Folate Pathway Enzyme Gene Polymorphisms and the Efficacy and Toxicity of Methotrexate in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To determine the association between folate pathway gene polymorphisms and the effectiveness, toxicity, and drug survival of methotrexate (MTX) in psoriatic arthritis (PsA). METHODS: Data were obtained from a longitudinal cohort of PsA patients evaluated according to a standard protocol. Data on duration of drug therapy, dose, side effects, and reasons for discontinuation are systematically recorded. Patients treated with MTX after clinic admission who had > or = 3 swollen joints prior to initiating MTX therapy were selected for evaluation of effectiveness. Response to MTX treatment was assessed at 6 months. Data from all patients treated in the clinic with MTX were used in evaluation of toxicity and drug survival. The following single-nucleotide polymorphisms (SNP) were measured using the Sequenom platform: MTHFR 677C>T (rs1801133), MTHFR 1298A>C (rs1801131), DHFR -473T>C (rs1650697), DHFR 35289A>G (rs1232027), and RFC 80G>A (rs1051266). Fisher's exact test, logistic regression, and Cox proportional hazard analyses were used to determine association. RESULTS: Two hundred eighty-one patients were identified from the database. All patients were included in the analysis for side effects and drug survival, and 119 patients were included in the effectiveness analysis. The minor A allele of DHFR gene at +35289 was the only SNP demonstrating association with response to MTX therapy (OR 2.99, p = 0.02). Patients homozygous for the minor allele of MTHFR 677C/T (677TT) had more liver toxicity (Fisher exact test, p = 0.04). CONCLUSION: Polymorphisms of the DHFR gene may be associated with MTX efficacy. MTHFR 677TT may have a relationship with MTX-induced liver toxicity in PsA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".