ArticleNature communications2016
Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.
Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 47 papers, 2 of them syntheses that pooled it.
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
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 87 citations in OpenAlex.
- Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers.International journal of molecular sciences · 2023Pooled it
- Pooled it
- Exploring promising biomarkers based on pathogenic mechanisms in interstitial cystitis/bladder pain syndrome.Nature reviews. Urology · 2026Review
- Pathogenic Drivers of Difficult-to-Treat Rheumatoid Arthritis: Synovium and Beyond.International journal of molecular sciences · 2026Review
- Frontiers in Rheumatoid Arthritis: Emerging Research and Unmet Needs in Pharmacologic Management.Pharmaceuticals (Basel, Switzerland) · 2026Review
- From Multimorbidity to Network Medicine in Patients with Rheumatic Diseases.Rheumatology and therapy · 2025Review
- Carriers of HLA-DRB1*04:05 have a better clinical response to abatacept in rheumatoid arthritis.Scientific reports · 2023Article
- Machine learning identifies a profile of inadequate responder to methotrexate in rheumatoid arthritis.Rheumatology (Oxford, England) · 2023Article
- Developing better digital health measures of Parkinson's disease using free living data and a crowdsourced data analysis challenge.PLOS digital health · 2023Article
- Does persistence to methotrexate treatment in early rheumatoid arthritis have a familial component?Arthritis research & therapy · 2022Article
- Machine learning predicts response to TNF inhibitors in rheumatoid arthritis: results on the ESPOIR and ABIRISK cohorts.RMD open · 2022Article
- Integrating multimodal data through interpretable heterogeneous ensembles.bioRxiv : the preprint server for biology · 2022Article
- Integrating multimodal data through interpretable heterogeneous ensembles.Bioinformatics advances · 2022Article
- Multi-omics approach to precision medicine for immune-mediated diseases.Inflammation and regeneration · 2021Review
- Red meat intake is associated with early onset of rheumatoid arthritis: a cross-sectional study.Scientific reports · 2021Article
- Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines.Patterns (New York, N.Y.) · 2020Review
- Lower peripheral helper T cell levels in the synovium are associated with a better response to anti-TNF therapy in rheumatoid arthritis.Arthritis research & therapy · 2020Article
- Data Heterogeneity: The Enzyme to Catalyze Translational Bioinformatics?Journal of medical Internet research · 2020Article
- Predicting the treatment response of certolizumab for individual adult patients with rheumatoid arthritis: protocol for an individual participant data meta-analysis.Systematic reviews · 2020Article
- Tumor neoantigenicity assessment with CSiN score incorporates clonality and immunogenicity to predict immunotherapy outcomes.Science immunology · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
94 authors at 20 institutions in 12 countries.
Funding
Abstract
Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
Indexed as
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.