Interim analysis

In clinical trials and other scientific studies, an interim analysis is an analysis of data that is conducted before data collection has been completed. Clinical trials are unusual in that enrollment of patients is a continual process staggered in time. This means that if a treatment is particularly beneficial or harmful compared to the concurrent placebo group while the study is on-going, the investigators are ethically obliged to assess that difference using the data at hand and to make a deliberate consideration of terminating the study earlier than planned.

Statistical methods

The design of many clinical trials includes some strategy for early stopping if an interim analysis reveals large differences between treatment groups. In addition to saving time and resources, such a design feature can reduce study participants' exposure to the inferior treatment. However, when repeated significance testing on accumulating data is done, some adjustment of the usual hypothesis testing procedure must be made to maintain an overall significance level.^[1][2] The methods described by Pocock^[3][4] and O'Brien & Fleming,^[5] among others,^[6] are popular implementations of group sequential testing for clinical trials.^[7][8][9] Sometimes interim analyses are equally spaced in terms of calendar time or the information available from the data, but this assumption can be relaxed to allow for unplanned or unequally spaced analyses.

Example

The second Multicenter Automatic Defibrillator Implantation Trial (MADIT II) was conducted to help better identify patients with coronary heart disease who would benefit from an ICD. MADIT II is the latest in a series of trials involving the use of ICDs to improve management and clinical treatment of arrhythmia patients. The Antiarrhythmics versus Implantable Defibrillators (AVID) Trial compared ICDs with antiarrhythmic-drug therapy (amiodarone or sotalol, predominantly the former) in patients who had survived life-threatening ventricular arrhythmias. After inclusion of 1,232 patients, the MADIT II study was terminated when interim analysis showed significant (31%) reduction in all-cause death in patients assigned to ICD therapy.^[10]

References

1. Armitage, P.; McPherson, C.K.; Rowe, B.C. (1969). "Repeated Significance Tests on Accumulating Data". Journal of the Royal Statistical Society, Series A 132: 235–244. JSTOR 2343787.
2. McPherson, C.K.; Armitage, P. (1971). "Repeated Significance Tests on Accumulating Data". Journal of the Royal Statistical Society, Series A 134: 15–26. doi:10.2307/2343971.
3. Pocock, S.J. (1977). "Group sequential methods in the design and analysis of clinical trials". Biometrika 64: 191–199. doi:10.2307/2335684.
4. Pocock, S.J. (1982). "Interim Analyses for Randomized Clinical trials: The Group Sequential Approach". Biometrics 38: 153–162. doi:10.2307/2530298. PMID 7082757.
5. O’Brien, P.C.; Fleming, T.R. (1979). "A Multiple Testing Procedure for Clinical Trials". Biometrics 35: 549–556. doi:10.2307/2530245. PMID 497341.
6. Lan, K.G.; DeMets, D.L. (1983). "Discrete sequential boundaries for clinical trials". Biometrika 70: 659–663. doi:10.1093/biomet/70.3.659. JSTOR 2336502.
7. Jennison, Christopher; Turnbull, Bruce C. (1999). Group Sequential Methods with Applications to Clinical Trials. Boca Raton, FL: Chapman & Hall/CRC. ISBN 0-8493-0316-8.
8. Chin, Richard (2012). Adaptive and Flexible Clinical Trials. Boca Raton, FL: Chapman & Hall/CRC. ISBN 978-1-4398-3832-7.
9. Chow, Shein-Chow; Chang, Mark (2012). Adaptive Design Methods in Clinical Trials (2 ed.). Boca Raton, FL: Chapman & Hall/CRC. ISBN 978-1-4398-3987-4.
10. Moss AJ, Zareba W, Hall WJ, Klein H, Wilber DJ, Cannom DS, Daubert JP, Higgins SL, Brown MW, Andrews ML (2002). "Prophylactic Implantation of a Defibrillator in Patients with Myocardial Infarction and Reduced Ejection Fraction". New England Journal of Medicine 346 (12): 877–83. doi:10.1056/NEJMoa013474. PMID 11907286.