Constantine A. Gatsonis - US grants

DESCRIPTION: (Applicant's Description) This application responds to the need for a Data and Statistics Center operations for the Multi-Institutional Consortium for Clinical Evaluation of Magnetic Resonance Imaging in Breast Cancer, announced in RFA CA96-012. The proposed center will be based at the Center for Statistical Sciences, Brown University in Philadelphia, PA. Data collection and management will be carried out by the DMC of ACR. Data will be transferred at regular intervals to the Statistics Center at Brown where study monitoring and interim and final analyses will be performed. The key aspects of the operation of the Data and Statistics Center are described in the following specific aims: 1) To provide support and methodological leadership to Consortium investigators in the design, development and implementation of the new protocol; 2) To work with Consortium investigators in the design, development and implementation of data collection forms and procedures. To carry out appropriate pilot testing of protocol implementation and data collection procedures; 3) To carry out the data collection and to develop and maintain a primary study database at the Data Center. To implement an efficient and accurate mechanism for data transfer to the Statistics Center and to develop a database at the Statistics Center for purposes of study monitoring and data analysis; 4) To continually monitor and verify the quality of imaging studies and the compliance to the common protocol. To develop and implement a process for performing site audits and to generate timely audit reports; 5) To continually monitor and verify the quality of the data, including checks of accuracy, completeness and timeliness; 6) To address methodological issues arising in the design and analysis of this multi-center study; 7) To design and perform interim and final analyses of the data and to generate relevant reports; 8) To provide methodological leadership and support in summarizing and interpreting study findings and in the preparation of abstracts and manuscripts. This application for a Data and Statistics Center was planned and submitted in coordination with the application for Headquarters submitted by Dr. Mitchell Schnall, from the University of Pennsylvania.

This proposal responds to the need for Biostatistics and Data Management Center (BDMC) as described in RFA 97-020, "Co-operative Trials in Diagnostic Imaging". Pursuant to the RFA, this proposal is submitted in co-ordination with a proposal for Headquarters of the "American college of Radiology Oncologic Imaging network" (ACROIN). Should the grant be awarded, the proposed BDMC of ACROIN will be organized and operated jointly by the Center for Statistical Sciences, Brown University and the American college of Radiology. Data collection and management will be carried out at the Philadelphia facilities of the ACR. Study design, monitoring and data analysis will be preformed at brown. Key aspectes of the operation of BDMC will be the folloowing: (1) To provide support and methodological leadership to ACROIN investigators in the design, development and implementation of network studies. (2) To work with ACROOIN investiggators in the desgin, development and implementation of data collection forms and procedures and to carry out appropriate pilot testing of protocol implementation and data collection procedures. (3) To cary out the data collection in each ACROIN protocol and develop and maintain a primary study database at the Data Management Center in Philadelphia. To imlement an efficient and accurate mechanism for on-line access to the study database by the Biostatistics Center personnell for purposes of study, monotoring, and analysis. (4) to monitor and verify the quality of the data, including checks of accuracy, completness and timeliness. (5) To monitor and verify compliance to all aspects of the propocol and to desgin and implement rigourous quality control for imaging and other studies; to develop and implement a process for performing site audits and to generate timely audit reports. (6) To design and perform intermin and final analyses of the data, geerate relevant reports and co-author abstracts and manuscripts. (7) To address methodolocial issues arising in the design and analysis of ACROIN studies and to carry out research on statistical methodology for the evaluation of imaging in cancer diagnosis and management

[unreadable] DESCRIPTION (provided by applicant): This proposal responds to RFA CA-03-502I "Letter to American College of Radiology Imaging Network: Cooperative trials in diagnostic imaging" and addresses the needs of ACRIN's Biostatistics and Data Management Center (BDMC). This proposal is submitted in co-ordination with a proposal from the Headquarters of ACRIN. Should the funding be awarded, the BDMC of ACRIN will continue to be operated jointly by the Center for Statistical Sciences, Brown University and the American College of Radiology. The main responsibility for data collection and management is with the Philadelphia office of the ACR. The overall direction of the BDMC, as well as the main responsibility for study design, monitoring, and data analysis is with Brown. Key aspects of the BDMC operation will be the following: 1. To provide support and methodological leadership to ACRIN investigators in the design, development and implementation of network studies. 2. To work with ACRIN investigators in the design, development and implementation of data collection forms and procedures. To carry out appropriate pilot testing of protocol implementation and data collection procedures. 3. To carry out the data collection in each ACRIN protocol and to develop and maintain a primary study database at the Data Management Center in Philadelphia. To implement an efficient and accurate mechanism for on-line access to the study database by the Biostatistics Center personnel for purposes of study monitoring and analysis. 4. To continually monitor and verify the quality of the data, including checks of accuracy, completeness, and timeliness. To implement procedures for guaranteeing the integrity of the database. 5. To continually monitor and verify compliance to all aspects of the protocol and to design and implement rigorous quality control for imaging and other studies. To provide methodological expertise for the design and implementation of a process for performing site audits. 6. To design and perform interim and final analyses of the data and to generate relevant reports. To provide methodological leadership and support in summarizing and interpreting study findings and in preparing abstracts and manuscripts. 7. To address methodological issues arising in the design and analysis of ACRIN studies and to carry out research on statistical methodology for the evaluation of imaging in cancer diagnosis and management. [unreadable] [unreadable] PERFORMANCE SITES: [unreadable] Center for Statistical Sciences, Brown University, Providence, RI [unreadable] Rhode Island Hospital, Providence, RI [unreadable] American College of Radiology, Philadelphia, PA [unreadable] [unreadable] [unreadable]

This grant will provide support for the Statistics and Data Management Center (SDMC) of the ECOG- ACRIN Cancer Research Group. The SDMC is organized and operated jointly by the Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute (DFCI), the Department of Biostatistics at Brown University, the ECOG-ACRIN Medical Research Foundation (EAMRF), and the American College of Radiology (ACR), under the direction of the Group Statisticians. The primary responsibility for data collection and management belongs to the Data Management Center, consisting of EAMRF and ACR. The primary responsibility for study design, monitoring, and analysis, and for overseeing and coordinating SDMC operations, belongs to the Biostatistics Center, consisting of DFCI and Brown University. The primary contact site for grant administration is DFCI. ECOG-ACRIN is a multi-modality group conducting a wide range of studies, including definitive phase III trials of therapeutic interventions, earlier phase studies developing new therapies, studies focused on diagnosis and of advanced imaging methods, investigation of laboratory and imaging based biomarkers, and studies incorporating patient reported outcomes. The SDMC is responsible for all quantitative aspects of EA's activities. Our overall goals are to conduct clinical trials to the highest standards in statistical methods, data management, and regulatory compliance, while continually improving efficiency of all of our processes and systems to optimize the use of our limited resources. Areas of particular focus in this grant include studies incorporating tissue and imaging biomarkers to direct therapy, studies of immunotherapy, studies of de-intensification of therapy to reduce morbidity, studies investigating novel biomarkers, and studies investigating the relationship of biomarkers and therapy in populations defined by race, ethnicity, gender, and age.

PROJECT  SUMMARY  There  are  limited  formal  opportunities  for  biomedical  and  health  science  trainees  to  acquire  essential  data  science  skills.  Along  with  the  growth  in  biomedical  and  health  data,  there  will  be  a  need  for  researchers  to  develop  approaches  for  leveraging  them  to discover and validate hypotheses. The Training and Teaching for  Transforming  Big  Data  to  Knowledge  (T3BD2K)  Initiative  will  address  these  needs  by:  (1)  Developing  a  ten­week  short  course  to  teach  pragmatic  data  science  skills?  and  (2)  Coordinating  data  science  education  across  training  programs  in  Rhode  Island.  The  T3BD2K Initiative will directly impact all currently funded NIH  training  programs  and  be  developed  synergistically  with  the  Data  Science  Initiative  at  Brown  University.  A  significant  artifact  of  this  training  program  will  be  a  publicly  available  curriculum  and  associated  teaching  materials  aimed  at  biomedical  trainees  for  providing  pragmatic  training  in  biomedical  informatics  and  data  science  (e.g.,  biostatistics,  computer  science,  and applied mathematics), alongside fundamental principles of  team science, that could be utilized by students nationally. All course materials will be made available using a  Creative Commons CC­BY­4.0 license, and made available through publicly accessible systems (GitBooks and  GitHub).  Additionally,  all  lectures  will  be  video  captured,  with the goal of transitioning a traditional format mode  for  teaching  the  course  to  a  ?flipped?  classroom.  The  course  will  culminate  in  a  symposium that showcases  participants applications of data science in biomedical and health contexts, with project abstracts, posters, and  oral  presentations  being  made  available  through  a  publicly  accessible  data  repository  that  is  maintained  by  Brown  University  (the  Brown  Digital  Repository  [BDR]).  The  overall  success  of  the  T3BD2K Initiative will be  poised to transform pragmatic data science training and teaching in Rhode Island, with the potential to inform  biomedical  data  scientist  training  nationally.