Second neoplasm in cutaneous T-cell lymphoma patients: a marker of worse prognosis?
Bibliographic record
Abstract
BACKGROUND: Epidemiologic studies have shown that cutaneous T-cell lymphoma (CTCL) patients have an increased risk of the development of a second neoplasm (SN). The aim of our study was to evaluate the risk of SN and to correlate any possible change in CTCL course after the diagnosis of a subsequent neoplasm.METHODS: A ten-year retrospective study was carried out in two centers (Bologna and Florence) all the patients who developed a SN six months at least after a CTCL were included. Two groups were selected: group 1 featuring patients who developed a SN and group 2 characterized by patients affected by MF age and sex-matched with group 1 (control group). Data concerning any stage change after SN, time between MF and SN onset, modified Severity Weighted Assessment Tool (mSWAT) score before and after SN, concerning Group 1 and after a median time of 36 months in Group 2 were analyzed.RESULTS: Thirteen patients were detected. Before SN onset, early MF patients were mainly present, while SN cases in advanced stage (ten patients) were observed. SN type predominant was lung cancer, along with prostate and pancreatic cancer, while isolated cases presenting with vulvar, colon, mammalian, prostate cancer along with Hodgkin’s Lymphoma. Mean mSWAT at MF diagnosis and after SN showed a significant difference (P value = 0.0037). After SN diagnosis, nine patients experienced an MF stage progression and ten patients died at follow-up.CONCLUSIONS: In all the instances, statistical analysis showed that mean mSWAT score before/after SN diagnosis had a significantly difference (P=0.0037) suggesting that patients with a SN may have a worse clinical outcome. By secreting immunosuppressive cytokines or recruiting immunosuppressive cells, a sort of mutual help between the two neoplasms may be prompted. Our data suggested that SN development in MF patients may be regarded as a worse prognostic marker.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".