Characteristics of Primary Cutaneous Lymphoma in Italy: A Tertiary Care, Single-Center Study
Bibliographic record
Abstract
Data on primary cutaneous lymphomas (PCLs) patients in the Italian population are limited, and, despite the existence of several treatment options, the management of those patients remains challenging. Our study aimed to investigate the clinical and therapeutic features of PCL patients in a referral center in Italy. We conducted a retrospective study on 100 consecutive PCL patients between January 2017 and December 2022. The mean (SD) age of our cohort was 70.33 (14.14) years. Cutaneous T-cell lymphomas (CTCLs) represented 65% of all cases; the majority were mycosis fungoides (42%), followed by cases of Sezary syndrome (10%) and primary cutaneous anaplastic large cell lymphoma (4%). Cutaneous B-cell lymphomas (CBCLs) accounted for 35 % of PCLs, with 15 cases of primary cutaneous follicle center lymphoma, 10 cases of primary cutaneous diffuse large B-cell lymphoma leg type, and 9 cases of marginal zone B-cell lymphoma. A higher frequency of pruritus (p = 0.008) and higher peripheral blood levels of beta-2 microglobulin (p ≤ 0.001) and lactate dehydrogenase (p = 0.025) were found in CTCLs compared to those of CBCLs. Considering all therapeutic lines performed, treatments were extremely heterogeneous and skin-directed therapies represented the most frequently used approach. Our study confirms the distribution of PCL subtypes formerly reported in the literature and highlights the utility of real-life data in treatments to improve the current management of PCL patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".