Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

Abandoning false beliefs about sample-size planning would facilitate funding and conduct of innovative clinical research with small sample sizes. Innovative clinical and translational research is often delayed or prevented by reviewers’ expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an n of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation.

[1]  C H Best,et al.  Pancreatic Extracts in The Treatment of Diabetes Mellitus , 1956, Diabetes.

[2]  M. Gardner,et al.  Confidence intervals rather than P values: estimation rather than hypothesis testing. , 1986, British medical journal.

[3]  A S Detsky,et al.  Using cost-effectiveness analysis to improve the efficiency of allocating funds to clinical trials. , 1990, Statistics in medicine.

[4]  K J Rothman,et al.  No Adjustments Are Needed for Multiple Comparisons , 1990, Epidemiology.

[5]  Jacob Cohen The earth is round (p < .05) , 1994 .

[6]  S. Goodman,et al.  The Use of Predicted Confidence Intervals When Planning Experiments and the Misuse of Power When Interpreting Results , 1994, Annals of Internal Medicine.

[7]  J. Matthews,et al.  Small clinical trials: are they all bad? , 1995, Statistics in medicine.

[8]  Stephen Senn,et al.  Statistical Issues in Drug Development , 1997 .

[9]  C. Gross,et al.  The myth of the medical breakthrough: smallpox, vaccination, and Jenner reconsidered. , 1998, International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases.

[10]  S. Goodman Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy , 1999, Annals of Internal Medicine.

[11]  Jacques Poitevineau,et al.  Uses, Abuses and Misuses of Significance Tests in the Scientific Community: Won't the Bayesian Choice be Unavoidable? , 2001 .

[12]  Peter Bacchetti,et al.  Peer review of statistics in medical research: the other problem , 2002, BMJ : British Medical Journal.

[13]  J. Karlawish,et al.  The continuing unethical conduct of underpowered clinical trials. , 2002, JAMA.

[14]  G. Gigerenzer Mindless statistics , 2004 .

[15]  K. Schulz,et al.  Sample size calculations in randomised trials: mandatory and mystical , 2005, The Lancet.

[16]  Andrew R Willan,et al.  The value of information and optimal clinical trial design , 2005, Statistics in medicine.

[17]  S. Halpern Adding nails to the coffin of underpowered trials. , 2005, The Journal of rheumatology.

[18]  L. Koniaris,et al.  The Discovery of Insulin: The Rochester, New York, Connection , 2005, Annals of Internal Medicine.

[19]  J. Ioannidis Why Most Published Research Findings Are False , 2005 .

[20]  C. McCulloch,et al.  Ethics and sample size. , 2005, American journal of epidemiology.

[21]  H. Kraemer,et al.  Caution regarding the use of pilot studies to guide power calculations for study proposals. , 2006, Archives of general psychiatry.

[22]  J. Armstrong Significance Tests Harm Progress in Forecasting , 2007 .

[23]  Andrew R Willan,et al.  Optimal sample size determinations from an industry perspective based on the expected value of information , 2008, Clinical trials.

[24]  Gordon H Guyatt,et al.  In the Era of Systematic Reviews, Does the Size of an Individual Trial Still Matter? , 2008, PLoS medicine.

[25]  M. Segal,et al.  Simple, Defensible Sample Sizes Based on Cost Efficiency , 2008, Biometrics.

[26]  M. Hersen,et al.  Handbook of clinical psychology , 2008 .

[27]  M. J. Broadhurst,et al.  IL-22+ CD4+ T Cells Are Associated with Therapeutic Trichuris trichiura Infection in an Ulcerative Colitis Patient , 2010, Science Translational Medicine.

[28]  Ana Fernández-Somoano,et al.  The null hypothesis significance test in health sciences research (1995-2006): statistical analysis and interpretation , 2010, BMC medical research methodology.

[29]  Peter Bacchetti,et al.  Current sample size conventions: Flaws, harms, and alternatives , 2010, BMC medicine.

[30]  E. Thiel,et al.  Evidence for the cure of HIV infection by CCR5Δ32/Δ32 stem cell transplantation. , 2011, Blood.