An internal pilot study for a randomized trial aimed at evaluating the effectiveness of iron interventions in children with non-anemic iron deficiency: the OptEC trial

Kawsari Abdullah, Kevin E Thorpe, Eva Mamak, Jonathon L Maguire, Catherine S Birken, Darcy Fehlings, Anthony J Hanley, Colin Macarthur, Stanley H Zlotkin, Patricia C Parkin, Kawsari Abdullah, Kevin E Thorpe, Eva Mamak, Jonathon L Maguire, Catherine S Birken, Darcy Fehlings, Anthony J Hanley, Colin Macarthur, Stanley H Zlotkin, Patricia C Parkin

Abstract

Background: The OptEC trial aims to evaluate the effectiveness of oral iron in young children with non-anemic iron deficiency (NAID). The initial sample size calculated for the OptEC trial ranged from 112-198 subjects. Given the uncertainty regarding the parameters used to calculate the sample, an internal pilot study was conducted. The objectives of this internal pilot study were to obtain reliable estimate of parameters (standard deviation and design factor) to recalculate the sample size and to assess the adherence rate and reasons for non-adherence in children enrolled in the pilot study.

Methods: The first 30 subjects enrolled into the OptEC trial constituted the internal pilot study. The primary outcome of the OptEC trial is the Early Learning Composite (ELC). For estimation of the SD of the ELC, descriptive statistics of the 4 month follow-up ELC scores were assessed within each intervention group. The observed SD within each group was then pooled to obtain an estimated SD (S2) of the ELC. Correlation (ρ) between the ELC measured at baseline and follow-up was assessed. Recalculation of the sample size was performed using analysis of covariance (ANCOVA) method which uses the design factor (1- ρ(2)). Adherence rate was calculated using a parent reported rate of missed doses of the study intervention.

Conclusion: The new estimate of the SD of the ELC was found to be 17.40 (S2). The design factor was (1- ρ2) = 0.21. Using a significance level of 5%, power of 80%, S2 = 17.40 and effect estimate (Δ) ranging from 6-8 points, the new sample size based on ANCOVA method ranged from 32-56 subjects (16-28 per group). Adherence ranged between 14% and 100% with 44% of the children having an adherence rate ≥ 86%. Information generated from our internal pilot study was used to update the design of the full and definitive trial, including recalculation of sample size, determination of the adequacy of adherence, and application of strategies to improve adherence.

Trial registration: ClinicalTrials.gov Identifier: NCT01481766 (date of registration: November 22, 2011).

Figures

Fig. 1
Fig. 1
Participant flow diagram for the internal pilot study

References

    1. Abdullah K, Thorpe KE, Mamak E, Maguire JL, Birken CS, Fehlings D, et al. Optimizing early child development for young children with non-anemic iron deficiency in the primary care practice setting (OptEC): study protocol for a randomized controlled trial. Trials. 2015;16:132. doi: 10.1186/s13063-015-0635-z.
    1. Lancaster GA, Dodd S, Williamson PR. Design and analysis of pilot studies: recommendations for good practice. J Eval Clin Pract. 2004;10(2):307–12. doi: 10.1111/j..2002.384.doc.x.
    1. Birkett M, Day SJ. Internal pilot studies for estimating sample size. Stat Med. 1994;13:2455–63. doi: 10.1002/sim.4780132309.
    1. Wittes J, Brittain E. The role of internal pilot studies in increasing the efficiency of clinical trials. Stat Med. 1990;9:65–72. doi: 10.1002/sim.4780090113.
    1. Browne RH. On the use of a pilot sample for sample size determination. Stat Med. 1995;14:1933–40. doi: 10.1002/sim.4780141709.
    1. Friede T, Kieser M. Sample size recalculation in internal pilot study designs: a review. Biom J. 2006;48(4):537–55. doi: 10.1002/bimj.200510238.
    1. Borm GF, Fransen J, Lemmens WAJG. A simple sample size formula for analysis of covariance in randomized clinical trials. J Clin Epidemiol. 2007;60:1234–8. doi: 10.1016/j.jclinepi.2007.02.006.
    1. Galloway R, McGuire J. Determinants of compliance with iroon supplementation: supplies, side effects, or psychology. Soc Sci Med. 1994;39(3):381–90. doi: 10.1016/0277-9536(94)90135-X.
    1. Low M, Farrell A, Biggs B, Pasricha S. Effects of daily iron supplementation in primary-school-aged children: systematic review and meta-analysis of randomized controlled trials. CMAJ. 2013;185(17):E791–802. doi: 10.1503/cmaj.130628.
    1. Pullar T, Kumar S, Feely M. Compliance in clinical trials. Ann Rheum Dis. 1989;48:871–5. doi: 10.1136/ard.48.10.871.
    1. Albert JM. Accounting for non-compliance in the design of clinical trials. Drug Inf J. 1997;31:157–65.
    1. Stichele RV. Measurement of patient compliance and the interpretation of randomized clinical trials. Eur J Clin Pharmacol. 1991;41:27–35. doi: 10.1007/BF00280102.
    1. Cnaan A, Zhao H, Silber JH. Proceedings of the ENAR spring meeting - Biometric section to include ENAR and WNAR. 2002. Measuring compliance and its effects on analysis in longitudinal clinical trials.
    1. Thabane L, Ma J, Chu R, Cheng J, Ismaila A, Rios LP, et al. A tutorial on pilot studies: the what, why and how. BMC Med Res Methodol. 2010;10:1–10. doi: 10.1186/1471-2288-10-1.
    1. Mullen EM. Mullen scales of early learning. Circle Pines, MN: American Guidance Services, Inc.; 1995.
    1. Statistics Canada, CANSIM, table 111–0009. Statistics Canada; [cited 2014 December 4]; Available from: .
    1. Pagano M, Gauvreau K. Principles of biostatistics. 2nd ed. Crockett C, editor. Brooks/Cole: Belmont, CA; 2000.
    1. Klerk ED, Linden SVD, Heijde DVD, Urquhart J. Facilitated analysis of data on drug regimen compliance. Stat Med. 1997;16:1653–64. doi: 10.1002/(SICI)1097-0258(19970730)16:14<1653::AID-SIM591>;2-#.
    1. PS: Power and sample size calculator. Vanderbilt University, Department of Biostatistics; [cited 2014 December 7]; Available from: .
    1. Tweel I, Askie L, Vandermeer B, Ellenberg S, Fernandes RM, Saloojee H, et al. Standard 4: determining adequate sample sizes. Pediatrics. 2012;129:S138. doi: 10.1542/peds.2012-0055G.

Source: PubMed

3
Subscribe