Transcript Risky Business: Understanding Risk and the Application of

Risky Business: Understanding
Risk and the Application of
Number-Needed-to-Treat
Patti Ragan PhD, MPH, PA-C
Brenda Quincy PhD, MPH, PA-C
AAPA San Francisco, CA.
May 24, 2016
1
Session Objectives
• At the end of this session, participants will be able to:
1.
Define, compare and contrast the concepts of: absolute
risk reduction (or increase), relative risk reduction
(RRR), number-needed-to-treat (NNT) and numberneeded-to-harm (NNH)
2.
Discuss how NNT, NNH, and NNS (number-needed-toscreen) provide tools to translate the outcomes of large
clinical studies to individual patient situations
3.
Calculate NNT, NNH and NNS from raw data and
study outcomes
4.
Identify published NNT resources
2
It’s the Information Age…
• So, what is the problem???
• The question is raised…
• How do the findings from randomized
controlled trials or systematic review and
meta-analyses apply to individual patients??
3
Application Challenges
• The risk of an individual may not be similar to the
“average risk” of the group studied
• In a study with a small sample size, subgroup analyses
must be conducted and interpreted cautiously
• Effective treatments or preventive measures from a large
study may not translate to the same benefit in an
individual patient
• The relative risk or odds ratio for a given outcome may
difficult to conceptualize for an individual patient
4
How Can We Apply Results to Our
Patients?
• An outcome measure with greater clinical utility
than the relative risk (RR) or odds ratio (OR) is the
number-needed-to-treat (NNT) or the numberneeded-to-harm (NNH)
• NNT – the number of people who must undergo the
proposed intervention for one person to experience
benefit
• NNH – the number of people who must undergo the
proposed intervention for one additional person to
experience harm
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Other Expressions of Risk
• Absolute risk reduction
• Relative risk reduction
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Absolute Risk Reduction
• Absolute risk reduction (ARR) is the difference in risk
between treatment (experimental) and control groups
• Calculate the risk in the experimental group
# in treatment group who experience the outcome
Total number in treatment group
• Calculate the risk in the control group
# in control group who experience the outcome
Total number in control group
• Subtract the risk in the experimental group from the risk in
the control group
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Relative Risk Reduction
• Let’s start with relative risk…
• RR = risk in treatment group/risk in control group
• RR > 1 means risk is higher with treatment
• RR < 1 means treatment is protective
• RR = 1 means the risk is the same for both groups
• RRR- the amount by which the risk in the treatment
group is reduced relative to the controls
• RRR = (risk in controls – risk in treatment)
•
risk in controls
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An Example
• Hypothetical example
• 100 women take a new drug (treatment) to see if it
reduces the incidence of breast cancer vs. 100 women
who take a placebo (control). After 5 years of follow-up,
2 women in the treatment group get breast cancer,
compared to 4 in the control group.
• 100 women in treatment group followed 5 years → 2
develop breast cancer
• 100 women in control group followed 5 years → 4 develop
breast cancer
Source credit: Extrapolated from Cuzick, Powles, Veronesi, Forbes, et al. Overview of the main outcomes in breast cancer
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prevention trials. The Lancet. Vol.361 Jan 25, 2003
Absolute Risk Reduction
• ARR = risk in control group – risk in treatment group
• Risk (controls) = # breast cancers in control group
total # in control group
= 4/100 = .04 or 4%
• Risk (tx group) = # breast cancers in treatment group
total # in treatment group
= 2/100 = .02 or 2%
• ARR = 4% - 2% = 2% reduction in risk
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Relative Risk Reduction
• RRR = risk reduction with new treatment relative to
control
• RRR = (risk in controls – risk in treatment group)
risk in controls
= .04 - .02
.04
= 0.5  50% relative risk reduction
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What is the Difference?
• Can you see the headline????
• New drug reduces breast cancer risk by 2%
Or
• In a newly released study, women taking a new breast cancer
prevention drug had a relative reduction in their breast cancer
risk of 50%!
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ARR versus RRR
4.5
Absolute Risk
Reduc on –
Rela ve Risk
Reduc on –
4 /100 - 2 /100 =
2 /100 = 2%
reduc on
(4/100 - 2 /100)/
(4/100) = 2/4 =
50% reduc on
4
3.5
3
2.5
2
1.5
1
Control
0.5
Experimental
0
ARR
RRR
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Back to Clinical Utility
• Is there a more clinically useful measure of the
effects of a new treatment on risk than the ARR and
RRR?
• Number-Needed-to-Treat (NNT)
• The number of people who need to receive a new
therapy for one more person to benefit (have a good
outcome)
• NNT = 1
ARR
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Caveats for Applying NNT
• There needs to be a sense of follow-up time
• How long do you have to treat to obtain the good
outcome or prevent the bad outcome?
• NNT is an estimate and should be viewed with
confidence intervals. especially in a small study
• The smaller the NNT, the better.
• NNT= 1 means every person benefits
15
NNT
• NNT = 1/ARR
• ARR = the amount of risk reduction for those receiving
the treatment
• Example
• If a new drug reduces risk of a MI from 50% to 30%
• ARR = 0.5 – 0.3 = 0.2
• NNT = 1/0.2 = 5
• Interpretation – 5 people need to be treated with the new drug to
prevent a MI in one person
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Source credit: Center for Evidence Based Medicine: http://www.cebm.net/index.aspx?o=1044
Number-Needed-to-Harm (NNH)
• NNH – the number of people who need to be treated
for one more person to experience harm
• NNH = 1/(absolute risk increase ARI)
• ARI = risk of bad outcome in tx group minus risk of
bad outcome in control group
• Example
• If a drug increases the risk of a bad outcome (adverse
effect) from 10% to 40%
• ARI = 0.4 – 0.1 = 0.3 (30%)
• NNH = 1/0.3 = 3
• Interpretation: 3 people need to be treated for 1 more
person to experience the bad outcome (adverse effect)
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NNT Example
• Aim – to determine the effect on mortality of giving
thrombolytic therapy in the treatment of acute MI
• If mortality is 12% in the control group and 9% in the
thrombolytic therapy group:
• ARR = 0.12 – 0.09 = 0.03 (3%)
•
then
• NNT = 1/ARR = 1/0.03 = 33
• Interpretation: In the setting of an acute MI, 33 patients
would need to be treated with thrombolytic therapy to
save one additional life
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The “Risks” of Benefits
• Giving thrombolytic therapy also increases the risk
of intracranial hemorrhage. NNH can help us
evaluate the potential risk…
• If the absolute risk increase is 1%, then
• NNH = 1/0.01 = 100
• Interpretation: 100 patients would need to be given
thrombolytic therapy to cause one fatal intracranial
hemorrhage
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Terminology Definitionsaquations
Test characteristic
Absolute Risk Reduction (ARR)
Definition
Absolute risk reduction (ARR) is the amount by which therapy reduces the risk of a bad
outcome.
ARR = CER (control event rate) – EER (experimental event rate)
Relative risk reduction (RRR) is the ratio of the absolute risk reduction (ARR) divided by
the control event rate (CER).
Relative Risk Reduction (RRR)
Absolute Risk Increase (ARI)
RRR = CER - EER
CER
Absolute risk increase (ARI) is the amount by which therapy increases the risk of one
additional bad outcome.
ARI = EER (experimental event rate) – CER (control event rate)
Number Needed to Treat (NNT)
Number needed to treat (NNT) is the number of patients that need to be treated for
one to receive benefit. It can also represent the number of patients that need to be
treated to prevent one additional bad outcome.
NNT*= 1/ARR
Number Needed to Harm
(NNH)
Number needed to harm (NNH) is the number of patients that need to be treated for
one additional bad outcome to occur (harm).
NNH* = 1/ARI
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* If using percentage instead of proportion with ARR or ARI, divide into 100 instead of 1.
1
Key points for NNTs
Number-needed-to-treat…..
• Can be used to evaluate benefit and risk for an individual patient, based on his/her
values and preferences
• Can be calculated from raw data, OR, RRR and expected prevalence
• Is typically calculated for binary (dichotomous) outcomes – time-to-event
outcomes require more complex calculations
• Is an estimate of effect size (should include a confidence interval as a reflection of
precision)
• Should only be calculated from comparable studies with clinical homogeneity
• Should include the duration of treatment for the given effect
• Is more certain when calculated from rigorous systematic reviews or meta-analyses
• Is best when it is a small number (small number need treatment to see benefit)
• Is only applicable if current patient has similar characteristic to those in the study
from which NNT is derived
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Time for Application
• Case 1: A 54 year-old male presents to the
emergency room with complaints of pleuritic chest
pain that seems to be worse when lying supine. His
past medical history is significant for the placement
of a LAD stent following acute myocardial
infarction 8 weeks ago. He has been faithfully
attending cardiac rehab and compliant with his
medications. The pain started this morning with no
clear precipitating factors.
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Additional History
• He denies shortness of breath, orthopnea, PND or pedal
edema. The pain worsens with deep breathing so he has
tried to breathe more shallowly. He reports no
palpitations. This does not feel like the pain he had with
his heart attack. He tried nitroglycerin and it did not help.
He denies fever, chills, cough or congestion.
• Current medications: metoprolol 100mg po BID,
lisinopril 10mg po BID, clopidogrel 75mg po q day,
aspirin 81 mg po q day, atorvastatin 80 mg po q day;
nitroglycerin 0.4mg SL q 5 min x 3 prn chest pain
• Allergies: NKDA
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Physical Exam
General assessment: Well developed, well nourished
male appears moderately uncomfortable.
Vitals: BP 132/86; HR 102 bpm, regular; RR 20; Ht
5’10”, Wt 180lbs; O2 sat by pulse oximetry 97%
Lungs – clear to A&P
Heart – heart tones distant; regular rate and rhythm
without m/g/r; questionable pericardial friction rub
Abd - +BS, soft, nontender
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Labs
• CBC and Chem panel within reference range
• Cardiac enzymes – within reference range
• ESR & CRP – both elevated
• Chest x-ray – mild cardiac enlargement
• EKG – diffuse concave upward ST segment elevation
with PR segment depression in II, AvF and V4-V6.
• Transthoracic echocardiogram – pericardial effusion
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Diagnosis & Management
• What is the most likely diagnosis?
• Dressler’s syndrome
• What is the current standard of care for management
for this patient?
26
A Randomized Trial of Colchicine
for Acute Pericarditis
Background
Colchicine is effective for the treatment of recurrent pericarditis. However,
conclusive data are lacking regarding the use of colchicine during a first attack of
acute pericarditis and in the prevention of recurrent symptoms.
Methods
In a multicenter, double-blind trial, eligible adults with acute pericarditis were
randomly assigned to receive either colchicine (at a dose of 0.5 mg twice daily for
3 months for patients weighing >70 kg or 0.5 mg once daily for patients weighing
≤70 kg) or placebo in addition to conventional antiinflammatory therapy with
aspirin or ibuprofen. The primary study outcome was incessant or recurrent
pericarditis.
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A Randomized Trial of Colchicine
for Acute Pericarditis
Results: A total of 240 patients were enrolled, and 120 were randomly assigned to
each of the two study groups. The primary outcome occurred in 20 patients (16.7%)
in the colchicine group and 45 patients (37.5%) in the placebo group (relative risk
reduction in the colchicine group, 0.56; 95% confidence interval, 0.30 to 0.72;
number needed to treat, 4; P<0.001). Colchicine reduced the rate of symptom
persistence at 72 hours (19.2% vs. 40.0%, P = 0.001), the number of recurrences per
patient (0.21 vs. 0.52, P = 0.001), and the hospitalization rate (5.0% vs. 14.2%, P =
0.02). Colchicine also improved the remission rate at 1 week (85.0% vs. 58.3%,
P<0.001). Overall adverse effects and rates of study-drug discontinuation were
similar in the two study groups. No serious adverse events were observed.
Conclusions: In patients with acute pericarditis, colchicine, when added to
conventional antiinflammatory therapy, significantly reduced the rate of incessant or
recurrent pericarditis.
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Colchicine and Acute Pericarditis
• Describe the intervention and the primary outcome
in this study.
• Intervention is colchicine or placebo + NSAIDs.
• Primary outcome is incessant or recurrent pericarditis
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ARR
• What is the absolute risk reduction for the primary
outcome?
• Risk (incidence) colchicine = 20/120 = 0.1667
• Risk (incidence) placebo = 45/120 = 0.375
• Absolute risk reduction = 0.375 – 0.1667 = 0.2083
• What does this mean?
• The risk of incessant or recurrent pericarditis is 20% lower for those
taking colchicine in addition to usual care compared with usual care
alone
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NNT
• Calculate the NNT for the primary outcome.
• NNT = 1/0.2083 = 4.8 = 4
• Explain what the result means.
• 4 people need to be treated with colchicine and traditional
NSAID to prevent one case of incessant or recurrent
pericarditis.
Note: always go conservative – round down for NNT and up for NNH
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Case 2
• L.S. is a 49 year-old female who presents for her
annual well woman exam including a Pap test and
mammogram. Recently she read something about
ovarian cancer risk being higher in nulliparous women.
She has never been pregnant and remembered that one
of her mother’s 4 sisters had ovarian cancer and she
was the only one of them who had not had children.
L.S. wonders if she should have “the ovarian cancer
test.”
32
Questions, Questions
• What are the risk factors for ovarian cancer?
• What are the symptoms of ovarian cancer?
• What tests are available to screen for ovarian
cancer?
33
Ovarian CA Screening Guidelines
• USPSTF – recommends against screening for ovarian
cancer in asymptomatic women without known gene
mutations (Grade D)
• Why? Low incidence, low PPV, high FPs, no evidence
that screening decreases mortality
• ACOG and NIH Consensus Panel also recommend
against screening
• ACOG recommends annual gynecologic exam
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Purpose of Screening
• To identify disease for which there is an effective therapy
early enough for the treatment to positively impact the
outcome
35
Criteria for a Good Screening Program
• Disease state
• Early detection and early treatment leads to better
outcomes
• Major cause of death and substantial prevalence
• Treatments and facilities should be available
• Test
•
•
•
•
Simple
Acceptable & safe
Cost effective
Accurate (high sensitivity, specificity, PPV, NPV, LR)
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WHO criteria
Review of Test Characteristics
• Sensitivity
• Ability of the test to capture a true positive
• Probability of a positive test result in those with disease
• Specificity
• Ability of test to capture a true negative
• Probability of a negative test in those without disease
• Positive predictive value
• Probability of disease in those with a positive test
• Negative predictive value
• Probability of no disease in those with a negative test
• Likelihood ratio
• Probability of a test result in people with disease divided by the
probability of a test result in people without the disease
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Two Potential Biases
• Lead time bias
• Definition – when a disease is detected prior to
symptom development but the treatment does not make
the patient live longer; it may look like life expectancy
increased but really it was simply detected earlier
• Length bias
• Diseases with a more insidious onset tend to have a
longer pre-symptomatic stage so are more likely to be
detected in a screening program, again appearing to
lengthen survival time
38
Lead Time
Bias
39
Length Bias
40
Back to Our Patient…
• 49 years old
• Nulliparous
• Maternal aunt with ovarian cancer
Do we recommend screening?
41
Effect of Screening on Ovarian Cancer Mortality
The Prostate, Lung, Colorectal and Ovarian (PLCO)
Cancer Screening Randomized Controlled Trial
Context: Screening for ovarian cancer with cancer antigen 125 (CA125) and transvaginal ultrasound has an unknown effect on mortality.
Objective To evaluate the effect of screening for ovarian cancer on
mortality in the Prostate, Lung, Colorectal and Ovarian (PLCO)
Cancer Screening Trial.
Design, Setting, and Participants Randomized controlled trial of
78,216 women aged 55 to 74 years assigned to undergo either annual
screening (n=39,105) or usual care (n=39,111) at 10 screening centers
across the United States between November 1993 and July 2001.
42
Effect of Screening on Ovarian Cancer Mortality
The Prostate, Lung, Colorectal and Ovarian (PLCO)
Cancer Screening Randomized Controlled Trial
Intervention The intervention group was offered annual
screening with CA-125 for 6 years and transvaginal ultrasound
for 4 years. Participants and their health care practitioners
received the screening test results and managed evaluation of
abnormal results. The usual care group was not offered annual
screening with CA-125 for 6 years or transvaginal ultrasound
but received their usual medical care. Participants were
followed up for a maximum of 13 years (median [range], 12.4
years [10.9-13.0 years]) for cancer diagnoses and death until
February 28, 2010.
43
Effect of Screening on Ovarian Cancer Mortality
The Prostate, Lung, Colorectal and Ovarian (PLCO)
Cancer Screening Randomized Controlled Trial
Main Outcome Measures Mortality from ovarian cancer, including primary
peritoneal and fallopian tube cancers. Secondary outcomes included ovarian cancer
incidence and complications associated with screening examinations and diagnostic
procedures.
Results Ovarian cancer was diagnosed in 212 women (5.7 per 10 000 person-years)
in the intervention group and 176 (4.7 per 10000 person-years) in the usual care
group (rate ratio [RR], 1.21; 95% confidence interval [CI], 0.99-1.48). There were
118 deaths caused by ovarian cancer (3.1 per 10000 person-years) in the intervention
group and 100 deaths (2.6 per 10000 person-years) in the usual care group (mortality
RR,1.18; 95% CI, 0.82-1.71). Of 3285 women with false-positive results, 1080
underwent surgical follow-up; of whom, 163 women experienced at least 1 serious
complication (15%). There were 2924 deaths due to other causes (excluding ovarian,
colorectal, and lung cancer) (76.6 per 10000 person-years) in the intervention group
and 2914 deaths (76.2 per 10000 person-years) in the usual care group (RR, 1.01;
95% CI, 0.96-1.06).
44
Effect of Screening on Ovarian Cancer Mortality
The Prostate, Lung, Colorectal and Ovarian (PLCO)
Cancer Screening Randomized Controlled Trial
Conclusions Among women in the general US population,
simultaneous screening with CA-125 and transvaginal
ultrasound compared with usual care did not reduce
ovarian cancer mortality. Diagnostic evaluation following a
false-positive screening test result was associated with
complications.
Trial Registration clinicaltrials.gov Identifier: NCT00002540
JAMA. 2011;305(22):2295-2303
Published online June 4, 2011. doi:10.1001/jama.2011.766
45
Ovarian Cancer Risk
• Calculate the incidence of ovarian cancer in the screened
group
• Incidence = (# new cases in screened)/(# screened) = 212/34253
= .00619
• Calculate the incidence of ovarian cancer in the usual
care group
• Incidence = (#new cases in usual care)/(#women in usual care)
= 176/34304= .00513
46
Another Way to Frame the Dilemma
• Number needed to screen
• Definition - the number of people who need to be screened
to prevent 1 death
• NNS = 1/absolute risk reduction (ARR)
• Absolute risk is the same as incidence…the number of
new cases in a given group
• Absolute risk reduction is how much the risk decreases
with a particular intervention
• In this study, it is the risk of ovarian cancer in the
screening group minus the risk of ovarian cancer in the
usual care group
47
Calculation Time!
• ARR =
# new cases screened -
#new cases usual care
total # screened
=
212
34253
total # usual care
-
176
34304
= .00619 - .00513
= .00106
48
NNS
• NNS = 1/ARR
• NNS = 1/.00106 = 943
• Interpretation
• 943 women would need to be screened with TVUS
and CA125 to prevent 1 ovarian cancer death
49
Case 3
• Carpenter CR., Keim SM., Milne WK., et al. (2010).
Thrombolytic therapy for acute ischemic stroke
beyond three hours. The Journal of Emergency
Medicine, 40(1); 82-92.
50
Clinical Question
Does the intravenous systemic administration of tPA
within 4.5 hours to select patients with acute ischemic
stroke improve functional outcomes?
51
History of Present Problem
• NINDS 1995
• “alteplase…within 3 h of symptom onset significantly
improved functionally independent outcomes at 3 months in
highly select acute stroke patients.”
• Medical community response
• FDA approved in 1996
• AHA upgraded recommendation to Level 1 in 2000
• European Medicines Agency called for alteplase safety study in
community setting and RCT of thrombolysis window beyond 3
hours
52
More Context
• Controversy in EM over Level I recommendation with
only one study
• Other “real world” studies couldn’t reproduce the
findings
• Ambiguous standard of care for those within 3 hours
• Re-analysis of NINDS data suggest benefit less
substantial than originally believed
• Cochrane review  overall benefit in spite of more
deaths and intracranial hemorrhages
53
Bottom Line…
• We need to review the evidence for ourselves!
54
Efficacy and Safety of Tissue Plasminogen
Activator 3 to 4.5 Hours After Acute Ischemic
Stroke: A Meta-Analysis
Background and purpose — The ECASS-3 study demonstrated
a benefit of treatment with intravenous tPA for acute stroke in the
3-4.5 hour time-window. Prior studies, however, have failed to
demonstrate a significant benefit of tPA for patients treated beyond
3 hours. The purpose of this study was to produce reliable and
precise estimates of the treatment effect of tPA by pooling data
from all relevant studies.
Methods — A meta-analysis was undertaken to determine the
efficacy of tPA in the 3-4.5 hour time window. The effect of tPA on
favorable outcome and mortality was assessed.
55
Efficacy and Safety of Tissue Plasminogen
Activator 3 to 4.5 Hours After Acute Ischemic
Stroke: A Meta-Analysis
Results — The meta-analysis included data from patients treated
in the 3-4.5 hour time-window in ECASS-1 (n=234), ECASS-2
(n=265), ECASS-3 (n=821) and ATLANTIS (n=302). tPA
treatment was associated with an increased chance of favorable
outcome (OR 1.31, 95% CI 1.10-1.56; p=0.002) and no significant
difference in mortality (OR 1.04; 95% CI 0.75-1.43; p=0.83)
compared to placebo treated patients.
Conclusions — Treatment with tPA in the 3-4.5 hour timewindow is beneficial. It results in an increased rate of favorable
outcome without adversely affecting mortality.
56
NINDS
• Population
• 37 hospitals, ischemic CVA, clear onset, < 3 hours
• Measurable sustained deficit NIHSS, no ICH
• Study design
• Randomized to placebo or alteplase
• Primary outcome
• 3mo functional outcome
• 4 instruments
• Those who died given worse possible score on all
57
NINDS
• Exclusion
• Extensive; see Table 1
• Main results
• 1 day outcome – better in those treated within 90 min
• 3 months
• 12% absolute increase in favorable outcomes (NNT = 8)
• No sig difference in mortality
• ICH
• More likely in tPA group (20/312) vs (2/312) placebo
58
ECASS I
• Population
• 75 hospitalized, 14 Euro countries, mod to high grade
hemispheric stroke (SSS); < 6 hrs; no or min. infarct on
CT
• Study design
• Randomized to alteplase or placebo
• Primary outcome
• Barthel index and mRS at 3mo post-treatment
59
ECASS I
• Exclusion criteria
• See Table 2
• Main results
• In the ITT analysis, there was no difference in Barthel
or mRS.
• mRS in TP analysis was significantly better in tPA
group
• No significant difference in mortality
• Early ICH, fatal cerebral edema and early mortality
were higher in treatment group
60
ECASS II
• Population
• 108 centers in 14 Euro countries, Australia & New Zealand;
• Mod to severe ischemic stroke; no or min. CT evidence; < 6 hrs.
• Study design
• Randomized to alteplase or placebo
• Primary outcome
• mRS at 90 days
61
ECASS II
• Exclusion criteria
• See Table 3
• Main results
•
•
•
•
•
•
No sig difference in mRS (for score 0 or 1) at 3 months
Including mRS = 2, tPA better with NNT = 12
No difference in mortality at 3 months
Parenchymal hemorrhage 4x higher in tPA
Space occupying ICH 10x higher in tPA
Hemorrhagic conversion of the strokes did not differ.
62
ATLANTIS
• Population
• 140 North American sites; ischemic stroke, measurable
neuro deficit with ability to treat within 3-5 hours of onset
• Study design
• Randomized to tPA or placebo
• Primary outcome
• NIHSS score at 3 months
63
ATLANTIS
• Exclusion criteria
• See Table 4
• Main results
• No difference for NIHSS at 3 months.
• tPA significantly increased symptomatic and fatal
ICH…trend toward higher mortality at 3 months
64
ECASS III
• Population
• 130 sites, 19 Euro countries, clinically suspected acute
ischemic stroke; 3-4.5h p sx onset
• Study Design
• Randomized to alteplase or placebo
• Primary Outcome
• 90 day mRS favorable outcome (score = 0 or 1)
65
ECASS III
• Exclusion
• See Table 5
• Main results
• mRS 0 or 1 in 52.4% of tPA vs. 45.2% of placebo
(NNT = 14)
• No significant difference in mortality rates
• Symptomatic ICH significantly more likely with tPA
(27% vs. 17.6%, NNH 47)
66
Meta Analysis
• Population
• Acute ischemic stroke treated with tPA in 3-4.5h window
• Study design
• Meta analysis of RCTs
• Primary outcome
• Global odds ratio (mRS 0-1, NIHSS 0-1, Barthel Index >=95)
• Good functional outcome at 90 days (mRS 0 or 1)
• 90 day mortality
6767676
7
Meta Analysis
• Exclusion criteria
• Observational studies and RCTs with n < 100
• Main results
• Global outcome
• Sig. better than placebo (OR 1.31, p = 0.002)
• mRS
• Sig better than placebo (OR 1.31, p = 0.008; NNT 15)
• No difference in 90 day mortality
68
69
Conclusion
• What is the conclusion of the article with regard to
the use of thrombolytic therapy for ischemic stroke
with symptom onset beyond three hours?
• “Treatment with tPA in the 3-4.5 hour time-window is
beneficial. It results in an increased rate of favorable outcome
without adversely affecting mortality”
• Is the conclusion supported by the NNTs for each
set of data?
70
ECASS-1
ECASS-2
ECASS-3
ATLANTIS
TOTAL
71
NNT
13
11
14
N/A
15
Is the Review Valid?
• Are there any concerns with the validity of this
review?
• Size of meta analysis
• Heterogeneity of data
• Need CI to interpret NNT
72
Summary
• Questions of risk arise every day in clinical practice
• Clinicians need a reliable expression of risk that
allows application of RCT results to individual
patients and that makes sense is patients
• NNT, NNH and NNS are useful tools for this
purpose
73
The NNT
• The NNT
• A group of physicians who have evaluated the evidence
for a variety of therapies and diagnostics
• They provide a summary of the evidence and the
bottom line benefits (NNTs) and harms (NNHs) scores
• Also includes a NNT tutorial
• www.theNNT.com
• The NNT quiz – let’s try it!
• http://www.thennt.com/the-nnt-intervention-quiz/
74
THE NNT.COM
• Their NNT rating system
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Quiz Question 1
76
Quiz Question 1 Answer
77
Quiz Question 2
78
Quiz Question 2 Answer
79
Quiz Question 3
80
Quiz Question 3 Answer
81
Quiz Question 4
82
Quiz Question 4 Answer
83
Quiz Question 5
84
Quiz Question 5 Answer
85
Quiz Question 6
86
Quiz Question 6 Answer
87
Lingering Questions?
88