Publication: Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials
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Issued Date
2019-12-18
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14752875
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2-s2.0-85076888374
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Mahidol University
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SCOPUS
Bibliographic Citation
Malaria Journal. Vol.18, No.1 (2019)
Suggested Citation
Pimnara Peerawaranun, Jordi Landier, Francois H. Nosten, Thuy Nhien Nguyen, Tran Tinh Hien, Rupam Tripura, Thomas J. Peto, Koukeo Phommasone, Mayfong Mayxay, Nicholas P.J. Day, Arjen Dondorp, Nick White, Lorenz Von Seidlein, Mavuto Mukaka Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials. Malaria Journal. Vol.18, No.1 (2019). doi:10.1186/s12936-019-3062-x Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/50978
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Title
Intracluster correlation coefficients in the Greater Mekong Subregion for sample size calculations of cluster randomized malaria trials
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Sciences Economiques et Sociales de la Santé et Traitement de l'Information Médicale
Mahidol University
Nuffield Department of Clinical Medicine
Amsterdam UMC - University of Amsterdam
Mahosot Hospital
Amsterdam Institute for Global Health and Development
University of Health Sciences
Oxford University Clinical Research Unit
Mahidol University
Nuffield Department of Clinical Medicine
Amsterdam UMC - University of Amsterdam
Mahosot Hospital
Amsterdam Institute for Global Health and Development
University of Health Sciences
Oxford University Clinical Research Unit
Abstract
© 2019 The Author(s). Background: Sample size calculations for cluster randomized trials are a recognized methodological challenge for malaria research in pre-elimination settings. Positively correlated responses from the participants in the same cluster are a key feature in the estimated sample size required for a cluster randomized trial. The degree of correlation is measured by the intracluster correlation coefficient (ICC) where a higher coefficient suggests a closer correlation hence less heterogeneity within clusters but more heterogeneity between clusters. Methods: Data on uPCR-detected Plasmodium falciparum and Plasmodium vivax infections from a recent cluster randomized trial which aimed at interrupting malaria transmission through mass drug administrations were used to calculate the ICCs for prevalence and incidence of Plasmodium infections. The trial was conducted in four countries in the Greater Mekong Subregion, Laos, Myanmar, Vietnam and Cambodia. Exact and simulation approaches were used to estimate ICC values for both the prevalence and the incidence of parasitaemia. In addition, the latent variable approach to estimate ICCs for the prevalence was utilized. Results: The ICCs for prevalence ranged between 0.001 and 0.082 for all countries. The ICC from the combined 16 villages in the Greater Mekong Subregion were 0.26 and 0.21 for P. falciparum and P. vivax respectively. The ICCs for incidence of parasitaemia ranged between 0.002 and 0.075 for Myanmar, Cambodia and Vietnam. There were very high ICCs for incidence in the range of 0.701 to 0.806 in Laos during follow-up. Conclusion: ICC estimates can help researchers when designing malaria cluster randomized trials. A high variability in ICCs and hence sample size requirements between study sites was observed. Realistic sample size estimates for cluster randomized malaria trials in the Greater Mekong Subregion have to assume high between cluster heterogeneity and ICCs. This work focused on uPCR-detected infections; there remains a need to develop more ICC references for trials designed around prevalence and incidence of clinical outcomes. Adequately powered trials are critical to estimate the benefit of interventions to malaria in a reliable and reproducible fashion.