Table 1.

LIFE-Moms Committees

Committee	Purpose
Steering	Designs the research study activities and establishes priorities; develops common protocols and manuals, questionnaires and other data recording forms; establishes and maintains quality control among awardees; reviews progress; monitors participant recruitment and retention; coordinates and standardizes data management; and collaborates on the publication of results. Major scientific decisions are determined by the Steering Committee.
Executive	Manages the day-to-day operations of the Consortium and recommends potential solutions and policies for consideration by the Steering Committee for discussion and vote.
Recruitment & Retention	Develops plans to track recruitment and retention across all clinical trials; regularly monitors recruitment and retention at individual centers; provides a mechanism to share the best practices and lessons learned about recruitment and retention strategies; and addresses study-specific recruitment and retentions issues.
Ancillary Studies	Develops a policy for submission and evaluation of ancillary proposals intended for securing external funding to collect or conduct additional assessments, using existing study data, and/or utilizing commonly-collected bio-specimens stored in the repository; and reviews and approves ancillary study proposals.
Publications & Presentations	Develops a policy for publications and presentations; reviews proposals, abstracts and manuscripts; and identifies opportunities for other Consortium-wide publications.
Safety	Develops definitions of safety-related exclusion criteria, adverse and serious adverse events, and safety alert values for participant assessments; and reviews all adverse and serious adverse events in aggregate on a regular basis.
Design, Data Quality and Analysis	Develops the template for the DSMB reports including data quality measures; defines the Consortium’s primary and secondary outcomes and the analysis plan; develops strategies to facilitate data sharing across trials; recommends approaches to primary data analysis common across the trials; develops standardized methods to handle missing and censored data; develops strategies for pooled data analyses and potential meta-analyses among trials; and responds to analytic issues raised by the DSMB.