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Case-Crossover Studies

Case-Crossover Studies. Analytic Study Designs. Case-crossover study: • Only subjects (cases) who have experienced the disease of interest are selected. • Investigator postulates a critical exposure period (“empirical induction period”) for the exposure of interest.

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Case-Crossover Studies

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  1. Case-Crossover Studies

  2. Analytic Study Designs Case-crossover study: • Only subjects (cases) who have experienced the disease of interest are selected. • Investigator postulates a critical exposure period (“empirical induction period”) for the exposure of interest. • Presence of the exposure is compared between the critical exposure period and other periods of exposure (e.g. conditional odds ratio). • Good for studying effects of transient exposures.

  3. Analytic Study Designs Case-crossover study: (B) (A) Hypothesized irrelevant (non-causal) exposure Hypothesized relevant (causal) exposure Outcome event Normal background risk “Empirical induction period” Compare presence of exposure between hypothesized non-causal (A) and hypothesized causal (B) periods of exposure

  4. Analytic Study Designs Case-crossover study: • Biased selection of controls (selection bias) is eliminated (assuming matched analysis is conducted) since controls represent the population that produced the cases. • Since each subject serves as their own control, thus, “fixed” confounders are eliminated. • However, confounding can occur from factors that vary over time and are associated with the exposure and disease of interest (e.g. smoking).

  5. Analytic Study Designs Case-crossover study: • If exposure ascertainment differs between the case and control intervals, information bias may be present. • Overestimation or underestimation of the empirical induction period results in non- differential misclassification – hence bias towards the null.

  6. Case control vs. case-crossover From the topics listed below, select whether the case-control or case-crossover study design is more appropriate.

  7. Case control vs. case-crossover From the topics listed below, select whether the case-control or case-crossover study design is more appropriate.

  8. Review of Recommended ReadingTraffic law enforcement and risk of crashes --- Case-crossover study designed to assess effect of prior driving conviction on subsequent risk of fatal vehicle crashes. --- Identified all drivers involved in fatal crashes between 1988 and 1999 in Ontario, Canada. --- Matched date of fatal crash to previous driving history records (convictions) in Ontario in 1-month period before (case period) and 13-months before (control period) crash. --- Most common prior driving conviction was speeding, with crashes and convictions more common in the summer. --- Explored how long a potential association with prior driving convictions may have persisted.

  9. Discussion Question 1 Interpret the results in figure 1 and table 2, including use of alternate control periods and among various subgroups. Do these results support the primary study hypothesis? Source: Lancet 2003; 361:2177-2182.

  10. Discussion Question 2 Interpret the results in figure 2. Do the results suggest that the effect of traffic law enforcement on risk of crashes persists over time? Source: Lancet 2003; 361:2177-2182.

  11. Discussion Question 3 Which of the following potential sources of confounding were essentially eliminated by the use of the case-crossover design? ●Age ● # prior driving convictions ●Gender ● # years as licensed driver ●Alcohol use while ● cell phone use while driving Source: Lancet 2003; 361:2177-2182.

  12. Cross-Sectional Studies

  13. Cross-Sectional Study • Both a descriptive and analytic study design. • Snapshot of the health status of populations at a certain point in time. • For each subject, exposure and disease outcome are assessed simultaneously (hence also called a “prevalence study/survey”). • Compare prevalence of disease in persons with and without the exposure of interest (e.g. prevalence ratio – same formula as risk ratio).

  14. Cross-Sectional Study Advantages: • Quick, easy, and cheap. • Can study multiple exposures and disease outcomes simultaneously. • Good for describing the magnitude and distribution of health problems.

  15. Cross-Sectional Study Disadvantages: • Prevalent rather than incident cases of disease are identified – exposures may be associated with survival rather than risk of development of disease. • “Chicken or egg” dilemma – do not know whether the exposure preceded disease, or was a consequence of disease development.

  16. Cross-Sectional Study Example: Hypothesis: Obesity is a risk factor for knee osteoarthritis Sample: 100 retirees living at “University Village”

  17. Cross-Sectional Study Medical exam + X-rays to diagnose osteoarthritis of the knee Osteoarthritis - + 50 + 40 10 Obesity - 50 20 30

  18. Cross-Sectional Study Prevalence of osteoarthritis among obese subjects: 40/50 = 0.8 Prevalence of osteoarthritis among non-obese subjects: 20/50 = 0.4 Prevalence ratio = 0.8/0.4 = 2.0

  19. Cross-Sectional Study Obese subjects are two times more likely to have osteoarthritis of the knee than non-obese subjects.

  20. Cross-Sectional Study Chicken or egg dilemma What came first? Obesity or Osteoarthritis

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