Effect of Therapeutic Interventions on Health-related Quality of Life in Parkinson’s Disease
Bibliographic record
Abstract
Health-related quality of life (HRQoL) used to be considered a secondary parameter in clinical trials of Parkinson’s disease (PD) and in routine clinical practice, but is now increasingly recognised as an important measure of patient status. A number of studies have shown that the severity of PD is strongly associated with poor HRQoL scores and that measuring HRQoL domains provides a valuable assessment of overall patient status. Current guidelines from the Movement Disorder Society Task Force and the European Parkinson’s Disease Association recommend the use of HRQoL measures in the diagnosis and monitoring of patients. The European Medicines Agency PD Guidelines, however, do not yet recommend the use of such indirect endpoints in clinical trials. A series of phase III and post-marketing studies evaluating the selective monoamine oxidase type B inhibitor, rasagiline in PD, including between 404 and 1,176 patients, showed that treatment with rasagiline leads to significant improvements in HRQoL parameters such as the Parkinson’s Disease Quality of Life questionnaire (PDQUALIF), the 39-Item Parkinson’s Disease Questionnaire (PDQ-39), the PDQ-8 and other HRQoL-related parameters. Other clinical trials have shown significant improvements in parameters including: Short-Form-36, EuroQuol 5D, PDQUALIF, PDQ-39 and HRQoL-related parameters in PD patients treated with dopamine agonists, selegiline, tocopherol or levodopa/carbidopa/entacapone or levodopa/carbidopa combinations. Experience gained with these instruments is likely to increase the attention paid to HRQoL in PD assessment and could improve diagnosis and monitoring of PD and may ultimately improve patient outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".