Predicting Prognosis of Early-Stage Mycosis Fungoides with Utilization of Machine Learning.

Mycosis fungoides (MF) is the most prevalent type of cutaneous T cell lymphomas. Studies on the prognosis of MF are limited, and no research exists on the potential of artificial intelligence to predict MF prognosis. This study aimed to compare the predictive capabilities of various machine learning (ML) algorithms in predicting progression, treatment response, and relapse and to assess their predictive power against that of the Cox proportional hazards (CPH) model in patients with early-stage MF.

Evaluation of demographic and clinical characteristics of 728 patients with mycosis fungoides and their relationship with systemic comorbidities: multicenter, registry-based (MF-TR) study from Türkiye.

Background: Mycosis fungoides (MF) is the most common cutaneous lymphoma with a chronic disease course. MF patients may also suffer from systemic comorbidities such as cardiovascular and metabolic diseases.

Methods: In this study, we aimed to evaluate the demographic and clinical features of MF patients registered in the MF-TR registry system and to examine the relationship of these features with systemic comorbidities.

A comprehensive study on aberrant CD20+ mycosis fungoides: clinical and prognostic insights.

Background: As the majority of T-cell lymphomas lack CD20 expression, cases of mycosis fungoides (MF) exhibiting aberrant CD20 expression are exceedingly uncommon.

Objectives: To comprehensively evaluate the clinical, histopathological and prognostic features of seven patients diagnosed with CD20+ MF.

Methods: This retrospective study involved seven cases of MF with aberrant CD20 expression.