The MATRICS consensus cognitive battery: what we know 6 years later.

Following a competitive application process sponsored by the National Institute of Mental Health (NIMH), the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative was launched. After 2 years of large consensus meetings, a five-site psychometric and validation study, complex intellectual property agreements, and an endorsement by NIMH and the U.S. Food andDrug Administration (FDA), theMATRICS Consensus Cognitive Battery (MCCB) was initially presented in a series of three articles in the Journal in 2008 (1–3). Since then, theMCCBhas been evaluated and scrutinized in away that few test assessment batteries have been. Over time its strengths and limitations have come into sharper focus, and we believe it is a good time to review what we know about the MCCB 6 years later. The MATRICS initiative was designed to address a particular issue—the FDA was previously unwilling to approve a drug for enhancing cognition in schizophrenia without consensus on domains, measurement, and study design (4, 5). The overarching goal of MATRICS was to construct a pathway for drug approval in this area. Identifying consensus cognitive domains and developing a consensus battery were part of the broader MATRICS agenda that included agreement on study design, subject selection, neuropharmacological targets, and government-industry interactions. Though itwas only one component of a much larger initiative, the MCCB was the most concrete deliverable. The components of the MCCB were selected through both consensus and data collection methods (1, 6). The first step was to agree on cognitive domains that should be represented in schizophrenia treatment trials (7) and then to select tests at the domain level on the basis of a priori criteria. It was hoped that the MCCB would behave well in clinical trials, but that was an educated guess at the time. In this commentary we will summarize recent results regarding the test qualities of the MCCB when used in multisite clinical trials, its sensitivity to treatment effects, and its covariation with biomarkers.