How well is the female population represented in clinical trials with infusion therapies for Parkinson's disease? A systematic review and metanalysis
Bibliographic record
Abstract
Abstract Background Parkinson's disease (PD) is a neurodegenerative disorder affecting both sexes, but differences exist between male and female in clinical manifestations, functional impact of symptoms and hormonal influences. Therefore, representativeness of females in PD trials indirectly determines the external validity of the clinical research in this field. Objective To estimate the representativeness of female in infusion therapy trials for advanced PD. Methods PubMed and EMBASE databases were searched (1980 to September 2023), along with congress abstracts, to identify controlled clinical trials and large non‐controlled studies on infusion therapies in PD enrolling >100 patients. Random‐effect meta‐analysis was conducted to estimate mean pooled prevalence of females included in the studies. Subgroup analyses were conducted accordingly to study design and intervention. Results We included 15 studies (six studies on levodopa‐carbidopa intestinal gel, six on subcutaneous levodopa, two on subcutaneous apomorphine, and one on levodopa‐carbidopa‐entacapone intestinal gel). Sex was not a randomisation stratification factor in any of these studies. Only one study explored differences in the outcome estimated according to sex. Overall, the proportion of female included was 38% (95% CI:33%–43%; I2 = 74%), without differences between studies assessing different type of interventions (p = 0.72) or between study design (p = 0.35). In two studies, females represented the majority of included patients. Conclusion Female with advanced PD are underrepresented in infusion therapy trials. Most trials have overlooked sex‐based biological differences that can impact clinical and functional outcomes, raising concerns about the generalizability of these findings to real‐world contexts.
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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 | 0.066 | 0.146 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.050 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".