discussion 02
TRANSCRIPT
7/30/2019 Discussion 02
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Biostat 513
Discussion week 2
(4/8/13 – 4/12/13)
7/30/2019 Discussion 02
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Feedback from HW 1
Question 1
• ….475 inmates were cross-classified with respect to HIV
sero-positivity and their history of intravenous drug use….
• Cross-sectional study – cannot estimate IR or IRR.
• Incorrect to say “risk of acquiring HIV infection”
• Correct – prevalence of HIV infection in this population
• Use the csi command with “or” option to estimate ORs
7/30/2019 Discussion 02
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Measures of Association
• Recall, for two binomial probabilities p0 and
p1:
– Risk Difference: RD = p1 – p0
– Risk Ratio or Relative Risk: RR = p1/p0
– Odds Ratio: OR = [p1/(1‐p1)] / [p0/(1‐p0)]
7/30/2019 Discussion 02
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Measures of Association
• OR is the only appropriate measure of association for acase-control study (sampling by disease status); it isapproximately equal to the RR if disease is rare in thepopulation
•
RR, RD (and OR) all appropriate for prospective (samplingby exposure status) or cross-sectional studies – RR doesn’t provide information on absolute risk
– RR most useful when there is a clear referent group
– RR may better describe the biological or scientific effect
–
RD may better describe the public health or clinical impact“My system will double your chance of winning the lottery” v “Mysystem will increase your chance of winning the lottery by 0.000000143”
7/30/2019 Discussion 02
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Measures of Association
• OR is the only appropriate measure of association for acase-control study (sampling by disease status); it isapproximately equal to the RR if disease is rare in thepopulation
•
RR, RD (and OR) all appropriate for prospective (samplingby exposure status) or cross-sectional studies – RR doesn’t provide information on absolute risk
– RR most useful when there is a clear referent group
– RR may better describe the biological or scientific effect
–
RD may better describe the public health or clinical impact“My system will double your chance of winning the lottery”
“My system will increase your chance of winning the lottery by0.000000143”
7/30/2019 Discussion 02
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Measures of Association
• OR is the only appropriate measure of association for acase-control study (sampling by disease status); it isapproximately equal to the RR if disease is rare in thepopulation.
•
RR, RD (and OR) all appropriate for prospective (samplingby exposure status) or cross-sectional studies – RR doesn’t provide information on absolute risk
– RR most useful when there is a clear referent group
– RR may better describe the biological or scientific effect
–
RD may better describe the public health or clinical impact“My system will double your chance of winning the lottery” vs
“My system will increase your chance of winning the lottery by0.000000143”
7/30/2019 Discussion 02
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Measures of Association
• How do we choose a measure of association?
– Study design
– Scientific question of interest
7/30/2019 Discussion 02
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Example 1
• CARE Study (Breast Cancer) – case-control
study of BC and OC use
•
Which measure of association best describesthe association between breast cancer and
oral contraceptive use?
Any OC Use None Total
BC Cases 3497 1032 4529
Controls 3658 980 4638
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Example 1
• Odds Ratio
– Recall that since this is a case‐control study, we
don’t have P(disease|exposed) or
P(disease|unexposed) so, in general, we can’testimate the relative risk
– In this case, since breast cancer is rare, the OR will
be a good approximate to the RR
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Example 1
• Again, because we are dealing with a case
control study, we would use the odds ratio.
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Example 2
• APPROVe trial - RCT
• What measure of association best describes the
association between treatment (Vioxx) and thepresence of adenomatous polyps found bycolonoscopy during years 1‐3 of follow‐up?
Vioxx Placebo
Adenomatous Polyps
years 1‐3
460 646
None 698 596
Total 1158 1215
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Example 2
• Relative Risk
– Our scientific question of interest asks us tocompare the risk of developing adenomatous
polyps in the treatment and placebo groups. – Since the disease frequency in the placebo group
is high, the OR and RR will not be close; also,upper bound on RR is ~1.9
– If we were interested in the absolute difference inrisk between the two groups, we could easilycalculate the risk difference.
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Example 3
• Swedish mammography study – 15 year followupof women invited to have annual mammogram,or not
• What measure of association best summarizesthe benefit of mammograms in this population of women?
Invited Not
Died of BC 511 584
Alive/died other cause 129,239 116,676
Total 129,750 117,260
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Example 3
• The RR is .80 indicating a 20% relative benefit
due to mammograms
• The RD is -0.001 suggesting that the
mammograms prevent 7 deaths per 100,000
women per year.
RD x 100,000 women / (15 years) = -6.7
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Example 4
• A randomized controlled trial was carried out
to compare the effects of a single dose of
prednisone and placebo in children with acute
asthma.
Row TotalsPrednisone Placebo
Discharged Yes 20 2 22
No 47 71 118
Total 67 73 140
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Example 4
The results section states “2 patients in the placebogroup (3%, 95%CI: -1 to 6%) and 20 in theprednisolone group (30%, 95%CI: 19 to 41%) were
discharged at first exam ( p < 0.0001)”. The methodssection explains that Fisher’s exact test was used forthe p-value.
• Was it necessary to use Fisher’s exact test? Was it
acceptable?• What’s wrong with the CI’s and how could you do
it better?
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Example 5
• A study looks at the risk of bone fractures(over the past 5 years) in women with highcalcium levels in their drinking water versuswomen with low calcium levels.
• What is the study design?
• Which measures of association are valid?
Rate of fractures over 5 years by age andcalcium level
Age 20 - 35 Age 55 - 80 Overall(pooled)
High calcium 1.1% 11.0% 7.8%
Low calcium 3.3% 13.2% 10.0%
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Example 5
• Using RR as your measure of association, is
age an effect modifier? yes
• Using RD as your measure of association, is
age an effect modifier? no !
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Example 6 (optional)
Nevirapine may be given to HIV-infected women at the onsetof labor to prevent MTCT of HIV. Women are given the drugduring a prenatal visit, but may also be offered the drug whenthey present in labor (in case they lost or did not take the pillat the onset of labor).
Suppose we want to compare two different strategies of offering NVP to women but, for logistical reasons, thesestrategies can only be implemented at the clinic level. Thus,we will randomly assign each antenatal clinic and each L&Dclinic to the “T” or “C” strategy.
We want to evaluate the overall effect of the “T” strategy vsthe “C” strategy. But a difficulty is that a given woman may goto an antenatal clinic with one strategy and a L&D clinic with adifferent strategy
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Example 6 (optional)
• List the (4) counterfactual outcomes for any givenHIV-infected woman [TT/TC/CC/CT]
• Which of these 4 counterfactuals correspond to
outcomes of real-world interest? Express thecausal effect of interest in terms of thecounterfactuals
• What key assumption do you have to make to
estimate the causal effect from the availabledata? Completely random allocation of womeninto four categories. No self-selection by women
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Example 7 (optional)
“To adjust or not adjust, that is the question”
Consider the causal relationships
educ age
car
exposure disease Should we adjust for “car type” in studying the exposure-
disease relationship?
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Example 7 (optional)
• Associational criteria for C being a confounder:
– C is associated with exposure
– C is associated with disease, within exposure strata
• “car type” meets the criteria for confounding
• Further, adjustment for “car type” will (likely)
change the exposure – disease odds ratio
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Example 7 (optional)
• However, we should NOT adjust for “car type”
since it does not causally influence the
exposure or disease (it is only incidentally
associated with them)
• Only consider adjusting for factors that are
causally related to exposure or disease
• Decision to adjust for confounding depends on
the underlying causal model!