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Cutaneous allodynia in the migraine population.

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Cutaneous Allodynia in the Migraine
Population
Richard B. Lipton, MD,1–3 Marcelo E. Bigal, MD, PhD,1,3,4 Sait Ashina, MD,1 Rami Burstein, PhD,5
Stephen Silberstein, MD,6 Michael L. Reed, PhD,7 Daniel Serrano, MA,7 Walter F. Stewart, PhD,8
on behalf of the American Migraine Prevalence Prevention Advisory Group
Objective: To develop and validate a questionnaire for assessing cutaneous allodynia (CA), and to estimate the prevalence and
severity of CA in the migraine population.
Methods: Migraineurs (n ⫽ 11,388) completed the Allodynia Symptom Checklist, assessing the frequency of allodynia symptoms during headache. Response options were never (0), rarely (0), less than 50% of the time (1), ⱖ50% of the time (2), and
none (0). We used item response theory to explore how well each item discriminated CA. The relations of CA to headache
features were examined.
Results: All 12 questions had excellent item properties. The greatest discrimination occurred with CA during “taking a shower”
(discrimination ⫽ 2.54), wearing a necklace (2.39) or ring (2.31), and exposure to heat (2.1) or cold (2.0). The factor analysis
demonstrated three factors: thermal, mechanical static, and mechanical dynamic. Based on the psychometrics, we developed a
scale distinguishing no CA (scores 0 –2), mild (3–5), moderate (6 – 8), and severe (ⱖ9). The prevalence of allodynia among
migraineurs was 63.2%. Severe CA occurred in 20.4% of migraineurs. CA was associated with migraine defining features (eg,
unilateral pain: odds ratio, 2.3; 95% confidence interval, 2.0 –2.4; throbbing pain: odds ratio, 2.3; 95% confidence interval,
2.1–2.6; nausea: odds ratio, 2.3; 95% confidence interval, 2.1–2.6), as well as illness duration, attack frequency, and disability.
Interpretation: The Allodynia Symptom Checklist measures overall allodynia and subtypes. CA affects 63% of migraineurs in
the population and is associated with frequency, severity, disability, and associated symptoms of migraine. CA maps onto
migraine biology.
Ann Neurol 2008;63:148 –158
Cutaneous allodynia (CA) is characterized by pain provoked by stimulation of the skin that would ordinarily
not produce pain.1 The underlying mechanism of facial CA is sensitization of the nociceptive neurons in
the trigeminal nucleus caudalis, which receives convergent afferent input from the dura mater and periorbital
skin.2,3 Clinic-based studies suggest that about two
thirds of migraine sufferers experience development of
CA.4 – 6 As a marker of central sensitization, allodynia
has been proposed as a risk factor for progression to
chronic migraine.7–9 Therefore, CA has significant implications for our understanding of the pathophysiology of migraine attacks, for the implementation of
treatment, and for assessing prognosis.
CA is usually assessed by quantitative sensory testing
(QST). QST requires specialized equipment, training,
and testing; it is too cumbersome and costly for widespread use in clinical practice or epidemiological re-
search and is subject to temporal sampling error. As a
consequence, most studies on headache and CA come
from a small number of headache centers and the
highly selected patients treated there.5,10,11 There is an
urgent need to develop and validate simple methods
for assessing CA to better characterize CA in representative samples and to facilitate clinical practice.
Several groups have developed questionnaires to assess CA,10,12,13 but only one instrument has been validated against QST.13 Most questionnaires use dichotomous response options and score CA as present or
absent. However, CA is not an all-or-none phenomenon; it varies over time, emerging and remitting during
the course of a migraine attack.13 In addition, the
available questionnaires assess CA as a unitary dimension,12,13 though at least three types of CA are well
described (ie, thermal, dynamic mechanical, and static
mechanical allodynia).1,14 Thermal allodynia is tested
From the Departments of 1Neurology and 2Epidemiology and Population Health, Albert Einstein College of Medicine; 3Montefiore
Headache Center, Bronx, NY; 4New England Center for Headache,
Stamford, CT; 5Harvard Medical School, Cambridge, MA; 6Jefferson Headache Center, Philadelphia, PA; 7Vedanta Research, Chapel
Hill, NC; and 8Center for Health Research, Geisinger Clinic, Danville, PA.
Members of the American Migraine Prevalence and Prevention Advisory Group are listed in the Appendix on page xx.
Received Apr 24, 2007, and in revised form Jun 21. Accepted for
publication Jul 6, 2007.
148
Published online Dec 4, 2007, in Wiley InterScience
(www.interscience.wiley.com). DOI: 10.1002/ana.21211
Address correspondence to Dr Lipton, Albert Einstein College of
Medicine, 1300 Morris Park Avenue, Bronx, NY 10461.
E-mail: rlipton@aecom.yu.edu
© 2007 American Neurological Association
Published by Wiley-Liss, Inc., through Wiley Subscription Services
Fig. The 12-item Allodynia Symptom Checklist (ASC-12).
with QST by measuring nociceptive thresholds to hot
and cold. It is mediated by C nociceptive and A␦ fibers.1,14 Dynamic mechanical allodynia (brush allodynia), assessed by brushing the skin, is likely mediated
by A␤ mechanoreceptive and capsaicin-insensitive A␤
fibers.14 Von Frey hair filaments have been used to assess static mechanical (or pressure) allodynia, which is
mediated by A␦ nociceptive fibers.15
We developed the Allodynia Symptom Checklist
(ASC) by modifying Jakubowski and colleagues’14 instrument to provide graded response options. Our
goals were to quantify CA overall and to determine
whether there were natural subtypes of allodynia. We
administered the ASC to a population sample of severe
headache sufferers identified through the American Migraine Prevalence and Prevention (AMPP) project.
Herein we describe the questionnaire and its psychometric attributes in the general migraine population.
We also describe the prevalence distribution and characteristics of allodynia in this population.
Subjects and Methods
This study was conducted as a part of the AMPP project, the
details of which are reported elsewhere.15 This research protocol was approved by the Institutional Review Board at the
Albert Einstein College of Medicine. In brief, we first
screened a sample of 120,000 US households selected to be
representative of the US population using a validated headache questionnaire (AMPP phase 1). Of 162,576 individual
respondents, 30,721 reported having at least one severe headache in the prior year that was not caused by a head injury
or by a disease, such as the flu. We selected a random sample
of 24,000 of these severe headache sufferers and sent them a
second mailed questionnaire in phase 2. This questionnaire
was used to determine headache diagnoses for up to three
types of headache based on the Second Edition of the International Classification of Headache Disorders criteria.16 It
was also used to assess details of headache frequency, burden,
treatment, and comorbidities. This phase 2 instrument also
included the ASC, as detailed in the following section.
Allodynia Symptom Checklist
The ASC included 12 questions (Fig) about the frequency of
various allodynia symptoms in association with headache attacks. For individuals with more than one type of headache,
questions were directed to the “most severe type of headache,” based on the prior evidence indicating that the most
severe type was likely to be migraine.17–19 Instead of using a
dichotomous option (yes or no), the response categories were
“never,” “rarely,” “less than half the time,” and “half the time
or more.” Based on prior studies, the option “rarely” was
considered a negative response to reduce false-positive symptom reporting.17,18,20 In addition, subjects could also indicate that an item “does not apply to me.” That option was
used by someone who never shaved their face or someone
who never wore a ponytail.
Data Analysis
ASC items were scored as 0 (ie, never, rarely, or does not
apply to me), 1 (less than half the time), and 2 (half the time
or more), yielding scores that ranged from 0 to 24. Alternative scoring strategies were evaluated but did not materially
alter our results.21,22
Exploratory factor analysis was performed to determine
whether the 12 items could be reduced to a set of independent factors representing the various dimensions of CA. Factor analysis was completed using ordinary least-squares ex-
Lipton et al: Allodynia and Migraines
149
traction and oblique equimax rotation of the solutions.23
Ordinary least squares was used for factor extraction instead
of maximum likelihood because the items are categorical.
Items were retained in the factor on which they had highest
loading. Three factors emerged from the exploratory factor
analyses (see Results).
Item response theory was used to determine the relation
between individual items and allodynia severity. We first applied a traditional item response model, treating allodynia as
a single underlying construct. We then applied a nonlinear
mixed-effects model to each of the factors in the three-factor
solution.21 Interfactor correlations were estimated among the
three allodynia domains. We modeled our data using Gaussian adaptive quadrature, with four quadrature points per dimension.24
To assess the severity of allodynia, we estimated two parameters: discrimination and threshold. Discrimination corresponds to the slope of a logistic function. High item discrimination values (values greater than 1) indicate that the
item distinguishes subjects with high values on the CA latent
variable from those with lower values. Threshold indicates
the score of allodynia associated with a 50% chance of endorsing a given response category for an item. Because there
are three levels of responses to each item on the ASC, there
are two thresholds. The first threshold is between “never” or
“rarely” and “less than the half the time,” and the second is
between “less than half the time” and “half the time or
more.” The first threshold demarcates the location on the
latent variable scale beyond which subjects are more likely to
indicate that the symptoms occur “less than half the time”
rather than “never” or “rarely.” The second threshold demarcates the location on the allodynia scale beyond which the
probability of endorsing “half the time or more” exceeds “less
than half the time,” “never,” or “rarely.” Because we assume
that latent variables follow standard normal distributions, the
thresholds can be interpreted as the number of standard deviations above or below the mean of the latent variable required for a respondent to have a 50% chance of endorsing
the response category. Because 98% of the standard normal
distribution is bounded between three standard deviations,
items with thresholds beyond two standard deviations discriminate at very high or low levels of the latent variable.
Missing Data
Missing data were handled through multiple imputation
(missing data were assumed missing at random) to minimize
impact on subsequent parameter estimates. Our approach
performs multiple categorical imputations under a saturated
multinomial model using an established algorithm.23–25
Migraine and Allodynia
We modeled CA as the outcome variable in a series of Poisson regression models. In Model 1, we adjusted for demographic variables (eg, age, sex, race, income). In Model 2, we
added to adjustments for headache frequency, severity, and
duration of illness. In Model 3, we added to Model 2 adjustments that included comorbidities, use of preventive
medication, use of triptans, and use of opioids.
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Annals of Neurology
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February 2008
Results
Study Population
Of 24,000 mailed questionnaires, 16,577 headache sufferers returned usable surveys (69.1% response rate).
Among these respondents, 11,388 met Second Edition
of the International Classification of Headache Disorders criteria for migraine. Demographics for the returned sample closely matched those of the outgoing
sample of past year headache sufferers (Table 1).
Identifying Questionnaire Factors
Examination of the screen plot and eigenvalues suggested three CA factors (Table 2). We interpreted the
three factors to represent thermal, mechanical static,
and mechanical dynamic allodynia, and labeled them
accordingly. The thermal factor, which reflects pain
sensitivity to heat and cold, includes five items (ie,
shaving your face, taking a shower, resting your face or
head on a pillow, exposure to heat, and exposure to
cold). The mechanical static factor is composed of five
items (ie, wearing eyeglasses, wearing contact lenses,
wearing earrings, wearing a necklace, and wearing tight
clothing) and reflects pressure in a fixed locus. The mechanical dynamic factor comprises two items (ie,
combing your hair and pulling your hair back) and reflects a more dynamic pressure across an area of skin.
The three factors were intercorrelated. Items on the
thermal allodynia factor were correlated to the mechanical static factor (0.44) and the mechanical dynamic
factor (0.41). Items on the mechanical static and mechanical dynamic factors were also correlated (0.42).
Item Analysis
The first item analysis treated allodynia as a single underlying construct. The model demonstrated excellent
item properties (data not shown). The discrimination
score for an item measures how well it distinguishes
those with high scores on the allodynia scale from
those with low scores. Scores greater than 1 indicate
items that are highly discriminating. We then applied a
nonlinear mixed-effects model treating the three allodynia factors separately (mechanical static, mechanical
dynamic, and thermal), as shown in Table 3. The
items with the highest discrimination included “combing your hair” (discrimination ⫽4.89), “pulling your
hair back” (4.15), “wearing a necklace” (4.04), as well
as “wearing earrings” (3.63) or “taking a shower”
(3.02). Even the items with the lowest levels of discrimination, “resting your face or head on a pillow”
(1.75) and “wearing contact lenses” (1.89), were highly
discriminating.
Each of the items has three levels (never/rarely, less
than half the time, and half the time or more). The
first threshold (see Table 3) indicates how well an item
discriminates severity of allodynia in respondents who
Table 1. Demographic Features for the Target Sample and Respondent Sample
Demographic Features
Sex
Male
Female
Race
White
Black
Asian, Pacific Islander
American, Indian
Other
Unknown/no answer
Age, yr
18–24
25–34
35–44
45–54
55–64
65–74
ⱖ75
Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific
Urbanization
⬍100,000
100,000–499,999
500,000–1,999,999
ⱖ2,000,000
Household size
1 member
2 members
3 members
4 members
ⱖ5 members
Family annual income
⬍$22,500
$22,500–$39,999
$40,000–$59,999
$60,000–$89,999
ⱖ$90,000
Target Sample
(N ⴝ 24,000), n (%)
Returned Sample
(N ⴝ 16,577), n (%)
Response Rate
7,077 (29.5)
16,923 (70.5)
4,053 (24.4)
12,524 (75.6)
57%
74%
20,528 (85.5)
2,021 (8.4)
243 (1.0)
216 (0.9)
362 (1.5)
630 (2.6)
14,364 (86.6)
1,311(7.9)
142 (0.8)
124 (0.7)
225 (1.3)
411 (2.5)
70%
65%
60%
60%
62%
65%
1,768 (7.4)
4,179 (17.4)
5,414 (22.6)
6,191 (25.8)
3,706 (15.4)
1,676 (6.9)
1,066 (4.4)
741 (4.5)
2,478 (14.9)
3,693 (22.3)
4,616 (27.9)
2,977 (17.9)
1,321 (8.0)
751 (4.5)
42%
59%
68%
75%
80%
79%
70%
1,104 (4.6)
3,313 (13.8)
3,827 (15.9)
1,696 (7.1)
4,672 (19.5)
1,824 (7.6)
2,791 (11.6)
1,550 (6.5)
3,223 (13.4)
758 (4.6)
2,259 (13.6)
2,682 (16.3)
1,200 (7.2)
3,213 (19.4)
1,306 (7.9)
1,904 (11.5)
1,087 (6.6)
2,168 (13.0)
69%
68%
70%
71%
69%
72%
68%
70
67%
3,883 (16.2)
4,174 (17.4)
5,772 (24.1)
10,171 (42.4)
2,770 (16.7)
2,916 (17.6)
3,987 (24.0)
6,904 (41.7)
71%
70%
69%
68%
4,527 (18.9)
7,950 (33.1)
4,421 (18.4)
4,018 (16.7)
3,084 (12.9)
3,129 (18.9)
5,680 (34.3)
3,045 (18.4)
2,706 (16.3)
2,017 (12.2)
69%
71%
69%
67%
65%
6,378 (26.6)
4,893 (20.4)
4,390 (18.3)
4,234 (17.6)
4,105 (17.1)
4,267 (25.7)
3,312 (19.9)
3,094 (18.7)
2,993 (18.1)
2,911 (17.7)
67%
68%
70%
70%
71%
Lipton et al: Allodynia and Migraines
151
Table 2. Exploratory Factor Analysis for 12-Item Allodynia Symptom Checklist in Second Edition of the
International Classification of Headache Disorders Migraine Sufferers from the General Population (n ⴝ 11,194)
Items
Combing your hair
Pulling your hair back
Shaving your face
Wearing eyeglasses
Wearing contact lenses
Wearing earrings
Wearing a necklace
Wearing tight clothing
Taking a shower
Resting your face or head
on a pillow
Exposure to heat
Exposure to cold
Communality
Estimates
Loading SE
Thermal
Allodynia
Static Mechanical
Allodynia
Dynamic Mechanical
Allodynia
0.654
0.998
0.257
0.352
0.195
0.776
0.876
0.559
0.686
0.212 (0.018)
⫺0.176 (0.018)
0.381 (0.013)a
0.182 (0.011)
⫺0.011 (0.009)
0.040 (0.011)
0.037 (0.012)
0.157 (0.011)
0.622 (0.012)a
0.041 (0.015)
⫺0.034 (0.020)
0.258 (0.011)
0.346 (0.011)a
0.383 (0.011)a
0.784 (0.015)a
0.874 (0.016)a
0.575 (0.012)a
0.165 (0.011)
0.677 (0.032)a
1.071 (0.052)a
⫺0.093 (0.012)
0.219 (0.011)
0.119 (0.010)
0.155 (0.011)
0.095 (0.011)
0.161 (0.011)
0.213 (0.011)
0.497
0.661
0.649
0.613 (0.012)a
0.704 (0.013)a
0.719 (0.013)a
0.017 (0.010)
0.020 (0.011)
0.004 (0.010)
0.166 (0.011)
0.194 (0.011)
0.171 (0.011)
a
The measures that load on each factor.
SE ⫽ standard error. Values in parentheses are standard errors of factor loading.
say never/rarely versus less than half the time. For example, in the “exposure to heat” item, Threshold 1 is
0.32. This indicates that subjects whose level on the
thermal allodynia factor was 0.32 or more standard deviations greater than the mean were more likely to endorse “less than half the time” than “never” or “rarely.”
The second threshold of 1.0 indicated that subjects
with a thermal allodynia factor score more than 1 standard deviation greater than the mean were more likely
to say that exposure to heat increased their pain “half
the time or more” than to say that it happened “less
than half the time.”
The item responses span the thresholds from 0.28
standard deviation less than the mean (Threshold 1 for
pulling your hair) to 1.89 standard deviations greater
than the mean (Threshold 2 for shaving the face). The
item response model factors were highly correlated,
with interfactor correlations exceeding those observed
in the exploratory factor analysis. Thermal allodynia
correlated 0.76 with static mechanical allodynia, and
0.71 with dynamic mechanical allodynia. Static mechanical and dynamic mechanical allodynia were highly
correlated as well, with an interfactor correlation of
0.69.
Allodynia Severity and Migraine Symptoms
Based on the distribution of scores, we developed a CA
scale defining no CA (scores 0 –2), mild CA (3–5),
moderate CA (6 – 8), and severe CA (ⱖ9). Using these
scores, we found that 63.2% of migraine sufferers had
CA. Allodynia was absent in 36.8% of migraine sufferers, mild in 25.1%, moderate in 17.1%, and severe in
20.4%.
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Annals of Neurology
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February 2008
We examined the relation of these categories of CA
with the headache symptoms in our migraine sample
(Table 4). Severe CA was associated with headache frequency. Although just 12.9% of those with less than 6
headaches in the past year had severe CA, 20.3% of
those with headaches 13 to 24 days per year had it
(odds ratio [OR], 1.8; 95% confidence interval [CI],
1.5–2.2). The proportion increased to 25.9% in those
with headaches 104 to 179 days per year (OR, 2.5;
95% CI, 2.0⫽3.0). Severe CA was also more frequent
in those with throbbing versus nonthrobbing migraines
(25.9 vs 18.1%; OR, 2.3; 95% CI, 2.1⫽2.6), unilateral versus bilateral pain (24.9 vs 18.8%; OR, 2.2;
95% CI, 2.0⫽2.4), moderate or severe headaches versus mild headaches (25.8 vs 18%; OR, 2.9; 95% CI,
2.3–3.1), and being aggravated by physical activities
versus not aggravated (29.3 vs 17.9%; OR, 2.8; 95%
CI, 2.5–3.1).
Severe CA was associated with the level of disability
experienced by migraineurs, as measured by the Migraine Disability Assessment (MIDAS) questionnaire
(see Table 4). Whereas 13.5% of those with no disability had severe CA, the proportion increased to 20.7%
in those with mild disability (OR, 1.7; 95% CI, 1.5–
1.9), to 25.9% in those with moderate disability (OR,
2.2; 95% CI, 1.9 –2.5), and to 35.1% in the severely
disabled (OR, 3.4; 95% CI, 3.0 –3.9).
The presence of severe CA was also related with the
presence of associated symptoms in individuals with
migraine (Table 5). It was more common in those who
typically experience nausea (27.1 vs 19.2%; OR, 2.3;
95% CI, 2.1–2.6), photophobia (26.9 vs 18.9%; OR,
Table 3. Three-Factor Confirmatory Graded Item Response Model Analysis of 12-Item Allodynia Symptom
Checklist in Individuals with Second Edition of the International Classification of Headache Disorders Migraine
(n ⴝ 11,194)
Item Stem
Mechanical Static
Thermal
Mechanical Dynamic
Discrimination Threshold Threshold Discrimination Threshold Threshold Discrimination Threshold Threshold
1
2
1
2
1
2
Wearing
eyeglasses
Wearing contact
lenses
Wearing
earrings
Wearing a
necklace
Wearing tight
clothing
Shaving your
face
Taking a shower
Resting your
face or head
on a pillow
Exposure to
heat
Exposure to
cold
Combing your
hair
Pulling your
hair back
1.9514
0.1196
0.8856
1.8997
0.6416
1.1307
3.6352
1.223
1.6683
4.0447
1.2601
1.6846
2.5968
0.7158
1.2445
2.0753
1.2749
1.896
3.0162
1.756
0.8284
0.3824
1.4668
1.2418
2.6084
0.3216
1.0032
2.4227
0.5997
1.3494
4.8975
4.1534
0.1732
0.6593
⫺0.02689 0.375
The discrimination score reflects how well the item distinguishes subjects with high levels on the factor from those with low levels on
the factor. Larger discrimination parameters indicate stronger measurement of the latent variable. Threshold 1 contrasts “never” and
“rarely” versus “less than half the time” as response option. Threshold 2 contrasts “never,” “rarely,” and “less than half the time” versus
“half the time or more.”
2.4; 95% CI, 2.1–2.7), and phonophobia (26.9 vs
17.7%; OR, 2.4; 95% CI, 2.1–2.7).
Finally, a greater proportion of individuals with migraine with aura (31.3%) experienced severe CA compared with migraineurs without aura (14.2%) (OR,
3.5; 95% CI, 3.2–3.8).
Multivariate Analyses of Allodynia in Migraineurs
Table 6 summarizes predictors of CA in a series of
Poisson regression models. Among migraineurs, CA
was more common in Asians and Native Americans.
Women had a greater prevalence of CA than men in
all three models (Model 3: prevalence ratio [PR], 1.43;
95% CI, 1.28 –1.59).
CA did not vary as a function of education level,
and its relative frequency decreased with age over 65 in
all 3 models; whereas 28.8% of those migraineurs 75
years or older had CA, 37.9% of those aged 18 to 24
had CA (Model 3: PR, 0.64; 95% CI, 0.43⫽0.95).
The prevalence of CA increased in those with long
duration of illness relative to those with migraine for
less than 10 years, peaking after 40 to 49 years of illness (PR, 1.28; 95% CI, 1.01–1.64). CA was also associated with high frequency of attacks (from 24.9% in
those with less than 6 migraine attacks/year to 48% in
those with 2–3 attacks/week) and higher disability (Migraine Disability Assessment IV vs I: PR, 1.61; 95%
CI, 1.46 –1.75). Finally, CA was more common in
those with increased body mass index in all models (see
Table 6).
Discussion
We modified Jakubowski and colleagues’14 allodynia
questionnaire and administered it to a population sample of severe headache sufferers. In this article, we focus
on results obtained in more than 11,000 migraine sufferers from the general population. Our goals were to
refine the measurement of CA using a questionnaire, to
estimate the prevalence and severity of CA in the migraine population, to develop measures for allodynia
subtypes (thermal, static mechanical, and dynamic mechanical), and to contrast migraine sufferers with and
without CA on the ASC. In this discussion, we first
consider the scoring of the ASC instrument and then
the relation of ASC scores to the features of migraine.
Next, we discuss the three subscales that emerge from
factor analysis corresponding with different types of allodynia. After considering the limitations of this study,
we discuss its implications and directions for future research.
Lipton et al: Allodynia and Migraines
153
Table 4. Severity of Cutaneous Allodynia as Measured by the Allodynia Symptom Checklist-Questionnaire and
Migraine Headache Features and Disability in Second Edition of the International Classification of Headache
Disorders Migraine Sufferers from the General Population
Headache
Features
Total
Headache frequency
(attacks/yr)a
⬍6
6–12
13–24
24–51
52–103
104–179
Throbbinga
No
Yes
Unilaterala
No
Yes
Aggravated by
physical activitiesa
No
Yes
Moderate or severea
Yes
No
Disability
MIDAS I
MIDAS II
MIDAS III
MIDAS IV
None
Mild
Moderate
Severe
OR (95% CI)
n
%
n
%
n
%
n
%
3,724
36.8
2,545
25.1
1,794
17.7
2,061
20.4
431
840
516
1,136
455
205
54.4
42.5
38.3
35.4
28.4
28.0
167
452
396
819
435
175
21.1
22.9
29.4
25.5
27.1
23.9
92
348
251
589
298
162
11.6
17.6
18.6
18.4
18.6
22.2
102
336
273
664
416
189
12.9
17.0
20.3
20.7
25.9
25.9
1
1.6 (1.3–1.9)
1.8 (1.5–2.2)
2 (1.6–2.4)
2.5 (2.0–3.0)
2.5 (2.0–3.0)
2,846
878
39.6
29.8
1,811
734
25.2
24.9
1228
566
17.0
19.2
1,297
764
18.1
25.9
1
2.3 (2.1–2.6)
2,964
760
39.1
29.9
1,896
649
24.9
25.6
1,301
493
17.1
19.4
1,429
632
18.8
24.9
1
2.2 (2.0–2.4)
3,163
561
39.5
26.4
2,031
514
25.4
24.2
1,366
428
17.1
20.1
1,439
622
17.9
29.3
1
2.8 (2.5–3.1)
2,822
902
29.8
39.7
1,809
736
24.3
25.4
1,187
607
20.0
16.7
1,280
781
25.8
18.0
1
2.4 (2.2–2.7)
2,174
620
459
280
46.7
32.3
27.3
19.9
1,153
499
455
333
24.8
26.0
27.1
23.7
698
401
333
299
15.0
20.9
19.8
21.3
630
397
435
493
13.5
20.7
25.9
35.1
1
1.7 (1.5–1.9)
2.2 (1.9–2.5)
3.4 (3.0–3.9)
Complete data for these analyses were obtained from 10,124 migraineurs.
a
For clarity and brevity, the “do not know–do not remember” categories were omitted.
OR ⫽ odds ratio; CI ⫽ confidence interval; MIDAS ⫽ Migraine Disability Assessment questionnaire.
In the questionnaire that Jakubowski and colleagues’14 developed, subjects who gave a positive response to any of the 12 CA questions were considered
to have allodynia. The sensitivity of the questionnaire
was 84.8%, whereas the specificity was 52.2%, using
QST as a gold standard. If we accept the gold standard, the low specificity may reflect false-positive
symptom reporting, meaning that nonallodynic patients report allodynia symptoms. Based on prior work,
to reduce false-positives, we provided graded response
options and considered “rarely” as a negative response.17–19 These graded responses also created an opportunity to measure the severity of allodynia.
The psychometric analysis confirms that CA can be
considered as a quantitative trait. This quantitative perspective is consistent with clinical impressions of allodynia. Some patients do not develop allodynia at all.
Others develop it for some attacks, particularly if they
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are left untreated for a period of time. In chronic migraine, allodynia may be present between attacks.26
Thus, duration and severity of allodynia may depend
both on within-person biological factors and environmental factors, including treatment strategy.2,3,26 Our
goal was to develop a measure that summarized a patient’s allodynia experience over multiple attacks.
Quantitative response options lend themselves to the
development of a robust allodynia scale.
Using the ASC, we found that in the population,
CA was present in about 63.2% of migraine sufferers, a
number remarkably consistent with estimates based on
QST in clinical samples.12,13 The convergence of these
estimates lends credibility to our findings. This result
also demonstrates that allodynia is a common feature
of migraine, not just in specialty care but in the population. We found a distribution of scores: 36.8% had
no allodynia, and 25.1% had mild, 17.7% had mod-
Table 5. Severity of Cutaneous Allodynia, as Measured by the Allodynia Symptom Checklist-Questionnaire and
Associated Symptoms in Second Edition of the International Classification of Headache Disorders Migraine
Sufferers from the General Population
Associated
Symptoms
Nausea
No
Yes
Photophobia
No
Yes
Phonophobia
No
Yes
Aura
No
Yes
None
Mild
Moderate
Severe
OR (95% CI) for
Severe Allodynia
n
%
n
%
n
%
n
%
3,298
426
38.0
29.4
2,192
353
25.2
24.4
1,518
276
17.4
19.1
1,669
392
19.2
27.1
1
2.3 (2.1–2.6)
3,209
515
38.6
28.1
2,080
465
25.1
25.4
1,438
356
17.3
19.4
1,567
494
18.9
26.9
1
2.4 (2.1–2.7)
3,127
597
38.9
28.6
3,030
525
25.1
25.1
1,391
403
17.3
19.3
1,500
561
18.7
26.9
1
2.4 (2.1–2.7)
2,831
893
43.5
24.7
1,690
855
25.9
23.6
1,060
734
16.2
20.2
927
1,134
14.2
31.3.2
1
3.5 (3.2–3.8)
OR ⫽ odds ratio; CI ⫽ confidence interval.
erate, and 20.4% had severe CA using our somewhat
arbitrary categorical scale.
The presence and severity of allodynia was associated
with many aspects of migraine. The odds of CA more
than doubled in migraineurs with nausea, photophobia, and phonophobia. This association has not been
reported previously in representative sample of migraineurs. Particularly striking was the relation between
allodynia and headache frequency. As headache frequency increased, the proportion of migraine sufferers
with severe allodynia also increased. In a cross-sectional
study, it is not possible to disentangle causal sequence.
However, these findings are consistent with the idea
that repeated attacks of migraine lead to the development of allodynia.27,28 On the other hand, allodynia
may be a marker of risk for frequent and severe attacks.
We plan to explore these possibilities in the longitudinal data from AMPP. Finally, the odds of severe CA
increased 3.5-fold in migraine with aura. Because the
association is stronger for aura than for other associated
symptoms, aura may have a stronger link with CA.
Studies demonstrate that cortical spreading depression,
the physiological basis of aura, can activate brainstem
regions involved in the processing of nociceptive information via trigeminovascular mechanisms.29,30 Perhaps
this process lowers the threshold of nociceptive neurons
at the trigeminal nucleus caudalis and thalamus, predisposing to CA.
Though allodynia is sometimes considered a unitary
factor, physiological research suggests that there are
several subdomains of allodynia.14 Our exploratory factor analysis demonstrated factors that correspond to
the subdomains of thermal, mechanical dynamic, and
mechanical static allodynia. Thermal allodynia (mediated by C nociceptive and A␦ nociceptive fibers) is
measured by questions that tap sensitivity to heat and
cold (eg, taking a shower, washing your face).14 It is
interesting to note that shaving loaded with the thermal factor, perhaps because hot water is often used
when shaving. Mechanical dynamic or brush allodynia
is likely mediated by A␤ mechanoreceptors, which are
capsaicin insensitive; it was measured by questions
about combing hair and pulling the hair back.14 Mechanical static or pressure allodynia is mediated by A␦
nociceptive fibers; it loaded on questions about pain
while wearing earrings, necklace, or tight clothing.
These subtypes of allodynia can be assessed in relation
to direct measures of psychophysical thresholds using
QST. It is not clear whether these different types of
allodynia as measured by ASC are differentially associated with clinically important outcomes such as poor
response to acute treatment late in the migraine attack
or to headache progression.14 In future work, we will
map these subtypes of allodynia onto domain-specific
QST, as well as clinical features and outcomes.
This study should be interpreted with caution for
several reasons. First, we have not yet compared allodynia classification based on ASC with classification
based on QST. Though QST is sometimes regarded as
the gold standard for determining whether a patient
has allodynia at a particular point in time, it is subject
to temporal sampling error.13,14 For example, if testing
is conducted 5 minutes into an attack, and CA emerges
just 2 hours into the attack, CA will not be detected by
QST. Therefore, it may also be of greater clinical interest to validate the ASC against either physiological
Lipton et al: Allodynia and Migraines
155
Table 6. Prevalence of Allodynia and Adjusted Prevalence Ratios in Individuals with Migraine
Characteristics
Race
No answer
White
Black
Asian
Native American
Other
Sex
Male
Female
Highest education level
Junior high or less
Some high school
HSD or GED
Some college
Bachelor’s degree
Graduate school
Age, yr
18–24
25–34
35–44
45–54
55–64
65–74
⬎74
Illness duration, yr
⬍10
10–19
20–29
30–39
40–49
50–59
⬎60
Attack frequency,
attacks/yr
⬍6
6–12
13–24
24–51
52–103
ⱖ104
Disability
No
Mild
Moderate
Severe
Body mass index
Normal
Overweight
Obese
Morbidly obese
With
Allodynia
n
%
98
3,307
308
32
44
66
38.58
37.43
42.66
40
51.16
44.9
476
3,379
Total
Sample, N
PR (95% CI)
Model 1
Model 2
Model 3
275
9,696
784
86
96
157
Not calculated
1
1.14 (1.04–1.25)
1.07 (0.82–1.40)
1.37 (1.11–1.68)
1.20 (1.00–1.44)
Not calculated
1
1.07 (0.98–1.17)
1.18 (0.91–1.54)
1.33 (1.08–1.63)
1.15 (0.96–1.37)
Not calculated
1
1.08 (0.97–1.20)
1.28 (1.02–1.61)
1.32 (1.07–1.64)
1.10 (0.88–1.39)
24.56
41.28
2,192
8,902
1
1.68 (1.55–1.82)
1
1.68 (1.54–1.82)
1
1.43 (1.28–1.59)
55
202
914
1,614
665
371
48.67
44.59
38.19
41.34
32.52
32.92
117
501
2,628
4,256
2,259
1,232
1
0.92 (0.74–1.14)
0.78 (0.65–0.95)
0.85 (0.70–1.03)
0.67 (0.55–0.82)
0.68 (0.55–0.83)
1
0.82 (0.67–1.01)
0.68 (0.57–0.82)
0.73 (0.61–0.88)
0.58 (0.48–0.69)
0.61 (0.50–0.75)
1
0.88 (0.67–1.16)
0.80 (0.62–1.02)
0.85 (0.66–1.08)
0.69 (0.53–0.89)
0.71 (0.55–0.92)
185
682
959
1,113
636
199
81
37.91
40.77
39.32
38.55
36.87
31.54
28.83
541
1,798
2,659
3,168
1,917
700
311
1
1.08 (0.95–1.22)
1.04 (0.92–1.17)
1.02 (0.90–1.15)
0.97 (0.85–1.11)
0.83 (0.71–0.98)
0.76 (0.61–0.94)
1
0.99 (0.88–1.13)
0.97 (0.86–1.09)
0.95 (0.84–1.07)
0.90 (0.79–1.02)
0.78 (0.67–0.92)
0.66 (0.53–0.84)
1
1.02 (0.87–1.20)
0.96 (0.82–1.14)
0.90 (0.77–1.07)
0.86 (0.72–1.02)
0.78 (0.62–0.97)
0.64 (0.43–0.95)
648
594
363
145
63
663
20
43.37
49.13
46.9
43.81
47.01
41.44
42.55
1,611
1,304
831
356
149
1,730
53
1
1.13 (1.04–1.23)
1.08 (0.98–1.19)
1.01 (0.88–1.16)
1.08 (0.90–1.31)
0.96 (0.88–1.04)
0.98 (0.70–1.37)
1
1.16 (1.07–1.27)
1.22 (1.10–1.35)
1.21 (1.05–1.41)
1.31 (1.04–1.66)
0.95 (0.88–1.04)
1.46(0.95–2.26)
1
1.15 (1.06–1.25)
1.19 (1.08–1.32)
1.22 (1.05–1.43)
1.28 (1.01–1.64)
0.95 (0.87–1.03)
1.12 (0.63–1.98)
194
684
524
1,253
714
351
24.49
34.62
36.49
39.06
44.51
48.02
891
2,181
1,577
3,507
1,744
781
1
1.41 (1.23–1.62)
1.49 (1.30–1.71)
1.59 (1.40–1.82)
1.82 (1.59–2.08)
1.96 (1.70–2.26)
1
1.37 (1.19–1.58)
1.41 (1.22–1.62)
1.51 (1.32–1.72)
1.67 (1.46–1.92)
1.40 (1.31–1.51)
1
1.21 (1.00–1.46)
1.19 (0.98–1.44)
1.15 (0.96–1.39)
1.19 (0.98–1.44)
1.22 (1.00–1.50)
1,328
798
768
792
28.53
41.63
45.66
56.37
5,185
2,113
1,796
1,483
1
1.46 (1.36–1.56)
1.72 (1.54–1.91)
1.98 (1.85–2.11)
1
1.51 (1.41–1.62)
1.60 (1.49–1.72)
1.26 (1.17–1.37)
1
1.32 (1.21–1.45)
1.88 (1.76–2.00)
1.61 (1.46–1.78)
1,141
1,039
728
816
35.34
37.01
39.54
42.86
3,547
3,085
2,014
2,063
1
1.05 (0.98–1.12)
1.12 (1.04–1.20)
1.21 (1.13–1.30)
1
1.15 (1.07–1.24)
1.22 (1.14–1.31)
1.40 (1.32–1.48)
1
1.11 (1.03–1.20)
1.16 (1.06–1.26)
1.11 (1.02–1.21)
In Model 1, adjustment was conducted for demographic variables (eg, age, sex, race, income). In Model 2, adjustment was made for
demographics and also headache frequency, severity, and duration of illness. In Model 3, we used the same adjustments for Model 2
and also included comorbidities, use of preventive medication, and use of opioids.
PR ⫽ prevalence ratio; CI ⫽ confidence interval; HSD ⫽ high school diploma; GED ⫽ general equivalency diploma.
156
Annals of Neurology
Vol 63
No 2
February 2008
measures or patient outcomes. Second, this report does
not examine the prevalence of CA as defined by the
ASC in individuals with other types of headache; in a
separate report, we show that the prevalence of allodynia based on the ASC is greatest in transformed migraine, followed by migraine and probable migraine.28
Third, measuring the severity of symptoms and signs
for chronic disorders with episodic manifestations such
as migraine or epilepsy is challenging. Chronic disorders with episodic manifestations are characterized by
episodic attacks superimposed on an enduring predisposition to attacks.31 In measuring migraine severity,
pain intensity, number and severity of associated symptoms, and disability all index the severity of a particular
attack. Because attacks are transient and recurrent, time
enters into the assessment of severity. ASC measures
severity in the conventional sense by tapping into a
range of partially correlated symptoms and summarizing them. To assess the severity of allodynia at a particular point in time, we ascertained the presence or
absence of each ASC item at that point in time. But to
ascertain the overall severity of allodynia, we included a
measure of frequency for each of the 12 items. Thus,
our ASC score is based on the assumption that both
number and frequency of symptoms can be scaled together to measure severity. The psychometric validation using item response theory provides strong support for this assumption. Severity measures for other
chronic disorders with episodic manifestations, such as
asthma, combine symptom number and frequency.32
In addition, the definitions of mild, moderate, and severe allodynia are somewhat arbitrary. In longitudinal
analysis, we will assess the relation between ASC score
and headache prognosis to develop an empirical foundation for cut scores. Finally, though allodynia is associated with attack frequency at cross section, its relation with headache progression has not yet been
assessed.
Despite these limitations, a simple, quantitative tool
for assessing allodynia should find applications in research and, we hope, in clinical practice. If CA predicts
response to triptan therapy,6 knowing whether a patient has allodynia has clinical implications. In addition, migraine is now viewed as a sometimes progressive disorder that may lead to chronic migraine.31,33
Because migraine progresses to chronic migraine in
some but not most individuals, identifying the risk factors for progression has emerged as an important public health priority. We have divided risk factors for progression into those that are modifiable (eg, obesity,
attack frequency) and those that are nonmodifiable (eg,
female sex).27 CA may be a modifiable risk factor for
migraine progression if pharmacological or nonpharmacological strategies reduce the frequency of CA by
reducing the frequency of attacks.
This study was sponsored by the National Headache Foundation,
which is supported by Ortho-McNeil Neurologics (grant number
991836659 [R.L. M.B., D.S., M.R.]
We thank S. Simons, Dr K. M. Fanning, and K. Ward
for help with data management and statistical analyses.
Appendix
The members of the AMPP advisory group are Richard
B. Lipton, MD (principal investigator), Marcelo E. Bigal, MD, PhD, Dawn Buse, MD, Michael L. Reed,
PhD, Walter Stewart, PhD, Merle Diamond, MD,
Frederick Freitag, DO, Elisabeth Hazard, PhD, Jonothan Tierce, CPhil, Elizabeth Loder, MD, Paul Winner, MD, Stephen Silberstein, MD, Suzanne Simons,
and Seymour Diamond, MD.
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