Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Trials
Published in: Trials 1/2015

Open Access 01-12-2015 | Methodology

A sample size planning approach that considers both statistical significance and clinical significance

Authors: Bin Jia, Henry S Lynn

Published in: Trials | Issue 1/2015

Login to get access

Abstract

Background

The CONSORT statement requires clinical trials to report confidence intervals, which help to assess the precision and clinical importance of the treatment effect. Conventional sample size calculations for clinical trials, however, only consider issues of statistical significance (that is, significance level and power).

Method

A more consistent approach is proposed whereby sample size planning also incorporates information on clinical significance as indicated by the boundaries of the confidence limits of the treatment effect.

Results

The probabilities of declaring a “definitive-positive” or “definitive-negative” result (as defined by Guyatt et al., CMAJ 152(2):169-173, 1995) are controlled by calculating the sample size such that the lower confidence limit under H1 and the upper confidence limit under H0 are bounded by relevant cut-offs. Adjustments to the traditional sample size can be directly derived for the comparison of two normally distributed means in a test of nonequality, while simulations are used to estimate the sample size for evaluating the hazards ratio in a proportional-hazards model.

Conclusions

This sample size planning approach allows for an assessment of the potential clinical importance and precision of the treatment effect in a clinical trial in addition to considerations of statistical power and type I error.
Appendix
Available only for authorised users
Literature
1.
Simon R, Wittes RE. Methodologic guidelines for reports of clinical trials. Cancer Treat Rep. 1985;69:1–3.PubMed
2.
Bailar JC, Mosteller F. Guidelines for statistical reporting in articles for medical journals. Ann Intern Med. 1988;108:266–73.CrossRefPubMed
3.
Lang T. Documenting research in scientific articles: guidelines for authors. 1. Reporting research designs and activities. Chest. 2006;130:1263–8.PubMed
4.
Rothman K. Modern epidemiology. Boston: Little Brown; 1986.
5.
Altman DG, Schulz KF, Moher D, Egger M, Davidoff F, Elbourne D, et al. The revised CONSORT statement for reporting randomized trials: explanation and elaboration. Ann Intern Med. 2001;134:663–94.CrossRefPubMed
6.
Goodman S, Berlin J. The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results. Ann Intern Med. 1994;121:200–6.CrossRefPubMed
7.
Bacchetti P. Current sample size conventions: flaws, harms, and alternatives. BMC Med. 2010;8, e17.CrossRef
8.
Beal SL. Sample size determination for confidence intervals on the population mean and on the difference between two population means. Biometrics. 1989;45:969–77.CrossRefPubMed
9.
Liu XS. Implications of statistical power for confidence intervals. Br J Math Stat Psychol. 2012;65:427–37.CrossRefPubMed
10.
Jiroutek MR, Muller KE, Kupper LL, Stewart PW. A new method for choosing sample size for confidence interval-based inferences. Biometrics. 2003;59:580–90.CrossRefPubMed
11.
Cesana BM, Reina G, Marubini E. Sample size for testing a proportion in clinical trials: a ’two-step’ procedure combining power and confidence interval expected width. Am Stat. 2001;55:288–92.CrossRef
12.
Cesana BM. Sample size for testing and estimating the difference between two paired and unpaired proportions: a ‘two-step’ procedure combining power and the probability of obtaining a precise estimate. Stat Med. 2004;23:2359–73.CrossRefPubMed
13.
Guyatt G, Jaeschke R, Heddle N, Cook D, Shannon H, Walter S. Basic statistics for clinicians: 2. Interpreting study results: confidence intervals. Can Med Assoc J. 1995;152:169–73.
14.
Schoenfeld DA. Sample-size formula for the proportional-hazards regression model. Biometrics. 1983;39:499–503.CrossRefPubMed
15.
Freedman LS. Tables of the number of patients required in clinical trials using the logrank test. Stat Med. 1982;1:121–9.CrossRefPubMed
16.
Halabi S, Bahadur S. Sample size determination for comparing several survival curves with unequal allocations. Stat Med. 2004;23:1793–815.CrossRefPubMed
17.
Greenland S. On sample-size and power calculations for studies using confidence intervals. Am J Epidemiol. 1988;128:231–7.CrossRefPubMed
Metadata
Title
A sample size planning approach that considers both statistical significance and clinical significance
Authors
Bin Jia
Henry S Lynn
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Trials / Issue 1/2015
Electronic ISSN: 1745-6215
DOI
https://doi.org/10.1186/s13063-015-0727-9

Other articles of this Issue 1/2015

Trials 1/2015 Go to the issue

Research

Opioid substitution and antagonist therapy trials exclude the common addiction patient: a systematic review and analysis of eligibility criteria

Research

A simple technique to identify key recruitment issues in randomised controlled trials: Q-QAT - quanti-qualitative appointment timing

Research

Uncovering the emotional aspects of working on a clinical trial: a qualitative study of the experiences and views of staff involved in a type 1 diabetes trial

Review

Interventions in randomised controlled trials in surgery: issues to consider during trial design

Study protocol

Supervised exercise training as an adjunctive therapy for venous leg ulcers: study protocol for a randomised controlled trial

Study protocol

The role of a structured exercise training program on cardiac structure and function after acute myocardial infarction: study protocol for a randomized controlled trial