Influence of Vitamin D and Its Analogues in Type-B Lymphomas
Bibliographic record
Abstract
Lymphomas represent a heterogeneous group of blood tumors, generally divided into non-Hodgkin lymphoma (NHL) (90% of all lymphomas) and Hodgkin lymphoma (HL). High-grade NHL can rapidly progress so that new strategies and potentially therapeutical options are needed. Recently, it was shown that Vitamin D (VitD) inhibits the growth of cancer cells, controls their invasion and metastasis, and strengthens the antitumor activity of various types of chemotherapeutic anticancer agents. Therefore, we reviewed the recent literature about the influence of VitD and its analogues (VDAs) on the treatment and the prognosis of B-cell lymphomas. As to the in vitro studies in different cell lines, VitD3 and VDAs enhanced the anti-proliferative efficacy of various chemotherapeutics and increased the expression of VitD receptor. In in vivo studies, blood levels of VitD were considered: higher values of plasma bioavailable VitD were correlated with better progression-free survival (PFS) and overall survival (OS), while an unfavorable PFS and OS were observed in VitD deficient groups. No clinical trial was made on the analogs, thus confirming the absence of in vivo positive role of these synthetic drugs. In conclusion, higher levels of circulating VitD are related to improved OS, reduced cancer-specific mortality, and better disease-free survival. VitD and analogs showed also positive effects in in vitro studies, while only VitD was able to improve clinical parameters. Furthermore, a complex approach with plant-based diet, adequate levels for motor exercise, and/or eventual VitD supplementation could be a valuable strategy to challenge lymphomas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".