A non-parametric statistical test of null treatment effect in sub-populations

References

• Bardy, G. H., K. L. Lee, D. B. Mark, J. E. Poole, D. L. Packer, R. Boineau, M. Domanski, C. Troutman, J. Anderson, G. Johnson, et al. 2005. Amiodarone or an implantable cardioverter–Defibrillator for congestive heart failure. The New England Journal of Medicine 352 (3):225–237. doi:10.1056/NEJMoa043399.
   PubMed Web of Science ®Google Scholar
• Bayman, E. Ö., K. Chaloner, and M. K. Cowles. 2009. Detecting qualitative interactions: A bayesian approach. Statistics in Medicine 29 (4):455–463.
   Web of Science ®Google Scholar
• Bonetti, M., and R. Gelber. 2004. Patterns of treatment effects in subsets of patients in clinical trials. Biostatistics 5 (3):465–481. doi:10.1093/biostatistics/5.3.465.
   PubMed Web of Science ®Google Scholar
• Chen, W., D. Ghosh, T. Raghunathan, M. Norkin, D. Sargent, and G. Bepler. 2012. On Bayesian methods of exploring qualitative interactions for targeted treatment. Statistics in Medicine 31 (28):3693–3707. doi:10.1002/sim.5429.
   PubMed Web of Science ®Google Scholar
• Dusseldorp, E., and I. V. Mechelen. 2014. Qualitative interaction trees: A tool to identify qualitative treatment–Subgroup interactions. Statistics in Medicine 33 (2):219–237. doi:10.1002/sim.5933.
   PubMed Web of Science ®Google Scholar
• Foster, J. C., J. M. Taylor, and S. Ruberg. 2011. Subgroup identification from randomized clinical trial data. Statistics in Medicine 30 (24):2867–2880. doi:10.1002/sim.4322.
   PubMed Web of Science ®Google Scholar
• Gail, M., and R. Simon. 1985. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics 41:361–372.
   PubMed Web of Science ®Google Scholar
• Goldenberg, I., A. K. Vyas, W. J. Hall, A. J. Moss, H. Wang, H. He, W. Zareba, S. McNitt, and M. L. Andrews. 2008. Risk stratification for primary implantation of a cardioverter-defibrillator in patients with ischemic left ventricular dysfunction. Journal of the American College of Cardiology 51 (3):288–296. doi:10.1016/j.jacc.2007.08.058.
   PubMed Web of Science ®Google Scholar
• Kravitz, R. L., N. Duan, and J. Braslow. 2004. Evidence‐based medicine, heterogeneity of treatment effects, and the trouble with averages. The Milbank Quarterly 82 (4):661–687. doi:10.1111/j.0887-378X.2004.00327.x.
   PubMed Web of Science ®Google Scholar
• Lagakos, S. W. 2006. The challenge of subgroup analyses-reporting without distorting. The New England Journal of Medicine 354 (16):1667–1669. doi:10.1056/NEJMp068070.
   PubMed Web of Science ®Google Scholar
• Levy, W. C., K. L. Lee, A. S. Hellkamp, J. E. Poole, D. Mozaffarian, D. T. Linker, A. P. Maggioni, I. Anand, P. A. Poole-Wilson, D. P. Fishbein, et al. 2009. Maximizing survival benefit with primary prevention implantable cardioverter-defibrillator therapy in a heart failure population. Circulation 120 (10):835–842. doi:10.1161/CIRCULATIONAHA.108.816884.
   PubMed Web of Science ®Google Scholar
• Li, J., and I. S. Chan. 2006. Detecting qualitative interactions in clinical trials: An extension of range test. Journal of Biopharmaceutical Statistics 16 (6):831–841. doi:10.1080/10543400600801588.
   PubMed Web of Science ®Google Scholar
• Moss, A. J., W. Zareba, W. J. Hall, H. Klein, D. J. Wilber, D. S. Cannom, J. P. Daubert, S. L. Higgins, M. W. Brown, and M. L. Andrews. 2002. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. The New England Journal of Medicine 346 (12):877–883. doi:10.1056/NEJMoa013474.
   PubMed Web of Science ®Google Scholar
• Peto, R. 1982. Statistical aspects of cancer trials. In: The treatment of cancer, Halnan K, ed, 867–871. London: Chapman & Hall.
   Google Scholar
• Piantadosi, S., and M. Gail. 1993. A comparison of the power of two tests for qualitative interactions. Statistics in Medicine 12 (13):1239–1248.
   PubMed Web of Science ®Google Scholar
• Rothwell, P. M. 2005. Subgroup analysis in randomised controlled trials: Importance, indications, and interpretation. The Lancet 365 (9454):176–186. doi:10.1016/S0140-6736(05)17709-5.
   PubMed Web of Science ®Google Scholar
• Shen, C., J. Jeong, X. Li, and P. S. Chen. 2013. Treatment benefit and treatment harm rate to characterize heterogeneity in treatment effect. Biometrics 69 (3):724–731. doi:10.1111/biom.12038.
   PubMed Web of Science ®Google Scholar
• Simon, R. 1980. Patient heterogeneity in clinical trials. Cancer Treatment Reports 64:405–410.
   PubMedGoogle Scholar
• Sørensen, T. I. 1996. Which patients may be harmed by good treatments? The Lancet 348 (9024):351–352. doi:10.1016/S0140-6736(05)64988-4.
   PubMed Web of Science ®Google Scholar
• Steinbeck, G., D. Andresen, K. Seidl, J. Brachmann, E. Hoffmann, D. Wojciechowski, Z. Kornacewicz-Jach, B. Sredniawa, G. Lupkovics, F. Hofgärtner, et al. 2009. Defibrillator implantation early after myocardial infarction. The New England Journal of Medicine 361 (15):1427–1436. doi:10.1056/NEJMoa0901889.
   PubMed Web of Science ®Google Scholar
• Tian, L., A. Alizadeh, A. Gentles, and R. Tibshirani. 2012. Simple method for estimating interactions between a treatment and a large number of covariates. Journal of the American Statistical Association 109(508): 1517–1532. 
   Google Scholar
• Wang, R., S. W. Lagakos, J. H. Ware, D. J. Hunter, and J. M. Drazen. 2007. Statistics in medicine—Reporting of subgroup analyses in clinical trials. The New England Journal of Medicine 357 (21):2189–2194. doi:10.1056/NEJMsr077003.
   PubMed Web of Science ®Google Scholar