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      Histological criteria for atypical pituitary adenomas – data from the German pituitary adenoma registry suggests modifications

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          Abstract

          Introduction

          The term atypical pituitary adenoma (APA) was revised in the 2004 World Health Organization (WHO) classification of pituitary tumors. However, two of the four parameters required for the diagnosis of APAs were formulated rather vaguely (i.e., “extensive” nuclear staining for p53; “elevated” mitotic index). Based on a case-control study using a representative cohort of typical pituitary adenomas and APAs selected from the German Pituitary Tumor Registry, we aimed to obtain reliable cut-off values for both p53 and the mitotic index. In addition, we analyzed the impact of all four individual parameters (invasiveness, Ki67-index, p53, mitotic index) on the selectivity for differentiating both adenoma subtypes.

          Methods

          Of the 308 patients included in the study, 98 were diagnosed as APAs (incidence 2.9 %) and 10 patients suffered from a pituitary carcinoma (incidence 0.2 %). As a control group, we selected 200 group matched patients with typical pituitary adenomas (TPAs). Cut-off values were attained using ROC analysis.

          Results

          We determined significant threshold values for p53 (≥2 %; AUC: 0.94) and the mitotic index (≥2 mitosis within 10 high power fields; AUC: 0.89). The most reliable individual marker for differentiating TPAs and APAs was a Ki-67-labeling index ≥ 4 % (AUC: 0.98). Using logistic regression analysis (LRA) we were able to show that all four criteria (Ki-67 ( p < 0.001); OR 5.2// p53 ( p < 0.001); OR 3.1// mitotic index ( p < 0.001); OR 2.1// invasiveness ( p < 0.001); OR 8.2)) were significant for the group of APAs. Furthermore, we describe the presence of nucleoli as a new favorable parameter for TPAs ( p = 0.008; OR: 0.4; CI95 %: 0.18; 0.77).

          Conclusions

          Here we present a proposed rectification of the current WHO classification of pituitary tumors describing an additional marker for TPA and specific threshold values for p53 and the mitotic index. This will greatly help in the reliable diagnosis of APAs and facilitate further studies to ascertain the prognostic relevance of this categorization.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40478-015-0229-8) contains supplementary material, which is available to authorized users.

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          Most cited references66

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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              Measuring the accuracy of diagnostic systems.

              J Swets (1988)
              Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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                Author and article information

                Contributors
                ++49-9131-85-26031 , rolf.buslei@uk-erlangen.de
                Journal
                Acta Neuropathol Commun
                Acta Neuropathol Commun
                Acta Neuropathologica Communications
                BioMed Central (London )
                2051-5960
                19 August 2015
                19 August 2015
                2015
                : 3
                : 50
                Affiliations
                [ ]Departments of Neuropathology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany
                [ ]ENDOC Center for Endocrine Tumors, Hamburg & University of Duisburg-Essen, Essen, Germany
                [ ]Departments of Neurosurgery, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
                [ ]Department of Neurosurgery, International Neuroscience Institute, Hannover, Germany
                [ ]Departments of Neurosurgery, University Clinic Hamburg-Eppendorf, Hamburg, Germany
                [ ]Department of Neuropathology, Klinikum Bremen Mitte, Bremen, Germany
                [ ]Department of Neurosurgery, Johannes Wesling Hospital Minden, Minden, Germany
                [ ]Department of Pathology, Ruhr University Bochum, Bochum, Germany
                [ ]Departments of Neuropathology, University Clinic Hamburg-Eppendorf, Hamburg, Germany
                Article
                229
                10.1186/s40478-015-0229-8
                4545559
                26285571
                628a97cc-0d98-489a-9e21-4265b681d64b
                © Miermeister et al. 2015

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 4 August 2015
                : 6 August 2015
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