This is an application from the Center for Clinical Epidemiology and Biostatistics (CCEB) at the University of Pennsylvania, Perelman School of Medicine to continue to serve as the Data Coordinating Core (DCC) for the Multi-disciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network. This proposal brings together a highly experienced DCC team, currently supporting the NIDDK's MAPP Research Network (www.mappnetwork.org), including urology, neurology and pain measurement, and biostatistics co-investigators with extensive expertise in urologic chronic pelvic pain syndromes (UCPPS), pain measurement and longitudinal methods for multiple outcomes. The DCC will continue to provide biostatistical study design and analysis support, comprehensive data management and research computing services for ongoing and new protocols, selected Discovery Site projects, and close collaboration with the Tissue Analysis &Technology Core (TATC).
The specific aims of the DCC are to 1) conduct a Symptom Patterns Study across the MAPP Research Network;2) provide scientific leadership and coordination in the design and implementation of inter-disciplinary research projects across the MAPP Research Network;3) provide biostatistical expertise in research designs, outcome measures and analytical strategies for clinical and translational research investigations of UCPPS;4) provide comprehensive DCC administrative support for the MAPP Research Network, promoting effective communications, coordinating teleconferences, meetings, working groups, and document development and management;5) collaborate with the Tissue Analysis and Technology Core (TATC) on best practices for data collection, specimen tracking and storage, as well as to support technical processes between the DCC, TATC, and the NIDDK repository;6) promote network-wide quality assurance standards, practices and tools, including a comprehensive, secure www-based data management system (DMS) for collection and centralized storage of all multi-site study data;7) support the MAPP Research Network Ancillary Projects, assisting in their design, submission, review and implementation, as well as administration of MAPP network sub-contracts in support of selected goals. The DCC will continue to leverage their considerable biostatistical and scientific expertise, coordinating and project leadership, as well as urological and epidemiological expertise, to promote DCC best practices for the ongoing conduct of clinical and translational science research projects, and design and planning for MAPP Phase II protocols within the MAPP Research Network.

Public Health Relevance

To provide a foundational platform for MAPP-II studies, the MAPP Research Network is proposing a Symptom Patterns Study. Targeted analyses of MAPP-I data addressing the specified MAPP-I hypotheses are ongoing, in support of approved manuscript proposals. Furthermore, extensive analyses in support of designing the Symptom Patterns Study proposed for MAPP-II are underway, focusing on cluster analyses to discover prognostically important UCPPS subtypes that follow differential profiles of improving or worsening over time. Urological, non-urological, psychosocial, biomarker, pressure pain threshold, infectious etiology and neuroimaging domains are under investigation for their potential risk factors for differential longitudinal change.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
2U01DK082316-07
Application #
8775981
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Mullins, Christopher V
Project Start
2008-09-15
Project End
2019-06-30
Budget Start
2014-09-15
Budget End
2015-06-30
Support Year
7
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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Naliboff, Bruce D; Stephens, Alisa J; Lai, H Henry et al. (2017) Clinical and Psychosocial Predictors of Urological Chronic Pelvic Pain Symptom Change in 1 Year: A Prospective Study from the MAPP Research Network. J Urol 198:848-857
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