(Stroke. 2001;32:909.)
© 2001 American Heart Association, Inc.
Original Contributions |
Entry Criteria and Baseline Characteristics Predict Outcome in Acute Stroke Trials
From the Department of Neurology and Statistics, University of Washington, Seattle.
Correspondence to Steven C. Cramer, MD, University of Washington, Department of Neurology, 1959 NE Pacific St, Room RR650, Box 356465, Seattle, WA 98195-6465. E-mail cramers{at}u.washington.edu
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Abstract |
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Background and Purpose—We sought to study the range of entry criteria and baseline characteristics in acute stroke trials and to understand their effects on patient outcomes.
Methods—Randomized, placebo-controlled therapeutic trials in patients with acute ischemic stroke were identified. Entry criteria, baseline clinical characteristics, and outcome were extracted for the placebo group of each trial. The relationship between key variables was then determined.
Results—Across 90
placebo groups identified, there was great variation in entry
criteria and outcome measures. This was associated with divergent
outcomes; for example, in some studies most placebo group patients
died, while in other studies nearly all had no disability. Entry
criteria were significantly correlated with outcome; for example,
higher age cutoff for study entry correlated with 3-month mortality.
Entry criteria also predicted baseline clinical characteristics; for
example, wider time window for study entry correlated directly with
time to treatment and inversely with stroke severity (initial National
Institutes of Health Stroke Scale score). Baseline characteristics
predicted outcome. Greater stroke severity predicted higher 3-month
mortality rate; despite this, successful thrombolytic
trials have enrolled more severe strokes than most trials. The mean age
of enrollees also predicted 3-month mortality and was inversely related
to percentage of patients with 3-month Barthel Index score 
95. The
strongest predictors of 3-month mortality were obtained with
multivariate models.
Conclusions—Acute stroke studies vary widely in entry criteria and outcome measures. Across multiple studies, differences in entry criteria, and the baseline clinical characteristics they predict, influence patient outcomes along a continuum. In some studies, enrolling a specific subset of patients may have improved the chances of identifying a treatment-related effect, while in others, such chances may have been reduced. These findings may be useful in the design of future stroke therapeutic trials.
Key Words: clinical trials • outcome • stroke, acute
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Introduction |
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Anumber of reasons have been advanced to explain the paucity of successful human stroke trials.1 2 Trial design may also be important because it influences the population under study and thus the likelihood of identifying a difference between treatment and placebo groups.
Several aspects of trial design may be important to interpreting results of previous stroke studies. Stroke study entry criteria result in enrollment of patients who are not representative of the stroke population in general.3 4 Selectively enrolling a particular subpopulation of stroke patients could affect study outcome, and therefore there is a need to better understand how changes in entry criteria influence the specific population under study. Differences in baseline patient characteristics can also influence study group outcomes. In stroke studies using a single cohort of patients, a number of clinical characteristics have been shown to influence final clinical status. For example, age,5 stroke severity,6 and stroke subtype7 each influence mortality rate.
A recent study noted the lack of consensus on acute stroke trial outcome measures.8 There has been limited study of the range of entry criteria used and the baseline characteristics measured in acute stroke trials. These issues were explored in the present study. Furthermore, the effect that variation in entry criteria and baseline clinical characteristics has on clinical outcome has received limited attention. This study addressed this issue by exploring the hypothesis that the clinical outcome of patients randomized to placebo group has been very different across studies and that some of these differences can be accounted for on the basis of variation in entry criteria and baseline characteristics across studies.
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Methods |
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Randomized, placebo-controlled, therapeutic trials of human patients with acute ischemic stroke were identified by searching the Cochrane Controlled Trials Register with the terms stroke, acute, and therapy. Additional trials were identified through a MEDLINE search with the keywords ischemic, stroke, acute, therapy, and trials. Secondary references and review articles were also used to identify relevant studies. Studies published in abstract form, having no placebo group, or enrolling patients >72 hours after stroke were excluded. When treatment subgroups were prespecified and placebo group data were reported separately, each subgroup was evaluated separately. Data from intention-to-treat analyses were used whenever possible. Entry criteria, baseline characteristics, and outcome measures were identified for the placebo group in each trial.
A wide range of entry criteria was used across stroke studies. Of these, 2 entry criteria appeared most often and were extracted for each study: the maximum age for study entry and the maximum time from stroke onset to study entry (time window). The definition for time of stroke onset varied across studies, ranging from the last time the patient was known to be normal to the first time the patient was found to have neurological abnormalities. The definition for time of study entry also varied across studies and included time to treatment and time to randomization. The minimum time window of 1 hour specified in several trials was not further considered in the present analysis.
A large number of baseline characteristics at study entry were identified. Mean age, mean time from stroke onset to treatment, median National Institutes of Health Stroke Scale (NIHSS) score, and stroke subtype were noted for each study. For the purposes of this analysis, median values were also accepted when mean values were not reported. The definitions for each stroke subtype were determined by the individual studies. As a secondary analysis, the prevalence in placebo group patients was also noted for 8 other baseline characteristics: previous stroke, previous transient ischemic attack, aspirin use, hypertension, diabetes mellitus, coronary artery disease, atrial fibrillation, and tobacco use.
Finally, across the studies, a large number of outcome
measures were used. Of these, mortality at 3 months and the percentage
of patients with a Barthel Index 95 at 3 months were extracted for
each study. Data collected at 90 days were not distinguished from data
collected at 3 months. A secondary analysis included the
mortality rate at 6 months, the percentage of patients with Barthel
Index 60 at 3 months, and the mean Barthel Index at 3 months. The
primary end point used by each trial was also noted.
The bivariate relationships between entry criteria and outcome measures, between baseline characteristics and outcome measures, and between entry criteria and baseline characteristics were evaluated with Spearman rank-order correlation statistic; significance was set at P<0.05. We acknowledge that multiple tests may produce an occasional spurious result when there are truly no relationships; however, in the context of this analysis we believe that the consequences of missing an important relationship outweigh those of reporting a spurious one.
Multiple linear regression was used to evaluate
multivariate relationships between entry criteria and
baseline characteristics in predicting outcome. In addition, because
the NIHSS score is known to be a powerful predictor of
outcome,9 entry criteria were
used to model NIHSS score. For outcome measures that are proportions
(3-month mortality, percentage of patients with Barthel score >95),
the arcsine–square root transform was used to stabilize
variance.10 Because studies
varied widely in the criteria and outcomes reported, sample sizes
available for multiple regression were consistently smaller
than the 90 studies surveyed. We considered only regression models in
which 10 studies reported both dependent and independent
variables. Multivariate models were weighted
according to placebo group size.
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Results |
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A total of 87 trials that met criteria were identified, published during 1978–2000.11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 Three of these trials had 2 prespecified placebo subgroups, results for which were reported separately, leading to a total of 90 placebo groups evaluated and 31 919 patients. The trials evaluated a wide range of stroke therapies, including neuroprotectants (29 trials), thrombolytics (15 trials), calcium channel blockers (15 trials), hemodilution (10 trials), anticoagulants (5 trials), and other interventions (16 trials).
Table 1
describes the number of studies reporting each
entry criterion, baseline characteristic, and outcome measure for
placebo groups. The range of values is also shown, as is the median
value for these trial placebo groups.
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A broad range of outcome measures was used across the
studies
(Table 1
). As a result, a limited number of studies were
available for comparison of each pair of variables. The most common
time for assessing clinical outcome was 3 months, followed by 1 month
and 6 months after stroke. Several measures were used to assess
clinical outcome, including survival, dependence, mobility, infarct
volume, cerebral blood flow, as well as the following 12 scales:
Barthel Index, NIHSS, Scandinavian Stroke Scale, Toronto Stroke
Scale, Canadian Neurological Scale, Glasgow Outcome Scale, modified
Rankin Scale, modified Mathew Scale, Orgogozo Scale, Turnhill weighted
neurological scale, WHO disability score, and European Stroke
Scale.
Bivariate analysis identified several relationships
between entry criteria, baseline characteristics, and outcome
(Table 2). Across studies performed at many sites in
numerous countries across several decades, several variables were
powerful predictors of outcome. Entry criteria also predicted placebo
group characteristics at study entry. Examples are shown in the
Figure.
Interestingly, the year of study publication correlated inversely with
time window to treatment
(r=-0.47,
P<0.0001), from a median of 72
hours in 1978 to 9 hours in 2000.
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Few of the baseline characteristics considered in secondary
analyses showed a significant relationship with entry criteria
or outcome. In addition, none of the entry criteria or baseline
characteristics correlated with the 6-month mortality rate, the 3-month
median Barthel Index, or the percentage of patients with 3-month
Barthel Index 60.
In multiple linear regression modeling, weighted by group
size, NIHSS score was the single best predictor of observed 3-month
mortality, accounting for 91% of the observed variation. Adding mean
age further improved the model to account for 95% of the variation in
mortality, based on 16 studies reporting all 3 variables. Adding
time to treatment instead also improved the model, accounting for 96%
of the variation in mortality, based on 12 studies. To summarize, we
predict 3-month mortality as
follows.
 | (1) |
Multivariate modeling did not improve
univariate analysis in predicting percentage of
patients with Barthel score 95.
The NIHSS score was well predicted in a model that combined 2 entry criteria. This model accounted for 62% of the observed variation and was based on 11 studies:
 | (2) |
 | (3) |
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Discussion |
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The present study of placebo group patients provides some insight into how entry criteria and patient characteristics influence outcome in acute stroke trials. Previous studies of a single cohort of patients have described a number of predictors of outcome after stroke. Many of these relationships hold true in placebo groups from randomized controlled trials of acute ischemic stroke, despite great variability between trials in the year, site, and conditions of evaluation.
Clinical trials vary widely in the choice of entry criteria. These entry criteria determine which patients are included in the study. Entry criteria also influence patient baseline characteristics, and both influence clinical outcome and thus the likelihood of finding a difference between treatment arms. In particular, enrollment of patients with greater neurological deficits or a smaller proportion of patients with small-artery strokes is associated with higher mortality. Enrollment of younger patients is associated with lower rates of placebo group mortality and disability at 3 months. Patients enrolled many hours after stroke onset have less severe deficits at time of enrollment. Many of these relationships have been established in previous studies examining a single cohort of patients, such as the relationship between early presentation and greater stroke severity,97 98 or the influence of age5 and stroke severity6 on mortality. The present study confirms the role of these factors in acute stroke trials and furthermore describes the continuum by which these principles are expressed across multiple studies of acute ischemic stroke. Findings are based on data from placebo group patients, but many of the same relationships are likely operative in those patients randomized to active-treatment groups.
Many studies enroll patients whose outcome deviates from studies of historical controls, though the latter may be imperfect for comparison given their own vulnerability to bias. In some instances, enrollment was biased toward patients with better than average outcomes. The mean age of placebo group patients across 77 studies was 68 years. This is somewhat lower than most,5 99 100 but not all,101 previously published values, typically 73 to 74 years, in population-based studies and stroke data banks. In 8 studies, the mean age was lower, being <64 years; the maximum age for study entry was <80 years in 3 of these studies, while in 4 of these studies no maximum age was used. In 1 study that limited the upper age for study enrollment to 69 years,48 the mean age of placebo group patients was 58 years. As another example, in 7 studies,26 48 51 80 84 88 91 the 3-month placebo group mortality rate was <10%, also lower than the value found in most stroke trials and in historical controls. Some stroke studies enroll patients with greater severity of illness. The median value for 6-month mortality rate was 28% among the placebo groups of the 13 studies reporting this measure, with 3 studies having rates >30%. These values are higher than the rates of 21% to 22% reported in unselected historical controls.5 99 These variations from historical controls are in part due to choice of entry criteria and study design.
Enrolling patients with a relatively high or low chance of
having a good outcome may influence the ability of a study to
demonstrate a treatment-related benefit. In some trials, enrolling
patients with a poorer prognosis might increase the likelihood of
demonstrating a treatment-related benefit. Some successful trials of
thrombolytics have enrolled patients with more severe
strokes, their median NIHSS scores of 14 to 17 being higher than the
value of 12 over all acute stroke studies
(Table 1). On the other hand, enrolling patients with a very
good prognosis may impede the ability to identify a significant
treatment effect. The median value for 3-month Barthel Index among
placebo group patients in 10 stroke studies was 67, similar to the
value of 69 found in historical
controls.102 In 5 studies,
however, the majority of placebo group patients reached a Barthel Index
score 95. In these studies, identifying a treatment-related effect
would be very difficult using this outcome measure. Trials most
vulnerable to this effect may be those that enter all patients
regardless of stroke subtype, those that use a relatively low age
cutoff for study entry, or those with a wide time window.
The results of this study may have value in the design of
future trials. The bivariate relationships
(Table 2 and
Figure)
and results of multiple linear regression modeling may be useful for
predicting placebo group morbidity and mortality and thus for power
calculations. Such predictions may aid in selection of entry criteria
as well as target baseline patient characteristics. Studies that
include variables most frequently used in previous trials (those
with the highest n in
Table 1) will best be able to make use of this information.
Mortality is a central issue in stroke studies, and its rate correlated
strongly with several entry criteria and baseline characteristics.
Although 3 disability measures obtained at 3 months after stroke (mean
Barthel Index score, percentage of patients with Barthel 60,
percentage of patients with Barthel 95) were used by studies with
almost equal frequency
(Table 1), only the percentage of patients with Barthel 95
correlated with baseline patient characteristics
(Table 2). Among the 3, this measure may therefore most
reliably reflect differences in clinical status between
patients.
Several approaches can be used during study design to ensure
that the natural course of enrollees is not so favorable, or
unfavorable, as to reduce the likelihood of identifying a possible
treatment effect. Stratification, blocking, and other randomization
methods103 can be used to
ensure that the proportion of patients with certain characteristics,
such as those with small-artery disease or a particular range of NIHSS
scores, does not exceed a desired limit. Depending on the drug under
study, there may be a need to avoid enrolling a large proportion of
patients expected to have a very good outcome, such as those with mild
strokes or a young age. In such a case, consideration should be given
to setting the maximum age for study entry to 80 years and to
using a time window for study entry 
12 hours. Some studies, such as
Stroke Treatment with Acrod
(STAT),96 Prolyse in Acute
Cerebral Thromboembolism (PROACT
II),82 and part 2 of the
National Institute of Neurological Disorders and Stroke tissue
plasminogen activator (tPA)
trial,58 specified a minimum
score on neurological testing as an entry criterion to specifically
exclude patients with mild neurological deficits. Enrolling a selected
population may, however, limit the extent to which results can be
generalized to all stroke patients.
Divergent entry criteria and outcome measures have been used during the decades of acute stroke studies. As a result, most of the statistical evaluations described in this report are based on a limited number of comparisons. A wide range of measures was used to assess outcome, including mortality, radiological measures, physiological assessments, and combinations of 12 different neurological scales. Studies also varied widely in choice of entry criteria. The number of different entry criteria and outcome measures used in these trials in part reflects the heterogeneity of the trials reviewed and also highlights the nonuniformity of primary end points in stroke therapeutic trials. This variability limits the ability to make direct comparisons across studies and increases the likelihood of a type I error in the present analyses.
The present analysis of clinical trials, restricted to patients enrolled within 72 hours of stroke onset, confirms the findings of Duncan et al,8 who analyzed a broader set of stroke trials and found a lack of consensus on choice and timing of clinical end points. In the present study a wide range of values was also found for entry criteria and baseline characteristics. Entry criteria, as well as the baseline patient characteristics they predict, are significantly related to clinical outcome when evaluated across multiple stroke trials. These resulting effects on placebo group outcomes may influence the likelihood of demonstrating therapeutic efficacy. The present results provide some insight into how entry criteria and baseline characteristics influence outcome measures in acute stroke trials and may be of utility in the design of future trials.
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Acknowledgments |
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Dr Cramer is supported by grants from the National Institute of Child Health and Human Development and the American Heart Association, Northwest Affiliate (to Dr Cramer).
Received July 10, 2000; revision received November 3, 2000; accepted December 21, 2000.
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