title: Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review.
abstract: BACKGROUND
  Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated.
  
  
  RESULTS
  In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy.
  
  
  CONCLUSIONS
  Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.
authors.affiliation: Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan. furukawa@kuhp.kyoto-u.ac.jp.
authors.forename: Toshi A
authors.initials: TA
authors.lastname: Furukawa
authors.affiliation: Department of Neuropsychiatry Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
authors.forename: Tomofumi
authors.initials: T
authors.lastname: Miura
authors.affiliation: Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, 45110, Ioannina, Greece.
authors.forename: Anna
authors.initials: A
authors.lastname: Chaimani
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität München, Ismaningerstr. 22, 81675, Munich, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Leucht
authors.affiliation: Department of Psychiatry, University of Oxford, Warneford Lane, Headington, Oxford, OX3 7JX, UK.
authors.forename: Andrea
authors.initials: A
authors.lastname: Cipriani
authors.affiliation: Department of Data Science, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan.
authors.forename: Hisashi
authors.initials: H
authors.lastname: Noma
authors.affiliation: Department of Neuropsychiatry Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Mitsuyasu
authors.affiliation: Department of Neuropsychiatry Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
authors.forename: Shegenobu
authors.initials: S
authors.lastname: Kanba
authors.affiliation: Institute of Social and Preventive Medicine (ISPM) & Berner Institut für Hausarztmedizin (BIHAM), University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
authors.forename: Georgia
authors.initials: G
authors.lastname: Salanti
mesh_terms: D000465:Algorithms; D015982:Bias; D001714:Bipolar Disorder / Q000188:drug therapy*; D006801:Humans; D060046:Maintenance Chemotherapy / Q000379:methods*; D008962:Models, Theoretical; D012196:Review Literature as Topic
keywords: Enrichment design; GRADE; Network meta-analysis; Risk of bias; Study limitations