Literature DB >> 23577230

Building useful evidence: changing the clinical research paradigm to account for comparative effectiveness research.

Sheldon Greenfield, Sherrie H Kaplan.   

Abstract

Comparative effectiveness research (CER) calls for substantial changes in the way clinical research is conducted, interpreted and practically applied in the USA, in order to produce useful clinical evidence. Departing from classic efficacy and effectiveness research, the evolving CER paradigm requires structural and substantive innovations that address three basic questions: what works? for whom? and in whose hands? Addressing these questions will require fundamental changes in the approach to clinical research that include: the use of active treatments (or comparators) versus placebos in the comparisons of treatments, innovative or 'alternative' research methods, the specification and a priori design of studies to account for important subgroups, accounting for the nested nature of healthcare delivery in design and analysis of CER, the simultaneous study of multiple treatments or treatment modalities, the study of multiple outcomes (benefits and harms) for each treatment compared, and the reassessment of the value of different study designs in the hierarchy of collective 'evidence'. In order to aid individual providers and patients in making informed, personalized treatment decisions, guided by the best evidence possible, CER studies must generalize to a broad range of subgroups reflecting the spectrum of patients, providers and health systems that populate real-world practice settings. Without expansion in the scope, conduct and subsequent interpretation of clinical research reflected in the issues outlined above, CER will fall short of its potential for informing evidence-based practice and personalized medicine. The current paradigm for conducting, interpreting and applying clinical research does not meet the needs of optimal generalizability and application to individual physician-patient efforts to identify the most effective treatment, and therefore does not support the basic requirements of CER. The proposed changes should neither require decades nor exorbitant budgets to achieve. Using two examples, prostate cancer, and comparisons of single medications, we illustrated how the proposed changes in clinical research, matching strategy to each application, might be addressed.

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Year:  2012        PMID: 23577230      PMCID: PMC3619728          DOI: 10.2217/CER.12.23

Source DB:  PubMed          Journal:  J Comp Eff Res        ISSN: 2042-6305            Impact factor:   1.744


  27 in total

1.  Prediction of benefit from carotid endarterectomy in individual patients: a risk-modelling study. European Carotid Surgery Trialists' Collaborative Group.

Authors:  P M Rothwell; C P Warlow
Journal:  Lancet       Date:  1999-06-19       Impact factor: 79.321

Review 2.  Methodological shortcomings predicted lower harm estimates in one of two sets of studies of clinical interventions.

Authors:  Roger Chou; Rongwei Fu; Susan Carson; Somnath Saha; Mark Helfand
Journal:  J Clin Epidemiol       Date:  2006-09-07       Impact factor: 6.437

Review 3.  Heterogeneity of treatment effects: implications for guidelines, payment, and quality assessment.

Authors:  Sheldon Greenfield; Richard Kravitz; Naihua Duan; Sherrie H Kaplan
Journal:  Am J Med       Date:  2007-04       Impact factor: 4.965

4.  When are randomised trials unnecessary? Picking signal from noise.

Authors:  Paul Glasziou; Iain Chalmers; Michael Rawlins; Peter McCulloch
Journal:  BMJ       Date:  2007-02-17

5.  Use of propensity score technique to account for exposure-related covariates: an example and lesson.

Authors:  John D Seeger; Tobias Kurth; Alexander M Walker
Journal:  Med Care       Date:  2007-10       Impact factor: 2.983

6.  Performance of propensity score calibration--a simulation study.

Authors:  Til Stürmer; Sebastian Schneeweiss; Kenneth J Rothman; Jerry Avorn; Robert J Glynn
Journal:  Am J Epidemiol       Date:  2007-03-28       Impact factor: 4.897

7.  Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification.

Authors:  David M Kent; Rodney A Hayward
Journal:  JAMA       Date:  2007-09-12       Impact factor: 56.272

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

Authors:  Mary E Tinetti; Stephanie A Studenski
Journal:  N Engl J Med       Date:  2011-06-22       Impact factor: 91.245

9.  Assessment of prognosis with the total illness burden index for prostate cancer: aiding clinicians in treatment choice.

Authors:  Mark S Litwin; Sheldon Greenfield; Eric P Elkin; Deborah P Lubeck; Jeanette M Broering; Sherrie H Kaplan
Journal:  Cancer       Date:  2007-05-01       Impact factor: 6.860

10.  Selecting patients with atrial fibrillation for anticoagulation: stroke risk stratification in patients taking aspirin.

Authors:  Brian F Gage; Carl van Walraven; Lesly Pearce; Robert G Hart; Peter J Koudstaal; B S P Boode; Palle Petersen
Journal:  Circulation       Date:  2004-10-11       Impact factor: 29.690

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  3 in total

1.  Comparative and cost-effectiveness research: Competencies, opportunities, and training for nurse scientists.

Authors:  Patricia W Stone; Catherine Cohen; Harold Alan Pincus
Journal:  Nurs Outlook       Date:  2017-04-20       Impact factor: 3.250

2.  Using a population-based observational cohort study to address difficult comparative effectiveness research questions: the CEASAR study.

Authors:  Daniel A Barocas; Vivien Chen; Matthew Cooperberg; Michael Goodman; John J Graff; Sheldon Greenfield; Ann Hamilton; Karen Hoffman; Sherrie Kaplan; Tatsuki Koyama; Alicia Morgans; Lisa E Paddock; Sharon Phillips; Matthew J Resnick; Antoinette Stroup; Xiao-Cheng Wu; David F Penson
Journal:  J Comp Eff Res       Date:  2013-07       Impact factor: 1.744

3.  Comparative effectiveness and the future of clinical research in diabetes.

Authors:  Sheldon Greenfield
Journal:  Diabetes Care       Date:  2013-08       Impact factor: 19.112

  3 in total

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