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

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?

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

N-of-1 trials (1932)

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

Methodenlehre der Therapeutischen Untersuchung, 1932,

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

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.

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

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

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

How should I treat my 2 year old?

What do you want to know about antibiotic treatment?

What would you want to know?

% Pain @ 24 hrs135/351 = 37%

No change in Pain @ 24 hrs

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

1/3 reduction Pain @ 2-7d

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

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?

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

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”

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

Antibiotics for Acute Otitis Media

For Pain(at 2-7 days)

RRR ARR NNT

C Cates: www.nntonline.net

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

2. Are there true variation in effects? Patients

• Severity/stage Intervention

• intensity/timing? Comparison Outcome?

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

Subgroup Analysis

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

stroke?

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

Not different

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

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

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

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.

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,

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

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

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

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

The Risk-Cost Pyramid

Harms outweigh benefits

PossiblyCost-effective

Costsaving

High Risk

Medium Risk

Low Risk

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

The problem: The “Leaks” between research & practice

Aware Accept Target Doable Recall Agree Done

ValidResearch