Presentation on theme: "M2 Medical Epidemiology"— Presentation transcript:
1M2 Medical Epidemiology Corrections for confounding.Effect Modification
2Corrections for Confounding Adjusting measures of frequency for confoundingDirect rate adjustmentIndirect rate adjustmentAdjusting measures of association for confoundingBy stratificationSpecific vs. Crude association measuresConfounding vs. Effect modificationMantel-Haenszel confounder-adjusted odds ratioFine stratification: matched pairs studiesWhen to use or avoid mantel-Haenszel methodsBy multivariable statistical modelingMultiple regression models for continuous outcomesMultiple logistic regression models for dichotomous outcomes
3Specific Vs. Crude Association Measures Crude rate, ratio, or proportion: calculated in an overall, heterogeneous population of interest.Specific rate, ratio, or proportion: calculated in a subgroup that shares specific values or levels of some characteristic(s), e.g. age, sex, age and sex.Crude odds ratio (OR) or relative risk (RR): calculated in an overall, heterogeneous population of interest, e.g. OR between smoking and lung cancer in CU.Specific odds ratio (OR) or relative risk (RR): calculated in a subgroup that shares specific values or levels of some characteristic(s), e.g. OR between smoking and lung cancer among CU men (sex-specific), CU year-old men (age by sex specific).
4Confounding Vs. Effect Modification Effect ModifiersWhen the degree of association between an exposure variable E and a disease outcome D(as expressed by an odds ratio, relative risk or other appropriate parameter),changes according to the value or level of a third variable M,then M is called an “effect modifier” --because M modifies the “effect” of E on D.
14Confounding Vs. Effect Modification What is effect modification?Different relationships between exposure and disease in subgroups of the population, i.e. different specific measures of association at different levels of a stratification variable.How do you look for it?Stratify the data andCompare stratum-specific association measures to one anotherWhat do you do about it?Report the stratum-specific association measures and ignore the crude association measure.
15Confounding Vs. Effect Modification What is confounding?Distortion of an exposure disease relationship by failure to account for a third variable related to both.How do you look for it?Stratify the data andCompare stratum-specific association measures to the crude measure from the pooled data.What do you do about it?Adjust for it!HOW?
16Mantel-Haenszel Confounder-adjusted Odds Ratio An adjusted odds-ratio(analogous to a directly-adjusted rate, but forrepresenting association)Replaces the crude odds-ratio to correct for confounding(just as the adjusted rate replaces the crude rateunder similar conditions)As the adjusted rate, is obtained bydividing data into subgroups, that is, by stratifyingandreassembling data from the subgroups in a special way
17Mantel-Haenszel Confounder-adjusted Odds Ratio Odds-ratio for a single table=ad/bcConsider stratified dataetc.
18Mantel-Haenszel Confounder-adjusted Odds Ratio etc.CRUDE odds-ratio=ad/bc = (ai)(di)/(bi)(ci),where the summations are over all strata.Mantel-Haenszel adjusted odds-ratio=(aidi/Ti)/( bici/Ti),where the summations are also over all strata.
25Mantel-Haenszel Analysis: Matched Studies Four types of matched pairs:
26Mantel-Haenszel Analysis: Matched Studies For concordant pairsad=bc=0, so they contribute nothing to the Mantel-Haenszel odds ratioeach count is equal to its expectation, so they contribute nothing to the Mantel-Haenszel test statisticFor discordant pairsthe Mantel-Haenszel odds ratio simplifies toNumber of discordant pairs with case exposed/Number of discordant pairs with control exposed
27Mantel-Haenszel Methods: When to Use When effect modification seems absent or minimal and confounding may be present.Then compare the adjusted OR to the crude OR.If different, confounding is present
28Mantel-Haenszel Methods: When to Avoid Avoid the Mantel-Haenszel or any single summary of association when stratum-specific association measures differ substantially and sample sizes are moderate to large. Report the stratum-specific results.Especially when stratum-specific association measures are in opposite directions, e.g. OR or RR>1 in some strata and <1 in others. In this case, major effects may be missed because positive associations in some strata can be cancelled out by negative associations in other strata.Report the stratum-specific results, perform tests of statistical significance for the effect modification and, if these are positive, look for explanations.
30Can You Have Both Confounding and Effect Modification? Yes.Difficult to see. But in extreme cases is easy to see.Example Crude RR=0.7RR in men is 2.0RR in women is 4.02 is different from 4, hence EMYou are not allowed to use adjustment to summarize (average) the 2 and 4. But you know that the effect is RR >1 in both genders. So, gender has distorted the RR