ReviewJournal of personalized medicine2013
Effect model law: an approach for the implementation of personalized medicine.
Review in Journal of personalized medicine, 2013. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
- Comparing the Efficacy of Two Generations of EGFR-TKIs: An Integrated Drug-Disease Mechanistic Model Approach in EGFR-Mutated Lung Adenocarcinoma.Biomedicines · 2024Article
- In Silico Clinical Trials: Is It Possible?Methods in molecular biology (Clifton, N.J.) · 2024Article
- Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions.Nature communications · 2022Article
- Article
- From Clinical Trial Efficacy to Real-Life Effectiveness: Why Conventional Metrics do not Work.Drugs - real world outcomes · 2019Article
- Measuring the individual benefit of a medical or behavioral treatment using generalized linear mixed-effects models.Statistics in medicine · 2016Article
- Bridging Systems Medicine and Patient Needs.CPT: pharmacometrics & systems pharmacology · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The effect model law states that a natural relationship exists between the frequency (observation) or the probability (prediction) of a morbid event without any treatment and the frequency or probability of the same event with a treatment. This relationship is called the effect model. It applies to a single individual, individuals within a population, or groups. In the latter case, frequencies or probabilities are averages of the group. The relationship is specific to a therapy, a disease or an event, and a period of observation. If one single disease is expressed through several distinct events, a treatment will be characterized by as many effect models. Empirical evidence, simulations with models of diseases and therapies and virtual populations, as well as theoretical derivation support the existence of the law. The effect model could be estimated through statistical fitting or mathematical modelling. It enables the prediction of the (absolute) benefit of a treatment for a given patient. It thus constitutes the theoretical basis for the design of practical tools for personalized medicine.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.