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Hébert HL, Pascal MM, Smith BH, Wynick D, Bennett DL. Big data, big consortia, and pain: UK Biobank, PAINSTORM, and DOLORisk. Pain Rep 2023; 8:e1086. [PMID: 38225956 PMCID: PMC10789453 DOI: 10.1097/pr9.0000000000001086] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 01/17/2024] Open
Abstract
Chronic pain (CP) is a common and often debilitating disorder that has major social and economic impacts. A subset of patients develop CP that significantly interferes with their activities of daily living and requires a high level of healthcare support. The challenge for treating physicians is in preventing the onset of refractory CP or effectively managing existing pain. To be able to do this, it is necessary to understand the risk factors, both genetic and environmental, for the onset of CP and response to treatment, as well as the pathogenesis of the disorder, which is highly heterogenous. However, studies of CP, particularly pain with neuropathic characteristics, have been hindered by a lack of consensus on phenotyping and data collection, making comparisons difficult. Furthermore, existing cohorts have suffered from small sample sizes meaning that analyses, especially genome-wide association studies, are insufficiently powered. The key to overcoming these issues is through the creation of large consortia such as DOLORisk and PAINSTORM and biorepositories, such as UK Biobank, where a common approach can be taken to CP phenotyping, which allows harmonisation across different cohorts and in turn increased study power. This review describes the approach that was used for studying neuropathic pain in DOLORisk and how this has informed current projects such as PAINSTORM, the rephenotyping of UK Biobank, and other endeavours. Moreover, an overview is provided of the outputs from these studies and the lessons learnt for future projects.
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Affiliation(s)
- Harry L. Hébert
- Chronic Pain Research Group, Division of Population Health and Genomics, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - Mathilde M.V. Pascal
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Blair H. Smith
- Chronic Pain Research Group, Division of Population Health and Genomics, Ninewells Hospital & Medical School, University of Dundee, Dundee, United Kingdom
| | - David Wynick
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David L.H. Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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Hébert HL, Veluchamy A, Baskozos G, Fardo F, Van Ryckeghem D, Pearson ER, Colvin LA, Crombez G, Bennett DLH, Meng W, Palmer CNA, Smith BH. Development and external validation of multivariable risk models to predict incident and resolved neuropathic pain: a DOLORisk Dundee study. J Neurol 2023; 270:1076-1094. [PMID: 36355188 PMCID: PMC9886655 DOI: 10.1007/s00415-022-11478-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/12/2022]
Abstract
Neuropathic pain is difficult to treat, and an understanding of the risk factors for its onset and resolution is warranted. This study aimed to develop and externally validate two clinical risk models to predict onset and resolution of chronic neuropathic pain. Participants of Generation Scotland: Scottish Family Health Study (GS; general Scottish population; n = 20,221) and Genetic of Diabetes Audit and Research in Tayside Scotland (GoDARTS; n = 5236) were sent a questionnaire on neuropathic pain and followed- -up 18 months later. Chronic neuropathic pain was defined using DN4 scores (≥ 3/7) and pain for 3 months or more. The models were developed in GS using logistic regression with backward elimination based on the Akaike information criterion. External validation was conducted in GoDARTS and assessed model discrimination (ROC and Precision-Recall curves), calibration and clinical utility (decision curve analysis [DCA]). Analysis revealed incidences of neuropathic pain onset (6.0% in GS [236/3903] and 10.7% in GoDARTS [61/571]) and resolution (42.6% in GS [230/540] and 23.7% in GoDARTS [56/236]). Psychosocial and lifestyle factors were included in both onset and resolved prediction models. In GoDARTS, these models showed adequate discrimination (ROC = 0.636 and 0.699), but there was evidence of miscalibration (Intercept = - 0.511 and - 0.424; slope = 0.623 and 0.999). The DCA indicated that the models would provide clinical benefit over a range of possible risk thresholds. To our knowledge, these are the first externally validated risk models for neuropathic pain. The findings are of interest to patients and clinicians in the community, who may take preventative or remedial measures.
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Affiliation(s)
- Harry L Hébert
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Abirami Veluchamy
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Georgios Baskozos
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Francesca Fardo
- Danish Pain Research Center, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Dimitri Van Ryckeghem
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
- Section Experimental Health Psychology, Clinical Psychological Science, Departments, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Ewan R Pearson
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Lesley A Colvin
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Geert Crombez
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | - David L H Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Weihua Meng
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Blair H Smith
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK.
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