http://stroke.ahajournals.org/content/48/11/2946?etoc=
Abstract
Background and Purpose—Determining
the minimal clinically important difference (MCID) is essential for
evaluating novel therapies. For acute ischemic stroke, expert surveys
have yielded MCIDs that are substantially higher than the MCIDs observed
in actual expert behavior in guideline writing and clinical practice,
potentially because of anchoring bias.
Methods—We
administered a structured, internet-based survey to a cross-section of
academic stroke neurologists in the United States. Survey responses
assessed demographic and clinical experience, and expert judgment of the
MCID of the absolute increase needed in the proportion of patients
achieving functional independence at 3 months to consider a novel, safe
neuroprotective agent as clinically worthwhile. To mitigate anchoring
bias, the survey response framework used a base 1000 rather than base
100 patient framework.
Results—Survey
responses were received from 122 of 333 academic stroke neurologists,
there were 23% women, 72.8% had ≥6 years of practice experience, and
neurovascular disease accounted for more than half of practice time in
>70%. Responder–nonresponder and continuum of resistance tests
indicated that responders were representative of the full expert
population. Among respondents, the median MCID was 1.3% (interquartile
range, 0.8% to >2%).
Conclusions—Stroke
expert responses to MCID surveys are affected by anchoring and
centrality bias. When survey design takes these into account, the
expert-derived MCID for a safe acute ischemic stroke treatment is 1.1%
to 1.5%, in accord with actual physician behavior in guideline writing
and clinical practice. This revised MCID value can guide clinical trial
design and grant-funding and regulatory agency decisions.
Introduction
The
minimal clinically important difference (MCID) is the smallest change
in a treatment outcome that a patient, a care provider, or both would
consider worthwhile.1
Establishing
the MCID for a disease state is an essential prerequisite for clinical
trial sample size calculation and informs funding decisions by the
National Institutes of Health and other sponsors and drug or device
approval decisions by the Food and Drug Administration and other
regulatory agencies. For superiority trials, declarations that a novel
treatment is clinically superior to standard therapy require that the
improved outcome rate exceeds the MCID. For equivalence and
noninferiority trials, declarations that 2 treatments are of equal
clinical efficacy require that their outcome rates fall within the MCID.
The smaller the MCID, the larger the sample size needed for a
randomized trial to ensure that the study is adequately powered to
detect or exclude a treatment benefit of clinical relevance.
Approaches
to establishing the MCID for a particular disease or symptom fall into 3
categories: distribution-based, anchor-based, and Delphi expert–based
approaches. Distribution-based approaches statistically derive an MCID
from the distribution of outcome data, such as using one half the SD of
an end point. They have the advantage of direct calculation from outcome
data sets, but the drawback of not clearly correlating with clinically
important change.
Anchor-based approaches compare change
in end point scores with an external anchor, most commonly a patient
global impression of change. Patient judgments that a change has been
meaningful are relatively straightforward to elicit for treatments that
are applied to patients with a previously stable disease-related health
state. When interventions move patients from one to another long-lasting
disease–related health state, patients can draw on their personal
experience of both the before and the after states to render assessments
comparing the 2. However, patient judgments that a change has been
meaningful are challenging to derive for treatments that are applied to
patients with an abrupt onset new condition, such as acute ischemic
stroke. With acute onset conditions, patients can draw on their personal
experience of only 1 stable disease-related health state, their own
final outcome, and cannot compare this state to any alternative,
personally experienced outcome state.
Given the
limitations of the distribution- and anchor-based approaches for acute
stroke, the survey methods have been the leading technique for
determining what is a minimally important change in stroke outcomes.
Surveys are administered to physicians, nurses, and other healthcare
providers about the worth of different outcome states. Because
healthcare providers have direct observational familiarity with a range
of stroke outcomes, they are able to knowledgeably make comparative
judgments of the value of alternative disease-related health states.
But, for simple and safe therapies for acute ischemic stroke, MCIDs
derived from expert judgment (5%–10%)2 have been higher than MCIDs derived from econometric modeling (2%–3%)3 and higher than MCIDs derived from observations of actual physician behavior and medical guidelines (1%–1.5%).4–7
These elevated expert-derived MICD values have been highlighted in
European and American consensus statements on acute ischemic stroke
clinical trial design.2,8
Recent
studies of both nonexperts and experts have shown that human judgment
in a wide variety of settings is prone to cognitive biases—systematic
deviations from rationality. Notably, the architecture of questions used
to elicit expert opinion may bias the resulting responses.9
Investigations of expert judgment of acute stroke MCID have generally
used multiple choice questions, which are subject to anchoring and
centrality bias. We sought to determine whether altering the question
anchor framework would yield expert-derived MCIDs for acute stroke that
better accord with actual expert behavior.
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