Comparing drug effectiveness in children: A systematic review
Bibliographic record
Abstract
PURPOSE: The purpose of the study is to assess the current state of the art in pediatric comparative effectiveness research, potential gaps, and areas for improvement. METHODS: Relevant articles from inception to February 2015 were retrieved from Embase and Medline. We sequentially screened titles, abstracts, and full texts, with independent validation. Data regarding general information and study methods including statistical analysis were extracted. Study quality was assessed using Newcastle-Ottawa Scale (NOS). Investigated drugs were ranked and compared with data on the prevalence of pediatric drug use. RESULTS: Three thousand nine hundred twenty-six abstracts were screened for eligibility and inclusion, and 164 articles were included in the review. Most studies were from North America (46.7%). Only 78 studies (47.6%) reported the design: 90.8% were cohort studies. Neonates were least frequently investigated. The drugs that were most often studied included systemic antibacterials (11.4%), psycholeptics (7.9%), and antiepileptics (7.6%). Adjustment for confounding was made using propensity scores in 8.5% of the studies. Studies that did not report the design were of lower quality. Many effectiveness studies were done on antineoplastic agents, which are not frequently used and few studies on analgesics and drugs for obstructive airway diseases which are frequently prescribed. CONCLUSIONS: There is ample opportunity to improve comparative effectiveness research for drugs used in pediatrics. Routinely prescribed drugs were seldom investigated. Modern methods for confounding adjustment, such as propensity scores, were rarely used.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".