Updated review on prognostic factors in mycosis fungoides and new skin lymphoma trials

Abstract

Background Ten-year survival rates in mycosis fungoides (MF) broadly varies, however, there is no standardized prognostic index available. This is presumably due to low prevalence, heterogeneity, and diagnostic challenges in MF. Recent studies have focused on identifying objective prognostic indices by using different parameters for survival determinants. The Cutaneous Lymphoma International Prognostic Index (CLIPI) and the Prospective Cutaneous Lymphoma International Prognostic Index (PROCLIPI) represent prototypical studies that identify prognostic factors, seeking to improve management and outcomes in early-stage MF. Detecting these factors and stratifying MF patients according to their disease progression risk may help to manage these patients more efficiently.

Aims Review the current literature to determine the risk factors determining prognosis in MF.

Methodology A Comprehensive literature search was performed using electronic online databases "PubMed" and "Google Scholar" using key words ‘prognostic factor’, ‘prognostic indicator’, ‘mycosis fungoides’, ‘Sezary syndrome’, ‘Skin Lymphoma’, ‘Cutaneous Lymphoma’. Articles published in English language were considered for the review.

Results The strongest prognostic factor in MF patients is the stage of the disease. T stage and the presence of extracutaneous disease are the most important factors for survival. Other factors that are associated with worse prognosis are male gender, age >60, presence of plaques, folliculotropism, eosinophilia and lymph node stage above N1/Nx. Elevated LDH was associated with later tumor stages and large cell phenotype at diagnosis had a better prognosis. KIR3DL2 was associated with malignant transformation.

Conclusion The PROCLIPI study has assessed risk factors collected in MF patients from different countries and across different ethnicities following a rigorous clinicopathologic process. The findings presented here illustrated that disease prognosis in early stages depends on many contributing factors. Detection and stratification of such factors may allow a personalized approach to management of these patients.