Summary of Measures and Design Hein Stigum Presentation, data and programs at: http://folk.uio.no/heins/ Nov-19 H.S.

Epidemiological measures Frequency prevalence incidence Association Risk difference Risk ratio Odds ratio Potential impact Attributable fraction How much disease? More disease among exposed? We have covered .. We turn now to Association measures Does smoking cause lung cancer? We measure the strength of the association between the risk factor (smoking) and the disease. assoc. measures are calculated from freq measures Important cause? Nov-19 H.S.

Time E,D No time E → D prospective E ← D retrospective Present time Nov-19 H.S.

Cohorts Closed cohort Open cohort Count persons Count person-time start end end start Count persons Count person-time Closed cohort with time varying covariates start end Count person-time Nov-19 H.S.

Mathematical concepts Proportion (risk) Rate Odds 2 math quatities prop: fraction, numerator (top) is part of denominator (bottom) ex: females in class , no dimension, 0-1 rate: change in one quantity per change in another (time), ex: speed, drive 100 km in 2 h then average speed is 50 km/h, dimension, no upper bound Statistical concept: risk: probability, no dimension, ex: flip coin Nov-19 H.S.

Frequency measures ! Name Equation Type Unit Prevalence risk cases/person Incidence Proportion (Cumulative Incidence) Incidence Rate rate cases/person-time Odds odds ! Nov-19 H.S.

Disease frequency depicted Show: Prevalence Incidence proportion, closed pop, no loss to follow up Incidence rate, takes observation time into account, (could also have loss to follow up) H.S.

Association measures Nov-19 H.S.

Association measures More disease among exposed? Compare frequency among exposed1 and unexposed0 Difference: RD=IP1-IP0 0=no effect Ratio: RR=IP1/IP0 1=no effect Frequency Association or Effect Difference Ratio Risk Risk Difference, RD Risk Ratio, RR Rate - Rate Ratio, RR, IRR, (HRR) Odds Odds Ratio, OR Dekoder til bakkenett: 1 kr vs 0.5 kr Situation 0-1 Can use all 3 types of measures, ex=incidence prop 2 types: null value=no association RR=2 means exposed twize the risk Nov-19 H.S.

Adjusted measures Remove the effect of confounders in regression models Frequency Association or Effect Difference Ratio Risk RD: RR: Rate - IRR: Odds OR: Linear-binomial Log-binomial Cox, Poisson Logistic Standardize freq measures on sex and age Remove effect of sex and age on association measures in regression glm=generalized linear models Nov-19 H.S.

Being bullied, 3 models Bullied=17% glm bullied Island Norway Finland Denmark sex age, family(binomial) link(logit) glm bullied Island Norway Finland Denmark sex age, family(binomial) link(log) glm bullied Island Norway Finland Denmark sex age, family(binomial) link(identity) Bullied=17% After OR/RR, what is the prevalence of bullying? After RD, what is the risk of being bullied if girls from Finland? Nov-19 H.S.

Designs Aims Designs Disease occurrence Exposure-Disease association Cross-sectional studies Cohort studies Case-control studies Case-Cohort Nested Case Control Traditional Case Control Aim: find association Designs: unit of analysis, time for finding exposure and disease Nov-19 H.S.

The 2 by 2 table Nov-19 H.S.

The 2 by 2 table The lowest number sets the precision .01+.01+.1 +.01 =.13 To increase power: In a cohort study: oversample unexposed In a case control study: oversample disease To increase power: Cohort: balance exposure Case-Control: balance disease Nov-19 H.S.

Cohort Nov-19 H.S.

Disease frequency depicted = Risk time Show: Prevalence Incidence proportion, closed pop, no loss to follow up Incidence rate, takes observation time into account, (could also have loss to follow up) Nov-19 H.S.

Cohort: Risk, Odds and Rate Full Cohort, 3 year Risk: Balance? Full Cohort, Rate: 3 years follow up time 10 000 subject followed for 3 years, 0.017*3 appr=0.05 95% CI 0.4 0.6 Gene-Diabetes as cohort: Gene freq 5% * dis freq 1%=0.05% Number in exposed, diseased cell=100 000*0.05%=50 100 000 Nov-19 H.S.

1) Case-Cohort Case-Control studies: Inside an existing cohort 2) Nested Case-Control 3) Traditional Case-Control Inside an existing cohort At the end of an imaginary cohort 1) Case-Cohort Nov-19 H.S.

Case-Cohort . controls Prospective Nov-19 H.S.

Case-Cohort, Risk Full Cohort, Risk: Case-Cohort, Risk: In practice: CHD N + - Exercise 100 1 900 2 000 Inactive 800 7 200 8 000 10 000 Frequency Pseudo Risk 0.50 1.00 Association RR 0.50 1 Risk time: 3*2000=6000 get a bit less 3*8000=24 000 RR (Rate Ratio) almost equal to Risk Ratio 3 year risk=1-exp(-3*rate) app=3*rate In practice: Count: person time Analyze: Cox model Sample controls from healthy at start Nov-19 H.S.

2) Nested Case-Control Nov-19 H.S.

. . . . Nested Case-Control case case controls controls risk set Prospective Nov-19 H.S.

Nested Case-Control, Rate Full Cohort, Rate: Nested Case-Control: CHD Risk time + - Exercise 100 1900 5 850 Inactive 800 7200 22 800 28 650 Frequency Pseudo Rate 0.171 0.351 Association IRR 0.49 1 Sample controls from risk time Analyze: Conditional logistic model Nov-19 H.S.

3) Traditional Case Control Nov-19 H.S.

Traditional Case-Control . controls Retrospective Nov-19 H.S.

Traditional Case-Control Full Cohort, Odds: Trad. Case-Control, Odds: CHD + - Exercise 100 1 900 Inactive 800 7 200 Frequency Pseudo Odds 0.53 1.11 Association OR 0.47 1 Sample controls from non-disease at end Analyze: Logistic model Nov-19 H.S.

Case-Control studies Cohort studies Case-Control studies Measure the exposure experience of the entire population Case-Control studies Measure the exposure experience of a sample of the source population of cases Key assumption Sample controls independent of exposure ( same sampling fraction) Prospective or retrospective Nov-19 H.S.

Summing up ! Measures Designs Cohort full cohort Frequency Association or Effect Difference Ratio Risk RD RR Rate - IRR Odds OR ! Designs Cohort full cohort Case-Control all cases + sample of healthy Case-Cohort sample at start Nested Case-Control sample during Trad. Case-Control sample at end of follow up Nov-19 H.S.