Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Epidemiology research in rheumatology—progress and pitfalls

Key Points

  • Epidemiology is the study of the distribution and determinants of disease in populations

  • The recent increase in computer power has enabled epidemiological studies to be conducted with very large databases and to explore multiple risk factors of outcomes within the same analysis

  • The main epidemiological study designs are cross-sectional, cohort and case–control

  • Clinical trials, a type of cohort study, can test the superiority, noninferiority or equivalence of two or more treatments

  • Absolute and attributable risks are more meaningful to the clinician and patient than relative risks

Abstract

Epidemiology research is a vital component of clinical studies in all medical fields. This Review provides a brief introduction to the methodology and interpretation of population and clinical epidemiology studies of musculoskeletal disorders. Data sources (including 'big data' and the issue of missing data), study design (cross-sectional, case–control and cohort studies, including clinical trial design) and the interpretation of study results are discussed with examples from the field of rheumatology, particularly using findings in patients with rheumatoid arthritis. Two or more treatments can be compared in clinical trials using a variety of study designs including superiority, noninferiority or equivalence. The different types of risk in epidemiological studies—absolute, attributable, background and relative—are important concepts in epidemiological research and their relative usefulness to clinicians and patients should be considered carefully. The potential pitfalls and challenges of generalizing the results of epidemiological studies to understanding disease aetiology and to clinical practice are also emphasized. The aim of the Review is to help readers to critically appraise published articles that use epidemiological designs or methods.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Gene–environment interaction in the aetiology of RA.
Figure 2: Gene–environment interaction in the aetiology of increased cardiovascular mortality in RA—results from the Norfolk Arthritis Register.
Figure 3: Different types of trial design comparing treatment 'A' with 'control'.

Similar content being viewed by others

References

  1. Kremer, J. The CORRONA database. Ann. Rheum. Dis. 64 (Suppl. 4), iv37–iv41 (2005).

    PubMed  PubMed Central  Google Scholar 

  2. Corrona. Corrona—data to empower [online], (2005).

  3. Symmons, D. P. M. & Silman, A. J. The Norfolk Arthritis Register. Clin. Exp. Rheum. 21; S94–S99 (2003).

    CAS  Google Scholar 

  4. Center for Disease Control and Prevention. National Health and Nutrition Examination Survey [online], (2015).

  5. UK Biobank. UK Biobank [online], (2015).

  6. Nurses' Health Study. The Nurses' Health Study [online], (2015).

  7. Askling, J. et al. Swedish registers to examine drug safety and clinical issues in RA. Ann. Rheum. Dis. 65, 707–712 (2006).

    Article  CAS  Google Scholar 

  8. Askling, J. et al. Risks of solid cancers in patients with rheumatoid arthritis and after treatment with tumour necrosis factor antagonists. Ann. Rheum. Dis. 64, 1421–1426 (2005).

    Article  CAS  Google Scholar 

  9. NHS National Institute for Health Research. The Clinical Practice Research Datalink [online], (2015).

  10. Centers for Medicare & Medicaid Services. Research, Statistics, Data & Systems [online], (2015).

  11. Kaiser Permanente. Division of Research [online], (2015).

  12. US Department of Veterans Affairs. Office of Research & Development [online], (2015).

  13. Khoury, M. J. & Ioannidis, J. P. A. Medicine. Big data meets public health. Science 346, 1054–1055 (2014).

    Article  CAS  Google Scholar 

  14. Ioannidis, J. P. A., Loy, E. Y., Poulton, R. & Chia, K. S. Researching genetic versus nongenetic determinant of disease: a comparion and proposed unification. Sci. Transl. Med. 1, 7ps8 (2009).

    Article  Google Scholar 

  15. Sarrazin, M. S. & Rosenthal, G. E. Finding pure and simple truths with administrative data. JAMA 307, 1433–1435 (2012).

    Article  Google Scholar 

  16. Little, R. J. A. & Rubin, D. B. Statistical Analysis With Missing Data 2nd edn (Wiley and Sons, 2002).

    Book  Google Scholar 

  17. Sterne, J. A. C. et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 338, b2393 (2009).

    Article  Google Scholar 

  18. Ware, J. H., Harrington, D., Hunter, D. J. & D'Agostino, R. B. Missing data. N. Engl. J. Med 367, 1353–1354 (2012).

    Article  CAS  Google Scholar 

  19. von Elm, E. et al. Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 335, 806–808 (2007).

    Article  Google Scholar 

  20. American College of Rheumatology. Practice Management [online], (2014).

  21. EULAR. The European League Against Rheumatism [online], (2015).

  22. OMERACT. Outcome Measures in Rheumatology [online], (2015).

  23. Prevoo, M. L. et al. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 38, 44–48 (1995).

    Article  CAS  Google Scholar 

  24. van Gestel, A. M. et al. Development and validation of the European League Against Rheumatism response criteria for rheumatoid arthritis. Comparison with the preliminary American College of Rheumatology and the World Health Organization/International League Against Rheumatism Criteria. Arthritis Rheum. 39, 34–40 (1996).

    Article  CAS  Google Scholar 

  25. Felson, D. T. et al. American College of Rheumatology. Preliminary definition of improvement in rheumatoid arthritis. Arthritis Rheum. 38, 727–735 (1995).

    Article  CAS  Google Scholar 

  26. Wellcome Trust Case Control Consortium et al. Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls. Nature 464, 713–720 (2010).

  27. Panoutsopoulos, K. et al. Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study. Ann. Rheum. Dis. 70, 864–867 (2011).

    Article  Google Scholar 

  28. Mirkov, M. U. et al. Genome wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis. Ann. Rheum. Dis. 72, 1375–1381 (2013).

    Article  CAS  Google Scholar 

  29. Hunt, J. R. & White, E. Retaining and tracking cohort study members. Epidemiol. Rev. 20, 57–70 (1998).

    Article  CAS  Google Scholar 

  30. Miettinen, O. S. The “case-control” study: valid selection of subjects. J. Chronic Dis. 38, 543–548 (1985).

    Article  CAS  Google Scholar 

  31. Correa, A., Stewart, W. F., Yeh, H. C. & Santos-Burgoa, C. Exposure measurement in case-control studies: reported methods and recommendations. Epidemiol. Rev. 16, 18–32 (1994).

    Article  CAS  Google Scholar 

  32. Wacholder, S., McLaughlin, J. K., Silverman, D. T. & Mandel, J. S. Selection of controls in case-control studies: I. Principles. Am. J. Epidemiol. 135, 1019–1028 (1992).

    Article  CAS  Google Scholar 

  33. Wacholder, S., Silverman, D. T., McLaughlin, J. K. & Mandel, J. S. Selection of controls in case-control studies: II. Types of controls. Am. J. Epidemiol. 135, 1029–1041 (1992).

    Article  CAS  Google Scholar 

  34. Wacholder, S., Silverman, D. T., McLaughlin, J. K. & Mandel, J. S. Selection of controls in case-control studies: III. Design options. Am. J. Epidemiol. 135, 1042–1050 (1992).

    Article  CAS  Google Scholar 

  35. Costenbader, K. H., Feskanich, D., Mandl, L. A. & Karlson, E. W. Smoking intensity, duration, and cessation, and risk of rheumatoid arthritis in women. Am. J. Med. 119, 503–511 (2006).

    Article  Google Scholar 

  36. Puett, R. C., Hart, J. E., Laden, F., Costenbader, K. H. & Karlson, E. W. Exposure to traffic pollution and increased risk of rheumatoid arthritis. Environ. Health Perspect. 117, 1065–1069 (2009).

    Article  Google Scholar 

  37. Hirakil, L. T. et al. Circulating 25-hydroxyvitamin D level and risk of developing rheumatoid arthritis. Rheumatology (Oxford) 53, 2243–2248 (2014).

    Article  Google Scholar 

  38. Lahiri, M., Morgan, C., Symmons, D. P. & Bruce, I. N. Modifiable risk factors for RA: prevention, better than cure? Rheumatology (Oxford) 51, 499–512 (2012).

    Article  CAS  Google Scholar 

  39. Stolt, P. et al. Quantification of the influence of smoking on rheumatoid arthritis: results from a population-based case-control study. Ann. Rheum. Dis. 62, 835–841 (2003).

    Article  CAS  Google Scholar 

  40. Stolt, P. et al. Silica exposure is associated with increased risk of developing rheumatoid arthritis: results from the Swedish EIRA study. Ann. Rheum. Dis. 64, 582–586 (2005).

    Article  CAS  Google Scholar 

  41. Maradit, K. H., Crowson, C. S. & Gabriel, S. E. Rochester Epidemiology Project: a unique resource for research in the rheumatic diseases. Rheum. Dis. Clin. North Am. 30, 819–834 (2004).

    Article  Google Scholar 

  42. Maradit-Kremers, H., Nicola, P. J., Crowson, C. S., Ballman, K. V. & Gabriel, S. E. Cardiovascular death in rheumatoid arthritis: a population based study. Arthritis Rheum. 52, 722–732 (2005).

    Article  Google Scholar 

  43. Goodson, N. J. et al. Mortality in early inflammatory polyarthritis: cardiovascular mortality is increased in seropositive patients. Arthritis Rheum. 46, 2010–2019 (2002).

    Article  Google Scholar 

  44. Franklin, J., Lunt, M., Bunn, D., Symmons, D. & Silman, A. Incidence of lymphoma in a large primary care derived cohort of inflammatory arthritis. Ann. Rheum. Dis. 65, 617–622 (2006).

    Article  CAS  Google Scholar 

  45. Bukhari, M. et al. The performance of anti-cyclic citrullinated peptide antibodies in predicting the severity of radiologic damage in inflammatory polyarthritis: result from the Norfolk Arthritis Register. Arthritis Rheum. 56, 2929–2935 (2007).

    Article  CAS  Google Scholar 

  46. Schmajuk, G. et al. Receipt of disease-modifying antirheumatic drugs among patients with rheumatoid arthritis in Medicare managed care plans. JAMA 305, 480–486 (2011).

    Article  CAS  Google Scholar 

  47. Solomon, D. H. et al. Association between disease-modifying antirheumatic drugs and diabetes risk in patients with rheumatoid arthritis and psoriasis. JAMA 305, 2525–2531 (2001).

    Article  Google Scholar 

  48. Klareskog, L. et al. A new model for the aetiology of rheumatoid arthritis: smoking may trigger HLA-DR (shared epitope)-restricted immune reactions to autoantigens modified by citrullination. Arthritis Rheum. 54, 38–46 (2006).

    Article  CAS  Google Scholar 

  49. Farragher, T. et al. Association of HLA-DR1 gene with premature death, especially from cardiovascular disease, in patients with rheumatoid arthritis. Arthritis Rheum. 58, 359–369 (2008).

    Article  Google Scholar 

  50. Yarwood, A. et al. A weighted prediction score using all know susceptibility variants to estimate rheumatoid arthritis risk. Ann. Rheum. Dis. 74, 170–176 (2015).

    Article  Google Scholar 

  51. Karlson, E. W. et al. Association of environmental and genetic factors and gene-environment interactions with risk of developing rheumatoid arthritis. Arthritis Care Res. (Hoboken) 65, 1147–1156 (2013).

    Article  Google Scholar 

  52. Deane, K. D. Can rheumatoid arthritis be prevented? Best Prac t. Res. Clin. Rheumatol. 27, 467–485 (2013).

    Article  Google Scholar 

  53. Eder, L. et al. Association between environmental factors and onset of psoriatic arthritis in patients with psoriasis. Arthritis Care Res. (Hoboken) 63, 1091–1097 (2011).

    Article  Google Scholar 

  54. Singh, J. A., Reddy, S. G. & Kundukulam, J. Risk factors for gout and prevention: a systematic review of the literature. Curr. Opin. Rheumatol. 23, 192–202 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Simard, J. F. & Costenbader, K. H. What can epidemiology tell us about systemic lupus erythematosus? Int. J. Clin. Pract. 61, 1170–1180 (2007).

    Article  CAS  Google Scholar 

  56. Felson, D. T. et al. Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann. Intern. Med. 133, 635–646 (2000).

    Article  CAS  Google Scholar 

  57. Hackshaw, A. K. A Concise Guide to Clinical Trials (Wiley-Blackwell, 2009).

    Book  Google Scholar 

  58. Yoo, D. H. et al. A randomised, double-blind, parallel-group study to demonstrate equivalence in efficacy and safety of CT-P13 compared with innovator infliximab when coadministered with methotrexate in patients with active rheumatoid arthritis: the PLANETRA study. Ann. Rheum. Dis. 72, 1613–1620 (2013).

    Article  CAS  Google Scholar 

  59. Bingham III, C. O. et al. Efficacy and safety of etoricoxib 30 mg and celecoxib 200 mg in the treatment of osteoarthritis in two identically designed randomised placebo controlled non-inferiority studies. Rheumatology (Oxford) 46, 496–507 (2007).

    Article  Google Scholar 

  60. Le Henannf, A., Giraudeau, B., Baron, G. & Ravaud, P. Quality of reporting of non-inferiority and equivalence randomised trials. JAMA 205, 1147–1151 (2006).

    Article  Google Scholar 

  61. Head, S. J., Kaul, S., Bogers, A. J. & Kappetein, A. P. Non-inferiority study design: lessons to be learned from cardiovascular trials. Eur. Heart J. 33, 1318–1324 (2012).

    Article  Google Scholar 

  62. Piaggio, G. et al. Reporting of noninferiority and equivalence randomized trials: extension of the CONSORT 2010 statement. JAMA 308, 2594–2604 (2012).

    Article  CAS  Google Scholar 

  63. Strom, B. L., Kimmel, S. E. & Hennessey, S. (eds) Pharmacoepidemiology 5th edn (Wiley-Blackwell, 2012).

    Book  Google Scholar 

  64. Isaacs, J. D. & Ferraccioli, G. The need for personalised medicine for rheumatoid arthritis. Ann. Rheum. Dis. 70, 4–7 (2011).

    Article  CAS  Google Scholar 

  65. Galloway, J. B. et al. Anti-TNF therapy is associated with an increased risk of serious infections in patients with rheumatoid arthritis especially in the first 6 month of treatment, updated results from the British Society for Rheumatology Biologics Register with special emphasis on risk in the elderly. Rheumatology (Oxford) 50, 124–131 (2011).

    Article  CAS  Google Scholar 

  66. Cook, R. J. & Sackett, D. L. The number needed to treat: a clinically useful measure of treatment effect. BMJ 310, 452–454 (1995).

    Article  CAS  Google Scholar 

  67. Manzi, S. et al. Age-specific incidence rates of myocardial infarction and angina in women with systemic lupus erythematosus: comparison with the Framingham Study. Am. J. Epidemiol. 145, 408–415 (1997).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Deborah P. M. Symmons.

Ethics declarations

Competing interests

The author declares no competing financial interests.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Symmons, D. Epidemiology research in rheumatology—progress and pitfalls. Nat Rev Rheumatol 11, 631–638 (2015). https://doi.org/10.1038/nrrheum.2015.92

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrrheum.2015.92

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing