Dr. Cristina Ana Stoian

Resident Journal ClubJune 14, 2012

Objectives

Recognize strengths and limitations of various study designs

Calculate study parameters Sensitivity, specificity, PPV, NPV RR, ARR, RRR, NNT

Define some basic terms P-value, type I error, type II error

Discuss general approach to critical appraisal

Study Designs

Design ‘Starting point’

What is assessed

Strength Limitations

RCT Exposure status

Outcome Controls bias

Feasibility

Cohort Exposure status

Outcome Ability to determine incidence; temporality

Time and cost; rare outcome

Case control

Outcome Exposure status

Less time and cost

Bias (++)

The famous 2x2 table

Outcome

Yes No

Exposure Yes (treatment)

a b

No(control)

c d

Calculations

Control event rate (CER) = c/c+d Experimental event rate (EER) = a/a+b Relative Risk (RR) = EER/CER=(a/a+b)/(c/c+d) Relative Risk Reduction (RRR) = CER-EER/CER

(commonest reported measure of dichotomous treatment effect)

Absolute Risk Reduction (ARR) = CER-EER Number Needed to Treat (NNT) = 1/ARR

The famous 2x2 table

Outcome

Yes No

Exposure Treatment 15 85

Control 20 80

Assume a study which recruited 200 patients and randomized 100 patients in each of treatment and control groups. There were 15 deaths in the treatment group and 20 deaths in the control group

Calculations

Assume a study which recruited 200 patients and randomized 100 patients in each of treatment and control groups.

There were 15 deaths in the treatment group and 20 deaths in the control group

EER: 15/100 (0.15 or 15%) CER: 20/100 (0.20 or 20%) RR: 0.15/0.20 = 0.75 ARR: 0.20 – 0.15 = 0.05 RRR: (0.20-0.15)/0.20 = 0.25 (25%) NNT: 1/0.05 = 20

The famous 2x2 table

Sensitivity

Proportion of persons with condition who test positive

Sensitivity = true positive test result/ all patients with disease

Sensitivity = a/a + c (TP/TP+FP) SnNOut = a highly sensitive test that gives a negative

result rules out the Dx Desired for screening tests POWER = sensitivity = 1 – beta error

Specificity

Proportion of persons without condition who test negative

Specificity =true negative test results/all pts without disease

Specificity = d/ d + b (TN/TN+FN) SpPIn = if using a highly specific test, a positive test result

rules in the Dx

Example Some researchers have conducted a QI project to assess the

diagnostic accuracy of the urine dipstick leukocyte esterase test to predict a bacterial UTI. As part of their study, they assessed 100 patient urine samples which underwent both a dipstick and a urine culture. A dipstick was defined as positive if it showed ‘trace’ leukocytes or greater. A urine culture was defined as positive if it grew a single organism at > 1 x 107

75 patients had positive urine cultures. Of these, 60 had a positive dipstick. Of the 25 patients with negative cultures, 5 had a positive dipstick

Please calculate the Sn, Sp, PPV and NPV of the dipstick test

The famous 2x2 table

Another example

Test for strep throat. You test 100 swabs from patients complaining of sore throat. Test was positive 40 times and in 20 cases the culture came back positive for strep. Test was negative 60 times and only in 5 of these cases the cultures were positive.

Which of the following is true about the new test?

A. Positive predictive value = 50%

B. Sensitivity = 80%

C. Negative predictive value >90%

D. All of the above

The famous 2x2 table

Effectiveness vs Efficacy

• Effectiveness = ability of an intervention to achieve the desired results under USUAL conditions, ie day-to-day use. Effectiveness describes how well drug works, its side effects and ease of use

• Efficacy = ability of an intervention to achieve the desired results under IDEAL conditions, eg clinical trial. Does not describe how well tolerated/ease of use, only how well it gives the desired result.

Definitions Null hypothesis – there is no difference between the groups

being compared P-value – the probability that the difference observed in the

study is simply due to chance (also referred as type I error) Type II error – based on the estimate of the ‘true difference’

between groups, what is the chance that the difference in the study sample will not be statistically significant (incorrectly accepting the null hypothesis when there is a real effect)

Power = 1 – type II error

Measuring Outcomes

You can use the 2 x 2 table to look at error

Null Null HypothesisHypothesis

OutcomeOutcome

ChanceChance Real effectReal effect

AcceptAccept CorrectCorrectIncorrect Incorrect

Type II errorType II error

RejectRejectIncorrectIncorrect

Type I errorType I errorCorrectCorrect

General approach to critical appraisal

What is the primary research question? Methods

– Study design– Sample, exposure, outcome– Measurement– Analysis

Results Limitations Conclusions

Key points in critical appraisal

Internal validity– The degree to which the study truly answers the

question it poses

External validity – Can the study results be generalized to other

populations?– (can the results help me in caring for my patients)

Internal Validity

Were study participants randomized? Were all participants who entered the study

properly accounted for (follow-up)? Was the study ‘blinded’? Were the groups similar at the start of the trial? Aside from study intervention, were the groups

treated equally?

External Validity

Can the results be applied to my patient care?– Consider inclusion/exclusion criteria– Study population

Were all clinically important outcomes considered?

Are the likely treatment benefits worth the potential harm and costs?