Single nucleotide polymorphisms in non-coding region of the glucocorticoid receptor gene and prednisone response in childhood acute lymphoblastic leukemia
Bibliographic record
Abstract
Poor prednisone response predicts an inferior outcome in pediatric acute lymphoblastic leukemia (ALL) in Berlin-Frankfurt-Münster (BFM) treatment protocols. Here, we investigated five single nucleotide polymorphisms (SNPs) in both the coding and non-coding regions of the glucocorticoid receptor (GR) gene, and analyzed their association with prednisone responsiveness in vivo in 63 pediatric patients with ALL in China. Of the five SNPs, the rs41423247 and rs7701443 polymorphisms were significantly associated with prednisone response at the allelic level (rs41423247 odds ratio [OR] = 9.58; 95% confidence interval [CI]: 1.23-74.21; p = 0.01; rs7701443 OR = 3.12; 95% CI: 1.08-9; p = 0.02). Two polymorphisms (rs6189/6190 and rs6198) were not observed in the study cohort. Haplotypes composed of CCC alleles and TCG alleles at three loci (rs7701443, Tth111I and BclI) were both associated with prednisone response (p = 0.013; p = 0.028). Our results suggested that polymorphisms in the non-coding region of the GR gene were associated with prednisone response in vivo in pediatric ALL in Han Chinese.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".