SynthesisBMJ open2014
Stratified medicine in European Medicines Agency licensing: a systematic review of predictive biomarkers.
Synthesis in BMJ open, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 19 citations in OpenAlex.
- Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: Statistical recommendations for conduct and planning.Statistics in medicine · 2020Article
- Blood-derived biomarkers correlate with clinical progression in Duchenne muscular dystrophy.Journal of neuromuscular diseases · 2020Article
- Biomarkers in cardiovascular disease: Statistical assessment and section on key novel heart failure biomarkers.Trends in cardiovascular medicine · 2017Review
- An in vitro diagnostic certified point of care single nucleotide test for IL28B polymorphisms.PloS one · 2017Article
- Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs.Genetics in medicine : official journal of the American College of Medical Genetics · 2015Article
- [Individualized, personalized and stratified medicine: a challenge for allergology in ENT?].HNO · 2015Article
- A novel cohort of cancer-testis biomarker genes revealed through meta-analysis of clinical data sets.Oncoscience · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesStratified medicine is often heralded as the future of clinical practice. Key part of stratified medicine is the use of predictive biomarkers, which identify patient subgroups most likely to benefit (or least likely to experience harm) from an intervention. We investigated how many and what predictive biomarkers are currently included in European Medicines Agency (EMA) licensing.
settingEMA licensing.
participantsIndications and contraindications of all drugs considered by the EMA and published in 883 European Public Assessment Reports and Pending Decisions. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected on: the type of the biomarker, whether it selected a subgroup of patients based on efficacy or toxicity, therapeutic area, marketing status, date of licensing decision, date of inclusion of the biomarker in the indication or contraindication and on orphan designation.
results49 biomarker-indication-drug (B-I-D) combinations were identified over 16 years, which included 37 biomarkers and 41 different drugs. All identified biomarkers were molecular. Six drugs (relating to 10 B-I-D combinations) had an orphan designation at the time of licensing. The identified B-I-D combinations were mainly used in cancer and HIV treatment, and also in hepatitis C and three other indications (cystic fibrosis, hyperlipoproteinaemia type I and methemoglobinaemia). In 45 B-I-D combinations, biomarkers were used as predictive of drug efficacy and in four of drug toxicity. It appeared that there was an increase in the number of B-I-D combinations introduced each year; however, the numbers were too small to identify any trends.
conclusionsGiven the large body of literature documenting research into potential predictive biomarkers and extensive investment into stratified medicine, we identified relatively few predictive biomarkers included in licensing. These were also limited to a small number of clinical areas. This might suggest a need for improvement in methods of translation from laboratory findings to clinical practice.
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