applying trial results to individual patients paul glasziou centre for evidence based medicine...

35
Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford www.cebm.net

Post on 21-Dec-2015

217 views

Category:

Documents


3 download

TRANSCRIPT

Page 1: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Applying Trial Results to Individual Patients

Paul GlasziouCentre for Evidence Based MedicineUniversity of Oxford

www.cebm.net

Page 2: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Should Mr RM buy an electric toothbrush?

72 year old pensioner with Parkinson’s Disease• Has gingivitis and frequent caries

Trials in young healthy folk showing improvements in gingivitis scores but not caries.• Would the electric brush “work” for him?• What should he do?

Page 3: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Individualizing treatment

For some chronic conditions:• N-of-1 trials

Patient’s own randomised trial,Patient can choose own measures & interpret!

For most other problems:• Individualise predicted benefits and harms• Integrate the patient’s preferences

Page 4: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

N-of-1 trials (1932)

Paul Martini suggests• Multiple crossovers• Use of Placebos• Establish baseline• Focus on individual

Methodenlehre der Therapeutischen Untersuchung, 1932,

Page 5: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Osteoarthritis N-of-1s

Comparison of• 1,000mg paracetamol tds• 400mg ibuprofen tds

Two weeks x 6• Outcome diary of pain and

stiffness of target joint

NSAID Paracetamol

Paracetamol NSAID

NSAID Paracetamol

Pair 1

Pair 2

Pair 3

Page 6: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

N-of-1: overall & examples

0

2

4

6

8

AVERAGE PAIN

DRUG

PA

IN S

CO

RE

(ME

AN

+9

5%C

I)

Panadol Actiprofen0

2

4

6

8

AVERAGE PAIN

DRUG

PA

IN S

CO

RE

(ME

AN

+9

5%C

I)

Panadol Actiprofen

NSAID non-responder NSAID responder

Paracetamol has higher pain

Nikles CJ, Yelland M, Glasziou PP, Del Mar C. Am J Ther. 2005 Jan-Feb;12(1):92-7.

Page 7: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

N-of-1 PPI vs H2RAOf 27 patients•14 omeprazole (PPI) was better•6 ranitidine (H2RA) was better•5 equality•2 neither drug recommended

Page 8: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Levels of EvidenceIndividualisation would be ideal

1. N-of-1 Trial2. Systematic review of randomised

trials3. A single randomised trial4. Controlled, non-randomised

• Parallel control• Historical control• Case-control

5. Case-seriesGuyatt, JAMA, 2000

Page 9: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

When are n-of-1’s helpful?

N-of-1 useful when: • Chronic condition, and• Variation in individual responsiveness, and• Treatment effects are:

Symptomatic or Transient

N-of-1 not possible for:• Preventing ‘events’, e.g, stroke• Treating acute conditions, e.g., acute otitis

media

Page 10: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

How should I treat my 2 year old?

What do you want to know about antibiotic treatment?

Page 11: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

What would you want to know?

Page 12: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

% Pain @ 24 hrs135/351 = 37%

No change in Pain @ 24 hrs

% Pain @ 2-7 days248/1,118 = 22%

1/3 reduction Pain @ 2-7d

Page 13: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Who do group trials apply to?

If the trial showed it worked:1. Will it work as well in THIS patient?

• A 30% relative risk reduction (RRR) means It “worked” in 30% It didn’t work in 70%

(and they were at risk of adverse outcomes)

2. And what is the importance of it “working” for THIS patient?

H

Page 14: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Who do group trials apply to?

If it worked in RCT:1. Will it work in THIS

patient?• A 30% relative risk

reduction (RRR) means It “worked” in 30% It didn’t work in 70%

(and they were at risk of adverse outcomes)

And it may not have matter to most

2. How important is that?

Page 15: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Steps from trials to individual decisions

A. TRANSFERABILITY (across groups)1. What are the benefits and harms?2. Is there predictable variation in the effects?3. How does effect vary with predicted risk?

B. APPLICATION (to individual)4. What are the predicted absolute risk

reductions for individuals?5. Do the benefits outweigh the harms

in THIS individuals context?

From: Glasziou et al, Cochrane Applicability & Recommendations Methods Group

www.sph.uq.edu.au/CGP/training/CochraneMethodsGroup.html

Page 16: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

1. What are the benefits and harms?

List all important outcomes • beneficial and harmful

Get best estimate (from meta-analysis)

Summarise in a “clinical balance sheet”

Page 17: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Step 1: Summary of Findings

Outcome Number Subjects (# trials)

Control Group Outcome (range)

Effect Ratio (95% CI)

Change in events Per 100 patients

Quality of Evidence

Pain <1 day 717 (3) 38% 1.02 (0.85 – 1.22)

Nil A

Pain 2-7days 2,287 (9) 22% 0.70 (0.60 – 0.81)

7 fewer A

Mastoiditis 2,287 (9) - - - C “Glue ear” 3M

370 (2) 26% - - B

Adverse effect

11% 1.55 6 more B

GRADE

Page 18: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Antibiotics for Acute Otitis Media

For Pain(at 2-7 days)

RRR ARR NNT

C Cates: www.nntonline.net

Page 19: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Involving the patient

ICE - ideas, concerns and expectations

Explaining the options• What would happen if we did nothing? • What are the options• What is their impact on natural history

• +/- patient information handout

Page 20: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

2. Are there true variation in effects? Patients

• Severity/stage Intervention

• intensity/timing? Comparison Outcome?

Page 21: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Are antibiotics more effective in some children? (Little RCT)

Page 22: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Subgroup Analysis

Do “statins” work in those with a history (Hx) of

stroke?

(Circulation. 2001;103:387-392.)

Not different

Page 23: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Glasziou, Irwig BMJ, 1995

Step 3: How does effect vary with predicted risk?

When does benefit outweigh harm? Assumptions

• Benefit (rate difference) increases with risk or severity• Harm constant over event risk

H

0

2

4

6

8

0 5 10 15 20

Risk of outcome

Eff

ec

t o

f tr

ea

tme

nt

Benefit

Harm

threshold

Page 24: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

For biological effect &

transferabilityFor clinical

decision making

Impact of changing risk

BaselineRisk

RelativeRiskReduction

AbsoluteRiskReduction

Numberneeded toTreat

20% 75% 15% 7

8% 75% 6% 16

4% 75% 3% 33

1% 75% .75% 133

Trial patients

Typical patients

Page 25: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Rate versus rate plots

L’Abbe plot of trials of Warfarin in Atrial Fibrillation

Control group rate

Tre

atm

ent

gro

up

rat

e Line of equality

Constant relative reduction

Constant absolute risk reduction

Page 26: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Which risk measure is most constant?

Measure % varying with control group risk

Odds Ratio 13%

Relative Risk 14%

Risk Difference 31%

Analysis of the effect of control rate in 115 meta-analysis Schmid et al Stats in Med 1998: 1923-42.

Page 27: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Step 4: Benefit versus HarmClinical predictors of stroke

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0 0.05 0.1 0.15 0.2

Stroke Risk/Yr

Str

oke

Eq

uiv

alen

ts Benefit= 73% RRR

Harm= 0.01 deaths

1 ICH death = 4 strokes1 ICH death = 1 stroke

Risk Factors* 0 1 2 or 3Frequency 42% 46% 12% *hypertension, recent CCF, previous thromboembolism,

Page 28: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Individualizing treatment

For some chronic conditions:• N-of-1 trials

Patient’s own randomised trial,Patient can choose own measures & interpret!

For most other problems:• Individualise predicted benefits and harms• Integrate the patient’s preferences

Page 29: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford
Page 30: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Cost-effectiveness varies with risk

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

0

0.01

0.02

0.03

0.04

0.05

0.06

Cost

CEA

Effect

Page 31: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

Cost-effectiveness varies with risk

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

0

0.01

0.02

0.03

0.04

0.05

0.06

Cost

CEA

Effect

Treatmentthreshold

CEthreshold

Page 32: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

SSSS cost-effectivenessby cholesterol+age (model)

0

2,000

4,000

6,000

8,000

10,000

12,000

213 261 309

Initial Cholesterol

Co

st

pe

r L

ife

Ye

ar

age 36

age 58

age 70

Johannesson, NEJM, 1997: 332

Page 33: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

The Risk-Cost Pyramid

Harms outweigh benefits

PossiblyCost-effective

Costsaving

High Risk

Medium Risk

Low Risk

Page 34: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

When we can’t do n-of-1 From trial to Individual

TrialBalance Sheet

IndividualBalance Sheet

Stability and modifiersOf effects across groups(steps 2 and 3)

Individual features•Risk (step 4) & •Preferences (step 5)

www.sph.uq.edu.au/CGP/training/CochraneMethodsGroup.html

Page 35: Applying Trial Results to Individual Patients Paul Glasziou Centre for Evidence Based Medicine University of Oxford

The problem: The “Leaks” between research & practice

Aware Accept Target Doable Recall Agree Done

ValidResearch