Neurology. 2011 Mar 15; 76(11): 968–975.

doi: 10.1212/WNL.0b013e3182104407
PMCID: PMC3059137
PMID: 21403108

Early recognition of poor prognosis in Guillain-Barré syndrome

C. Walgaard, MD, H.F. Lingsma, PhD, L. Ruts, MD, P.A. van Doorn, MD, E.W. Steyerberg,
PhD, and B.C. Jacobs, MD

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Associated Data
Supplementary Materials

Abstract
Background:
Methods:
Results:
Conclusions:
Guillain-Barré syndrome (GBS) is a monophasic polyradiculoneuropathy with a
highly variable clinical severity and outcome. IV immunoglobulin (IVIg) and
plasma exchange (PE) are beneficial in patients who are severely affected,
although one-third recover incompletely.1 These patients require more effective
treatment, but the clinical diversity and the rarity of the disease hamper good and
well-powered randomized controlled trials in this patient group. To identify early
patients with a poor outcome, who are eligible for additional treatment, prognostic
models are needed. Prognostic models can also increase the power of therapeutic
studies by adjusting for prognostic factors.2 Ultimately, such prediction models can
be used to individualize therapy in accordance with the expected outcome.
Previous studies have identified patient characteristics associated with poor
outcome in GBS.3,–10 The Erasmus GBS Outcome Score (EGOS) is a prognostic
model based on age, diarrhea, and GBS disability score at 2 weeks after hospital
admission that accurately predicts the chance of being able to walk independently
at 6 months.8 However, prognostic models to optimize treatment in GBS should be
applicable in the earliest phase of the disease, when treatment is considered to be
most effective. Such models should also be designed to predict the primary
endpoints used in most treatment trials in GBS; i.e., the clinical recovery on the
GBS disability score at 4 weeks.11,–15 The aim of the current study was to develop a
readily applicable prognostic model for accurate selection of patients with a poor
prognosis, based on clinical information available in the first week of hospital
admission.

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METHODS
Patients.

Data collected prospectively from a cohort of 397 patients with GBS were used to
identify predictors for outcome. This derivation cohort consisted of patients who
had been included in 2 treatment trials and one pilot study. The first study was a
multicenter double-blind randomized controlled trial; this included 147 patients
between 1985 and 1991 and compared PE with IVIg.12 The second study was a
pilot study in 25 Dutch patients to determine the additional therapeutic effect of
methylprednisolone (MP) to IVIg.16 This combination was tested in the third study:
a multicenter double-blind randomized controlled trial in 225 patients included
between 1994 and 2000.15 Most patients were included in Dutch hospitals, the
others in 2 German and 2 Belgian hospitals. All 3 studies used the same inclusion
and exclusion criteria. Inclusion criteria were fulfillment of the National Institute
of Neurological Disorders and Stroke diagnostic criteria for GBS,17 inability to
walk unaided 10 meters across an open space (GBS disability score 3 or more), and
onset of weakness within 2 weeks before randomization. Exclusion criteria were
age below 6 years, pregnancy, previous GBS, known severe allergic reaction to
properly matched blood products, known selective IgA deficiency, previous steroid
therapy, severe concurrent disease, inability to attend follow-up, or
contraindications for corticosteroid treatment (not in first trial).

To validate the model, we used data collected prospectively from a cohort of 191
patients enrolled in a pilot study18 and an observational study19 in patients with
GBS, both performed in the Netherlands. The pilot study evaluated the additional
therapeutic effect of mycophenolate mofetil to IVIg and MP in 27 patients
included between 2002 and 2005. The same inclusion and exclusion criteria were
used as in the derivation cohort. Between 2005 and 2008, 164 patients with GBS
were included in the observational study, which assessed pain and autonomic
dysfunction (GRAPH study).19 Patients with a mild form of GBS (able to walk
throughout the course of the disease) (n = 33) were also included in this study, but
not used for validation.

Patient characteristics were described in more detail in the trial and survey
reports.12,15,16,18,19

Standard protocol approvals, registrations, and patient consents.

Approval was received by an ethical standards committee on human

experimentation for each of the studies mentioned above. Written informed
consent was received from all patients.

Data collection.
All data were collected prospectively. At hospital admission, information was
obtained regarding age, gender, diarrhea, or symptoms of an upper respiratory tract
infection in the 4 weeks preceding onset of weakness, day of onset of weakness,
cranial nerve dysfunction, Medical Research Counsel (MRC) sumscore,20 GBS
disability score,21 and sensory deficits. In addition, data on the MRC sumscore and
GBS disability score were collected at day 7 of hospital admission. The MRC
sumscore is defined as the sum of MRC scores of 6 different muscles measured
bilaterally, which results in a sumscore ranging from 0 (tetraplegic) to 60 (normal;
appendix e-1 on the Neurology® Web site at www.neurology.org).20 The GBS
disability score is a widely accepted scale for assessing the functional status of
patients with GBS, ranging from 0 (normal) to 6 (death; appendix e-
1).21 Pretreatment serum samples obtained within 4 weeks of onset of weakness
were used for serologic screening to identify recent infections with Campylobacter
jejuni and cytomegalovirus (CMV).

Age and MRC sumscore were categorized to facilitate the applicability in clinical
practice. Categories were based on even group sizes and predictive ability.

Outcome measures.

This study used walking ability as outcome measure. Poor outcome was defined as
the inability to walk unaided 10 meters across an open space (GBS disability score
of 3 or higher). Outcome was assessed at 4 weeks, 3 months, and 6 months after
inclusion in one of the studies. An additional outcome measure in this study was
the improvement of one or more points on the GBS disability score in the first 4
weeks after inclusion. No improvement was considered as poor outcome. Both
outcome measures have been used as primary endpoint in previous treatment trials
in GBS.11,–15
Model development.

Potential prognostic factors of outcome at 4 weeks, 3 months, and 6 months after

inclusion were first analyzed in the derivation cohort by univariable logistic
regression analysis. Statistically significant predictors for poor outcome at all
timepoints were further analyzed for their independent predictive value using
multivariable logistic modeling.

Missing values were imputed using a multiple imputation method.22 Odds ratios
(OR) were used to express the strength of prognostic effects and were compared
between the imputed and the complete case analyses. Predictive value was also
measured using the likelihood ratio χ2 test (LR chi2), to account for the prevalence
of the predictor. Variables that added significant predictive information were
selected for use in a multivariable model. A p value <0.05 was considered to be
significant.

The model was fitted using the ability to walk unaided at 4 weeks after hospital
admission as outcome measure. The model was constructed based on the
multivariable logistic regression coefficients in the derivation dataset.

Predictive performance of the model was quantified with respect to discrimination

(area under the receiver operating characteristic curve [AUC]). The AUC ranges
from 0.5 to 1.0 for sensible models. The internal validity of the model was assessed
by bootstrapping techniques, including both the selection of predictors and
estimation of the coefficients.22 The model was externally validated in an
independent validation cohort of patients with GBS. Model performance in the
validation set was quantified with respect to discrimination (AUC) and calibration.
Calibration was assessed graphically by plotting observed frequencies against
predicted probabilities.
Statistical analyses used SPSS version 15.0 for Windows, Stata version 11,
and R statistical software (version 2.7, using the Design library).

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RESULTS

Three (<1%) of the 397 patients in the derivation cohort died in the first week after
hospital admission and were excluded from the current study. In this cohort, the
primary endpoint was missing at 3 months for 3 (<1%) patients and at 6 months for
12 (3%) patients. Fifty-five percent had a poor outcome at 4 weeks, 30% at 3
months, and 19% at 6 months after hospital admission. In the validation cohort,
none of the patients died in the first week of follow-up. Due to the slightly
different follow-up structure of the observational study, outcome was unavailable
for 38 (24%) patients at 4 weeks, 14 (9%) patients at 3 months, and 7 (4%) patients
at 6 months after hospital admission. These patients were excluded from the study.
Of the remaining patients in the validation cohort, 54% had poor outcome at 4
weeks, 29% at 3 months, and 15% at 6 months after hospital admission.

Gender, bulbar and facial weakness, sensory deficit, and pain were not
significantly correlated with outcome (table e-1). In univariate analysis, 6
predictors of outcome—at 4 weeks, 3 months, and 6 months—were identified: age,
disease progression (expressed as number of days between onset of weakness and
hospital entry), MRC sumscore and GBS disability score, diarrhea in the 4 weeks
preceding GBS, and C jejuni serology (all p = 0.05–0.001) (table 1 and table e-
1). C jejuni serology was excluded for multivariable analysis because in clinical
practice serology results will be difficult to obtain shortly after hospital admission.
For further modeling, the MRC sumscore was selected over the GBS disability
score, because the model using the MRC sumscore had a substantially better
performance (LR statistic 69.75 vs 46.49 at admission and 195.27 vs 154.35 at 1
week). Disease progression lost its predictive ability when analyzed in a
multivariable model with age, diarrhea, and MRC sumscore. The results of the
multivariable analyses of the remaining prognostic factors are shown in table 2.

Table 1

Risk of poor outcome, defined as inability to walk unaided at 4 weeks, 3 months,

and 6 months after entry to the hospital, according to potential predictors in the
derivation set of 394 patients with GBS based on univariable regression analysis
 Open in a separate window
Abbreviations: CI = confidence interval; GBS = Guillain-Barré syndrome; MRC = Medical Research
Council; NS = nonsignificant; OR = odds ratio; URTI = upper respiratory tract infection.

Time between onset of weakness and admission in days, odds ratio per extra day.
a

b Symptoms of an infection in the 4 weeks preceding the onset of weakness.

Using pretreatment serum samples obtained at entry.
c

Table 2
Multivariable analysis of main predictors of poor outcome, defined as being unable
to walk at 4 weeks after hospital admission and as no improvement on the GBS
disability score in the first 4 weeks after admission

Abbreviations: AUC = area under the receiver operating characteristic curve; CI = confidence interval;
MRC = Medical Research Council; OR = odds ratio.

Diarrhea in the 4 weeks preceding the onset of weakness.

a

Age, diarrhea, and MRC sumscore were used to develop the model for clinical
practice. This model was a modification of the previously developed EGOS.8 In
contrast to the EGOS, this modified EGOS (mEGOS) can be applied already at
hospital admission and at day 7 of hospital admission. When used at admission, the
mEGOS scores ranged from 0 to 9 with 4 categories for the MRC sumscore, 3
categories for age, and 2 categories for preceding diarrhea (table 3 and figure 1A).
The predictive ability of the model was better when used at day 7 of admission,
because the MRC sumscore at this timepoint predicts outcome more accurately.
Therefore, the MRC sumscore was weighted stronger in the mEGOS when used at
1 week and the scores range from 0 to 12 (table 3 and figure 1B).

Table 3

Modified Erasmus GBS Outcome Scores

Abbreviations: mEGOS = modified Erasmus GBS Outcome Score; MRC = Medical Research Council.

Diarrhea in the 4 weeks preceding the onset of weakness.

a
Figure 1
Predicted fraction of patients unable to walk independently according to modified Erasmus
GBS Outcome Score (mEGOS)

Predicted fraction of patients unable to walk independently at 4 weeks (black lines), 3 months
(red lines), and 6 months (green lines) on the basis of the mEGOS at hospital admission (A) and
at day 7 of admission (B). The gray areas around the colored lines represent 90% confidence
intervals.

The performance of mEGOS when used at admission was good for prediction of
outcome at 4 weeks (AUC 0.73), at 3 months (AUC 0.73), and at 6 months (AUC
0.77) and was excellent when used at day 7 of admission, with AUCs for
predicting outcome at these 3 timepoints of 0.87, 0.84, and 0.84, respectively. The
mEGOS was validated in an independent cohort and showed a good calibration
(figure e-1) and a good discriminative ability for predicting outcome at all 3
timepoints (admission: AUC = 0.75, 0.73, and 0.75; 1 week: AUC = 0.81, 0.70,
and 0.77).

Age, preceding diarrhea, and MRC sumscore in multivariable analysis were also
independently associated with another endpoint that is frequently used in
therapeutic trials in GBS: the improvement of one or more points on the GBS
disability score at 4 weeks after hospital admission (table 2). In addition, the
mEGOS model predicted the failure to improve on the GBS disability score at 4
weeks with high accuracy (AUC of 0.71 and 0.87).

The current model can also be used to compare populations of patients included in
various therapeutic trials and for covariate adjustment. To illustrate this, we
compared 3 study populations12,15,19 with respect to the distribution of the patients
over the mEGOS categories (figure 2). The figure illustrates the ability of mEGOS
to make a distinction between different GBS populations with respect to prognosis.
The patients included in the observational study had an overall better prognosis, as
was expected because of the different inclusion criteria, which allowed the
inclusion of mildly affected patients.
Figure 2
Comparing 3 therapeutic study populations with respect to prognostic factors at hospital
admission using modified Erasmus GBS Outcome Score (mEGOS)

Points represent the percentages of patients with a specific mEGOS in a therapeutic trial
comparing plasma exchange vs IV immunoglobulin (IVIg) (green), a therapeutic trial comparing
IVIg/placebo vs IVIg/methylprednisolone (red), and an observational study (black). Smoothed
lines represent the distribution of the study population over the total mEGOS.

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DISCUSSION

The variation in clinical severity and outcome between patients with GBS hampers
optimizing of treatment, because heterogeneous study populations will reduce the
statistical power of treatment trials. New therapies and treatment modalities for
GBS may not further improve outcome in patients who already recover sufficiently
after standard treatment. Therefore, selective treatment trials should focus on a
more homogeneous subgroup of patients with poor recovery despite current
standard treatment. In this study a prognostic model is presented which early
identifies patients with poor outcome and can be used for future therapeutic trials.
The main predictors of being unable to walk independently at 4 weeks, 3 months,
and 6 months were MRC sumscore, age, and preceding diarrhea in our study.
Based on these predictors, a model was constructed which proved to be valid in an
independent cohort of patients with GBS. The model is applicable at hospital
admission as well as at day 7 of hospital admission and is therefore suitable to
study treatments which should be started immediately as well as after standard
treatment in patients with poor prognosis. The model may provide a first step
toward individualized treatment in GBS.
This mEGOS originates from the EGOS, which can be applied in clinical practice
at 2 weeks after hospital admission to predict outcome at 6 months and is based on
the predictors age, preceding diarrhea, and GBS disability score.8 The EGOS is a
simple, accurate, and validated prognostic model, but less suited for treatment
development because of the delay of 2 weeks and the predicted outcome measure.
The mEGOS was primarily designed for future treatment studies in GBS and for
this application has important advantages. First, the mEGOS model can be applied
already in the first week of admission, when treatment is considered to be most
effective. Second, the mEGOS predicts reaching independent walking or
improving on the GBS disability score at 4 weeks, which are the 2 primary
endpoints most frequently used in therapeutic trials in GBS. Third, the mEGOS
also accurately predicts long-term GBS disability scores, which were important
secondary endpoints in previous trials. Because of these features, the mEGOS
model can be used for early identification of patients with poor prognosis for future
selective therapeutic studies. In addition, this model can be used for covariate
adjustment, which is a powerful tool in heterogeneous patient populations to
estimate the effect of treatment in individuals and to increase the statistical power
of therapeutic trials.2,23,24 For example, adjustment for the effect of age on outcome
results in an estimated treatment effect for a patient of a given age instead of an
average age. When the results of these selective trials in patients with poor
prognosis are positive, the mEGOS may also be used to individualize treatment of
patients with GBS in routine clinical practice.

Our study confirms that poor outcome is associated with older age,4,5,7,8,10 rapid
disease progression,7,10severe disease indicated by GBS disability score or MRC
sumscore,3,4,7,8 preceding diarrhea, positive C jejuni serology,3,5,8 positive CMV
serology,9 and no symptoms of a preceding respiratory tract infection.3–4Two of
these studies used partly the same data as in this study.8–9 For the purpose of this
study, we selected age, preceding diarrhea, and MRC sumscore, which are readily
available at hospital admission of the patient. Prognostic biomarkers may further
improve those models in the future. Promising candidates are infection serology,
antiganglioside antibodies, and serum IgG level increase after IVIg treatment,
which were all related to outcome.3,5,6,8,9 The need for accurate prediction models
for outcome has also been acknowledged for traumatic brain injury25 and for
stroke.26,27 These neurologic conditions resemble GBS in the sense that they are
acute and monophasic and have a highly variable clinical course.

Our study had several limitations. First, the prognostic model was derived from
cohorts of Dutch Caucasians, which may restrict the application to those patients.
Second, information on outcome at 4 weeks was not available in 24% of patients
from the validation cohort. For this cohort data were used from an observational
study, in which 4 weeks was not a standardized evaluation timepoint. However,
percentages of patients with a poor outcome at 4 weeks in the derivation and
validation cohort were comparable (55% and 54%), so it is unlikely that this
caused bias. A third limitation is that the model only predicts the ability to walk
independently, and not the full ordinal GBS disability scores, as this would have
provided maximum statistical power.28 However, this specific outcome measure we
used is highly relevant for patients and was previously used by most therapeutic
trials in GBS. Finally, EMG may have prognostic relevance in GBS, as indicated
by several studies3,–5,7,10; unfortunately, EMG was not performed systematically in
the current study. Future studies are needed to define if EMG has additional value
for predicting outcome already at the day of hospital admission.

The mEGOS is an accurate and validated model for prediction of outcome at

several timepoints in the first 6 months after onset of GBS. An important
advantage above existing models is that the mEGOS can be used in the early phase
of disease when the process of nerve damage is ongoing and possibly reversible.
This model predicts commonly used trial endpoints in GBS and can be used to
conduct new trials selectively in patients with poor outcome. In addition, the model
can be used to compare patient populations with respect to prognostic factors and
expected outcome. This model may assist clinicians in optimizing treatment for
individual patients with GBS.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3059137/