Will It Work? Efficacy Studies and Clinical Research Glenn Pransky, M.D., M.Occ.H. Director, Liberty...

Will It Work?Efficacy Studies and Clinical Research

Glenn Pransky, M.D., M.Occ.H.

Director, Liberty Mutual Center for Disability Research

Associate Professor, UMass Medical School

How Do Doctors Decide?

• It ought to work - inductive reasoning

• Others vouch for it - abdication

• Demonstrated effect - deduction

Gastric Freezing

• Cooling to -5° C decreased secretions

• President of ACS tried -10° C; published case series of 20 pts: symptoms, X-ray healing

• 2500 gastric freezing machines sold 1962-66

• 15,000 treatments in US by 1969

Randomized Trial (Ruffin et al, NEJM, 1969; 281, p.16)

• Double - blinded intervention - treating MD and patient didn’t know

• Results:

– Recurrence in 30 (44%) of placebo (warm)

– Recurrence in 35 (51%) of treated patients

Efficacy

• For a given medical problem, efficacy is the probability that treatment significant improvement in outcome, under ideal conditions

• Effectiveness = efficacy in usual conditions of practice

Efficacy Studies

• Phase I - human dosage / toxicity

• Phase II - uncontrolled trial

• Phase III - randomized, controlled trial

RCT Strengths

• Show maximum effect vs. placebo

• Strongest design to bias from several potential sources

• Prove causation

• Compare treatments

RCT Weaknesses

• Infrequent side-effects missed

• Long latency effects often attenuated

• Community usage unknown

• problems with placebo definition

Home vs. Hospital Care for Suspect MI (Hill, Lancet, 1978, l:837)

• RCT, 6 week follow-up after acute ER visit

• Sickest patients excluded

• Results:

– HOME: 20% of 79 died

– HOSPITAL: 18% of 71 died

• Need 261 / grp. - detect 25% RR difference

• Need 45 / grp. - detect 50% RR difference

RCT Sample Size

• Type I error: false optimism; usually = 5% (p-value)

• Type II error: false pessimism; usually = 20%

• Power = prob. of finding A if A is true

• Required parameters:expected control outcome, expected intervention effect, rate of outcome / length follow-up

Preventive Intervention, Uncommon Adverse Outcome

• New treatment for HTN in pregnancy

• Goal: risk from 2% 1%

• Type 1 error 5%, type 2 error 20%

• 2511 individuals needed in each group!

Selection - Exclusions

• Old, young, demented, minorities, pregnant

• Liver or kidney disease - drug metabolism

• Noncompliant patients (run-in period)

Selection - Inclusions

• Volunteers - sicker, compliant

• Referral (selected) population

Treatment problems in efficacy studies

• Atypical = non-generalizable

• Randomized allocation with complex significant factor patterns– Propensity scoring as alternative

• Ethics of no rx. vs. comparison rx.

• Placebo effect

• Multifaceted intervention - investigator attributes to one element

Control

• Blinding - ideally pt., treaters, evaluators

– When is this not feasible?

• Surgical treatments - randomization, but patients & treaters know

Control

• Contamination type II error– sympathy, community care

• Cointervention type I error (unblinding)– ‘more is better,’ support of tertiary care

center vs usual care

Follow-up

• Adequate for stability of 1/ 2outcomes

• Multiple assessments

• Loss - sicker, toxicity, high study burden

• Assume the worst?

Surgery vs. Medical Rx for Bilateral Carotid Stenosis (Fields & Maslenikov, JAMA, 1970, 211: p1993)

• 79 surg, 79 med @ F/U 1 year later

• Surgery: 27% risk stroke/death (p=0.02)

• Of 16 LTFU, 15 were allocated surgery - all had early death or stroke

• Intention-to-treat analysis: risk 16%, p = 0.09

Outcomes

• Clinical / physiologic

• Function

• Employment

• Satisfaction, quality of life

• Side-effects

• Value of surrogate endpoints?

Analytic Methods

• Variable length follow-up Kaplan-Meier survival curve (for terminal event)

• Assumes constant probability

Problems

• Multiple comparisons

• Large trial: statistical but not practical significance

Typical Results

1 = follow-up too short (Type 2 error)

2 = follow-up too long; few subjects or overwhelming additional influences plateau usually = low numbers

0

50

100

t1 t2 t3 t4 t5

t

% a

live 1

2

Adherence Chola, Mortality in CDP (NEJM 303: 1038, 1980)

Risk reduction= .26-.16/.26= 38%

Convincing?

Post-MI secondary prevention trial with clofibrate.

CDP Study (2)

• Same results in placebo group

• Conclusion: compliance survival effect!

Are All Relevant Results Reported?

Measure Placebo Clofibrate

Avg. change serum chol. +1% -9%

Nonfatal MI/1000 7.2 5.8

Fatal MI/1000 1.7 1.6

Total deaths/1000 5.2 6.2

(Oliver et al WHO trial on primary prevention IHD using databrate Lancet 1980; 2, p. 379)

Generalizability

• Adequate description?

• Typical cohort, setting?

• Typical treatment; acceptable, cost, available

• Sideffects - effort to obtain information

Functional Restoration: Pitfalls in Evaluating Efficacy (Gatchel, Mayer, Hazard et al, Spine, 1991, 17:988)

• Staff Training

• Program duplication, same selection criteria & patients

• Consistent evaluation methods, close follow-up

• Report important details (drop-out, total costs)

• Understand key differences - jurisdiction, etc.

Placebo Effects, Other Issues in Pain Treatment (Turner, Deyo, et al., JAMA, 1994, 271:1609)

• Regression to mean apparent benefit regardless of treatment– Patients enroll @ worst point in cyclical course– Also may reflect meas. error, random variation

• Nonspecific Rx effect– Attention, concern; expectations of healing;

“facilitated” reporting

Placebo Effects

• “Change in illness attributable to symbolic import of treatment.”

• Up to 70% of responses to Rx’s initially thought to be efficacious eventually defined as placebo effects

• IMA procedure: 56% significant improvement, 42% NTG use – (Cobb, NEJM, 1959, 260, 1115-8: skin incision

placebo)

• Diskectomy - negative surgical exploration: 37% no sciatica, 42% no LBP

– (Spangfort, Acta Orth Scand, 1972, 142:1)

Factors Influencing Placebo Response

• Patient attitude to provider and treatment

• More compliance

• Provider attitude, unbliding

Placebo Effects in Pain Treatment

• Mimic expected dose-response relationship (pain medications)

• Mimic expected side-effects (drowsiness, nausea)

• Perception: large or injected = strong;

yellow = stimulant

• Suggestion worse condition (Nocebo effect)

Questions

1. Randomization?

2. Blinding?

3. Adequate data collection / reporting?

4. Statistical, clinical significance?

5. All participants included

6. Generalizable

7. Feasible?