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• W3188388520 startingPage "1271" @default.
• W3188388520 abstract "White matter hyperintensities (WMHs) are a highly prevalent MRI marker of cerebral small vessel disease (SVD), which predict stroke and dementia risk, and are being increasingly used as a surrogate marker in clinical trials. However, the influence of study population selection on WMH progression rate has not been studied and the effect of individual patient factors for WMH growth are not fully understood.We performed a systematic review and meta-analysis of the literature on progression of WMHs in longitudinal studies to determine rates of WMH growth, and how these varied according to population characteristics and cardiovascular risk factors. We used these data to calculate necessary sample sizes for clinical trials using WMH as an endpoint.WMH growth rate was highest in SVD (2.50cc/year), intermediate in unselected stroke patients (1.29cc/year) and lower in patients with non-stroke cardiovascular disease, and with cognitive impairment. Age was significantly associated with progression (correlation coefficient 0.15cc/year, 95% CI 0.02 to 0.28cc/year) as was baseline lesion volume (0.6cc/year, 95% CI 0.13 to 1.06 cc/year). Both hypertension (OR 1.72, 95% CI 1.19 to 2.46) and current smoking (OR 1.48, 95% CI 1.02 to 2.16) were associated with WMH growth. Sample sizes for a clinical trial varied greatly with patient population selection and baseline lesion volume; estimates are provided.WMH progression varies markedly according to the characteristics of the population being studied and this will have a major impact on sample sizes required in a clinical trial. Our sample size estimates provide data for planning clinical trials using WMH as an outcome measure.CRD42020191781." @default.
• W3188388520 created "2021-08-16" @default.
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• W3188388520 date "2021-08-03" @default.
• W3188388520 modified "2023-10-06" @default.
• W3188388520 title "Rate of, and risk factors for, white matter hyperintensity growth: a systematic review and meta-analysis with implications for clinical trial design" @default.
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• W3188388520 doi "https://doi.org/10.1136/jnnp-2021-326569" @default.
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