Sensitivity and specificity of T-cell receptor PCR BIOMED-2 clonality analysis for the diagnosis of cutaneous T-cell lymphoma

• Published in: EJD. European journal of dermatology Vol. 30; no. 1; pp. 12 - 15
• Main Authors: Moczko, Anja, Dimitriou, Florentia, Kresbach, Hanna, Amarov, Boyko, Hoetzenecker, Wolfram, Pascolo, Steve, Anzengruber, Florian, Koch, Tabea, Duda, Agathe, Guenova, Emmanuella
• Format: Journal Article
• Language: English
• Published: Paris John Libbey Eurotext 01.01.2020
• Subjects: Aged; Algorithms; Biopsy; Dermatology; DNA - analysis; Female; Humans; Investigative Report; Lymphoma, T-Cell, Cutaneous - diagnosis; Lymphoma, T-Cell, Cutaneous - pathology; Male; Medicine; Medicine & Public Health; Middle Aged; Polymerase Chain Reaction; Receptors, Antigen, T-Cell - genetics; Retrospective Studies; Sensitivity and Specificity; Skin - pathology; Skin Neoplasms - diagnosis; Skin Neoplasms - pathology; T-cell receptor; BIOMED-2; clonality; cutaneous lymphoma
• ISSN: 1952-4013; 1952-4013
• DOI: 10.1684/ejd.2020.3698

Background Early and precise diagnosis of cutaneous T-cell lymphomas (CTCL) is challenging. Currently, polymerase chain reaction (PCR)-based clonality assessment of the T-cell receptor (TCR) is a helpful tool for this diagnosis. Objective In this retrospective study, we aimed to assess the sensitivity and specificity of this method for the diagnosis of CTCL. Materials and Methods Monoclonal rearrangement of the TCR was investigated retrospectively by PCR-based clonality assessment based on 292 DNA samples from skin biopsies of patients with a suspicion of CTCL. Algorithms were based on different ratios (three or five-fold difference) between the dominant PCR peak and the third highest PCR peak. Results A PCR peak five-fold higher than the third highest PCR peak demonstrated significantly greater specificity (83.7% versus 76.4%) but lower sensitivity (59.8% versus 68.6%) compared to a cut-off of three-fold higher. Conclusion Our results confirm the diagnostic value of TCR clonality analysis which may be used to define the ideal cut-off in order to optimize sensitivity and specificity.