ArticleDrugs - real world outcomes2019
From Clinical Trial Efficacy to Real-Life Effectiveness: Why Conventional Metrics do not Work.
Article in Drugs - real world outcomes, 2019. 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.
- Relevance of improved reporting for non-pharmacological interventions in clinical trials: Bridging research to clinical practice.Brazilian journal of physical therapy · 2026Review
- Primary Technology-Enhanced Care for Hypertension Scaling Program: Trial-Based Economic Evaluation Examining Effectiveness and Cost-Effectiveness Using Real-World Data in Singapore.Journal of medical Internet research · 2025Article
- Real-life effectiveness of FLOT in resectable gastric cancer: existing challenges.Drugs in context · 2025Article
- Review
- Modeling the disruption of respiratory disease clinical trials by non-pharmaceutical COVID-19 interventions.Nature communications · 2022Article
- Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models?Frontiers in medical technology · 2022Article
- Article
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
backgroundRandomised, double-blind, clinical trial methodology minimises bias in the measurement of treatment efficacy. However, most phase III trials in non-orphan diseases do not include individuals from the population to whom efficacy findings will be applied in the real world. Thus, a translation process must be used to infer effectiveness for these populations. Current conventional translation processes are not formalised and do not have a clear theoretical or practical base. There is a growing need for accurate translation, both for public health considerations and for supporting the shift towards personalised medicine.
objectiveOur objective was to assess the results of translation of efficacy data to population efficacy from two simulated clinical trials for two drugs in three populations, using conventional methods.
methodsWe simulated three populations, two drugs with different efficacies and two trials with different sampling protocols.
resultsWith few exceptions, current translation methods do not result in accurate population effectiveness predictions. The reason for this failure is the non-linearity of the translation method. One of the consequences of this inaccuracy is that pharmacoeconomic and postmarketing surveillance studies based on direct use of clinical trial efficacy metrics are flawed.
conclusionThere is a clear need to develop and validate functional and relevant translation approaches for the translation of clinical trial efficacy to the real-world setting.
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.