Comorbidities in Mycosis Fungoides and Racial Differences in Co-Existent Lymphomatoid Papulosis: A Cross-Sectional Study of 580 Patients in an Urban Tertiary Care Center
Bibliographic record
Abstract
Background: Mycosis fungoides (MF) is a cutaneous T-cell lymphoma. Previous reports have suggested MF is associated with inflammatory conditions such as psoriasis, increased cardiovascular risk factors as well as secondary neoplasms. Methods: A cross-sectional study of MF patients seen from 2013 to 2019 was performed. Comorbidities were selected based on the 2015 Medicare report highlighting the most common chronic medical illnesses in the United States. Lifetime comorbidity occurrence in patients with MF were compared with that in patients with atopic dermatitis, psoriasis and patients without MF. Additional analyses were performed with patients sub-stratified by race. Results: Compared to control groups, MF was strongly associated with lymphomatoid papulosis and Hodgkin’s disease, but not significantly associated with lung, breast or colon cancer. Interestingly, the association with lymphomatoid papulosis was observed in Caucasians (CI 1062-4338; p < 0.001) and not African Americans (p = 0.9). Patients with MF had a greater association with congestive heart failure, hypertension (HT) and hyperlipidemia (HLD) compared with the general population. However, they were significantly less likely to have HT and HLD when compared with psoriasis patients (HT CI: 0.6–0.9; p < 0.001, and HLD CI: 0.05–0.07; p < 0.001). MF patients were also significantly less likely to have concomitant vitamin D deficiency compared with atopic dermatitis (AD) and psoriasis (p < 0.001). Conclusions: Our results suggest that the association of MF with lymphomatoid papulosis varies by race. Compared to the general population, hypertension and hyperlipidemia were positively associated with MF, however, these were significantly less likely on comparison to psoriasis. Unlike previously described, vitamin D deficiency was found to be significantly less in patients with MF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".