CoChat
Sign Up
Cited by 36

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Design choices for observational studies of the effect of exposure on disease incidence

Gail, Mitchell H, Altman, Douglas G, Cadarette, Suzanne M, Collins, Gary, Evans, Stephen JW, Sekula, Peggy, Williamson, Elizabeth, Woodward, Mark·2019·BMJ Open
DOI 10.1136/bmjopen-2019-031031PMC PMC6924819
Open this paper in CoChat — free account

Abstract

The purpose of this paper is to help readers choose an appropriate observational study design for measuring an association between an exposure and disease incidence. We discuss cohort studies, sub-samples from cohorts (case-cohort and nested case-control designs), and population-based or hospital-based case-control studies. Appropriate study design is the foundation of a scientifically valid observational study. Mistakes in design are often irremediable. Key steps are understanding the scientific aims of the study and what is required to achieve them. Some designs will not yield the information required to realise the aims. The choice of design also depends on the availability of source populations and resources. Choosing an appropriate design requires balancing the pros and cons of various designs in view of study aims and practical constraints. We compare various cohort and case-control designs to estimate the effect of an exposure on disease incidence and mention how certain design features can reduce threats to study validity.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/bmjopen-2019-031031

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Key points.
Figure 1 Key points.CC BY-NC · PubMed Central
Figure 2 Designs for estimating an association between an exposure and disease incidence.
Figure 2 Designs for estimating an association between an exposure and disease incidence.CC BY-NC · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 42

  1. Cornfield, 1959, Smoking and lung cancer: recent evidence and a discussion of some questions, J Natl Cancer Inst, 22, 173
  2. 10.1177/003591576505800503 · DOI · Paper page
  3. 10.1093/oxfordjournals.aje.a116396 · DOI · Paper page
  4. 10.1093/oxfordjournals.aje.a116397 · DOI
  5. 10.1093/oxfordjournals.aje.a116398 · DOI
  6. Cox, 2016, The design of empirical studies: towards a unified view, Eur J Epidemiol, 31, 217, 10.1007/s10654-016-0135-9 · DOI
  7. Breslow, 1980, Statistical methods in cancer research. Volume I - The analysis of case-control studies, IARC Sci Publ, 32, 5
  8. Rothman KJ , Greenland S , Lash TL . Modern epidemiology. 3rd edn. Philadelphia: Walters Kluwer | Lippincott Williams and Wilkins, 2008.
  9. Woodward M . Epidemiology study design and data analysis. 3rd edn. Boca Raton: CRC Press Taylor and Francis Group, 2014.
  10. 10.1016/j.ijsu.2014.07.014 · DOI · Paper page
  11. 10.1016/j.ijsu.2014.07.013 · DOI · Paper page
  12. 10.1093/biomet/73.1.1 · DOI
  13. 10.2307/2345280 · DOI
  14. Rothman KJ , Greenland S . Modern epidemiology. Philadelphia: Lippincott-Raven, 1998.
  15. Pfeiffer RM , Gail MH . Absolute risk: methods and applications in clinical management and public health. Baton Rouge: Chapman and Hall/CRC Taylor and Francis Group, 2017. · DOI
  16. Cornfield, 1951, A method of estimating comparative rates from clinical data; applications to cancer of the lung, breast, and cervix, J Natl Cancer Inst, 11, 1269
  17. 10.1136/bmj.2.4682.739 · DOI · Paper page
  18. Gail, 1996, Statistics in action, J Am Stat Assoc, 91, 1, 10.1080/01621459.1996.10476659 · DOI
  19. Cox, 1972, Regression models and Life-Tables, J R Stat Soc Series B, 34, 187, 10.1111/j.2517-6161.1972.tb00899.x · DOI · Paper page
  20. 10.2307/2533977 · DOI
  21. 10.1093/oxfordjournals.aje.a113439 · DOI
  22. 10.1093/ije/22.6.1189 · DOI · Paper page
  23. 10.1093/biomet/65.1.153 · DOI
  24. 10.1136/bmj.1.4877.1451 · DOI
  25. 10.1136/bmj.2.5001.1071 · DOI
  26. 10.1093/ije/dyq257 · DOI
  27. Pearce N . Analysis of matched case-control studies. BMJ 2016;352.doi:10.1136/bmj.i969 · DOI
  28. 10.1097/01.ede.0000152522.80261.e3 · DOI
  29. 10.1093/jnci/djp096 · DOI
  30. 10.1002/sim.6082 · DOI
  31. 10.1038/bjc.1976.220 · DOI · Paper page
  32. Gail MH , Haneuse S . Power and Sample Size for Case-Control Studies. In: Borgan O , Breslow NE , Chatterjee N , eds. Handbook of statistical methods for case-control studies. Boca Raton: CRC Press/Chapman and Hall, 2018. · DOI
  33. 10.1002/sim.4780080803 · DOI
  34. Rutten-Jacobs LCA , Larsson SC , Malik R , et al . Genetic risk, incident stroke, and the benefits of adhering to a healthy lifestyle: cohort study of 306 473 UK Biobank participants. BMJ 2018;363.doi:10.1136/bmj.k4168 · DOI
  35. 10.2307/2529548 · DOI · Paper page
  36. 10.2307/2287093 · DOI
  37. Rivera, 2016, Using the whole cohort in the analysis of countermatched samples, Biometrics, 72, 382, 10.1111/biom.12419 · DOI
  38. 10.1007/s10985-012-9214-8 · DOI
  39. 10.2307/2285927 · DOI
  40. 10.1016/0021-9681(76)90073-4 · DOI
  41. 10.1093/biomet/74.1.191 · DOI
  42. Borgan O , Breslow NE , Chatterjee N , et al . Handbook of statistical methods for case-control studies. Boca Raton: CRC Press/Chapman and Hall, 2018. · DOI

Cited by

Sorted by citations

See all 36

Metadata

Authors
Gail, M. H., Altman, D. G., Cadarette, S. M., Collins, G., Evans, S. J., Sekula, P., Williamson, E., & Woodward, M.
Affiliations
  • Biostatistics Branch, National Cancer Institute, Rockville, Maryland, USA
  • Nuffield Department of Orthopaedics, Centre for Statistics in Medicine, Oxford, UK
  • Faculty of Pharmacy and School of Public Health, University of Toronto, Toronto, Ontario, Canada
  • Centre for Statistics in Medicine, University of Oxford, Oxford, UK
  • Medical Statistics Unit, London School of Hygiene and Tropical Medicine, London, UK
  • Institute of Genetic Epidemiology and Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
  • Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
  • The George Institute for Global Health, Oxford University UK and University of New South Wales, Sydney, New South Wales, Australia
ORCID
Venue
BMJ Open
Publisher
BMJ
Published
2019-12
Volume
9
Issue
12
Pages
e031031
ISSN
2044-6055
DOI
10.1136/bmjopen-2019-031031
PMC
PMC6924819
Cited by
36
References
3
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review