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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
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
1471-2288
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
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).

Record type: Article

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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More information

Accepted/In Press date: 11 April 2020
e-pub ahead of print date: 15 April 2020
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
ORCID for Beth Stuart: ORCID iD orcid.org/0000-0001-5432-7437
ORCID for Michael Moore: ORCID iD orcid.org/0000-0002-5127-4509

Catalogue record

Date deposited: 23 Apr 2020 16:30
Last modified: 10 Jan 2022 02:51

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