Treatment of intracerebral hemorrhage in animal models: Meta-analysis

ORIGINAL ARTICLE

Treatment of Intracerebral Hemorrhagein Animal Models: Meta-Analysis

Joseph Frantzias, BSc, Emily S. Sena, PhD, Malcolm R. Macleod, PhD,

and Rustam Al-Shahi Salman, MA, PhD

Objective: Interventions that improve functional outcome after acute intracerebral hemorrhage (ICH) in animalsmight benefit humans. Therefore, we systematically reviewed the literature to find studies of nonsurgical treatmentstested in animal models of ICH.Methods: In July 2009 we searched Ovid Medline (from 1950), Embase (from 1980), and ISI Web of Knowledge(from 1969) for controlled animal studies of nonsurgical interventions given after the induction of ICH that reportedneurobehavioral outcome. We assessed study quality and performed meta-analysis using a weighted meandifference random effects model.Results: Of 13,343 publications, 88 controlled studies described the effects of 64 different medical interventions(given a median of 2 hours after ICH induction) on 38 different neurobehavioral scales in 2,616 treated or controlanimals (median 14 rodents per study). Twenty-seven (31%) studies randomized treatment allocation, and 7 (8%)reported allocation concealment; these studies had significantly smaller effect sizes than those without theseattributes (p < 0.001). Of 64 interventions stem cells, calcium channel blockers, anti-inflammatory drugs, ironchelators, and estrogens improved both structural outcomes and neurobehavioral scores in >1 study. Meta-regression revealed that together, structural outcome and the intervention used accounted for 65% of the observedheterogeneity in neurobehavioral score (p < 0.001, adjusted r2 ¼ 0.65).Interpretation: Further animal studies of the interventions that we found to improve both functional and structuraloutcomes in animals, using better experimental designs, could target efforts to translate effective treatments for ICHin animals into randomized controlled trials in humans.

ANN NEUROL 2011;69:389–399

The global burden of acute spontaneous (nontrau-

matic) intracerebral hemorrhage (ICH) and its out-

come appear unchanged over the past quarter century,1,2

despite the improvements in outcome that can be

achieved by organized stroke unit care and neurosurgical

hematoma evacuation.3–6 The quest for other effective

therapies has been fuelled by the recent failures of

recombinant activated factor VII and the neuroprotectant

drug NXY-059 to improve outcome after acute ICH in

humans.7,8 Randomized controlled trials of medical

therapies such as blood pressure lowering are ongoing,9

but the search for other candidate interventions may best

start with methodologically robust laboratory research in

animal models that accurately mimic human ICH.10

Therefore, we aimed to undertake a systematic review

of nonsurgical interventions in controlled studies of animal

models of ICH reporting neurobehavioral outcomes, to

explore their methodological quality, and to perform a

meta-analysis of the effects of each class of intervention.

Subjects and Methods

Eligibility CriteriaWe sought controlled studies, regardless of their language of

publication, of nonsurgical interventions given to wild-type

(nontransgenic) animals after the induction of ICH using auto-

logous blood or collagenase injection11 that reported neuro-

behavioral outcome.

Information SourcesIn July 2009, we searched Ovid Medline (from 1950), Ovid

Embase (from 1980), and ISI Web of Knowledge (from 1969)

using comprehensive electronic search strategies (Supporting

View this article online at wileyonlinelibrary.com. DOI: 10.1002/ana.22243

Received Jun 22, 2010, and in revised form Aug 2, 0000. Accepted for publication Aug 27, 2010.

Address correspondence to Dr Salman, Bramwell Dott Building, Division of Clinical Neurosciences, Western General Hospital, Crewe Road, Edinburgh

EH4 2XU, United Kingdom. E-mail: [email protected]

From the Division of Clinical Neurosciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.

Additional supporting information can be found in the online version of this article.

VC 2011 American Neurological Association 389

Information Table 1). We also searched the proceedings of the

Society for Neuroscience and the first and second International

Symposia on Cerebral Hemorrhage using the ISI Web of Knowl-

edge Conference Proceedings Citation Index. We screened the

bibliographies of eligible studies for other eligible studies. We

contacted authors to clarify study eligibility, where necessary.

Study SelectionOne investigator (J.F.) screened all titles and available abstracts

for eligibility, and removed duplicates. Studies that appeared to

be eligible were read in full by 2 investigators (J.F., and E.S.S. or

R.A.-S.S.), and disagreements were resolved by either discussion

or arbitration by a third investigator (M.R.M.). We obtained

translations of studies that were not written in English.

Data CollectionTwo investigators independently extracted data on experimental

design, study quality attributes, intervention characteristics, func-

tional outcome (neurobehavioral score, measured on any scale),

and structural outcomes (brain water content, or hematoma size).

We recorded these data in the Collaborative Approach to Meta-

Analysis and Review of Animal Data from Experimental Stroke

(CAMARADES) Microsoft Access 2003 data manager applica-

tion. For every treatment comparison (a given dose of an inter-

vention at a given time of administration after ICH), we

extracted the number of animals in each treatment group, the

mean outcome score, and the standard deviation or standard error

of the mean. We extracted all neurobehavioral outcomes at the

latest time of assessment, as well as at 7 6 2 days after the induc-

tion of ICH (if reported) and structural outcome data at the lat-

est time when animals were culled. We extracted outcome data

on untreated sham groups (in which ICH had not been induced)

from experiments where these were included; in experiments that

did not, we inferred sham neurobehavioral scores for functionally

unimpaired animals, sham hematoma volumes of zero, and sham

brain water content values corresponding to the contralateral

brain region of the control/vehicle group. Unless outcomes were

quantified at the relevant time points, we measured them from

publications’ figures (using Adobe measuring tools). We contacted

authors to obtain unpublished or missing data.

Quality AssessmentWe assessed each study’s quality according to the CAMARADES

10-item checklist,12 which consists of reporting of a sample size

calculation; use of animals with comorbidities (eg, hypertension or

diabetes); control of animals’ temperature; use of anesthetics other

than ketamine (because of its marked intrinsic neuroprotectant ac-

tivity13); randomized treatment allocation; treatment allocation

concealment; blinded assessment of outcome; publication in a

peer-reviewed journal; statement of compliance with regulatory

requirements; and statement of potential conflicts of interest.

Data Analysis

META-ANALYSIS. The prespecified primary outcome was

functional outcome as measured by neurobehavioral score at

the latest time point after ICH induction. Prespecified second-

ary outcomes were structural measures of brain injury: either

brain water content or hematoma volume. We quantified effect

sizes with the normalized (weighted) mean difference summary

statistic, using the summary measures of outcome provided in

the individual comparisons in studies where sufficient data were

available to allow this analysis (outcome reported for [1] animals

with ICH receiving the intervention, [2] control animals with

ICH receiving vehicle, and [3] sham animals neither undergoing

ICH nor receiving treatment). If the same group of animals was

assessed using several neurobehavioral scores or structural out-

comes in 1 study, we combined these using fixed effects meta-

analysis and used this pooled measure for further analysis. We

used the DerSimonian and Laird weighted mean difference ran-

dom effects model to aggregate the weighted summary statistic

for each individual comparison into a pooled estimate of effect

size,14 grouping interventions by their main putative mechanism

of action as attributed by the authors of individual studies.

SENSITIVITY ANALYSES. We assessed the effect of key

methodological study attributes by stratifying the pooled estimate

of effect in all studies by the use of randomization, allocation

concealment, and blinded assessment of outcome. For each class

of intervention, we assessed whether the pooled estimate of pri-

mary (neurobehavioral) outcome at the last time point of assess-

ment was modified if we restricted analyses to outcome data pro-

vided at 7 6 2 days after ICH induction. In a post hoc

sensitivity analysis, we explored whether the addition of studies

that administered interventions prior to the induction of ICH

affected the pooled estimate of effect on the primary outcome.

ASSESSMENT OF HETEROGENEITY. We used the chi-

square statistic to assess the significance of differences between

studies (with n � 1 degrees of freedom), and used the Bonfer-

roni correction to calculate significance, taking into account the

number of comparisons performed.

META-REGRESSION. We identified studies describing

functional and structural outcomes in the same group of ani-

mals. We used meta-regression to explore the relationship

between functional and structural outcome and: aspects of

study quality; the intervention tested; the time of treatment;

and the time of outcome assessment. Meta-regression extends

the random effects meta-analysis model by taking into account

1 or more study-level covariates and determines how much het-

erogeneity can be explained by taking into account both within-

and between-study variance.15 We performed meta-regression

using STATA 10 with the linear function metareg. We built the

regression model in a hierarchal manner, by running the regres-

sion analysis 1 variable (or group of dummy groups) at a time.

The variable with the most significant change in the F ratio was

the first variable to enter the model. The second variable was

then chosen by the largest change in the F ratio in the model

that already contained the first variable. This process was iter-

ated until there were no significant changes in the F ratio. The

adjusted R2 value provided indicates how much residual hetero-

geneity is accounted for by the covariates.

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390 Volume 69, No. 2

Results

Our searches identified 98 potentially eligible studies of

the effect of nonsurgical interventions on neurobehavioral

outcome (Fig 1). We excluded 10 studies because ICH

was not induced using collagenase or autologous blood

injection,16–18 outcome data could not be extracted or

obtained,19 variance values of zero precluded meta-analy-

sis,20,21 or interventions were administered before the

induction of ICH22–25 (although we included 3 of these

studies in a post hoc sensitivity analysis24–26). After cor-

responding authors clarified the data in 2 studies,27,28 we

included 88 studies reporting 151 different treatment

comparisons (87 of which had sham groups) that

described the effects of nonsurgical interventions on neu-

robehavioral outcome in 2,616 treated or control rodents

with ICH (Supporting Information Table 1).26–113

Study CharacteristicsThe most frequently used animal model of ICH was col-

lagenase injection (53 [60%] studies; see Supporting Infor-

mation Table 1), and ICH was induced in the striatum in

all but 1 study (99%).51 The median number of treated or

control animals used in each study was 14 (interquartile

range, 12–21; full range, 6–100). Only 2 studies

reported deaths prior to the planned time of culling: 7 of

63 animals died during ICH induction in 1 study, and 5

of 18 died during another (representing a case fatality

rate of 15%).86,94 Sixty-four different interventions were

given at a median interval after ICH induction of 2

hours (interquartile range, 20 minutes to 6 hours). The

included studies reported outcome using 38 different

neurobehavioral scales (see Supporting Information Table

1), most often the forelimb placing test (10%), neurolog-

ical severity score (10%),114 corner turn test (9%), and

modified limb-placing test (9%). Brain water content

was the most frequently reported structural outcome (38

[43%] studies, most of which [89%] used wet and dry

brain weights to quantify it), and hematoma volume was

reported in 30 (34%) studies (and was measured by sev-

eral techniques including a variety of histological meth-

ods, spectrophotometry, or magnetic resonance imaging).

Risk of Bias of Included StudiesThe median study quality score was 4/10 (interquartile

range, 3–5). Of 88 publications, 27 (31%) reported ran-

dom allocation to group, 7 (8%) reported allocation con-

cealment, and 43 (49%) reported the blinded assessment

of outcome. No study reported a sample size calculation,

only 1 study reported the use of animals with comorbid-

ities, and 28 (32%) used ketamine, which is an anes-

thetic agent with intrinsic neuroprotective properties.13

For neurobehavioral score, studies that did not report

random allocation to group were associated with larger

effect sizes (32%; 95% confidence interval [CI], 26–39;

n ¼ 107) compared to those that did (21%; 95% CI,

13–29; n ¼ 42; chi-square ¼ 437; df ¼ 1; p < 0.0001).

FIGURE 1: Summary of study selection.

Frantzias et al: ICH Animal Models

February 2011 391

Similarly, studies that did not report allocation conceal-

ment were associated with larger estimates of effect

(31%; 95% CI, 26–37; n ¼ 132) compared to studies

that did (20%; 95% CI, 6–33; n ¼ 17; chi-square ¼ 33,

df ¼ 1, p < 0.0001). The reporting of blinded assess-

ment of outcome accounts for a significant proportion of

between-study heterogeneity (chi-square ¼ 43, df ¼ 1,

p < 0.001), but there was no difference in effect sizes

between studies that did blind outcome assessment and

those that did not (29%; 95% CI, 22–36 vs 30%; 95%

CI, 21–38).

Neurobehavioral OutcomesStem cells, calcium channel blockers, anti-inflammatory

drugs, iron chelators, growth factors, thrombin inhibi-

tors, and peroxisome proliferator-activated receptor

gamma agonists improved neurobehavioral scores at the

last time point of assessment, although there was signifi-

cant between-study heterogeneity in several of these

classes of intervention (Fig 2). In a sensitivity analysis re-

stricted to studies reporting neurobehavioral outcome at

7 6 2 days after interventions delivered within 24 hours

of ICH (using 44% of the data used to evaluate the pri-

mary outcome), the improvement of neurobehavioral

outcome became statistically significant for some inter-

ventions (anti-oxidants, glutamate receptor antagonists,

heme oxygenase inhibitors, and minocycline) and insig-

nificant for others (calcium channel blockers, thrombin

inhibitors, and tumor necrosis factor (TNF)-a inhibitor

antisense oligonucleotide). In a post hoc sensitivity analy-

sis of the primary outcome in studies of interventions al-

ready included in the meta-analysis, also including stud-

ies that treated animals prior to ICH induction had no

significant impact on the pooled estimate for the 3 inter-

vention groups (antioxidants, estrogens, and TNF-a in-

hibitor antisense oligonucleotides) reporting both pre-

and post-ICH delivery of intervention (see Fig 2).24–26

We did not further analyze data from 2 studies that

treated animals prior to the induction ICH with agents

that had not also been administered after ICH

induction.22,23

Structural OutcomesIn the studies that reported brain water content in addi-

tion to neurobehavioral scores (Fig 3), the pooled reduc-

tion of brain water content was 34% (95% CI, 25–43)

in 78 comparisons involving 867 animals, with substan-

tial heterogeneity between studies (chi-square ¼ 956, p <

0.0001). Among 19 classes of intervention, 12 (63%)

significantly reduced brain water content (see Fig 3), and

8 of these also significantly improved neurobehavioral

scores (see Fig 2): stem cells, calcium channel blockers,

anti-inflammatory drugs, iron chelators, estrogens, micro-

glial inhibitors, propofol, and an angiotensin II receptor

blocker. Of these 8 interventions, the angiotensin II re-

ceptor blocker (81%; 95% CI, 68–94) and anti-inflam-

matory drugs (19%; 95% CI, 0.5–38) also reduced he-

matoma volume. There was neither an improvement in

neurobehavioral outcome nor a reduction in brain water

content for antioxidant drugs, glutamate receptor antago-

nists, hypothermia, and gap junction inhibitors. The

effects of the remaining 11 interventions on functional

and structural outcomes were discordant.

Meta-Regression of Structural andNeurobehavioral OutcomesFifty-three comparisons reported both a functional and a

structural outcome in the same group of animals. Struc-

tural outcome explained 38% of the observed heteroge-

neity in functional outcome (s2 ¼ 816, adjusted r2 ¼0.38, Fig 4). In a multivariate model, structural outcome

and the intervention used accounted for 65% of the

observed heterogeneity in neurobehavioral score (F15, 37

¼ 5.31, p < 0.001, df ¼ 52, s2 ¼ 286, adjusted r2 ¼0.65). Relative to structural benefit, additional functional

benefit was observed when animals were treated with

anti-inflammatory drugs (30%; 95% CI, 8–51), antia-

poptotic drugs (38%; 95% CI, 11–65), and albumin

(67%; 95% CI, 22–112) compared to antioxidants as

the reference group (chosen because this group contained

the largest quantity of data). Gap junction inhibitors

reduced functional benefit (�30%; 95% CI, �54 to

�7). These findings were not affected by whether the

structural outcome reported was hematoma volume or

brain water content. Study quality had no effect on the

relationship between structural and functional outcome.

Discussion

In a systematic review and meta-analysis of 88 controlled

studies describing the effects of 64 different nonsurgical

interventions on 38 different neurobehavioral scales in

2,616 rodents, interventions that improved both neuro-

behavioral score and structural outcome(s) in 2 or more

animal studies (albeit with some between-study heteroge-

neity) included stem cells, calcium channel blockers,

anti-inflammatory drugs, estrogens, and iron chelators.

We benefited from comprehensive search strategies

without language bias, prespecified outcomes and analytic

approaches, sensitivity analyses, and correction of statisti-

cal tests for multiple comparisons. Other reviews have

not meta-analyzed existing data.11,115 Nevertheless, publi-

cation bias is known to result in an overestimation of

effect sizes in animal models,116 and may have affected

ANNALS of Neurology


FIGURE 2: Weighted mean difference meta-analysis of the effects of nonsurgical interventions on neurobehavioral outcome incontrolled animal studies. Diamonds represent grouped estimates of effect (and their associated 95% confidence intervals) foreither classes of intervention or several studies of the same intervention. Effect estimates are organized by classes ofintervention followed by individual interventions, in descending order of sample size. Heterogeneity between studies withineach class of intervention is indicated in parentheses. Squares represent point estimates of effect, and horizontal lines aretheir 95% confidence intervals. Details of interventions and experimental design in the individual studies are provided inSupplementary Table 1. ATSC 5 adipose tissue-derived stromal cells; BMSC 5 bone marrow stem cells; NSC 5 nonspecificsuppressor cells; VEGF 5 vascular endothelial growth factor; MSC 5 mesenchymal stem cells; UCBC 5 umbilical cord bloodculture; GCSF 5 granulocyte colony-stimulating factor; GABA 5 gamma-aminobutyric acid; TNF 5 tumor necrosis factor.

our findings. Although the use of weighted mean differ-

ence meta-analysis allows the combination and compari-

son of outcomes across a large number of neurobehavio-

ral scales, these scales measure different functions, and

the findings presented here represent a summary of

available data.

FIGURE 3: Weighted mean difference meta-analysis of the effects of nonsurgical interventions on brain water content incontrolled animal studies. Diamonds represent grouped estimates of effect (and their associated 95% confidence intervals) foreither classes of intervention or several studies of the same intervention. Effect estimates are organized in the same order asFigure 2. Heterogeneity between studies within each class of intervention is indicated in parentheses. Squares represent pointestimates of effect, and horizontal lines are their 95% confidence intervals. Details of interventions and experimental design inthe individual studies are provided in Supplementary Table 1.

FIGURE 4: Meta-regression of functional (neurobehavioral score) and structural (brain water content or hematoma size)outcomes that were measured in the same groups of animals. The size of each point reflects the precision of each comparison.

ANNALS of Neurology


Methodological problems known to affect animal

studies were evident in the studies included in our analy-

ses.117 Their methodological quality was generally poor

(median score, 4/10), but variation among studies

enabled us to confirm the potent influences of random-

ization and allocation concealment on effect sizes. No

study reported a sample size calculation, the use of keta-

mine anesthesia was frequent despite its known intrinsic

neuroprotective properties,13 and every study bar 1 used

only healthy animals, which is known to bias animal stud-

ies of stroke.118 Furthermore, young animals without

comorbidities are unrepresentative of humans who suffer

ICH,9 and the predominantly striatal location of ICH

induction in the included studies did not fully represent

ICH in humans, which occurs in lobar regions and the

posterior fossa, may extend into other brain compartments,

and often causes hydrocephalus. Studies used a diverse array

of neurobehavioral scales, and several used only 1 scale

when a battery of tests might have given a more complete

description of neurobehavioral outcome.119 Many of the

scales have not been validated and rely on primarily motor

tasks. Moreover, the neurobehavioral scale used should

relate to whether an ICH is cortical or striatal, because the

neurological impairments arising from ICH vary by the an-

atomical location of the ICH.119 Furthermore, because

rodents have proportionately less white matter than

humans,11 and may have greater neuroplasticity,115 there

may be problems with the relevance of the animal models

to human ICH. There are differences between the 2 main

rodent models of ICH,120 but we found no evidence that

1 was any more relevant to the human condition than the

other. There was a general shortage of external validation of

interventions that appeared to improve outcome.

We have used meta-analysis to derive summary esti-

mates of efficacy from a collection of relatively small

studies, many of which were not sufficiently powered to

detect modest treatment effects. Where possible, we have

used weighted rather than standardized mean differences,

because this is a more powerful statistical approach when

the size of contributing studies is small.121 The use of

meta-analysis to aggregate data for neurobehavioral out-

comes described using ordinal scales is well established

(and indeed many of the contributing studies use para-

metric statistics to analyze these data), and is justified

because parametric analyses of nonparametric data

becomes more valid when large numbers of studies are

aggregated in this way.122

Importantly, only 40% of the variation in treatment

effect on neurobehavioral outcome was attributable to

the observed effect on structural outcome, increasing to

65% when drug-specific effects were also taken into

account. Although this provides some basis for the use of

structural outcomes in clinical trial programs, it does sug-

gest first that such structural outcomes capture only a

proportion of efficacy, and second that the relationship

between structural and functional outcome—and there-

fore the utility of such structural outcome measures—

may vary substantially between different drug classes.

Discordance has previously been reported between

animal and human studies in other diseases,123 and we

have shown that this is also the case for ICH. Of the

interventions that improved both structural outcomes

and neurobehavioral scores in animal models (see Figs 2

and 3), anti-inflammatory drugs have not improved out-

come in humans.124 Similarly, recombinant activated fac-

tor VII did not improve outcome in humans, and indeed

the first evidence of benefit on structural outcomes in

animals was reported after the start of human trials.7,125

For progress to be made in translational ICH

research, the quality of animal studies must improve.126

We have reasonable understanding of some of the patho-

physiological processes underlying ICH in animals,3,127

but future research might usefully focus on understand-

ing to what extent these mechanisms are important in

humans, allowing drug development to be targeted at the

key processes. Furthermore, we need animal models of

ICH that better mimic important pathophysiologic proc-

esses in humans, including hematoma expansion and re-

currence,3,10,115 and we need these experiments to be

conducted in such a way as to minimize the risk of study

quality bias. Only then may the translational paradigm

be reliable enough for effective treatments in animal

models to be tested in randomized controlled trials in

humans.

Acknowledgment

R.A.-S.S. was funded by a clinician scientist fellowship

from the UK Medical Research Council. M.R.M.

acknowledges the support of the MRC Trials Methodol-

ogy Hub.

We thank E. Lebedeva, A. Wong, and Dr C. Four-

naris for their generous assistance with translating studies

for this review.

Potential Conflicts of Interest

Nothing to report.

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Treatment of intracerebral hemorrhage in animal models: Meta-analysis