Prolactin, a potential biomarker for chronic GVHD activity
Bibliographic record
Abstract
INTRODUCTION: The polypeptide prolactin (PRL) is a peptide hormone and a cytokine mostly secreted from the anterior pituitary gland. PRL is also synthesized in extra pituitary tissues including thymocytes and T lymphocytes. Considering the need for chronic GVHD (cGVHD) biomarkers, we explored the relationship between hyperprolactinemia and active cGVHD in a cohort of long-term post-alloHCT survivors. METHODS: Three-hundred sixteen adults underwent alloHCT between 2010 and 2016, survived more than 1 year and were included. All patients underwent a regular annual assessment that includes a hormone profile with serum PRL levels. RESULTS: Overall, 236 (74.7%) patients had cGVHD, and in 199 (63%), the grade was moderate or severe. Sixty-five (21%) recipients had active cGVHD at the time of the annual evaluation, and hyperprolactinemia was documented in 63 (19.9%) patients. Hyperprolactinemia correlated with cGVHD activity (Odds Ratio 6.9 (95% CI; 3.6-13.1); P < .001) in the multivariate analysis. In conclusion, patients with hyperprolactinemia were 6.4 times more likely to have active cGVHD in comparison with those patients with normal levels of PRL (P < .001). CONCLUSION: Prolactin may serve as a biomarker for cGVHD activity. Further studies are required to confirm these findings, and to explore if hyperprolactinemia has an impact on cGVHD severity and prognosis.
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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) | 0.000 | 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) | 0.000 | 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".