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Validating the portal population of the United Kingdom Multiple Sclerosis Register

Validating the portal population of the United Kingdom Multiple Sclerosis Register
Validating the portal population of the United Kingdom Multiple Sclerosis Register

The UK Multiple Sclerosis Register (UKMSR) is a large cohort study designed to capture ‘real world’ information about living with multiple sclerosis (MS) in the UK from diverse sources. The primary source of data is directly from people with Multiple Sclerosis (pwMS) captured by longitudinal questionnaires via an internet portal. This population's diagnosis of MS is self-reported and therefore unverified. The second data source is clinical data which is captured from MS Specialist Treatment centres across the UK. This includes a clinically confirmed diagnosis of MS (by Macdonald criteria) for consented patients. A proportion of the internet population have also been consented at their hospital making comparisons possible. This dataset is called the ‘linked dataset’. The purpose of this paper is to examine the characteristics of the three datasets: the self-reported portal data, clinical data and linked data, in order to assess the validity of the self-reported portal data. The internet (n = 11,021) and clinical (n = 3,003) populations were studied for key shared characteristics. We found them to be closely matched for mean age at diagnosis (clinical = 37.39, portal = 39.28) and gender ratio (female %, portal = 73.1, clinical = 75.2). The Two Sample Kolmogorov-Smirnov test was for the continuous variables to examine is they were drawn from the same distribution. The null hypothesis was rejected only for age at diagnosis (D = 0.078, p < 0.01). The populations therefore, were drawn from different distributions, as there are more patients with relapsing disease in the clinical cohort. In all other analyses performed, the populations were shown to be drawn from the same distribution. Our analysis has shown that the UKMSR portal population is highly analogous to the entirely clinical (validated) population. This supports the validity of the self-reported diagnosis and therefore that the portal population can be utilised as a viable and valid cohort of people with Multiple Sclerosis for study.

Data linkage, Longitudinal, Multiple sclerosis, PROMs, Research register, Validation
2211-0348
3-10
Middleton, R.M.
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Rodgers, W.J.
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Chataway, J.
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Schmierer, K.
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Rog, D.
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Galea, I.
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Lockhart-Jones, H.
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Wilson, H.
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Middleton, R.M.
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Rodgers, W.J.
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Chataway, J.
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Schmierer, K.
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Rog, D.
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Galea, I.
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Akbari, A.
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Tuite-Dalton, K.
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Lockhart-Jones, H.
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Griffiths, D.
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Jones, K.H.
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Al-Din, A.
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Craner, M.
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Evangelou, N.
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Harman, P.
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Harrower, T.
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Hobart, J.
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Husseyin, H.
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Kasti, M.
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Kipps, C.
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McDonnell, G.
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Owen, C.
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Pearson, O.
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Rashid, W.
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Wilson, H.
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Ford, D.V.
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Middleton, R.M., Rodgers, W.J., Chataway, J., Schmierer, K., Rog, D., Galea, I., Akbari, A., Tuite-Dalton, K., Lockhart-Jones, H., Griffiths, D., Noble, D.G., Jones, K.H., Al-Din, A., Craner, M., Evangelou, N., Harman, P., Harrower, T., Hobart, J., Husseyin, H., Kasti, M., Kipps, C., McDonnell, G., Owen, C., Pearson, O., Rashid, W., Wilson, H. and Ford, D.V. (2018) Validating the portal population of the United Kingdom Multiple Sclerosis Register. Multiple Sclerosis and Related Disorders, 24, 3-10. (doi:10.1016/j.msard.2018.05.015).

Record type: Article

Abstract

The UK Multiple Sclerosis Register (UKMSR) is a large cohort study designed to capture ‘real world’ information about living with multiple sclerosis (MS) in the UK from diverse sources. The primary source of data is directly from people with Multiple Sclerosis (pwMS) captured by longitudinal questionnaires via an internet portal. This population's diagnosis of MS is self-reported and therefore unverified. The second data source is clinical data which is captured from MS Specialist Treatment centres across the UK. This includes a clinically confirmed diagnosis of MS (by Macdonald criteria) for consented patients. A proportion of the internet population have also been consented at their hospital making comparisons possible. This dataset is called the ‘linked dataset’. The purpose of this paper is to examine the characteristics of the three datasets: the self-reported portal data, clinical data and linked data, in order to assess the validity of the self-reported portal data. The internet (n = 11,021) and clinical (n = 3,003) populations were studied for key shared characteristics. We found them to be closely matched for mean age at diagnosis (clinical = 37.39, portal = 39.28) and gender ratio (female %, portal = 73.1, clinical = 75.2). The Two Sample Kolmogorov-Smirnov test was for the continuous variables to examine is they were drawn from the same distribution. The null hypothesis was rejected only for age at diagnosis (D = 0.078, p < 0.01). The populations therefore, were drawn from different distributions, as there are more patients with relapsing disease in the clinical cohort. In all other analyses performed, the populations were shown to be drawn from the same distribution. Our analysis has shown that the UKMSR portal population is highly analogous to the entirely clinical (validated) population. This supports the validity of the self-reported diagnosis and therefore that the portal population can be utilised as a viable and valid cohort of people with Multiple Sclerosis for study.

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Validating the Portal Population of the MS Register_preprint - Accepted Manuscript
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More information

Accepted/In Press date: 22 May 2018
e-pub ahead of print date: 25 May 2018
Published date: 1 August 2018
Keywords: Data linkage, Longitudinal, Multiple sclerosis, PROMs, Research register, Validation

Identifiers

Local EPrints ID: 422712
URI: http://eprints.soton.ac.uk/id/eprint/422712
ISSN: 2211-0348
PURE UUID: 6c1c2e66-de1f-4582-ab68-661a67a6144c
ORCID for I. Galea: ORCID iD orcid.org/0000-0002-1268-5102

Catalogue record

Date deposited: 31 Jul 2018 16:30
Last modified: 26 Nov 2021 05:21

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Contributors

Author: R.M. Middleton
Author: W.J. Rodgers
Author: J. Chataway
Author: K. Schmierer
Author: D. Rog
Author: I. Galea ORCID iD
Author: A. Akbari
Author: K. Tuite-Dalton
Author: H. Lockhart-Jones
Author: D. Griffiths
Author: D.G. Noble
Author: K.H. Jones
Author: A. Al-Din
Author: M. Craner
Author: N. Evangelou
Author: P. Harman
Author: T. Harrower
Author: J. Hobart
Author: H. Husseyin
Author: M. Kasti
Author: C. Kipps
Author: G. McDonnell
Author: C. Owen
Author: O. Pearson
Author: W. Rashid
Author: H. Wilson
Author: D.V. Ford

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