Random treatment assignment using mathematical equipoise for comparative effectiveness trials

Clinical and Translational Science

Volumn 4, Issue 1, 2011, Pages 10-16

  Selker, Harry P ^a   Ruthazer, Robin ^a   Terrin, Norma ^a   Griffith, John L ^a   Concannon, Thomas ^a   Kent, David M ^a  

^a TUFTS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Clinical trial; Comparative effectiveness research; Equipoise; Myocardial infarction

Indexed keywords

ARTICLE; CLINICAL PRACTICE; COMPARATIVE EFFECTIVENESS; CONTROLLED STUDY; EQUIPOISE; FIBRINOLYTIC THERAPY; HUMAN; MAJOR CLINICAL STUDY; MORTALITY; PERCUTANEOUS CORONARY INTERVENTION; PREDICTION; PRIORITY JOURNAL; RANDOM SAMPLE; RANDOMIZATION; ST SEGMENT ELEVATION MYOCARDIAL INFARCTION;

ANGIOPLASTY, BALLOON, CORONARY; COMPARATIVE EFFECTIVENESS RESEARCH; HUMANS; MYOCARDIAL INFARCTION; RANDOM ALLOCATION; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SURVIVAL ANALYSIS; THERAPEUTIC EQUIPOISE;

EID: 79951881250     PISSN: 17528054     EISSN: 17528062     Source Type: Journal    
DOI: 10.1111/j.1752-8062.2010.00253.x     Document Type: Article

References (24)

1. Rothwell PM. Can overall results of clinical trials be applied to all patients Lancet. 1995; 345(8965): 1616-1619.
2. Kravitz RL, Duan N, Braslow J. Evidence-based medicine, heterogeneity of treatment-effects, and the trouble with averages. Milbank Q. 2004; 82(4): 661-687.
3. Kent DM, Hayward F. Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification. JAMA. 2007; 298(10): 1209-1212.
4. Rothwell PM, Mehta Z, Howard SC, Gutnikov SA, Warlow CP. Treating individuals 3: from subgroups to individuals: general principles and the example of carotid endarterectomy. Lancet. 2005; 365(9455): 256-265.
5. Kent DM, Hayward RA. When averages hide individual differences in clinical trials. Am Sci. 2007; 95: 60-68.
6. Rothwell PM, Warlow CP. Prediction of benefit from carotid endarterectomy in individual patients: a risk-modelling study. European Carotid Surgery Trialist Collaborative Group. Lancet. 1999; 353(9170): 2105-2110.
7. Kent DM, Hayward RA, Griffith JL, Vijan S, Beshansky JR, Califf R, et al. An independently derived and validated predictive model for selecting patients with myocardial infarction who are likely to benefit from tissue plasminogen activator compared with streptokinase. Am J Med. 2002; 113: 104-111.
8. Hayward RA, Kent DM, Vijan S, Hofer TP. Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol. 2006; 6: 18.
9. Freedman, B. 1987. Equipoise and the ethics of clinical research. N Engl J Med. 317: 141-145.
10. Finkelstein MO, Levin B, Robbins H. Clinical and prophylactic trials with assured new treatment for those at greater risk: I. A design proposal. Am J Public Health. 1996; 86: 691-695.
11. Cappelleri JC, Trochim WM. Ethical and scientific features of cutoff-based designs of clinical trials: a simulation study. Med Decis Making. 1995; 15: 387-394.
12. Selker HP, Griffith JL, Beshansky JR, Schmid CH, Califf RM, D'Agostino RB, et al. Patient-specific predictions of outcomes in myocardial infarction for real-time emergency use: a thrombolytic predictive instrument. Ann Intern Med. 1997; 127: 538-556.
13. Selker HP, Beshansky JR, Griffith JL, for the TPI Trial Investigators. Use of the electrocardiograph-based thrombolytic predictive instrument to assist thrombolytic and reperfusion therapy for acute myocardial infarction: a multicenter randomized clinical effectiveness trial. Ann Intern Med. 2002; 137: 87-95.
14. Kent DM, Ruthazer R, Griffith JL, Beshansky JR, Grines CL, Aversano T, et al. Comparison of mortality benefit of immediate thrombolytic therapy versus delayed primary angioplasty. Am J Cardiol. 2007; 99(10): 1384-1388.
15. Kent DM, Ruthazer R, Griffith JL, Beshansky JR, Aversano T, Concanon TW, et al. A percutaneous coronary intervention thrombolytic predictive instrument (PCI-TPI) to assist choosing between immediate thrombolytic therapy versus delayed primary percutaneous coronary intervention for acute myocardial infarction. Am J Cardiol. 2008; 101(6): 790-795.
16. Savvides PS, Terrin NC, Erban J, Selker HP. Development and validation of a patient-specific predictive instrument for the need for dose reduction in chemotherapy for breast cancer: a potential decision aid for the use of myeloid growth factors. Support Care Cancer. 2003; 11(5): 313-320.
17. Thune JJ, Hoefsten DE, Lindholm MG, Mortensen LS, Andersen HR, Nielsen TT, et al. Danish Multicenter Randomized Study on fibrinolytic therapy versus acute coronary angioplasty in acute myocardial infarction (DANAMI)-2 investigators: simple risk stratification at admission to identify patients with reduced mortality from primary angioplasty. Circulation. 2005, 112: 2017-2021.
18. McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofar A, et al. The quality of health care delivered to adults in the United States N Engl J Med. 2003; 348(26): 2635-2645.
19. Selker HP, Griffith JL, Beshansky JR, Califf RM, D'Agostino RB, Laks MM, et al. The Thrombolytic Predictive Instrument (TPI) Project: Combining Clinical Study Databases to Take Medical Effectiveness Research to the Streets. USA Agency for Health Care Policy Research, DHHS; 1992: 9-31.
20. Hrynaszkiewicz I, Altman DG. Towards agreement on best practice for publishing raw clinical trial data. Trials. 2009, 10: 17.
21. Kent DM, Rothwell PM, Ioannidis JP, Altman DG, Hayward RA. Assessing and reporting heterogeneity of treatment effect in clinical trials: a proposal. Trials. 2010, 11: 85.
22. Guyatt G, Oxman A, Vist G, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008; 336: 924-926.
23. Hernandez AV, Boersma E, Murray GD, Habbema JD, Steyerberg EW. Subgroup analyses in therapeutic cardiovascular clinical trials: are most of them misleading Am Heart J. 2006; 151: 257-264.
24. Sun X, Briel M, Walter SD, Guyatt GH. Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. BMJ. 2010; 340: c117.