Literature DB >> 23017633

A framework for understanding cancer comparative effectiveness research data needs.

William R Carpenter1, Anne-Marie Meyer, Amy P Abernethy, Til Stürmer, Michael R Kosorok.   

Abstract

OBJECTIVES: Randomized controlled trials remain the gold standard for evaluating cancer intervention efficacy. Randomized trials are not always feasible, practical, or timely and often don't adequately reflect patient heterogeneity and real-world clinical practice. Comparative effectiveness research can leverage secondary data to help fill knowledge gaps randomized trials leave unaddressed; however, comparative effectiveness research also faces shortcomings. The goal of this project was to develop a new model and inform an evolving framework articulating cancer comparative effectiveness research data needs. STUDY DESIGN AND
SETTING: We examined prevalent models and conducted semi-structured discussions with 76 clinicians and comparative effectiveness research researchers affiliated with the Agency for Healthcare Research and Quality's cancer comparative effectiveness research programs.
RESULTS: A new model was iteratively developed and presents cancer comparative effectiveness research and important measures in a patient-centered, longitudinal chronic care model better reflecting contemporary cancer care in the context of the cancer care continuum, rather than a single-episode, acute-care perspective.
CONCLUSION: Immediately relevant for federally funded comparative effectiveness research programs, the model informs an evolving framework articulating cancer comparative effectiveness research data needs, including evolutionary enhancements to registries and epidemiologic research data systems. We discuss elements of contemporary clinical practice, methodology improvements, and related needs affecting comparative effectiveness research's ability to yield findings clinicians, policy makers, and stakeholders can confidently act on.
Copyright © 2012 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 23017633      PMCID: PMC3461183          DOI: 10.1016/j.jclinepi.2012.06.005

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  60 in total

1.  Defining comparative effectiveness research: the importance of getting it right.

Authors:  Harold C Sox
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2.  Using medicare data for comparative effectiveness research: opportunities and challenges.

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3.  Comparative effectiveness research and patients with multiple chronic conditions.

Authors:  Mary E Tinetti; Stephanie A Studenski
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4.  Supporting clinical practice decisions with real-time patient-reported outcomes.

Authors:  Ethan Basch; Amy P Abernethy
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Review 5.  Informatics in action: lessons learned in comparative effectiveness research.

Authors:  Bradford R Hirsch; Robert B Giffin; Laura C Esmail; Sean R Tunis; Amy P Abernethy; Sharon B Murphy
Journal:  Cancer J       Date:  2011 Jul-Aug       Impact factor: 3.360

6.  Launching accountable care organizations--the proposed rule for the Medicare Shared Savings Program.

Authors:  Donald M Berwick
Journal:  N Engl J Med       Date:  2011-03-31       Impact factor: 91.245

Review 7.  Making observational studies count: shaping the future of comparative effectiveness research.

Authors:  Nancy A Dreyer
Journal:  Epidemiology       Date:  2011-05       Impact factor: 4.822

8.  The promise of comparative effectiveness research.

Authors:  Paul Sullivan; Don Goldmann
Journal:  JAMA       Date:  2011-01-26       Impact factor: 56.272

9.  Health Insurance Portability and Accountability Act (HIPAA) authorization and survey nonresponse bias.

Authors:  Timothy J Beebe; Jeanette Y Ziegenfuss; Jennifer L St Sauver; Sarah M Jenkins; Lindsey Haas; Michael E Davern; Nicholas J Talley
Journal:  Med Care       Date:  2011-04       Impact factor: 2.983

Review 10.  Data for cancer comparative effectiveness research: past, present, and future potential.

Authors:  Anne-Marie Meyer; William R Carpenter; Amy P Abernethy; Til Stürmer; Michael R Kosorok
Journal:  Cancer       Date:  2012-04-19       Impact factor: 6.860

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Authors:  Joseph Lipscomb; K Robin Yabroff; Mark C Hornbrook; Anna Gigli; Silvia Francisci; Murray Krahn; Gemma Gatta; Annalisa Trama; Debra P Ritzwoller; Isabelle Durand-Zaleski; Ramzi Salloum; Neetu Chawla; Catia Angiolini; Emanuele Crocetti; Francesco Giusti; Stefano Guzzinati; Maura Mezzetti; Guido Miccinesi; Angela Mariotto
Journal:  J Natl Cancer Inst Monogr       Date:  2013

2.  The Cancer Research Network: a platform for epidemiologic and health services research on cancer prevention, care, and outcomes in large, stable populations.

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Review 3.  The COMET Handbook: version 1.0.

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Journal:  Trials       Date:  2017-06-20       Impact factor: 2.279

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5.  Big data for population-based cancer research: the integrated cancer information and surveillance system.

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6.  Comparative effectiveness of mitoxantrone plus prednisone versus prednisone alone in metastatic castrate-resistant prostate cancer after docetaxel failure.

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Journal:  Oncologist       Date:  2015-04-17

Review 7.  Data for cancer comparative effectiveness research: past, present, and future potential.

Authors:  Anne-Marie Meyer; William R Carpenter; Amy P Abernethy; Til Stürmer; Michael R Kosorok
Journal:  Cancer       Date:  2012-04-19       Impact factor: 6.860

8.  Outcomes of open versus laparoscopic surgery in patients with rectal cancer.

Authors:  José M Quintana; Ane Anton-Ladislao; Santiago Lázaro; Nerea Gonzalez; Marisa Bare; Nerea Fernandez de Larrea; Maximino Redondo; Eduardo Briones; Antonio Escobar; Cristina Sarasqueta; Susana Garcia-Gutierrez
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Review 9.  Facilitating biomedical researchers' interrogation of electronic health record data: Ideas from outside of biomedical informatics.

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10.  A data-driven concept schema for defining clinical research data needs.

Authors:  Gregory W Hruby; Julia Hoxha; Praveen Chandar Ravichandran; Eneida A Mendonça; David A Hanauer; Chunhua Weng
Journal:  Int J Med Inform       Date:  2016-04-02       Impact factor: 4.046

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