Analgesic clinical trials
and their assay
sensitivity
Robert H. Dworkin, PhD
Professor of Anesthesiology, Neurology, Oncology, and Psychiatry
Professor, Center for Human Experimental Therapeutics
University of Rochester School of Medicine and Dentistry
Outline
1. Limitations of existing pain treatments
2. Negative trials and some possible
explanations
3. An evidence-based approach to analgesic
clinical trial design
4. Study-level analyses
5. Subject-level analyses
6. Novel clinical trial designs
Limitations of existing pharmacologic
treatments for pain
• A substantial percentage of patients either fail to
obtain satisfactory relief or cannot tolerate the
side effects of treatment.
• In patients who do improve, there is typically
partial relief of pain, not complete relief.
• In patients whose pain is relieved, there are
often limited improvements in functioning and
sleep.
• Side effects of many pharmacologic treatments
are a burden to patients.
20 recent negative neuropathic pain trials
(and there are many others1)
Gabapentin enacarbil in painful DPN
Gabapentin extended-release in PHN
Lacosamide in painful DPN (2 trials)
Andinitpainful
would
be(2very
Lamotrigine
DPN
trials)easy to do a
Lamotrigine in mixed neuropathic pain conditions
similar
list for clinical trials of
Levetiracetam
in PHN
Oxcarbazepine in painful DPN (2 trials)
Oxcarbazepinechronic
in lumbosacral
radiculopathy
low back
pain,
Pregabalin in painful DPN (3 trials)
Pregabalin in painful
HIV neuropathyetc.
osteoarthritis,
Pregabalin in lumbosacral radiculopathy
Propentofylline in PHN
Topiramate in painful DPN (3 trials)
1see
Finnerup NB, et al. Pain 2010;150:573-581.
Unfortunately, we often do not know which of
these results are true negatives (i.e.,
examples of “drug failure”)
• some of these drugs may not be
efficacious in the specific pain conditions
in which they were studied
and which results are false negatives (i.e.,
examples of “study failure”)
• some of these may be failed studies of
truly efficacious drugs
Treatment
Trial results
Positive
Negative
Efficacious
Not
efficacious
True positive
False positive
False negative True negative
20 recent negative neuropathic pain trials
(and there are many others1)
Gabapentin enacarbil in painful DPN
Gabapentin extended-release in PHN
Lacosamide in painful DPN (2 trials)
Lamotrigine in painful DPN (2 trials)
Lamotrigine in mixed neuropathic pain conditions
Levetiracetam in PHN
Oxcarbazepine in painful DPN (2 trials)
Oxcarbazepine in lumbosacral radiculopathy
Pregabalin in painful DPN (3 trials)
Pregabalin in painful HIV neuropathy
Pregabalin in lumbosacral radiculopathy
Propentofylline in PHN
Topiramate in painful DPN (3 trials)
1see
Finnerup NB, et al. Pain 2010;150:573-581.
Why have so many recent analgesic trials
been negative?
1. Preclinical animal models and methods are identifying
some drugs that have limited or no efficacy.
2. Early proof-of-concept (i.e., Phase 2) trials are identifying
some drugs or dosages that have limited or no efficacy.
3. Many of these recent results are actually false negatives.
• ~ 50% of depression trials fail...
4. Placebo group patients improved “too much.”
5. The optimal pain conditions or pain patients were not
studied.
6. Temporal changes in characteristics of patients enrolling
in trials and in types of sites conducting trials.
An evidence-based
approach to analgesic
clinical trial design
1. Investigate relationships between the
methodologic features of clinical trials and
their “assay sensitivity” (i.e., their ability to
distinguish efficacious treatments from
placebo or less efficacious treatments)
• e.g., are certain patient, study design, or
study site characteristics associated with
greater assay sensitivity?
2. Determine whether assay sensitivity can be
increased by modifying these patient or
study features
• e.g., possibly by efforts to reduce placebo
group improvement
Patient factors
Study design factors
Study site factors
• Minimum pain duration
• Maximum pain
duration
• Baseline diary
compliance
• Minimum mean
baseline pain intensity
• Maximum mean
baseline pain intensity
• Baseline pain
variability
• Baseline pain
consistency
• History of treatment
failure(s)
• Sources of patient
referrals
• History of
psychopathology
• Research design
(e.g., parallel group vs.
cross-over)
• Number of treatment arms
• Study duration
• Study quality
• Baseline period duration
• Titration period presence
and duration
• Dosing strategy (e.g.,
flexible vs. fixed)
• Permitted use of rescue
and/or concomitant
analgesics
• Presence of active
comparator
• Outcome measures
• Methods of data collection
(e.g., paper vs. electronic)
• Sources of patient
referrals
• Number of sites
• Site investigator
and staff
experience
• Site investigator
and staff training
• Inclusion of patient
training
• Methods for
accelerating
enrollment
• Geographic region
Study-level analyses
Some recent findings on placebo group
responses in neuropathic pain trials
1. There is greater improvement in placebo groups
of negative vs. positive neuropathic pain trials.
• Katz J, Finnerup NB, Dworkin RH. Clinical trial outcome in neuropathic pain: relationship to study
characteristics. Neurology 2008;70:263-272.
2. There is greater placebo group improvement in
longer vs. shorter painful DPN trials.
• Quessy SN, Rowbotham MC. Placebo response in neuropathic pain trials. Pain 2008;138:479-483.
3. Placebo group improvement—but not active
treatment group improvement—is significantly
less in PHN compared with painful DPN trials.
• Dworkin RH, Turk DC, Peirce-Sandner S, et al. Placebo and treatment group responses in
postherpetic neuralgia vs. painful diabetic peripheral neuropathy clinical trials in the REPORT
database. Pain 2010;150:12-16.
Subject-level analyses
Can baseline pain diaries be used to
identify patients who will provide
increased assay sensitivity?
1. Minimum pain intensity
2. Maximum pain intensity
3. Variability
4. Consistency
5. Extreme ratings
6. Adherence
“Individuals with a greater pain variability index at baseline
were more likely to be responders ... to placebo ...
suggesting that a high pain variability may be a predictor of
a placebo response.”
Harris RE, et al. Arthritis Rheum 2005;52:3670-3674.
“Because of the larger placebo response for pain-related
endpoints … in the high variability patients, the apparent
treatment effect size of MLN was smaller in patients with
higher pain variability.”
Palmer RH, et al. International Conference on Accelerating the Development of Enhanced
Pain Treatments, Bermuda, March 2011.
“In duloxetine studies for 3 chronic pain conditions (DPNP,
CLBP, OA), patients with higher baseline pain variation had
a smaller effect size and/or lower treatment response
(relative to placebo) compared with patients with lower
baseline pain variation.
Zhang S, et al. International Conference on Accelerating the Development of Enhanced
Pain Treatments, Bermuda, March 2011.
Novel clinical trial
designs
Sequential Parallel Comparison Design (SPCD)
Efficacy analysis is based on results of the 8 groups in green boxes
Randomize
Treatment Phase 1
Results
Active
Treatment
Responder
Placebo
NonResponder
NonResponder
Responder
Randomize
Treatment
Phase 2
Active
Treatment
Active
Treatment
Active
Treatment
Active
Treatment
Placebo
Results
Res
NonRes
Res
NonRes
Res
NonRes
Res
NonRes
Res
NonRes
• The first treatment phase compares the active treatment
with placebo, as in a conventional parallel-group design.
• In addition, the first treatment phase identifies a group of
placebo non-responders.
• The second treatment phase compares the active
treatment with placebo in the placebo non-responders
from the first phase.
• The active-treatment vs. placebo difference in the
second phase is expected to be at least as large as in the
first phase, and larger if placebo non-response in the
first phase predicts placebo non-response in the second
phase.
“There is little doubt that reducing the
attrition rate of drug candidates in
clinical development represents the
greatest challenge and opportunity for
pharmaceutical research and
development.”
Paul SM, et al. Nature Rev Drug Disc 2010;9:203-214.
There is little doubt that reducing the
attrition rate of analgesic treatments
in clinical development represents the
greatest challenge and opportunity
for the ACTION public-private
partnership.