Context: -Pituitary adenoma classification is complex, and diagnostic strategies vary greatly from laboratory to laboratory. No optimal diagnostic algorithm has been defined.
Objective: -To develop a panel of immunohistochemical (IHC) stains that provides the optimal combination of cost, accuracy, and ease of use.
Design: -We examined 136 pituitary adenomas with stains of steroidogenic factor 1 (SF-1), Pit-1, anterior pituitary hormones, cytokeratin CAM5.2, and α subunit of human chorionic gonadotropin. Immunohistochemical staining was scored using the Allred system. Adenomas were assigned to a gold standard class based on IHC results and available clinical and serologic information. Correlation and cluster analyses were used to develop an algorithm for parsimoniously classifying adenomas.
Results: -The algorithm entailed a 1- or 2-step process: (1) a screening step consisting of IHC stains for SF-1, Pit-1, and adrenocorticotropic hormone; and (2) when screening IHC pattern and clinical history were not clearly gonadotrophic (SF-1 positive only), corticotrophic (adrenocorticotropic hormone positive only), or IHC null cell (negative-screening IHC), we subsequently used IHC for prolactin, growth hormone, thyroid-stimulating hormone, and cytokeratin CAM5.2.
Conclusions: -Comparison between diagnoses generated by our algorithm and the gold standard diagnoses showed excellent agreement. When compared with a commonly used panel using 6 IHC for anterior pituitary hormones plus IHC for a low-molecular-weight cytokeratin in certain tumors, our algorithm uses approximately one-third fewer IHC stains and detects gonadotroph adenomas with greater sensitivity.