ArticleBiometrical journal. Biometrische Zeitschrift2020
Extensions of the probabilistic ranking metrics of competing treatments in network meta-analysis to reflect clinically important relative differences on many outcomes.
Article in Biometrical journal. Biometrische Zeitschrift, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Comparative Effects of Various Delivery Methods of Cognitive Behavioral Therapy for Insomnia Among Patients With Cancers: Systematic Review and Network Meta-Analysis.Psycho-oncology · 2026Pooled it
- Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria.Research synthesis methods · 2026Article
- One cutoff is not enough: Assessing different area deprivation index cutoffs for insurance types on surgical Desirability of Outcome Ranking (DOOR).Healthcare (Amsterdam, Netherlands) · 2025Article
- Treatment recommendations based on network meta-analysis: Rules for risk-averse decision-makers.Research synthesis methods · 2025Article
- Ranking of treatments in network meta-analysis: incorporating minimally important differences.BMC medical research methodology · 2025Article
- Article
- Non-parametric Bayesian approach to multiple treatment comparisons in network meta-analysis with application to comparisons of anti-depressants.Journal of the Royal Statistical Society. Series C, Applied statistics · 2024Article
- A comparison of alternative ranking methods in two-stage clinical trials with multiple interventions: An application to the anxiolysis for laceration repair in children trial.Clinical trials (London, England) · 2024Article
- Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis.Systematic reviews · 2023Article
- The complexity underlying treatment rankings: how to use them and what to look at.BMJ evidence-based medicine · 2023Article
- PALM: PATIENT-CENTERED TREATMENT RANKING VIA LARGE-SCALE MULTIVARIATE NETWORK META-ANALYSIS.The annals of applied statistics · 2023Article
- Letter to the Editor Regarding Long-Term Benefit-Risk Profiles of Treatments for Moderate-to-Severe Plaque Psoriasis: A Network Meta-analysis.Dermatology and therapy · 2022Article
- A Response to: Letter to the Editor Regarding Long-Term Benefit-Risk Profiles of Treatments for Moderate-to-Severe Plaque Psoriasis: A Network Meta-analysis.Dermatology and therapy · 2022Article
- Evidence-based Shared-Decision-Making Assistant (SDM-assistant) for choosing antipsychotics: protocol of a cluster-randomized trial in hospitalized patients with schizophrenia.BMC psychiatry · 2022Article
- Network Meta-Analysis Techniques for Synthesizing Prevention Science Evidence.Prevention science : the official journal of the Society for Prevention Research · 2022Review
- Introducing the Treatment Hierarchy Question in Network Meta-Analysis.American journal of epidemiology · 2022Article
- Answering complex hierarchy questions in network meta-analysis.BMC medical research methodology · 2022Article
- Strategies for post-cardiac surgery acute kidney injury prevention: A network meta-analysis of randomized controlled trials.Frontiers in cardiovascular medicine · 2022Article
- Spie charts for quantifying treatment effectiveness and safety in multiple outcome network meta-analysis: a proof-of-concept study.BMC medical research methodology · 2020Article
- Extensions of the probabilistic ranking metrics of competing treatments in network meta-analysis to reflect clinically important relative differences on many outcomes.Biometrical journal. Biometrische Zeitschrift · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the key features of network meta-analysis is ranking of interventions according to outcomes of interest. Ranking metrics are prone to misinterpretation because of two limitations associated with the current ranking methods. First, differences in relative treatment effects might not be clinically important and this is not reflected in the ranking metrics. Second, there are no established methods to include several health outcomes in the ranking assessments. To address these two issues, we extended the P-score method to allow for multiple outcomes and modified it to measure the mean extent of certainty that a treatment is better than the competing treatments by a certain amount, for example, the minimum clinical important difference. We suggest to present the tradeoff between beneficial and harmful outcomes allowing stakeholders to consider how much adverse effect they are willing to tolerate for specific gains in efficacy. We used a published network of 212 trials comparing 15 antipsychotics and placebo using a random effects network meta-analysis model, focusing on three outcomes; reduction in symptoms of schizophrenia in a standardized scale, all-cause discontinuation, and weight gain.
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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.