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Measures of association

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1 Measures of association

2 Intermediate methods in observational epidemiology 2008
Measures of Association

3 1) Measures of association based on ratios
Cohort studies Relative risk (RR) Odds ratio (OR) Case control studies OR of exposure and OR of disease OR when the controls are a sample of the total population Prevalence ratio (or Prevalence OR) as an estimate of the RR 2) Measures of association based on absolute differences: attributable risk

4 Cohort studies Hypothetical cohort study of the one-year incidence (q) of acute myocardial infarction for individuals with severe systolic hypertension (HTN, ≥180 mm Hg) or normal systolic blood pressure (<120 mm Hg).

5 The OR can also be calculated from the “cross-products ratio” if the table is organized exactly as above :

6 When (and only when) the OR is used to estimate the RR, there is a “built-in” bias:
Example:

7 IN GENERAL: The OR is always further away from 1.0 than the RR. The higher the incidence, the higher the discrepancy.

8 Relationship between RR and OR
… when probability of the event (q) is low: or, in other words, (1-q)  1, and thus, the “built-in bias” term, and OR  RR. Example:

9 Relationship between RR and OR
… when probability of the event (q) is high: Example: Cohort study of the one-year recurrence of acute myocardial infarction (MI) among MI survivors with severe systolic hypertension (HTN, ≥180 mm Hg) and normal systolic blood pressure (<120 mm Hg). q 0.36 0.06

10 OR vs. RR: Advantages OR can be estimated from logistic regression.
OR can be estimated from a case-control study

11 Case-control studies A) Odds ratio of exposure and odds ratio of disease
Hypothetical cohort study of the one-year incidence of acute myocardial infarction for individuals with severe systolic hypertension (HTN, 180 mm Hg) and normal systolic blood pressure (<120 mm Hg). same Hypothetical case-control study assuming that all members of the cohort (cases and non cases) were identified Retrospective (case-control) studies can estimate the OR of disease because: ORexposure = ORdisease Because ORexp = ORdis, interpretation of the OR is always “prospective”.

12 Calculation of the Odds Ratios: Example of Use of Salicylates and Reye’s Syndrome
140 27 Total 87 1 No (26/1) ÷ (53/87) = 43.0 53 26 Yes Odds Ratios Controls Cases Past use of salicylates Preferred Interpretation: Children using salicylates have an odds (≈risk) of Reye’s syndrome 43 times higher than that of non-users. Another interpretation (less useful): Odds of past salicylate use is 43 times greater in cases than in controls. (Hurwitz et al, 1987, cited by Lilienfeld & Stolley, 1994)

13 Cohort study: In a retrospective (case-control) study, an unbiased sample of the cases and controls yields an unbiased OR It is not necessary that the sampling fraction be the same in both cases and controls. For example, a majority of cases (e.g., 90%) and a small sample of controls (e.g., 20%) could be chosen (assume no random variability). (As cases are less frequent, the sampling fraction for cases is usually greater than that for controls).

14 Case-control studies B) OR when controls are a sample of the total population
In a case-control study, when the control group is a sample of the total population (rather than only of the non-cases), the odds ratio of exposure is an unbiased estimate of the RELATIVE RISK

15 Example: Hypothetical cohort study of the one-year recurrence of acute myocardial infarction (MI) among MI survivors with severe systolic hypertension (HTN, ≥180 mm Hg) or normal systolic blood pressure (<120 mm Hg).

16 Example: Hypothetical cohort study of the one-year recurrence of acute myocardial infarction (MI) among MI survivors with severe systolic hypertension (HTN, 180+ mm Hg) or normal systolic blood pressure (<120 mm Hg). Using a traditional case-control strategy, cases of recurrent MI can be compared to non-cases, i.e., individuals without recurrent MI:

17 Example: Hypothetical cohort study of the one-year recurrence of acute myocardial infarction (MI) among MI survivors with severe systolic hypertension (HTN, 180+ mm Hg) or normal systolic blood pressure (<120 mm Hg). Using a case-cohort strategy, the controls are formed by the total population: Using a traditional case-control strategy, cases of recurrent MI are compared to non-cases, i.e., individuals without recurrent MI:

18 Note that it is not necessary to have a total group of cases and non-cases or the total population to assess an association in a case-control study. What is needed is a sample estimate of cases and either non-cases (to obtain the odds ratio of disease) or the total population (to obtain the relative risk). Example: samples of 20% cases and 10% total population: Thus… RR= unbiased exposure odds estimate in cases divided by unbiased exposure odds estimate in the total population.

19 To summarize, in a case-control study:

20 How to calculate the OR when there are more than two exposure categories
Example: Univariate analysis of the relationship between parity and eclampsia.* 1.0 (Reference) (21/11)÷(27/40)=2.9 (68/11)÷(33/40)=7.5 * Abi-Said et al: Am J Epidemiol 1995;142:

21 How to calculate the OR when there are more than two exposure categories
Example: Univariate analysis of the relationship between parity and eclampsia.* * Abi-Said et al: Am J Epidemiol 1995;142: Correct display: Log scale Baseline is 1.0

22 A note on the use of estimates from a cross-sectional study (prevalence ratio, OR) to estimate the RR If the prevalence is low (~≤5%)  If this ratio= 1.0 Prevalence Odds= Duration (prognosis) of the disease after onset is independent of exposure (similar in exposed and unexposed)... However, if exposure is also associated with shorter survival (D+ < D-), D+/D- <1  the prevalence ratio will underestimate the RR. Example? Smoking and emphysema

23 Attributable risk in the exposed:
Measures of association based on absolute differences (absolute measures of “effect”) Attributable risk in the exposed: The excess risk (e.g., incidence) among individuals exposed to a certain risk factor that can be attributed to the risk factor per se: 20/1000 ARexp Incidence (per 1000) 10/1000 Or, expressed as a proportion (e.g., percentage): Unexposed Exposed Alternative formula for the %ARexp:

24 Population attributable risk:
The excess risk in the population that can be attributed to a given risk factor. Usually expressed as a percentage: The Pop AR will depend not only on the RR, but also on the prevalence of the risk factor (pe). Levin’s formula (Levin: Acta Un Intern Cancer 1953;9:531-41) Incidence (per 1000) Unexposed Exposed ARexp Population Low exposure prevalence Pop AR Incidence (per 1000) Unexposed Population Exposed Pop AR ARexp High exposure prevalence

25 Dietary Calcium (mg/day)
Chu SP et al. Risk factors for proximal humerus fracture. Am J Epi 2004; 160: Cases: 448 incident cases identified at Kaiser Permanente. 45+ yrs old, identified through radiology reports and outpatient records, confirmed by radiography, bone scan or MRI. Pathologic fractures excluded (e.g., metastatic cancer). Controls: 2,023 controls sampled from Kaiser Permanente membership (random sample). Dietary Calcium (mg/day) Odds Ratios (95% CI) Highest quartile (≥970) 1.0 (reference) Third quartile ( ) 1.36 (0.96, 1.91) Second quartile ( ) 1.11 (0.81, 1.52) Lowest quartile (≤495) 1.54 (1.14, 2.07) What is the %AR in those exposed to the lowest quartile? More or less 1.0 Percent ARexposed ~ Interpretation: If those exposed to values in the lowest quartile had been exposed to other values, their odds (risk) would have been 35% lower. What is the Percent AR in the total population due to exposure in the lowest quartile? Levin’s formula for the Percent ARpopulation RR estimate ~ 1.54 Pexp ~ 0.25 Percent Population AR ~ Interpretation: The exposure to the lowest quartile is responsible for about 12% of the total incidence of humerus fracture in the Kaiser permanente population


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