Mixed phenotype acute leukemia (MPAL) is a rare neoplasm which accounts for 2–5% of all leukemias and it is classified under heading of acute leukemia of ambiguous lineage in 2008 WHO classification. This patient was a 61-year-old man who presented with malaise and weakness. In physical examination there was cervical and axillary lymphadenopathy. Paraclinical evaluation revealed anemia (Hb = 10.3 g/dL, MCV = 108 fl). Histologic sections of the axillary lymph node revealed leukemic involvement with two discrete populations of cells in immunohistochemistry. One population was immunoreactive for MPO and the other showed immunostaining for CD3, CD99, and tdt. Differential count of bone marrow cells in marrow aspirate had 6% blast. Karyotype study on bone marrow culture depicted an interesting finding which was t(1;5)(q23;q33). An extensive search on literature was done for the same genetic change. A similar translocation has been mentioned in literature for other hematologic malignancies but not for same neoplasm; anyhow this translocation was an imbalanced one and led to der(5)t(1;5)(q12-25;q13-q35).

Combining the results of different binary diagnostic markers to reach maximum area under the receiver operating characteristic (ROC) curve is the aim of the present study. To this end, the Neyman-Pearson lemma is utilized to combine the results of several binary diagnostic markers to obtain an optimum decision rule. The applied procedure has two advantages: (1) no distributional assumptions are considered for diagnostic markers, and (2) the derived rules are optimal in the sense that their ROC curves are maximized at each point. As an application, eleven different subsets of six diagnostic markers of classical Hodgkin lymphoma (CD15, CD20, CD30, CD3, Pax-5 and LCA) are applied. Four best subsets are then selected based on the area under the ROC curve (AUC) and their optimal decision rules are derived at 0.05 error rate.