Therapeutics: Finding a Therapeutics: Finding a “Cure”“Cure”

Why Assess Therapy Articles?Why Assess Therapy Articles?

Evidence-based medicineStarting point for treatment decisions

Apply evidence to your patients

Quality matters

Quality0 8

0

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RR

Relative Risk vs. QualityRelative Risk vs. Quality(Trials of TCA’s in HA prevention)(Trials of TCA’s in HA prevention)

Courtesy of Jeff Jackson, MD MPH (unpublished data)

Why Does Quality Matter…?Why Does Quality Matter…?

ObjectivesObjectives

Use the medical literature to find relevant trials to answer a patient-based clinical question

Describe the steps in critically appraising a clinical trial of a therapeutic intervention

Demonstrate how a focused clinical question can efficiently generate an evidence-based decision in patient care

Guyatt, et al. User’s Guide to the Medical Literature Series, No. II: How to Use an Article About Therapy or Prevention (A. ‘Are the Results of the Study Valid’ and B. ‘What were the Results and Will They Help Me in Caring for My Patients?’) Originally published in JAMA, 1993 Vol. 270(21) and 1994 Vol. 271(1)

Clinical Case*Clinical Case*

58yo male ER w/ rest anginal chest discomfort progressing x 6 hours

h/o CABG two years ago (LIMA to LAD, SVG to OM, SVG to PDA)

PMH: HTN, HLD, impaired glucose tolerance Meds: Metoprolol 100mg bid, Lisinopril 40mg qd,

Lipitor 80mg qhs, Glucophage 500mg bid, ASA Current non-smoker (30 pack-year history, quit 2

years ago).

*Nayak Special

Clinical CaseClinical Case (continued) (continued)

Exam: BP 142/80 HR 90 Chest: CTA Bilat RRR, S1 S2, II/VI early sys murmur at RUSB no JVD or edema, normal distal pulses Abd: no bruits/masses

ECG: NSR, 1mm ST depression and TW flattening in anterolateral leads

Patient stabilized in CCU on NTG drip and IV beta blocker. ACE-I/Statin/ASA continued.

Clinical CaseClinical Case (continued) (continued)

Normal CBC/chem panelCK MB Trop

I

Initial enzymes: 190 5.5 0.2 Second set: 400 9.0 3.3

Echo (HD #1): normal LVSF, no focal WMA, aortic sclerosis without stenosis

Left heart catheterization (HD #2): patent grafts with diffuse, severe native vessel coronary disease, but no focal lesions for PCI

How might you articulate a clinical question about therapeutic options for this gentleman…?

Asking the Right QuestionAsking the Right Question

Background questions – general knowledge Foreground questions – more specific (‘PICO’)

Patient (or problem) of interest Intervention of interest– “an exposure” Comparison intervention (if relevant) Outcome of clinical interest

How do you manage ACS?

In NSTEMI patients with

preserved LV…?

Foreground Question: Our CaseForeground Question: Our Case

In patients with Acute Coronary Syndrome (ACS) w/o ST elevation…

…does adding clopidogrel to ASA…

…reduce cardiovascular mortality

MeSH is your friendMeSH is your friend

The search for a The search for a ‘CURE’….‘CURE’….

McMaster’s MethodMcMaster’s Method

Validity

Results

Generalizability

ValidityValidity

Randomization (4 questions)Blinding (1 question)

What’s so important about randomization?….

RandomizationRandomization

Why do it? Eliminates selection bias Both known and unknown confounders are

randomized

How can it be maintained? Complete follow up Intention-to-treat analysis

Once randomized, always analyzed

ValidityValidity

Primary Guides Randomized? All patients accounted for…

Follow up complete? Intention to treat analysis used?

Skim abstract, methods, results

OR

Is it worthYour time…?

ValidityValidity

Secondary Guides Were patients, physicians, and

outcome assessors blinded? Were the groups similar (was there an

adequate Table 1)? If not, were adjustments made?

Were the groups treated equally?

ResultsResults

How large was the treatment effect?

How precise was the estimate?Were confidence intervals given?

Measures of the EffectMeasures of the Effect

Absolute Risk Reduction (ARR)Proportion control – Proportion experimental

Number Needed to Treat (NNT) = 1/ARR

Number Needed to Harm (NNH) = 1/ARRProportion experimental – Proportion control

11.4% - 9.3% = 2.1% (composite CV mortality)

18.8% - 16.5% = 2.3% (above or refractory ischemia)

1 / 0.021 = 48 (or 1/0.23 = 43)

3.7% - 2.7% = 1% (major bleeding)

1 / 0.01 = 100 (life-threatening bleed, CVA not significant)

Measures of EffectsMeasures of Effects

Relative Risk (RR)Proportion experimental/Proportion control

Relative Risk Reduction (RRR)1-RR x 100%

1 - 0.8 x 100% = 20%

0.093 / 0.114 = 0.80

Compared with Absolute Risk

Reduction of 2.1%

Precision of Effect Estimate?Precision of Effect Estimate?

p values

Are Confidence Intervals Given?

If 95% CI doesn’t contain null value (ie 1 for relative risk and 0 for risk difference), then p value always < 0.05

CI adds better estimate of precision to p value

Generalizable?Generalizable?

Can the results be applied to my patients? Inclusion/exclusion criteria Subgroup (age, race, gender)

All clinically important outcomes considered?

Likely benefits worth the potential harms and costs?

SummarySummary

Focused question (PICO) Targeted search/study selection Validity

Randomization preserved Blinded

Results Absolute Risk Reduction, NNT

Generalizable Study population similar to your patients Potential benefits worth the risks

Questions?Questions?