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Clinical Trials: Handling the Data

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Success in Academic Surgery: Clinical Trials

Part of the book series: Success in Academic Surgery ((SIAS))

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Abstract

Randomized control trials (RCTs) provide the foundation for evidence-based medicine, which is the cornerstone of medical practice. RCTs are prospective studies that compare the effect of an intervention between an intervention and control group. An understanding of statistical methods is fundamental to the interpretation of RCT methods and results. This chapter will not provide an in-depth description of the methods of statistical analysis (this information can be obtained from any introductory statistics textbook). Instead, this chapter will provide a brief review of common statistical methods used to analyze data and discuss some issues associated with data analysis.

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References

  1. Friedman LM, Furberg C, DeMets DL. Fundamentals of clinical trials. 3rd ed. New York: Springer; 1998. xviii, 361 p.

    Book  Google Scholar 

  2. Dawson B, Trapp RG. Basic & clinical biostatistics. 4th ed. New York: Lange Medical Books-McGraw-Hill, Medical Pub. Division; 2004. x, 438 p.

    Google Scholar 

  3. Wang D, Bakhai A, Maffulli N. A primer for statistical analysis of clinical trials. Arthroscopy. 2003;19(8):874–81.

    Article  PubMed  Google Scholar 

  4. Dawson B, Trapp RG. Basic & clinical biostatistics. 4th ed. New York: Lange Medical Books/McGraw-Hill; 2004.

    Google Scholar 

  5. Straus SE. Evidence-based medicine : how to practice and teach it. 4th ed. Edinburgh: Elsevier Churchill Livingstone; 2011. xvii, 293 p.

    Google Scholar 

  6. Troidl H. Principles and practice of research: strategies for surgical investigators. Berlin/New York: Springer; 1986. xvii, 380 p.

    Book  Google Scholar 

  7. Newell DJ. Intention-to-treat analysis: implications for quantitative and qualitative research. Int J Epidemiol. 1992;21(5):837–41.

    Article  PubMed  CAS  Google Scholar 

  8. Hulley SB. Designing clinical research: an epidemiologic approach. 2nd ed. Philadelphia: Lippincott Williams & Wilkins; 2001. xv, 336 p.

    Google Scholar 

  9. Effects of estrogen or estrogen/progestin regimens on heart disease risk factors in postmenopausal women. The Postmenopausal Estrogen/Progestin Interventions (PEPI) Trial. The Writing Group for the PEPI Trial. JAMA. 1995;273(3):199–208.

    Google Scholar 

  10. Coronary-artery bypass surgery in stable angina pectoris: survival at two years. European Coronary Surgery Study Group. Lancet. 1979;1(8122):889–93.

    Google Scholar 

  11. Hollis S, Campbell F. What is meant by intention to treat analysis? Survey of published randomised controlled trials. BMJ. 1999;319(7211):670–4.

    Article  PubMed  CAS  Google Scholar 

  12. Gravel J, Opatrny L, Shapiro S. The intention-to-treat approach in randomized controlled trials: are authors saying what they do and doing what they say? Clin Trials. 2007;4(4):350–6.

    Article  PubMed  Google Scholar 

  13. Packer M, et al. The effect of carvedilol on morbidity and mortality in patients with chronic heart failure. U.S. Carvedilol Heart Failure Study Group. N Engl J Med. 1996;334(21):1349–55.

    Article  PubMed  CAS  Google Scholar 

  14. Pocock SJ, et al. Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Stat Med. 2002;21(19):2917–30.

    Article  PubMed  Google Scholar 

  15. Wang R, et al. Statistics in medicine–reporting of subgroup analyses in clinical trials. N Engl J Med. 2007;357(21):2189–94.

    Article  PubMed  CAS  Google Scholar 

  16. Hernandez AV, et al. Subgroup analyses in therapeutic cardiovascular clinical trials: are most of them misleading? Am Heart J. 2006;151(2):257–64.

    Article  PubMed  Google Scholar 

  17. Little RJ, et al. The prevention and treatment of missing data in clinical trials. N Engl J Med. 2012;367(14):1355–60.

    Article  PubMed  CAS  Google Scholar 

  18. Little RJ, et al. The design and conduct of clinical trials to limit missing data. Stat Med. 2012;31(28):3433–43.

    Article  PubMed  CAS  Google Scholar 

  19. Wood AM, White IR, Thompson SG. Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals. Clin Trials. 2004;1(4):368–76.

    Article  PubMed  Google Scholar 

  20. Council NR. The prevention and treatment of missing data in clinical trials. Washington, DC: National Academic Press; 2010.

    Google Scholar 

  21. Moher D, et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. J Clin Epidemiol. 2010;63(8):e1–37.

    Article  PubMed  Google Scholar 

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Correspondence to George J. Chang MD, MS .

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© 2014 Springer-Verlag London

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Bailey, C.E., Chang, G.J. (2014). Clinical Trials: Handling the Data. In: Pawlik, T., Sosa, J. (eds) Success in Academic Surgery: Clinical Trials. Success in Academic Surgery. Springer, London. https://doi.org/10.1007/978-1-4471-4679-7_4

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  • DOI: https://doi.org/10.1007/978-1-4471-4679-7_4

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