Post on 28-Dec-2015
Hss4303b – intro to epidemiology
April 8, 2010 – epidemiology and health policy
Exam Review
• April 22, 2pm-3:30pm, SCS E218
• April 26, 2pm-3:30pm, SCS E218
Poster Sh*t
• For those printing their posters with the Geography dept or Merriam Print, the deadline is TODAY in order to assure pick-up by Saturday
Important Poster Sh*t
• The agenda and list of presenters is now posted on the website
• Your presentation time is also listed• If you are scheduled to present in the
afternoon, you are still encouraged (dare I say, required?) to register in the morning– If you are not there to present to the judges when
they come around, you will receive zero
What is this?
OTTAWA - Health Canada is advising Canadians about important safety information for CRESTOR® (rosuvastatin). A recent US study has found that Asian patients may be at greater risk of developing muscle-related adverse events with this drug. CRESTOR® is a cholesterol-lowering drug in the "statin" family. "Statins" are a specific type of cholesterol-lowering medication.In Canada, and internationally, CRESTOR® has been associated with reports of a serious condition called rhabdomyolysis. Rhabdomyolysis results in muscle breakdown and the release of muscle cell contents into the bloodstream.
Symptoms of rhabdomyolysis include muscle pain, weakness, tenderness, fever, dark urine, nausea, and vomiting. In severe cases, rhabdomyolysis can lead to kidney failure and be life-threatening.
For some patients, there may be pre-existing conditions or other personal factors that could cause a greater risk of developing muscle-related problems, including rhabdomyolysis, if they are using "statin" medications.
RISK
The techniques of epidemiology are used to collect data and create information to quantify risk in order to allow more informed policy.
What is health policy?
Dark blue slides are from Dr Spasoff, supercourse
Light blue slides by Dr Akram, supercourse
Policy is like sausage: it may taste good, but it’s best that you don’t know what went into it
Epidemiology contributes at each step
“What if” questions
• “What if” questions like “What would be the effect on the overall health of the population if we reduced smoking by 20%?
• Sort of like program evaluation
Clinical Decision Making
• In a clinical medical environment, sometimes we need to use evidence to quantify our decision-making process
• Eg, to choose one therapy over another
Decision Tree
Also called “chance node”Also called “choice node”
Data for Decision Tree
• Epidemiology– Probabilities of outcomes– Meta-analyses– Systematic reviews– Analytical studies– Pilot studies
Motivating Case:Ms. Brooks is a 50 year old woman with an incidental cerebral aneurysm. She presented with new vertigo 3 weeks ago and her primary MD ordered a head MRI. Her vertigo has subsequently resolved and has been attributed to labyrinthitis.
Her MRI suggested a left posterior communicating artery aneurysm, and a catheter angiogram confirmed a 6 mm berry aneurysm.
Example Slides by Dr James Kahn, UCSF, 2010 “Decision Analysis”
Case Presentation (cont’d)
Past medical history is remarkable only for 35 pack-years of cigarette smoking. Exam is normal. Ms. Brooks: “I don’t want to die before my time.”
Question is: Do we recommend surgical clipping of the aneurysm or no treatment?
Overview of DA Steps1. Formulate an explicit question2. Make a decision tree.
(squares = decision nodes, circles = chance nodes) a) Alternative actions = branches of the decision node.b) Possible outcomes of each = branches of chance nodes.
3. Estimate probabilities of outcomes at each chance node.4. Estimate utilities = numerical preference for outcomes.5. Compute the expected utility of each possible action6. Perform sensitivity analysis
1. FORMULATE AN EXPLICIT QUESTION
- Formulate explicit, answerable question. - Formulate explicit, answerable question. - May require modification as analysis progresses. - May require modification as analysis progresses. - The simpler the question, without losing important - The simpler the question, without losing important
detail, the easier and better the decision analysis.detail, the easier and better the decision analysis.
In the aneurysm example, our interest is in determining In the aneurysm example, our interest is in determining what’s best for Ms. Brooks so we'll take her perspective. We what’s best for Ms. Brooks so we'll take her perspective. We will begin with the following question:will begin with the following question:
Which treatment strategy, surgical clipping or no Which treatment strategy, surgical clipping or no treatment, is better for Ms. Brooks considering her primary treatment, is better for Ms. Brooks considering her primary concern about living a normal life span?concern about living a normal life span?
2. MAKE A DECISION TREE
Creating a decision tree = Creating a decision tree = structuring the problemstructuring the problem
Provide a reasonably complete depiction of the Provide a reasonably complete depiction of the problem.problem.
Best is one Best is one decision nodedecision node (on the left, at the (on the left, at the beginning of the tree). beginning of the tree).
Branches of each Branches of each chance nodechance node -- -- exhaustiveexhaustive and and mutually exclusivemutually exclusive. .
Proceed incrementally. Begin simple. Proceed incrementally. Begin simple.
M s. B rooks
N o treatm ent
Surgery
N orm al surviva l
E a rly D ea th
S urgery:yes o r no?
N orm al surviva l
E a rly D ea th
Simple Tree
M s. Brooks
N o treatm ent
Surgery
S urgery:yes o r no?
AneurysmR upture?
N o N orm al surviva l
Yes E arly D eath
S urg ica lD eath?
N o
Yes
AneurysmR upture?
N o N orm al surviva l
Yes E arly D eath
E arly D eath
More complicated tree
M s. B rooks
N o treatm ent
Surgery
Surgery:yes or no?
AneurysmRupture?
N o N orm al surviva l
Yes
Early D eath
Surgica lDeath?
No
Yes Early D eath
Death?
No
Yes
N orm al surviva l
AneurysmRupture?
N o N orm al surviva l
Yes
Early D eath
Death?
No
Yes
N orm al surviva l
Crazy complicated
3. Fill in the Probabilities
• Use info from the literature– Case fatality rates– Population mortality rates– etc
M s. B rooks
No treatm ent
Surgery
Surgery:yes or no?
AneurysmR upture?
N op=0.9825 N orm al surviva l=1
Yesp=0.0175
Early D eath=0
Surgica lD eath?
N op=0.977
Yesp=0.023 Early D eath
D eath?
N op=.55
Yesp=.45
N orm al surviva l=1
AneurysmR upture?
N op=1.0 N orm al surviva l
Yesp=0
Early D eath
D eath?
N op=.55
Yesp=.45
N orm al surviva l
Expected Utility
• The average or expected outcome if one follows a given branch of the tree
• Sum of desirable outcomes within a given branch
Example of Expected utility
• Disease = cardiac valve failure• Intervention (decision) = surgery vs no surgery• If surgery, possible outcomes are:
complications vs no complications– Further possible outcomes are death or survival
• If no surgery, the only possible outcomes are death or survival
Example of Expected utility
• Let’s follow surgery node:– 90% chance of no complications
• 90% survive
– 10% chance of complications• 50% survive
• What is expected utility at the surgery node?
Example of Expected utility
• Let’s follow surgery node:– 90% chance of no complications
• 90% survive
– 10% chance of complications• 50% survive
EU = (P of no complications)(survival) + (P of complications)(survival) = 0.90 x 0.90 + 0.10 x 0.50 = 0.81 + 0.05 = 0.86
COMPUTE THE EXPECTED UTILITY OF EACH BRANCH
Called "folding back" the tree. Expected utility of action = each possible
outcome weighted by its probability. Simple arithmetic calculations
Back to Ms Brooks
(Using a fairly complex system that I won’t expect you to duplicate)
5. Compute expected utility of each branch
M s. B rooks
N o trea tm ent
S urgery
Surgery:yes or no?
AneurysmRupture?
Nop=0.9825 Norm al surviva l=1
Yesp=0.0175
Early Death=0
SurgicalDeath?
Nop=0.977
Yesp=0.023 Early Death=0
Death?
Nop=.55
Yesp=.45
Norm al surviva l=1
AneurysmRupture?
Nop=1.0 Norm al surviva l=1
Yesp=0
Early Death=0
Death?
Nop=.55
Yesp=.45
Norm al surviva l=1
=0
=0
=.55
=.55
5. Compute expected utility of each branch
M s. B rooks
N o trea tm ent
S urgery
Surgery:yes or no?
AneurysmRupture?
Nop=0.9825 Norm al surviva l=1
Yesp=0.0175
Early Death=0
SurgicalDeath?
Nop=0.977
Yesp=0.023 Early Death=0
Death?
Nop=.55
Yesp=.45
Norm al surviva l=1
AneurysmRupture?
Nop=1.0 Norm al surviva l=1
Yesp=0
Early Death=0
Death?
Nop=.55
Yesp=.45
Norm al surviva l=1
=1.0
=.55
=.55
=.9825
=0
=.9921
=.977
Ms. Brooks
• “Thanks… But I meant I wanted to live the most years possible. Dying at age 80 isn’t as bad as dying tomorrow…”
We recommend NO surgery.
Improve the Analysis
Add layers of complexity to produce a more realistic analysis.
Eg: Add Another Outcome
M s. B rooks
N o trea tm ent
Surgery
Surgery:yes or no?
AneurysmR upture?
N o Norm al surv ival
Yes
Early Death
SurgicalDeath?
N o
Yes Im m ediate Death
Death?
N o
Yes
Norm al surv ival
AneurysmR upture?
N o Norm al surv ival
Yes
Early Death
Death?
N o
Yes
Norm al surv ival
Three outcomesDetermine utility as a portion of expected life span
-Normal survival 1.0-Early death 0.5-Immediate death 0
Summary of Formal Decision Analysis
• Explicit question.• Decision tree.• Probabilities of each outcome.• Utilities for each outcome.• Expected utility of each course of
action.• Sensitivity analysis.