Clinical Significance for Quality of Life Endpoints in Clinical Trials

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Clinical Significance for Quality of Life
Endpoints in Clinical Trials
Jeff A. Sloan, Ph.D. Mayo Clinic, Rochester,
MN, USA

• FDA/Industry Statistics Workshop
• Washington, September 16, 2005

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Primary goal advance the state of the science
to help cancer patient QOL soar
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Take home messagethere is good news

• There are problems with using QOL assessments as
  indicators of efficacy in clinical trials.
• There are scientifically sound solutions to these
  problems. The problems have been disseminated
  widely and consistently. The solutions have not.

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It takes a certain amount of bravery to work in
QOL research
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Science is a candle in the dark - Carl Sagan
We will use the candle of science to improve the
QOL of cancer patients
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How do you determine the clinical significance
of QOL assessments?
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What is a clinically meaningful QOL burden?
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Why is it difficult to define clinical
significance for QOL?

• Pain analogy
• 25 years ago physicians were the sole raters of
  patient pain
• JCAHO 2000 guideline every patients pain to be
  assessed upon intake on a 0-10 scale
• Time and experience alleviates novelty and
  skepticism, and guidelines evolve

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Why is it difficult to define clinical
significance for QOL?

• Blood pressure analogy
• 100 years ago, clinical significance of BP scores
  was unknown (Lancet 1899)
• massage therapy was the gold standard
• present guidelines for BP clinical significance
  today redrawn (McCrory DC. Lewis SZ. Chest. 126(1
  Suppl)11S-13S, 2004)

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The solution found for tumor response cutoffs may
provide guidance

• We call a reduction of 50 a response.
• Have reductions of 49 all the time, but do not
  worry about misclassification.
• Moertel (1976) basis for 50 cutoff
• Find a cutoff and stick to it? (RECIST)

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What Clinical significance is NOT

• Statistical significance
• Example drawn from JCO 2001 (anonymous)
• HSQ before / after scores on 1300 patients
• all p-values lt0.0001
• conclusion all domains of QOL were significantly
  different across treatment groups
• problem 1300 patients provides 80 power to
  detect a change of 1 unit on 0-100 point scale

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EORTC QLQ-LC13

• Item n537 n346 Effect Size
• Coughing 46.2 44.3 small
• Dyspnea 17.2 16.2 small
• Pain 26.9 25.5 small
• all p-values were statistically significant

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The Six Papers

• 1) Methods used to date
• 2) Group versus individual differences
• 3) Single item versus multi-item
• 4) Patient, clinician, population perspectives
• 5) Changes over time
• 6) Practical considerations for specific
  audiences
• MCP, April, May, June 2002

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No single statistical decision rule or procedure
can take the place of well-reasoned consideration
of all aspects of the data by a group of
concerned, competent, and experienced persons
with a wide range of scientific backgrounds and
points of view. Canner (1981)
If it looks like a duck, sounds like a duck, and
walks like a duck, the odds of it being a worm or
an elephant in a clever disguise are small in the
extreme. Sloan (2001)
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Bottom Line

• Assessing the clinical significance of QOL can be
  as simple as a 10-point change on a 100-point
  scale, if that is consistent with the goals of
  the scientific enquiry. The real issue underlying
  the controversy over QOL is the relative novelty
  and lack of experience that presently exists with
  QOL. With time and familiarity this too shall
  pass.
• (Sloan, J Chronic Obs. Pul. Dis. 2 57-62, 2005.)

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Presenting global solutions is always interesting
you
me
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Two general methods for clinical significance

• Anchor-based methods requirements
• independent interpretable measure (the anchor)
  which has appreciable correlation between anchor
  and target
• Distribution-based methods
• rely on expression of magnitude of effect in
  terms of measure of variability of results
  (effect size)

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The MID method in one slide
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The Empirical Rule Effect Size (ERES) Approach
(Sloan et al, Cancer Integrative Medicine
1(1)41-47, 2003)

• QOL tool range 6 standard Deviations
• SD Estimate 100 percent / 6
• 16.7 of theoretical range
• Two-sample t-test effect sizes (J Cohen, 1988)
• small, moderate, large effect (0.2, 0.5, 0.8 SD
  shift)
• S,M,L effects 3, 8, 12 of range

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The Empirical Rule

• Tchebyshevs Theorem at least 1-1/k2 of any
  distribution will fall within k standard
  deviations (SDs) of the mean
• If the distribution is symmetric, 99 will fall
  within 3 standard deviations
• The pdf for the range is a function of the SD
• an estimate of the SD can be obtained via
• range 6 SD

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Assumption Checking for ERES(Dueck, Sloan, 2006,
J. Biopharm. Stats, in press)

• Tchebyshevs Inequality is conservative
• Tested the effect of various distributional
  assumptions
• Only a uniform distribution results in deviation
  from the assumption of a 6 SD-based estimate (28
  instead of 17)

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All Methods Give Similar Answers

• Cohen - 1/2 SD is moderate effect
• MCID - 1/2 point on 7-point Likert
• 7-1 6 point range gt SD of 1 unit
• so 1/2 point gt 1/2 SD
• Cella - 10 point on FACT-G
• 10/1.12 8.9 / 16.7 1/2 SD
• Feinstein - correlation approach
• Cohen was arbitrary, should be 0.6 SD

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The Good News

• Statistical, Philosophical, Empirical, Clinical,
  Historical, Practical approaches to defining a
  clinically significant effect for symptom
  assessments are all in the same ballpark
• A 10 point difference on a 100-point scale (1/2
  SD) is almost always going to be clinically
  significant
• Smaller differences may also be meaningful (data)
• Applies to groups or individuals (just different
  SD)
• Norman GR, Sloan JA, Wyrwich KW. Expert Review of
  Pharmacoeconomics and Outcomes Research Sept
  2004 4(5) 515 519
• Sloan JA, Cella D, Hays R. J Clin Epidemiol (in
  press).

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Four Guidelines(Sloan, Cella, Hays, JCE 2005,in
press)

• The method used to obtain an estimate of clinical
  significance should be scientifically
  supportable.
• The ½ SD is a conservative estimate of an effect
  size that is likely to be clinically meaningful.
  An effect size greater than ½ SD is not likely to
  be one that can be ignored. In the absence of
  other information, the ½ SD is a reasonable and
  scientifically supportable estimate of a
  meaningful effect.

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Four Guidelines(Sloan, Cella, Hays, JCE 2005,in
press)

• Effect sizes below ½ SD, supported by data
  regarding the specific characteristics of a
  particular QOL assessment or application, may
  also be meaningful. The minimally important
  difference may be below ½ SD in such cases.
• If feasible, multiple approaches to estimating a
  tools clinically meaningful effect size in
  multiple patient groups are helpful in assessing
  the variability of the estimates. However, the
  lack of multiple approaches with multiple groups
  should not preemptively restrict application of
  information gained to date.

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Summary

• Defining clinical significance for QOL
  assessments is today where pain was 25 years ago,
  tumor response was 50 years ago and blood
  pressure was 100 years ago
• Define clinical significance a priori, and use
  the definition in the analytical process
• Consensus is building as the answers from
  different approaches are similar and relatively
  robust

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New ideas have enabled us to make advances in QOL
science
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A Mayo/FDA meeting regardingguidance on
patient-reported outcomes (PRO)Discussion,
Education, and Operationalization

• FDA to release guidances for assessing PROs in
  all clinical trials (3rd quarter 2005?)
• Meeting co-sponsored with FDA to
• provide a focused process to facilitate
  discussion among all stakeholders
• educate stakeholders on background, content, and
  concerns
• provide an opportunity for input
• delineate ways to best operationalize the
  guidance into clinical trials
• February 23-25, 2006, DC (Westfields Marriott,
  Chantilly, VA, 7 miles from Dulles)

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The NCCTG QOL Team
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Thank you
Email jsloan_at_mayo.edu