BACKGROUND: The diagnosis of mycosis fungoides (MF) is notoriously difficult to establish because in the early stages, histological features may be nonspecific or merely suggestive. OBJECTIVES: To standardize the diagnosis of MF. METHODS: We studied 138 patients with suspected MF referred over a 7-year period to a university department of a dermatology-based cutaneous lymphoma clinic. Six diagnostic criteria were evaluated: clinical morphology, clinical distribution, skin biopsy T-cell receptor gene rearrangement (TCR-GR), skin biopsy pan T-cell marker loss > or = 2, skin biopsy CD4/CD8 ratio > or = 6, and skin biopsy diffuse epidermal HLA-DR expression. These six clinical and laboratory criteria were compared by logistic regression analysis in patients with histologically diagnosed MF and those with benign disease. RESULTS: Of the 138 patients, 74 had histology of MF, 47 of benign dermatoses and 17 were indeterminate. Close associations were found between a histological diagnosis of MF and TCR-GR (odds ratio 14.4), classical morphology (7.5), classical distribution (2.5) and diffuse epidermal HLA-DR expression (2.8). Logistic regression models were developed depending on the availability of data (either TCR-GR or HLA-DR). Probabilities for correctly diagnosing MF compared with histology as the 'gold standard' were derived from these logistic regression models. A scoring system assigning point values based on these probabilities was then created in order to assist the clinician in making the diagnosis. If using TCR-GR data, a positive TCR-GR = 2.5 points, the presence of classical morphology = 2.0 points, and the presence of classical distribution = 1.5 points. A total score of > or = 3.5 points assigns a high probability (> 85%) of having MF. If using HLA-DR expression, then the presence of classical morphology = 2.5 points, a positive diffuse epidermal HLA-DR expression = 2.0 points, and the presence of classical distribution = 1.5 points. In this case, a total score of > or = 4.0 points assigns a high probability (> 85%) of MF. CONCLUSIONS: The logistic regression models and scoring systems integrate clinical and laboratory assessments, allow rapid probability estimation, and provide a threshold for the diagnosis of MF in an objective, standardized manner.
BACKGROUND: The diagnosis of mycosis fungoides (MF) is notoriously difficult to establish because in the early stages, histological features may be nonspecific or merely suggestive. OBJECTIVES: To standardize the diagnosis of MF. METHODS: We studied 138 patients with suspected MF referred over a 7-year period to a university department of a dermatology-based cutaneous lymphoma clinic. Six diagnostic criteria were evaluated: clinical morphology, clinical distribution, skin biopsy T-cell receptor gene rearrangement (TCR-GR), skin biopsy pan T-cell marker loss > or = 2, skin biopsy CD4/CD8 ratio > or = 6, and skin biopsy diffuse epidermal HLA-DR expression. These six clinical and laboratory criteria were compared by logistic regression analysis in patients with histologically diagnosed MF and those with benign disease. RESULTS: Of the 138 patients, 74 had histology of MF, 47 of benign dermatoses and 17 were indeterminate. Close associations were found between a histological diagnosis of MF and TCR-GR (odds ratio 14.4), classical morphology (7.5), classical distribution (2.5) and diffuse epidermal HLA-DR expression (2.8). Logistic regression models were developed depending on the availability of data (either TCR-GR or HLA-DR). Probabilities for correctly diagnosing MF compared with histology as the 'gold standard' were derived from these logistic regression models. A scoring system assigning point values based on these probabilities was then created in order to assist the clinician in making the diagnosis. If using TCR-GR data, a positive TCR-GR = 2.5 points, the presence of classical morphology = 2.0 points, and the presence of classical distribution = 1.5 points. A total score of > or = 3.5 points assigns a high probability (> 85%) of having MF. If using HLA-DR expression, then the presence of classical morphology = 2.5 points, a positive diffuse epidermal HLA-DR expression = 2.0 points, and the presence of classical distribution = 1.5 points. In this case, a total score of > or = 4.0 points assigns a high probability (> 85%) of MF. CONCLUSIONS: The logistic regression models and scoring systems integrate clinical and laboratory assessments, allow rapid probability estimation, and provide a threshold for the diagnosis of MF in an objective, standardized manner.