Literature DB >> 32051191

Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.

James V Lacey1, Nadia T Chung2, Paul Hughes3, Jennifer L Benbow2, Christine Duffy4, Kristen E Savage2, Emma S Spielfogel2, Sophia S Wang2, Maria Elena Martinez5, Sandeep Chandra3.   

Abstract

BACKGROUND: Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear.
METHODS: The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses.
RESULTS: Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles.
CONCLUSIONS: Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework. IMPACT: The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science." ©2020 American Association for Cancer Research.

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Year:  2020        PMID: 32051191      PMCID: PMC9005205          DOI: 10.1158/1055-9965.EPI-19-0842

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  12 in total

1.  High breast cancer incidence rates among California teachers: results from the California Teachers Study (United States).

Authors:  Leslie Bernstein; Mark Allen; Hoda Anton-Culver; Dennis Deapen; Pamela L Horn-Ross; David Peel; Richard Pinder; Peggy Reynolds; Jane Sullivan-Halley; Dee West; William Wright; Al Ziogas; Ronald K Ross
Journal:  Cancer Causes Control       Date:  2002-09       Impact factor: 2.506

Review 2.  Progress Toward Cancer Data Ecosystems.

Authors:  Robert L Grossman
Journal:  Cancer J       Date:  2018 May/Jun       Impact factor: 3.360

3.  Factors Associated with Increased Adoption of a Research Data Warehouse.

Authors:  Ahmad Baghal; Meredith Zozus; Amanda Baghal; Shaymaa Al-Shukri; Fred Prior
Journal:  Stud Health Technol Inform       Date:  2019

Review 4.  Clinical Data Warehouse: An Effective Tool to Create Intelligence in Disease Management.

Authors:  Mahtab Karami; Azin Rahimi; Ali Hosseini Shahmirzadi
Journal:  Health Care Manag (Frederick)       Date:  2017 Oct/Dec

5.  Transforming epidemiology for 21st century medicine and public health.

Authors:  Muin J Khoury; Tram Kim Lam; John P A Ioannidis; Patricia Hartge; Margaret R Spitz; Julie E Buring; Stephen J Chanock; Robert T Croyle; Katrina A Goddard; Geoffrey S Ginsburg; Zdenko Herceg; Robert A Hiatt; Robert N Hoover; David J Hunter; Barnet S Kramer; Michael S Lauer; Jeffrey A Meyerhardt; Olufunmilayo I Olopade; Julie R Palmer; Thomas A Sellers; Daniela Seminara; David F Ransohoff; Timothy R Rebbeck; Georgia Tourassi; Deborah M Winn; Ann Zauber; Sheri D Schully
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-03-05       Impact factor: 4.254

Review 6.  The National Cancer Institute Cohort Consortium: An International Pooling Collaboration of 58 Cohorts from 20 Countries.

Authors:  Anthony J Swerdlow; Chinonye E Harvey; Roger L Milne; Camille A Pottinger; Celine M Vachon; Lynne R Wilkens; Susan M Gapstur; Mattias Johansson; Elisabete Weiderpass; Deborah M Winn
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-07-17       Impact factor: 4.254

7.  Architecture and Implementation of a Clinical Research Data Warehouse for Prostate Cancer.

Authors:  Martin G Seneviratne; Tina Seto; Douglas W Blayney; James D Brooks; Tina Hernandez-Boussard
Journal:  EGEMS (Wash DC)       Date:  2018-06-01

8.  A late-binding, distributed, NoSQL warehouse for integrating patient data from clinical trials.

Authors:  Eric Yang; Jeremy D Scheff; Shih C Shen; Michael A Farnum; James Sefton; Victor S Lobanov; Dimitris K Agrafiotis
Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

Review 9.  Data Lakes, Clouds, and Commons: A Review of Platforms for Analyzing and Sharing Genomic Data.

Authors:  Robert L Grossman
Journal:  Trends Genet       Date:  2019-01-25       Impact factor: 11.639

Review 10.  Collaborating on Data, Science, and Infrastructure: The 20-Year Journey of the Cancer Research Network.

Authors:  Mark C Hornbrook; Martin L Brown; V Paul Doria-Rose; Robert T Greenlee; Diana S M Buist; Diana L Miglioretti; Douglas A Corley; Jeffrey S Brown; Heather A Clancy; Leah Tuzzio; Lisa M Moy; Debra P Ritzwoller; Lawrence H Kushi; Sarah M Greene
Journal:  EGEMS (Wash DC)       Date:  2019-03-29
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  2 in total

1.  Pre-Diagnosis Diet and Physical Activity and Risk of Cardiovascular Disease Mortality among Female Cancer Survivors.

Authors:  Daphne Weikart; Dan Lin; Radha Dhingra; Laila Al-Shaar; Kathleen Sturgeon
Journal:  Cancers (Basel)       Date:  2022-06-23       Impact factor: 6.575

2.  Body size and risk of non-Hodgkin lymphoma by subtype: A pooled analysis from six prospective cohorts in the United States.

Authors:  Lauren R Teras; Kimberly A Bertrand; Emily L Deubler; Chun R Chao; James V Lacey; Alpa V Patel; Bernard A Rosner; Yu-Hsiang Shu; Ke Wang; Charlie Zhong; Sophia S Wang; Brenda M Birmann
Journal:  Br J Haematol       Date:  2022-03-29       Impact factor: 8.615

  2 in total

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