Clustering of continuous and binary outcomes at the general practice level in individually randomised studies in primary care - a review of 10 years of primary care trials
Clustering of continuous and binary outcomes at the general practice level in individually randomised studies in primary care - a review of 10 years of primary care trials
Background: in randomised controlled trials, the assumption of independence of individual observations is fundamental to the design, analysis and interpretation of studies. However, in individually randomised trials in primary care, this assumption may be violated because patients are naturally clustered within primary care practices. Ignoring clustering may lead to a loss of power or, in some cases, type I error.
Methods: Clustering can be quantified by intra-cluster correlation (ICC), a measure of the similarity between individuals within a cluster with respect to a particular outcome. We reviewed 17 trials undertaken by the Department of Primary Care at the University of Southampton over the last ten years. We calculated the ICC for the primary and secondary outcomes in each trial at the practice level and determined whether ignoring practice-level clustering still gave valid inferences. Where multiple studies collected the same outcome measure, the median ICC was calculated for that outcome.
Results: The median intra-cluster correlation (ICC) for all outcomes was 0.016, with interquartile range 0.00-0.03.
The median ICC for symptom severity was 0.02 (interquartile range (IQR) 0.01 to 0.07) and for reconsultation with new or worsening symptoms was 0.01 (IQR 0.00, 0.07). For HADS anxiety the ICC was 0.04 (IQR 0.02, 0.05) and for HADS depression was 0.02 (IQR 0.00, 0.05). The median ICC for EQ5D-3L was 0.01 (IQR 0.01, 0.04)
Conclusions: There is evidence of clustering in individually randomised trials primary care. The non-zero ICC suggests that, depending on study design, clustering may not be ignorable. It is important that this is fully considered at the study design phase.
Clustering, GP practice, Individually randomised trial, Intra-cluster correlation, Primary care
Stuart, Beth
626862fc-892b-4f6d-9cbb-7a8d7172b209
Becque, Taeko
ecd1b4d5-4db8-4442-81c2-04aa291cf2fd
Moore, Michael
1be81dad-7120-45f0-bbed-f3b0cc0cfe99
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
15 April 2020
Stuart, Beth
626862fc-892b-4f6d-9cbb-7a8d7172b209
Becque, Taeko
ecd1b4d5-4db8-4442-81c2-04aa291cf2fd
Moore, Michael
1be81dad-7120-45f0-bbed-f3b0cc0cfe99
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
Stuart, Beth, Becque, Taeko, Moore, Michael and Little, Paul
(2020)
Clustering of continuous and binary outcomes at the general practice level in individually randomised studies in primary care - a review of 10 years of primary care trials.
BMC Medical Research Methodology, 20 (1), [83].
(doi:10.1186/s12874-020-00971-7).
Abstract
Background: in randomised controlled trials, the assumption of independence of individual observations is fundamental to the design, analysis and interpretation of studies. However, in individually randomised trials in primary care, this assumption may be violated because patients are naturally clustered within primary care practices. Ignoring clustering may lead to a loss of power or, in some cases, type I error.
Methods: Clustering can be quantified by intra-cluster correlation (ICC), a measure of the similarity between individuals within a cluster with respect to a particular outcome. We reviewed 17 trials undertaken by the Department of Primary Care at the University of Southampton over the last ten years. We calculated the ICC for the primary and secondary outcomes in each trial at the practice level and determined whether ignoring practice-level clustering still gave valid inferences. Where multiple studies collected the same outcome measure, the median ICC was calculated for that outcome.
Results: The median intra-cluster correlation (ICC) for all outcomes was 0.016, with interquartile range 0.00-0.03.
The median ICC for symptom severity was 0.02 (interquartile range (IQR) 0.01 to 0.07) and for reconsultation with new or worsening symptoms was 0.01 (IQR 0.00, 0.07). For HADS anxiety the ICC was 0.04 (IQR 0.02, 0.05) and for HADS depression was 0.02 (IQR 0.00, 0.05). The median ICC for EQ5D-3L was 0.01 (IQR 0.01, 0.04)
Conclusions: There is evidence of clustering in individually randomised trials primary care. The non-zero ICC suggests that, depending on study design, clustering may not be ignorable. It is important that this is fully considered at the study design phase.
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Clustering of continuous and binary
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Accepted/In Press date: 11 April 2020
e-pub ahead of print date: 15 April 2020
Published date: 15 April 2020
Additional Information:
Funding Information:
This paper presents independent research funded by the National Institute for Health Research School for Primary Care Research (NIHR SPCR grant number 320). The views expressed are those of the author(s) and not necessarily those of the NIHR, the NHS or the Department of Health. The funder played no role in any of the design of the study, collection, analysis, and interpretation of data, writing the manuscript.
Publisher Copyright:
© 2020 The Author(s).
Keywords:
Clustering, GP practice, Individually randomised trial, Intra-cluster correlation, Primary care
Identifiers
Local EPrints ID: 439441
URI: http://eprints.soton.ac.uk/id/eprint/439441
ISSN: 1471-2288
PURE UUID: 42dcd4a4-4f67-4966-bb13-40f795ff98f9
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Date deposited: 23 Apr 2020 16:30
Last modified: 12 Jul 2024 01:51
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