Levodopa/carbidopa/entacapone versus levodopa/dopa-decarboxyiase inhibitor for the treatment of Parkinson's disease: systematic review, meta-analysis, and economic evaluation
Bibliographic record
Abstract
Zhan-Miao Yi,1–3 Ting-Ting Qiu,1,4 Yuan Zhang,5 Na Liu,6 Suo-Di Zhai1,3 1Department of Pharmacy, Peking University Third Hospital, 2Department of Pharmacy Administration and Clinical Pharmacy, Peking University School of Pharmaceutical Science, 3Institute for Drug Evaluation, Peking University Health Science Center, Beijing, China; 4Public Health Department, Aix-Marseille University, Marseille, France; 5Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; 6Department of Neurology, Peking University Third Hospital, Beijing, China Aims: To review the evidence for efficacy, safety, and cost-effectiveness of levodopa/carbidopa/entacapone (LCE) compared with levodopa/dopa-decarboxyiase inhibitor (DDCI) for Parkinson’s disease (PD).Methods: PubMed, Embase, the Cochrane Library, and Chinese databases WangFang Data, Chinese Sci-tech Journals Database and China National Knowledge Infrastructure, as well as ClinicalTrials.gov, were searched for randomized controlled trials with “levodopa/carbidopa/entacapone” as keywords. The search period was from inception to August 2017. We conducted meta-analyses to synthesize the evidence quantitatively.Results: A total of 5,693 records were obtained. We included seven randomized controlled trials and one cost-effectiveness study after the screening process. Compared with levodopa–DDCI, LCE improved patient Unified Parkinson’s Disease Rating Scale (UPDRS) II score (mean difference [MD] -1.17, 95% CI -1.64 to -0.71), UPDRS III score (MD -1.55, 95% CI -2.29 to -0.81), and Schwab and England daily activity rating (MD 2.05, 95% CI 0.85–3.26). There was no statistically significant difference in the risk of serious adverse events (AEs) or discontinuation due to AEs in patients with LCE, and the risk of total AEs was higher in the LCE group (risk ratio [RR] 1.33, 95% CI 1.05–1.70). The incremental cost-effectiveness ratio of LCE was £3,105 per quality-adjusted life-year (QALY) gained in the UK.Conclusion: LCE can improve PD patients’ motor symptoms and daily living functioning when compared with levodopa/DDCI. Keywords: Unified Parkinson’s Disease Rating Scale, quality of life, wearing off, adverse events, cost-effectiveness, health technology assessment
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.023 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".