The Relationship between COMT Genotype and the Clinical Effectiveness of Tolcapone, a COMT Inhibitor, in Patients with Parkinson's Disease
Bibliographic record
Abstract
Patients with Parkinson's Disease (PD) have a variable response to tolcapone, a catechol-O-methyltransferase (COMT) inhibitor. In addition, a subset of patients develop severe diarrhea as a side effect. Two codominant alleles for the COMT gene exist, coding for low and high activity, resulting in low-, medium-, and high-activity genotypes. This study investigates the relationship between this variation in genotype and clinical effects in patients with PD taking tolcapone. To investigate the relationship between COMT polymorphism and clinical response, 24 patients who completed tolcapone clinical trials provided blood samples for COMT genotype analysis. Change in levodopa dose and United Parkinson Disease Rating Scale (UPDRS) Part III (motor subscale) were analyzed at baseline, at 1-2 weeks, and 6 months after initiation of tolcapone. Genotype analysis was performed on seven patients who had diarrhea as a side effect. There was no significant correlation between genotype and improvement in UPDRS score (p = 0.29) according to a linear models approach that adjusted for the subject's severity of PD, tolcapone dose (either 100 or 200 mg three times daily) and initial differences in baseline scores. No significant difference was seen in change in daily levodopa intake and genotype. There was also no relation between diarrhea and COMT genotype. These results indicate that, in the treatment of Parkinson's disease, COMT genotype is not a major contributor to the clinical response to tolcapone.
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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) | 0.001 | 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) | 0.001 | 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".