MétaCan
Menu
Back to cohort
Record W3211032874 · doi:10.1093/pch/pxab061.058

73 Off-label use and safety of drug use in vascular anomalies

2021· article· en· W3211032874 on OpenAlexaff
Laurence Gariépy‐Assal, Simon Marcoux, Jérôme Coulombe, Julie Powell, Sandrine Essouri, Catherine McCuaïg, Josée Dubois, Niina Kleiber

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsMedicineDrugAdverse effectDosingSclerotherapyOff-label useIntensive care medicineVascular malformationInternal medicinePharmacologySurgery

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Clinical Pharmacology and Toxicology Background Vascular anomalies (VA) represent a heterogeneous group of disorders associated with an abnormal development and proliferation of blood and/or lymphatic vessels displaying variable clinical presentations and severity. Infantile hemangiomas, venous, and lymphatic malformations, for example, are commonly encountered in children. Other, less frequent diagnostics include Klippel-Trenaunay syndrome and PIK-3CA-related overgrowth spectrum (PROS). Severe phenotypes can alter organ function and/or lead to pain and chronic functional impairment, and are associated with significant morbidity and mortality. Management includes surgical, interventional radiology, and pharmacologic modalities. Drugs are administered by systemic (e.g., oral, intravenous) or local (topical, intralesional) routes, or by sclerotherapy (endovascular or percutaneous venous, lymphatic, or arterial injection). Off-label drug use is common in pediatrics and in rare diseases, two characteristics applying to vascular anomalies (VA). Off-label use is associated with an increased risk of adverse drug reactions. Objectives To quantify off-label drug use in VA and assess its safety. Design/Methods A guidelines search was conducted to extract a list of drugs used in VA management. The labelling status and safety of each drug was assessed based on the product monograph, Micromedex, and the FDA data. A drug was considered to have significant safety concerns if a black box warning (the FDA’s most stringent warning dedicated to serious or life-threatening risks) or if a serious adverse drug reaction was reported in at least 1% of the patients (leading to hospitalization, congenital malformation, persistent or significant disability or incapacity, life-threatening condition, or death). Results Among 87 drugs, 13 were unlicensed and 73 off-label. Figure 1 describes the reason for considering the 73 drugs off-label. Among 74 licensed drugs, only the oral solution of propranolol hydrochloride (Hemangeol®) for the treatment of infantile hemangiomas (IH) is approved. 98.9% of the drugs are used off-label or unlicensed. Except infantile hemangioma, all other VA are exclusively treated with off-label drugs. Significant safety issues concerned 73% of the drugs and were more frequent among systemic than locally delivered drugs (Figure 2). Conclusion This first study determining the rate of off-label drug use in vascular anomalies shows that off-label drug use in VA is the rule and not the exception. Significant safety concerns are common. It is needed to carefully weigh risk and benefits for every patient when using systemic and local treatments carrying safety concerns. Patients and families should be openly informed and involved in the decision-making process.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.054
GPT teacher head0.345
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicPharmaceutical studies and practicesFrench-language works237,207