Hss4303b – intro to epidemiology April 8, 2010 – epidemiology and health policy

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?


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?


Yes

Early D eath

Surgica lDeath?

No

Yes Early D eath

Death?

No

Yes

N orm al surviva l

AneurysmRupture?


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


• 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?


• 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?


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?


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?


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.

Documents

Hss4303b – intro to epidemiology April 8, 2010 – epidemiology and health policy