Literature DB >> 23697601

Comparative effectiveness research in oncology.

Gary H Lyman1.   

Abstract

Although randomized controlled trials represent the gold standard for comparative effective research (CER), a number of additional methods are available when randomized controlled trials are lacking or inconclusive because of the limitations of such trials. In addition to more relevant, efficient, and generalizable trials, there is a need for additional approaches utilizing rigorous methodology while fully recognizing their inherent limitations. CER is an important construct for defining and summarizing evidence on effectiveness and safety and comparing the value of competing strategies so that patients, providers, and policymakers can be offered appropriate recommendations for optimal patient care. Nevertheless, methodological as well as political and social challenges for CER remain. CER requires constant and sophisticated methodological oversight of study design and analysis similar to that required for randomized trials to reduce the potential for bias. At the same time, if appropriately conducted, CER offers an opportunity to identify the most effective and safe approach to patient care. Despite rising and unsustainable increases in health care costs, an even greater challenge to the implementation of CER arises from the social and political environment questioning the very motives and goals of CER. Oncologists and oncology professional societies are uniquely positioned to provide informed clinical and methodological expertise to steer the appropriate application of CER toward critical discussions related to health care costs, cost-effectiveness, and the comparative value of the available options for appropriate care of patients with cancer.

Entities:  

Keywords:  Clinical trials; Comparative effectiveness; Cost-effectiveness; Health policy; Outcomes

Mesh:

Year:  2013        PMID: 23697601      PMCID: PMC4063403          DOI: 10.1634/theoncologist.2012-0445

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  49 in total

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Journal:  Lancet       Date:  1999-11-27       Impact factor: 79.321

2.  Randomized, controlled trials, observational studies, and the hierarchy of research designs.

Authors:  J Concato; N Shah; R I Horwitz
Journal:  N Engl J Med       Date:  2000-06-22       Impact factor: 91.245

3.  A comparison of observational studies and randomized, controlled trials.

Authors:  K Benson; A J Hartz
Journal:  N Engl J Med       Date:  2000-06-22       Impact factor: 91.245

Review 4.  Comparison of evidence of treatment effects in randomized and nonrandomized studies.

Authors:  J P Ioannidis; A B Haidich; M Pappa; N Pantazis; S I Kokori; M G Tektonidou; D G Contopoulos-Ioannidis; J Lau
Journal:  JAMA       Date:  2001-08-15       Impact factor: 56.272

Review 5.  Lessons learned from recent cardiovascular clinical trials: Part I.

Authors:  David L DeMets; Robert M Califf
Journal:  Circulation       Date:  2002-08-06       Impact factor: 29.690

Review 6.  Parachute use to prevent death and major trauma related to gravitational challenge: systematic review of randomised controlled trials.

Authors:  Gordon C S Smith; Jill P Pell
Journal:  BMJ       Date:  2003-12-20

7.  Reporting of patient-reported outcomes in randomized trials: the CONSORT PRO extension.

Authors:  Melanie Calvert; Jane Blazeby; Douglas G Altman; Dennis A Revicki; David Moher; Michael D Brundage
Journal:  JAMA       Date:  2013-02-27       Impact factor: 56.272

Review 8.  Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group.

Authors:  D F Stroup; J A Berlin; S C Morton; I Olkin; G D Williamson; D Rennie; D Moher; B J Becker; T A Sipe; S B Thacker
Journal:  JAMA       Date:  2000-04-19       Impact factor: 56.272

9.  Reporting recommendations for tumor marker prognostic studies (REMARK).

Authors:  Lisa M McShane; Douglas G Altman; Willi Sauerbrei; Sheila E Taube; Massimo Gion; Gary M Clark
Journal:  J Natl Cancer Inst       Date:  2005-08-17       Impact factor: 13.506

10.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  6 in total

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Authors:  Thomas G Roberts
Journal:  Oncologist       Date:  2013-06

Review 2.  Strengths and limitations of large databases in lung cancer radiation oncology research.

Authors:  Vikram Jairam; Henry S Park
Journal:  Transl Lung Cancer Res       Date:  2019-09

Review 3.  Considerations for observational research using large data sets in radiation oncology.

Authors:  Reshma Jagsi; Justin E Bekelman; Aileen Chen; Ronald C Chen; Karen Hoffman; Ya-Chen Tina Shih; Benjamin D Smith; James B Yu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2014-09-01       Impact factor: 7.038

Review 4.  Value-Based Care in the Worldwide Battle Against Cancer.

Authors:  Niloufer J Johansen; Christobel M Saunders
Journal:  Cureus       Date:  2017-02-17

5.  A Retrospective Observational Analysis of Overall Survival with Sipuleucel-T in Medicare Beneficiaries Treated for Advanced Prostate Cancer.

Authors:  Rana R McKay; Jason M Hafron; Christine Ferro; Helen M Wilfehrt; Kate Fitch; Scott C Flanders; Michael D Fabrizio; Michael T Schweizer
Journal:  Adv Ther       Date:  2020-10-07       Impact factor: 3.845

6.  Real-world outcomes associated with new cancer medicines approved by the Food and Drug Administration and European Medicines Agency: A retrospective cohort study.

Authors:  Jemma M Boyle; Gemma Hegarty; Christopher Frampton; Elizabeth Harvey-Jones; Joanna Dodkins; Katharina Beyer; Gincy George; Richard Sullivan; Christopher Booth; Ajay Aggarwal
Journal:  Eur J Cancer       Date:  2021-08-06       Impact factor: 9.162

  6 in total

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