Alicia Morresi-Hauf, and Florian Länger are acknowledged for their valuable discussions.

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Correspondence to Arne Warth.

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Supplementary Figure 1

Distribution of mitotic counts for all observers and all evaluated cases. (PPT 114 kb)

Supplementary Figure 2

Distribution of overall Ki-67 count for all observers and all evaluated cases. Automated evaluation is given as a reference on the right hand side of each case (red bar). (PPT 115 kb)

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Warth, A., Fink, L., Fisseler-Eckhoff, A. et al. Interobserver agreement of proliferation index (Ki-67) outperforms mitotic count in pulmonary carcinoids. Virchows Arch 462, 507–513 (2013). https://doi.org/10.1007/s00428-013-1408-2

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  • DOI: https://doi.org/10.1007/s00428-013-1408-2

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