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Record W3081670498 · doi:10.9778/cmajo.20200010

Pediatric drug data in Canadian drug monographs: a descriptive analysis

2020· article· en· W3081670498 on OpenAlexafffundvenueabout
Preeya Raja, Mark Duffett, Maryann Mazer‐Amirshahi, Ashaka Patel, Andréa Gilpin, Catherine Litalien, Anthony K.C. Chan, John van den Anker, Thierry Lacaze‐Masmonteil, Samira Samiee‐Zafarghandy

Bibliographic record

VenueCMAJ Open · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsMcMaster UniversityHamilton Health SciencesCentre Hospitalier Universitaire Sainte-JustineAlberta Children's HospitalMcMaster Children's Hospital
FundersHealth Canada
KeywordsMedicineDrugPharmacotherapyPediatricsDescriptive statisticsOff-label useSummary of Product CharacteristicsFamily medicinePharmacologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Optimal drug therapy in children relies on the availability of pediatric-specific information. We aimed to describe the current status of pediatric pharmacotherapy data in monographs of new drugs approved by Health Canada. METHODS: In this descriptive analysis, we reviewed the quality and quantity of monographs of new drugs approved by Health Canada between Jan. 1, 2007, and Dec. 31, 2016. We excluded drugs withdrawn from the Canadian market and drugs with primary indications irrelevant to pediatrics. We determined the percentage of included drug monographs that listed pediatric-specific information. RESULTS: During this study period, Health Canada approved 281 drugs, 270 of which met our inclusion criteria. Pediatric-specific information and indication were present in 127 (47.1%) and 75 (27.8%) of the drug monographs, respectively. Of all pediatric age groups, neonates had the lowest number of indications listed in the product monographs (7, 2.6%). Only 9 (60%) oral drugs indicated for children 6 years of age or younger were available in child-friendly, age-appropriate dosage forms. INTERPRETATION: Most of the new drugs approved by Health Canada do not contain pediatric or neonatal indications in their product monographs, and therefore, are used "off-label." Regulatory mechanisms are required to promote both neonatal and pediatric drug development and submission of available pediatric data by manufacturers to Health Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.169
GPT teacher head0.404
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2020
Admission routes4
Has abstractyes

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