Keywords: Headache - Migraine Disorders - Neck Pain
Palavras-chave: Cefaleia - Transtornos de Enxaqueca - Cervicalgia
INTRODUCTION
The diagnosis of migraine is based on well-defined clinical characteristics that are
described in the International Classification of Headache Disorders, 3rd edition (ICHD-3)[1 ]. A comment about the clinical expression of migraine in the ICHD-3 recognizes the
frontotemporal region as the usual migraine pain site. However, other spatial information
has no formal diagnostic value.
In the largest study (n=1,283) dedicated to the topic of migraine pain location, Kelman
found that the orbital, frontal and temporal sites were the regions most prevalently
affected by migraine[2 ]. Interestingly, this study highlighted the diagnostic value of the pain site by
demonstrating that episodic migraine (EM) affects the eyes more frequently than does
chronic migraine (CM), which, in turn, is characterized by neck, occipital and diffuse
pain.
Most studies have used similar verbal descriptors to categorize the migraineurs’ pain
location. However, use of terms like “diffuse” and “eyes” to describe unspecific or
composite sites might hinder future comparisons. Also, the way in which borderline
regions are reported could result in overestimation or underestimation of the involvement
of some sites.
Fernándes-de-las-Peñas et al. demonstrated the use of drawings to explore pain extent
in migraineurs[3 ]. More recently, Uthaikhup et al. used the drawings of 114 participants to compare
pain location in EM (n=48), CM (n=30), and cervicogenic headache and explored the
associations between location and other headache features, psychological distress
and quality of life[4 ]. They found that the frontal and temporal regions were the most commonly affected
sites in migraineurs, with a trend towards more posterior pain in the CM group. Larger
pain extent was correlated with higher headache intensity and worse quality of life
in CM.
These studies show an intriguing association between CM and more posterior (extratrigeminal
sites) and/or diffuse pain.
Although migraine is predominantly associated with dysfunction of the trigeminal system,
a large number of articles have demonstrated that activation of the high cervical
nociceptive system occurs during attacks. This correctly reclassifies migraine as
a pathological condition related to dysfunction of the trigeminocervical system. The
caudal subnucleus of the trigeminal nucleus is an intermediate structure of the cranial
nociceptive system that receives nociceptive afferents from the first and second branches
of the trigeminal and the first cervical roots, resulting in a convergence mechanism
known as trigeminocervical convergence[5 ]. This physiological phenomenon has been clinically demonstrated through chemical
stimuli on the major occipital nerve, which generated immediate pain radiating to
the first branch of the trigeminal tract, mainly in the orbital and supraorbital region[6 ]. On the other hand, an anesthetic block of the major occipital nerve may be able
to control migraine attacks[7 ].
Hence, migraine is not a disorder that is static in space; and not even in time and
intensity. The episodic form (EM) can evolve to a progressive form (CM) characterized
by increases in the frequency, severity, duration and refractoriness of the attacks.
Genetic factors are probably involved in the neuronal mechanisms inside structures
participating in pain processing[8 ]. However, the influence of these alterations on the trigeminocervical process is
unclear.
The aim of the present study was to use non-verbal descriptors of migraine pain location
to identify the prevalence of the involvement of extratrigeminal sites (a manifestation
of trigeminocervical convergence) in the EM and CM groups. As a secondary objective,
we explored the factors associated with the presence of convergence, including a wide
range of variables related to demographic and psychological features, comorbidities,
lifestyle and other migraine characteristics.
METHODS
This research was originally designed to explore the role of certain genetic polymorphisms
in the clinical expression of migraine. The present study is a clinical data analysis
on the pain location pattern in our sample.
This study was approved by the Ethics Committee of Hospital de Clínicas, Universidade
Federal do Paraná (registration 2.732.610; CAAE number: 87998518.8.0000.0096) and
was registered in the Brazilian Registry of Clinical Trials (RBR-9wgwnj). Written
consent was obtained from all the patients prior to data collection.
We used a case-control design to compare different patterns of migraine pain location
between CM (cases) and EM (controls). Three centers participated in this research:
one tertiary-level healthcare center that exclusively serves the public healthcare
system (Hospital de Clínicas, Universidade Federal do Paraná); and two headache outpatient
clinics (Clínica de Neurologia São José and Hospital Marcelino Champagnat).
All the subjects invited to participate in the study presented the following characteristics:
(1) they had a definitive diagnosis of EM or CM (either associated with analgesic
abuse or not), in accordance with the ICHD-3; (2) they had been suffering from migraine
symptoms for at least six months before the research interview; (3) they had no limitations
on provision of information; (4) they had no associated condition that could make
the migraine diagnosis uncertain (e.g. HIV infection, active cancer or use of immunosuppressive
drugs); (5) they were 18 years of age or older; (6) they had complete medical records;
and (7) they agreed to participate in the study. All the subjects underwent a diagnostic
interview with one of the authors (MATU or EJP) who were experienced in management
of headache cases, to make decisions on inclusion in the study. Participants with
EM and CM were referenced in the same way in all centers, as a precaution to reduce
selection bias resulting from differences in the levels of complexity of cases handled
at these centers. We excluded subjects who: (1) withdrew the consent statement; or
(2) developed a new headache in the interval between the invitation and the study
interview. Interviews were conducted through using a semi-structured questionnaire
and took place between August 2018 and January 2020.
Body mass index (BMI) was calculated using the subjects’ self-reported weight and
height. Cardiovascular risk factors were recorded as binary variables that indicated
the presence of at least one of the following: hypertension, diabetes, dyslipidemia,
cardiovascular or cerebrovascular disease. Regular amounts of cigarette and illicit
drug consumption were recorded as three-level categorical variables: never, past and
current. Presence of alcohol consumption on a weekly basis was recorded as a binary
variable (i.e. present or absent). The adequacy of aerobic physical activity was recorded
in accordance with the World Health Organization recommendations: ≥150 minutes (moderate
intensity) or ≥75 minutes (vigorous intensity) per week. The monthly household income
per resident was calculated to evaluate possible effects from the socioeconomic class.
The monthly income of all working residents was added up and divided by the total
number of residents (either active workers or not).
The number of years with migraine was taken to be the period between the onset of
typical migraine symptoms and the interview date. As mentioned earlier, only individuals
whose migraine had been present for at least six months were included. The pain intensity
was classified as mild (no limitation), moderate or severe (disabling). Pain that
was described as pulsatile and/or pressing was recorded as a four-level variable:
never, occasionally, most times and always. Associated symptoms during migraine attacks
were recorded as binary variables and these included nausea, vomiting, photophobia,
phonophobia and movement and tactile allodynia. Movement allodynia was considered
to exist if the headache was aggravated through routine physical activity. Headache
frequency (days/month) was calculated as the average over the last six months in order
to better consider fluctuations in the frequency of attacks[9 ].
Each subject was asked if the attacks were: (1) predominantly on the right side; (2)
predominantly on the left side; (3) predominantly unilateral, but with possible side
shifts during attacks; or (4) predominantly bilateral. The patients were then asked
to select the locations that represented the most prevalent areas involved in their
usual attacks, through mouse clicks on an electronic form. Two images representing
the anterolateral and posterolateral views of a model head ([Figure 1 ]) were presented to each participant, who could indicate up to three points in each
image. The coordinates of each point were automatically classified according to 20
different head/neck regions: frontal, temporal, parietal, supraorbital, orbital, infraorbital,
nasal, occipital, suboccipital, anterior cervical, sternocleidomastoid, lateral cervical,
posterior cervical, zygomatic, auricular, mastoid, oral, mental, buccal and parotid[10 ]. We classified subjects as having extratrigeminal pain (convergent group) if they
selected a site outside of the trigeminal regions (occipital, suboccipital, sternocleidomastoid
and anterior/lateral/posterior cervical). Otherwise, the participants were included
in the non-convergent group. Areas with mixed innervation (e.g. auricular and temporal
sites) were considered to be trigeminal areas.
Figure 1 (A) Migraineurs with pain restricted to the trigeminal areas (non-convergent pain
group). (B) Migraineurs with pain beyond the trigeminal area (convergent pain group).
Each dark point represents a pain location selected by a patient. This heat map scale
uses a Kernel density estimate that translates the proportion of points in an area
into a color scale. Therefore, the scales are not the same for all images. However,
all color scales vary from green to red, with the latter indicating a higher point
density.
Each subject was asked about the presence of 44 symptoms in a typical migraine attack.
All the symptoms were presented in a random order and were classified into six domains
based, in part, on the neuroanatomic-correlated classification presented by Karsan[11 ]: (1) behavioral/cognitive impairment: hyperactivity, dyscognition, inattention,
fatigue, depression symptoms and irritability; (2) homeostatic changes: constipation,
urinary urgency, hyperphagia, polydipsia, hypertension, hypotension, diarrhea, yawning,
pallor and hyporexia; (3) non-painful migrainous symptoms/altered sensory sensitivity:
nausea, vomiting, photophobia, phonophobia, osmophobia, tactile allodynia and nuchal
rigidity; (4) cortical aura-like symptoms: negative and positive visual symptoms,
negative and positive sensory symptoms and fluent and non-fluent dysphasia; (5) brainstem
aura-like symptoms: dysarthria, vertigo, tinnitus, hypoacusis, diplopia, ataxia and
decreased level of consciousness; and (6) cranial autonomic changes: conjunctival
injection, lacrimation, nasal congestion, rhinorrhea, eyelid edema, facial sweating,
miosis and ptosis. The presence of tactile allodynia was based on the first question
of the Brazilian version of the 12-item Allodynia Symptom Checklist[12 ].
Presence of medication overuse and prodromic nuchal rigidity (within the 72 hours
prior to the headache) was recorded as binary variables. Use of preventive pharmacological
treatment for migraine was classified as never, past or current. The impact of the
headache was assessed using the Migraine Disability Assessment (MIDAS)[13 ]. Symptoms of depression and anxiety were quantified using the Patient Health Questionnaire-9
(PHQ-9) and the 7-item Generalized Anxiety Disorder Questionnaire (GAD-7) scales,
respectively[14 ],[15 ].
All statistical analyses were conducted using R version 4.0.2. The Shapiro-Wilk test
and quantile-quantile plots were used to check for normality. Accordingly, the sample
data were summarized as mean±standard deviation, median (interquartile range) and
count (percentage proportion). For visual exploration of the distribution of pain
sites, kernel estimation was used to analyze the density of points in the two-dimensional
plane. Missed data were dealt with through imputation via a k-nearest neighbor algorithm.
To analyze differences among the groups, the one-way ANOVA test for numerical variables
(Kruskal-Wallis test when the assumptions of ANOVA were not met) or the chi-square
test for categorical variables (Fisher test when the expected count in any cell was
less than five) was used. For post-hoc analysis, the Tukey honest significant difference
or Dunn test adjusted with the Holm method were used for numerical variables. In the
case of categorical variables, regression modeling adjusted through the Tukey method
was used. A multivariate logistic regression model was fitted with the presence of
convergence as the dependent variable. This model was selected using a backward elimination
algorithm and the corrected Akaike information criterion. To assess the model fit,
we used the following: residual analysis, ratio of residual deviance to residual degrees
of freedom, Hosmer and Lemeshow test, Osius-Rojek test, Stukel test and influence
analysis. All tests were performed at a significance level of 0.05. No sample size
calculation was conducted a priori for this secondary data analysis.
RESULTS
We invited a total of 254 subjects to participate in the study, of whom 212 agreed
to this (83%). After the study interview, we decided to exclude two patients. One
of them experienced a new headache that resembled an episodic paroxysmal hemicrania
and the other patient experienced a new cervicogenic headache. Both of them suffered
from CM. A total of 97 patients (46%) were diagnosed with EM and 113 (54%) with CM.
The former group consisted of 76 cases of migraine without aura (78%) and 21 cases
of migraine with aura (22%). In the CM group, 78 patients (69%) overused medications
to alleviate their condition. The subjects’ mean age was 39.45±12.63 years and 189
(90%) were female.
The general sample characteristics are shown in [Table 1 ]. Convergence was part of the manifestation of 116 cases (55%). To investigate the
variables potentially associated with occurrence of convergent pain, independently
of chronification status, we stratified the sample according to the presence of convergence
and chronification. There were significant differences in monthly household income,
presence of cardiovascular risks and presence of weekly alcohol consumption. For the
first two variables, the difference was only significant when comparing the two groups
characterized by being the least and the most severe groups, i.e. EM in the non-convergent
group and CM in the convergent group (monthly household income: p=0.01 and cardiovascular
risk: p=0.02). However, in the stratum defined by the non-convergent group, the prevalence
of weekly alcohol consumption was higher for EM than for CM (p=0.021).
Table 1
General features stratified according to the presence of convergence and chronification.
Episodic migraine (n=97)
Chronic migraine (n=113)
p-value[* ]
[† ]
Post-hoc p-values[* ]
[‡ ]
Non-convergent (n=48)
Convergent (n=49)
Non-convergent (n=46)
Convergent (n=67)
EMNC vs. EMC
EMNC vs. CMNC
EMNC vs. CMC
EMC vs. CMNC
EMC vs. CMC
CMNC vs. CMC
Sociodemographic variables
Age (years)
37.1±13.6
39.3±11.3
39.6±13.4
41.1±12.0
0.422
Skin color: white
42 (87.5%)
37 (75.5%)
34 (73.9%)
49 (73.1%)
0.275
Gender: female
42 (87.5%)
46 (93.9%)
40 (87.0%)
61 (91.0%)
0.608
Marital status: married
23 (47.9%)
33 (67.3%)
32 (69.6%)
39 (58.2%)
0.118
Income and occupation
Employed
33 (68.8%)
33 (67.3%)
24 (52.2%)
39 (58.2%)
0.288
Monthly household income per resident (Brazilian real)
2500.0 (2165.0)
2000.0 (2633.0)
1583.0 (1942.0)
1600.0 (1500.0)
0.014
0.412
0.121
0.010
0.851
0.468
0.494
Cardiovascular risk factors and lifestyle
BMI (kg/m2 )
24.1 (7.3)
25.7 (5.9)
25.6 (6.7)
26.1 (7.6)
0.172
Cardiovascular risk: present[§ ]
13 (27.1%)
20 (40.8%)
18 (39.1%)
36 (53.7%)
0.039
0.478
0.598
0.020
0.998
0.512
0.418
Current or former smoker
8 (16.7%)
10 (20.4%)
12 (26.1%)
19 (28.4%)
0.463
Weekly alcohol consumption
17 (35.4%)
7 (14.3%)
5 (10.9%)
9 (13.4%)
0.005
0.069
0.021
0.028
0.958
0.999
0.977
Adequate physical activity[¶ ]
11 (22.9%)
9 (18.4%)
10 (21.7%)
9 (13.4%)
0.557
EMNC: episodic migraine with non-convergent pain; EMC: episodic migraine with convergent
pain; CMNC: chronic migraine with non-convergent pain; CMC: chronic migraine with
convergent pain; BMI: body mass index. All data are summarized as mean±standard deviation,
median (interquartile ratio), or count (frequency, %) according to the variable type
and distribution.
* p-values<0.05 are indicated in bold.
† One-way ANOVA (or Kruskal-Wallis) test for numerical variables or chi-square (or Fisher)
test for categorical variables.
‡ Tukey honest significant difference (or Dunn) test for numerical variables or regression
modeling for categorical variables.
§ At least one of the following: hypertension, diabetes, dyslipidemia, cardiovascular
events and neurovascular events.
¶ At least 150 minutes of moderate-intensity or 75 minutes of vigorous-intensity aerobic
physical activity.
The pain location mapping is shown in [Figure 1 ]. The point density was higher in the posterior cervical region for the convergent
group. There was no significant difference for any trigeminal site between the convergent
and non-convergent groups (Fisher test; p>0.05). The posterior cervical site was more
often involved in the chronic than in the episodic migraine group (33 vs. 21%; p=0.034).
Only three subjects had had less than a year of migraine (all were cases of EM beginning
in the last six months). Most participants in the EM group (90.7%) and CM group (79.6%)
reported having a relatively stable attack frequency, with averages of less than 14
and more than 14 headache days in the last six months, respectively. The individuals
in the CM group with a lower frequency of headache had a more fluctuating course (n=19;
10–14 headache days), as did the patients with EM who had only recently evolved with
chronification (n=4; <10 headache days). The subjects with EM who reported having
an average of more than 14 headache days (n=9) were the ones who might evolve to CM
if they were followed up longitudinally. None of these nine cases presented less than
six months of migraine (median 10.3 years; range 3.5–33.5 years). The headache characteristics
are shown in [Table 2 ]. There were significant differences (p<0.001) in migraine severity, headache frequency,
use of preventive drugs and presence of medication overuse. However, most of the differences
were due to the chronification status.
Table 2
Headache features stratified according to the presence of convergence and chronification.
Episodic migraine (n=97)
Chronic migraine (n=113)
p-value[* ]
[† ]
Post-hoc p-values[* ]
[‡ ]
Non-convergent (n=48)
Convergent (n=49)
Non-convergent (n=46)
Convergent (n=67)
EMNC vs. EMC
EMNC vs. CMNC
EMNC vs. CMC
EMC vs. CMNC
EMC vs. CMC
CMNC vs. CMC
MIDAS score
18.0 (33.5)
25.0 (48.0)
52.5 (49.5)
71.0 (83.0)
<0.001
0.266
0.012
<0.001
0.356
0.012
0.218
Migraine duration (years)
8.5 (11.2)
10.0 (19.0)
10.0 (16.4)
13.0 (19.8)
0.080
Pain side: fixed-side
13 (27.1%)
16 (32.7%)
15 (32.6%)
19 (28.4%)
0.154
Pain side: unilateral with side-shifts
20 (41.7%)
11 (22.4%)
8 (17.4%)
24 (35.8%)
Pain side: bilateral
15 (31.3%)
22 (44.9%)
23 (50.0%)
24 (35.8%)
Headache days per month: <10
33 (68.8%)
31 (63.3%)
3 (6.5%)
1 (1.5%)
<0.001
Ref.
Ref.
Ref.
Ref.
Ref.
Ref.
Headache days per month: 10-14
11 (22.9%)
13 (26.5%)
7 (15.2%)
12 (17.9%)
0.633
0.012
0.001
0.025
0.002
0.190
Headache days per month: >14
4 (8.3%)
5 (10.2%)
36 (78.3%)
54 (80.6%)
0.699
<0.001
<0.001
<0.001
<0.001
0.201
Use of preventive drug: never
27 (56.3%)
27 (55.1%)
15 (32.6%)
14 (20.9%)
<0.001
Ref.
Ref.
Ref.
Ref.
Ref.
Ref.
Use of preventive drug: past
9 (18.8%)
8 (16.3%)
8 (17.4%)
17 (25.4%)
0.833
0.420
0.014
0.323
0.009
0.147
Use of preventive drug: current
12 (25.0%)
14 (28.6%)
23 (50.0%)
36 (53.7%)
0.747
0.010
<0.001
0.020
<0.001
0.258
Medication overuse
10 (20.8%)
14 (28.6%)
31 (67.4%)
47 (70.1%)
<0.001
0.812
<0.001
<0.001
0.001
<0.001
0.990
EMNC: episodic migraine with non-convergent pain; EMC: episodic migraine with convergent
pain; CMNC: chronic migraine with non-convergent pain; CMC: chronic migraine with
convergent pain; MIDAS: Migraine Disability Assessment test. All data are summarized
as mean±standard deviation, median (interquartile ratio), or count (frequency, %)
according to the variable type and distribution.
* p-values<0.05 are indicated in bold.
† One-way ANOVA (or Kruskal-Wallis) test for numerical variables or chi-square (or Fisher)
test for categorical variables.
‡ Tukey honest significant difference (or Dunn) test for numerical variables or regression
modeling for categorical variables. Ref.: reference level.
The results regarding PHQ-9 and GAD-7 scores and the distribution of the associated
symptoms during migraine attacks are shown in [Table 3 ]. There were significant differences for all the variables except for the cortical
aura-like symptom group (p=0.094). However, most of these differences were due to
the chronification status. Interestingly, however, patients with convergent pain showed
more migrainous/altered sensitivity symptoms in the EM group (p=0.025) and CM group
(p=0.002). Also, those with convergent pain showed more symptoms typical of brainstem
aura in the EM stratum (p=0.007).
Table 3
PHQ-9 and GAD-7 scores and number of attack symptoms per group stratified according
to the presence of convergence and chronification.
Episodic migraine (n=97)
Chronic migraine (n=113)
p-value[* ]
[† ]
Post-hoc p-values[* ]
[‡ ]
Non-convergent (n=48)
Convergent (n=49)
Non-convergent (n=46)
Convergent (n=67)
EMNC vs. EMC
EMNC vs. MNC
EMNC vs. CMC
EMC vs. CMNC
EMC vs. CMC
CMNC vs. MC
GAD-7 (anxiety)
8.0 (7.3)
7.0 (9.0)
12.0 (8.0)
11.0 (8.5)
0.037
0.762
0.030
0.193
0.266
0.778
0.737
PHQ-9 (depression)
6.0 (7.0)
8.0 (8.0)
9.5 (8.8)
10.0 (7.0)
0.015
0.601
0.020
0.055
0.371
0.478
0.518
Migrainous symptoms and/or altered sensory sensitivity
4.0 (2.0)
5.0 (2.0)
4.0 (2.0)
6.0 (2.0)
<0.001
0.025
0.998
0.003
0.015
0.968
0.002
Behavior/cognitive symptoms
3.0 (2.0)
4.0 (3.0)
4.0 (2.8)
4.0 (2.0)
0.008
0.371
0.123
0.004
0.461
0.331
0.723
Cortical aura-like symptoms
1.0 (2.3)
1.0 (4.0)
1.0 (3.8)
2.0 (3.0)
0.094
Brainstem aura-like symptoms
1.0 (2.0)
2.0 (4.0)
1.0 (2.8)
2.0 (3.0)
0.001
0.007
0.314
0.002
0.444
0.998
0.288
Homeostatic symptoms
1.0 (3.0)
2.0 (3.0)
2.0 (3.0)
2.0 (3.5)
0.014
0.236
0.321
0.006
0.999
0.573
0.487
Cranial autonomic symptoms
1.0 (2.0)
1.0 (2.0)
1.0 (2.0)
2.0 (4.0)
0.038
0.274
0.852
0.044
0.814
0.532
0.292
EMNC: episodic migraine with non-convergent pain; EMC: episodic migraine with convergent
pain; CMNC: chronic migraine with non-convergent pain; CMC: chronic migraine with
convergent pain; GAD-7: 7-item Generalized Anxiety Disorder Questionnaire; PHQ-9:
Patient Health Questionnaire-9. All data are summarized as mean±standard deviation,
median (interquartile ratio), or count (frequency, %) according to the variable type
and distribution.
* p-values<0.05 are indicated in bold.
† One-way ANOVA (or Kruskal-Wallis) test for numerical variables or chi-square (or Fisher)
test for categorical variables.
‡ Tukey honest significant difference (or Dunn) test for numerical variables or regression
modeling for categorical variables.
The model selected was adjusted for the chronification status, PHQ-9 score, BMI, MIDAS
score and migrainous/altered sensitivity and brainstem aura-like symptom groups. There
was a significant difference regarding the presence of one migrainous/altered sensitivity
symptom (OR=1.39; 95%CI 1.14–1.71) and marginal evidence for an increase in MIDAS
score of 10 points (OR=1.06; 95%CI 0.99–1.13). The group characterized by migrainous/altered
sensitivity symptoms was a composite one. Further analysis on each symptom found that
there were statistical associations between convergent pain and vomiting (p=0.045),
tactile allodynia (p<0.001), nuchal rigidity (p<0.001) and movement allodynia (p=0.031).
DISCUSSION
Extratrigeminal pain in migraine, which is an expression of the convergence phenomenon,
was characterized by involvement of the posterior cervical site or neck pain (NP).
Presence of convergence was associated with occurrence of migrainous/altered sensitivity
symptoms, mainly represented by allodynia. There was a trend towards an association
between convergence and migraine severity, although it was not statistically significant
at an alpha level of 0.05. These findings were independent of the chronification status.
However, given that allodynia and increased migraine severity are typically found
in CM, it is not surprising that we found convergence in this group more often.
In migraineurs, this convergence is expressed as an association of pain in the area
supplied by the trigeminal nerve and in the first cervical roots (C1 and C2) during
an attack. Usually, cervical pain or discomfort arises in the C1/C2 dermatome during
the premonitory phase, while trigeminal pain appears hours or days (up to 72 hours)
after the cervical symptoms[16 ].
The intriguing involvement of the neck in migraine pain has long been recognized[17 ]. Compared with our findings, most studies have reported higher neck pain (NP) prevalence
in migraine. A study conducted in a headache clinic showed NP prevalence of 70.5%[18 ]. In a population study, NP prevalence was 76.2% among those with pure migraine,
89.3% among those with coexisting tension-type headache (TTH) and 83.3% among those
with episodic migraine with or without episodic TTH[19 ]. Our recording method and the three-point limitation per image might have been responsible
for this discrepancy.
Interestingly, the abovementioned population study also showed that the frequency
of migraine attacks is correlated with the number of days with NP[19 ]. The largest study dedicated to this topic reported that there was higher frequency
of NP with migraine chronification, along with higher frequency of diffuse occipital
pain[2 ]. In a prospective study on a sample selected in both a headache clinic and the general
community, NP prevalence varied according to headache pain intensity: mild (42.8%),
moderate (61.1%) and severe (72.6%)[20 ]. Recent use of pain drawings has shown marginal evidence for greater pain extent
in the posterior region of the head in the CM group, compared with the EM group[4 ]. Therefore, associations of frequent migraine attacks and/or CM with the presence
of NP have been a recurrent finding in different studies. Those findings corroborate
ours, thus suggesting that patients with CM have higher rates of trigeminocervical
convergence.
In addition to this association with group classification, NP was also associated
with the following: presence of at least one cardiovascular risk factor; longer-term
migraine; more diffuse, frequent and intense attacks; presence of mechanical and tactile
allodynia; presence of medication overuse; and prodromal nuchal rigidity. Presence
of more diffuse pain was the most important NP-associated factor. NP could simply
represent a preferred location in the pain spreading process that is seen in individuals
with higher chronification risk. Data from the Chronic Migraine Epidemiology and Outcomes
Study (CaMEO) were used to investigate associations between the presence of non-cephalic
pain in eight body regions and occurrence of EM-to-CM progression and CM persistence
over three months[21 ]. At the baseline, the CM group showed 1.09-1.29 times more non-cephalic pain locations
than did the EM group. At three months, each additional location exerted some effect
on CM odds independently of other covariates (demographics, depression/anxiety, allodynia,
BMI and baseline acute headache treatment).
Calhoun et al. explored the role of NP in migraineurs through a series of studies,
and they found that: (1) NP was prevalent in migraine; (2) its presence on the day
preceding migraine was associated with treatment resistance; and (3) it was a predictor
of disability, independent of migraine frequency and severity[22 ]. They raised the possibility that NP in migraineurs represents hyperalgesia or allodynia.
This was in line with our findings that the presence of migrainous/altered sensitivity
symptoms is associated with convergence, independently of the chronification status.
Although we did not explore pressure sensitivity, several studies have demonstrated
lower pressure-pain thresholds (PPTs) in migraineurs, compared with controls, including
in the cervical and distant extra-trigeminal areas[23 ]–[25 ]. An anterior-to-posterior PPT gradient[23 ] in the scalp of migraineurs (and healthy controls) was found, mimicking the sites
discussed above as the ones most frequently affected by migraine pain. However, the
method used in that study differed essentially from the one used in the present study
because it focused on objective measurement of static mechanical pain hyperalgesia.
By asking migraineurs to indicate or draw the sites most frequently affected by pain,
we produced an alternative, meaningful and quick way to explore the anatomical features
of the complaint.
To the best of our knowledge, this was the largest study to use an explicit non-verbal
recording method to locate migraine pain. The diagnosis and evaluation by a headache
specialist further supported our findings, as did our use of balanced groups of individuals
with EM and CM. Our study included patients treated in different settings and had
a participation rate of 83%. The general characteristics of our sample were comparable
with those in other studies carried out in headache centers. Therefore, our results
seem to apply to CM and EM patients treated at these headache units.
Nonetheless, some limitations need to be considered, namely: (1) the non-longitudinal
design allowed us to establish associations of some explanatory variables with NP
that were not as causal relationships; (2) we did not stipulate any migraine-free
period before the interview, and memory bias may have interfered with our results;
(3) we did not use any standardized instrument to measure allodynia; (4) as discussed
earlier, the six-point limitation may have caused underestimation of the number of
sites affected by migraine pain; and (5) our results were mainly based on patient
reports and medical records.
Future studies should consider a prospective record of pain location using pain drawings
or registering more points per attack. Also, recording whether the neck and other
subregions respond differently to established migraine treatments would be interesting.
In conclusion, while migraine attacks most commonly involve the frontotemporal regions,
the convergence phenomenon is more common in chronic migraineurs. Some commonly observed
features such as tactile allodynia and greater severity of disease are associated
with this extratrigeminal site of pain.
