ARTHRITIS & RHEUMATISM
Vol. 48, No. 10, October 2003, pp 2916?2922
DOI 10.1002/art.11272
? 2003, American College of Rheumatology
Subgrouping of Fibromyalgia Patients on the Basis of
Pressure-Pain Thresholds and Psychological Factors
Thorsten Giesecke,1 David A. Williams,1 Richard E. Harris,1 Thomas R. Cupps,2
Xiaoming Tian,3 Thomas X. Tian,3 Richard H. Gracely,1 and Daniel J. Clauw1
Objective. Although the American College of
Rheumatology (ACR) criteria for fibromyalgia are used
to identify individuals with both widespread pain and
tenderness, individuals who meet these criteria are not
a homogeneous group. Patients differ in their accompa-
nying clinical symptoms, as well as in the relative
contributions of biologic, psychological, and cognitive
factors to their symptom expression. Therefore, it seems
useful to identify subsets of fibromyalgia patients on the
basis of which of these factors are present. Previous
attempts at identifying subsets have been based solely
on psychological and cognitive features. In this study,
we attempt to identify patient subsets by incorporating
these features as well as the degree of hyperalgesia/
tenderness, which is a key neurobiologic feature of this
illness.
Methods. Ninety-seven individuals meeting the
ACR criteria for fibromyalgia finished the same battery
of self-report and evoked-pain testing. Analyzed vari-
ables were obtained from several domains, consisting of
1) mood (evaluated by the Center for Epidemiologic
Studies Depression Scale [for depression] and the
State-Trait Personality Inventory [for symptoms of
trait-related anxiety]), 2) cognition (by the catastroph-
izing and control of pain subscales of the Coping
Strategies Questionnaire), and 3) hyperalgesia/
tenderness (by dolorimetry and random pressure-pain
applied at suprathreshold values). Cluster analytic pro-
cedures were used to distinguish subgroups of fibromy-
algia patients based on these domains.
Results. Three clusters best fit the data. Multi-
variate analysis of variance (ANOVA) confirmed that
each variable was differentiated by the cluster solution
(Wilks? H9261 [degrees of freedom 6,89] H11549 0.123, P <
0.0001), with univariate ANOVAs also indicating signif-
icant differences (all P < 0.05). One subgroup of
patients (n H11549 50) was characterized by moderate mood
ratings, moderate levels of catastrophizing and per-
ceived control over pain, and low levels of tenderness. A
second subgroup (n H11549 31) displayed significantly ele-
vated values on the mood assessments, the highest
values on the catastrophizing subscale, the lowest values
for perceived control over pain, and high levels of
tenderness. The third group (n H11549 16) had normal mood
ratings, very low levels of catastrophizing, and the
highest level of perceived control over pain, but these
subjects showed extreme tenderness on evoked-pain
testing.
Conclusion. These data help support the clinical
impression that there are distinct subgroups of patients
with fibromyalgia. There appears to be a group of
fibromyalgia patients who exhibit extreme tenderness
but lack any associated psychological/cognitive factors,
an intermediate group who display moderate tenderness
and have normal mood, and a group in whom mood and
cognitive factors may be significantly influencing the
symptom report.
Fibromyalgia (FM) is a complex, contentious
disease entity. It is currently defined by the 1990 Amer-
ican College of Rheumatology (ACR) classification cri-
teria (1), in which an individual is required to have both
a history of chronic widespread pain and the finding of
Supported by Department of Army grant DAMD 17-00-2-
0018, NIH grant 5-R01-AT 000004-02, and grant 5-M01-RR13297
from the General Clinical Research Center Program of the National
Center for Research Resources, NIH.
1Thorsten Giesecke, MD, David A. Williams, PhD, Richard
E. Harris, PhD, Richard H. Gracely, PhD, Daniel J. Clauw, MD:
University of Michigan, Ann Arbor; 2Thomas R. Cupps, MD: George-
town University, Washington, DC; 3Xiaoming Tian, MD, Thomas X.
Tian, MD: Academy of Acupuncture and Chinese Medicine, Bethesda,
Maryland.
Address correspondence and reprint requests to Daniel J.
Clauw, MD, University of Michigan Health System, Department of
Internal Medicine, Division of Rheumatology, 300 NIB NI7B10, Ann
Arbor, MI 48109-0483. E-mail: dclauw@med.umich.edu.
Submitted for publication February 12, 2003; accepted in
revised form June 6, 2003.
2916
11 of 18 possible tender points on examination. Tender
points are located in 9 paired regions of the body, and if
an individual reports pain when one of these regions is
palpated with 4 kilograms of pressure, this is considered
a positive tender point. Using the ACR criteria, the
prevalence of FM in industrialized countries ranges
from 0.5% to 4% (2).
There is, however, tremendous variability within
individuals whose disease manifestations match the
ACR criteria. Some individuals with FM experience only
pain, while others experience a variety of additional
symptoms. Moreover, there is substantial overlap be-
tween FM and other systemic entities (e.g., chronic
fatigue syndrome) and regional syndromes (e.g., irritable
bowel syndrome or temporomandibular disorders) (3).
Factor analytic techniques have been used in
population-based studies to identify the seminal features
of these conditions; in such studies, the key symptoms
that coaggregate are multifocal pain, fatigue, memory
difficulties, and mood disturbances (4). The term
chronic multisymptom illness has been coined by inves-
tigators from the United States Centers for Disease
Control and Prevention to describe this symptom com-
plex (5).
Given this heterogeneity of symptoms, it has
become increasingly clear that FM is not a discrete
entity, but rather one of many overlapping syndromes
and symptoms. Because of this, many investigators in the
field have suggested that there is a need for empirically
derived subgroups, ideally using constructs that would
help tailor more specific therapies to each patient (6?8).
Several studies have used sophisticated, multivariate
cluster analytic techniques to identify replicable, homo-
geneous subgroups of patients with chronic pain within
heterogeneous chronic pain populations. Bradley et al
(9) applied these methods to the analysis of personality
profiles in patients with chronic low back pain. Cluster
analytic methods revealed that there were distinct sub-
groups of patients with chronic pain, distinguished on
the basis of their Minnesota Multiphasic Personality
Inventory profiles. Keefe et al (10) used similar methods
to identify subgroups of patients with low back pain who
differed in terms of their overt pain behavior. Distinct
subgroups of patients divided on the basis of pain beliefs
as well as subgroups distinguished on the basis of
patients? responses to the Symptom Checklist 90 revised
have also been identified using cluster analytic methods
(11,12).
Turk et al (8) were the first investigators to show
that subgroups identified by cluster analysis, based upon
the Multidimensional Pain Inventory in various chronic
pain populations, could also be applicable to a popula-
tion of FM patients, and that each of these FM sub-
groups responds differently to treatment (13). In this
subgrouping performed by Turk et al among patients
with FM, psychosocial and cognitive characteristics of
the patients were used to distinguish the groups. In
addition to psychosocial and cognitive factors, however,
increasing evidence suggests a strong neurobiologic fac-
tor. Much of this work has been focused on determining
the mechanisms that might be operative in the hyperal-
gesia (increased sensitivity to painful stimuli) and allo-
dynia (sensitivity to normally nonpainful stimuli) seen in
this condition. Thus, it would be useful if a measure of
hyperalgesia could be incorporated into patient sub-
groupings.
One reason that hyperalgesia has not been used
in the past is that the measure of tenderness most often
used to assess FM, the tender point count, has many
features that confound its use in these types of models.
One problem with the tender point count is statistical;
within a group of FM patients, the most frequent results
will be 17 or 18 tender points. This abnormal distribution
and narrow range make it difficult to differentiate
patients using this measure. Another problem with the
use of tender points is that it is highly correlated with
measures of psychological distress (14,15). This is prob-
lematic in examining the independent contributions that
pressure-pain sensitivity and distress may make to ten-
derness in subgroups of patients. Recent work has made
it clear that other measures of pressure-pain sensitivity,
especially those in which stimuli are presented in a
random manner such that individuals cannot anticipate
the next stimulus, have a much wider range, have a
normal distribution, and are not correlated with mea-
sures of distress (15).
Thus, in the present study, we identified a group
of patients with FM on the basis of the ACR classifica-
tion criteria, and we examined the manner in which
neurobiologic, psychological, and cognitive features
could be clustered to form subgroups of FM patients.
PATIENTS AND METHODS
Patients. One hundred seventeen patients (102 female
and 15 male, ages 18?60 years) who met the 1990 ACR criteria
for the classification of FM (1) were recruited. Seven of these
patients (6 female, 1 male) were referrals to a tertiary rheu-
matology outpatient clinic, and 110 were recruited by newspa-
per advertisements. The patients were studied at the General
Clinical Research Center of Georgetown University Medical
Center. All patients underwent a comprehensive screening
during which the diagnosis was confirmed and comorbidities
SUBGROUPING FM PATIENTS BY NEUROBIOLOGIC AND PSYCHOSOCIAL FACTORS 2917
were evaluated. Exclusion criteria were severe physical impair-
ment (e.g., bilateral amputation, complete blindness, or deaf-
ness), medical conditions that were capable of causing patients?
symptoms (e.g., morbid obesity, autoimmune/inflammatory
diseases), cardiopulmonary disorders (i.e., angina, congestive
heart failure, chronic obstructive pulmonary disease, or
chronic asthma), uncontrolled endocrine or allergic disorders
(i.e., hyper-/hypothyroidism, diabetes, or allergic rhinitis), ma-
lignancy, severe psychiatric illnesses (e.g., current schizophre-
nia, substance abuse within 2 years), factors known to affect
the hypothalamic?pituitary?adrenal axis or autonomic func-
tion (e.g., cigarette smoking, daily intake of caffeine exceeding
the equivalent of 2 cups of coffee), and usage of medications
other than as-needed analgesics (excluding long-term use of
narcotics) and appropriate dosages of thyroid hormone.
When subjects were considered qualified for inclusion
in the study, they were given an appointment to begin partic-
ipation in a 2-day study protocol. They were asked to discon-
tinue intake of antidepressants within 1 week prior to the
appointment, but were allowed to take nonsteroidal antiin-
flammatory drugs until 3 days before the appointment. On the
first day of the study, patients completed the self-report
questionnaires and were familiarized with the pain testing. On
the following day, pain testing was performed.
Self-report measures. Visual analog scale (VAS). Clin-
ical pain was reported on a 0?100 VAS, with 0 being ?no pain?
and 100 being ?the worst pain imaginable.?
Center for Epidemiologic Studies Depression Scale
(CES-D). The CES-D (16) is a 20-item self-report question-
naire that assesses symptoms of depression in nonpsychiatric
adults. This instrument possesses strong psychometric proper-
ties and has demonstrated strong associations with other
measures of depressive symptoms (17). Cut-off scores have
been established to specify that scores in excess of 16 points are
indicative of ?probable depression.?
State-Trait Personality Inventory (STPI). Symptoms of
trait anxiety were assessed using the STPI (Form Y) (18). The
STPI is an 80-item self-report questionnaire with eight 10-item
scales for measuring state-related and trait-related anxiety,
anger, depression, and curiosity. For purposes of this study, the
10-item scale measuring trait anxiety was used. The STPI
possesses strong psychometric properties for the assessment of
these mood symptoms, since the items have been well validated
as part of larger instruments such as the State-Trait Anxiety
Inventory and the State-Trait Anger Inventory (19). Although
cut-off values that relate to clinical diagnostic categories have
not been established, a score above 22 points on the trait
anxiety scale corresponds to the 75th percentile of the score
among normal adults.
Coping Strategies Questionnaire (CSQ). The CSQ was
developed by Rosenstiel and Keefe as a measure of the
strategies utilized by patients to cope with chronic pain, and as
a measure of the perceived efficacy of those strategies when
used to control and decrease pain (20). The CSQ assesses the
use of 6 cognitive coping strategies (diverting attention, rein-
terpreting pain sensations, coping self-statements, ignoring
pain sensations, praying or hoping, and catastrophizing) and 1
behavioral coping strategy (increasing behavioral activity).
Each strategy subscale is composed of 6 items, and subjects are
asked to rate the frequency with which they use each strategy
on a 7-point scale (0 H11005never, 3 H11005sometimes, 6 H11005always). Two
single-item scales were used to assess the patients? belief in the
effectiveness of the coping strategies used to control or de-
crease their pain; each rating of efficacy is made on a 7-point
scale, with 0 indicating no efficacy and 7 indicating complete
efficacy. For the purposes of this study, we used the ?cata-
strophizing? and ?control over pain? subscales.
Medical Outcomes Study 36-item Short Form (SF-36)
health survey. The SF-36 is a self-report inventory that assesses
health across 6 functional domains and has been widely used in
outcome evaluation studies (21). In an analysis of the utility of
this instrument compared with other scales, this tool has been
shown to perform well as a measure of health status (22). For
the purposes of this study, the SF-36 physical component
summary score was used as a measure of clinical status. Raw
scores were transformed to a 0?100-point scale, with higher
scores being indicative of better functioning.
Experimental pain assessments. During the pain test-
ing session, a manual tender point count was performed,
followed by a dolorimeter examination in 3 paired points of the
body (epicondyle, mid-trapezius, and thumbnail), using a
continuous ascending paradigm. Pressure was increased at a
rate of 1 kg/second, and subjects indicated when the stimulus
first became painful (pain threshold). The final pain threshold
value was the statistical mean of the values of all 6 points. We
recently showed that this model predicts overall tenderness
with excellent accuracy (23).
Pressure-pain sensitivity was evaluated by subjective
scaling of multiple pressure-pain sensations of suprathreshold
intensities. Discrete 5-second pressure stimuli were applied to
the fixated left thumbnail with a 1-cm2 hard rubber probe.
Previous studies have shown that ?neutral? regions such as the
thumb accurately reflect an individual?s overall pressure-pain
sensitivity (15). The rubber probe was attached to a hydraulic
piston, a combination of valves (to control stimulus duration),
and a scale. Calibrated weights put on the scale produced
controlled, repeatable pressure-pain stimuli of rectangular
waveform at the thumbnail. Subjects rated the intensity of
pressure-pain sensations using a combined numeric analog
descriptor scale, which was developed from previously quanti-
fied verbal descriptors (24). First, a series of stimuli was
presented in a predictable, ?ascending? manner, beginning at
0.5 kg/cm2 and increasing in 0.5-kg/cm2 intervals up to toler-
ance or to a maximum of 10 kg/cm2. Following the ascending
series, 36 stimuli were delivered at 20-second intervals in
random order, using the multiple random-staircase (MRS)
pressure-pain sensitivity method (25). The MRS method is
response dependent, i.e., it determines the stimulus intensity
needed to elicit a specified response. For this analysis, we used
the stimulus intensities needed to elicit slightly intense pain
(13.5/20 pain scale units).
Statistical analysis. Patient subgroups were formed
using agglomerative hierarchic cluster analysis, with squared
Euclidean distances incorporated in the proximities matrix.
Ward?s method was used to form clusters at each stage so that
the squared within-group deviations around the mean value for
each cluster were minimized. This cluster analytic method has
been shown to produce the best recovery of structure for
clusters of all sizes (26). Following the formation of clusters,
multiple analyses of variance (ANOVAs) were used to confirm
that each variable used in the analysis was differentiated by the
2918 GIESECKE ET AL
cluster solution. All analyses were performed using SPSS for
Windows, version 10 (SPSS, Chicago, IL).
RESULTS
Characteristics of patients. All screened patients
finished the study protocol; however, complete data
were available on only 97 of the 117 patients. Because
missing data distort the results of clustering procedures,
we excluded 17 women and 3 men from further analysis.
Thus, 85 women (87.6%) and 12 men (12.4%) were
studied in the cluster analysis. The subjects were fairly
representative of the US population, with 78 whites
(80%), 11 African Americans (11%), 3 Asians (3%), 2
Hispanics (2%), and 3 subjects of other ethnicity (3%).
The characteristics of the study sample are shown in
Table 1.
Clustering and subgrouping. Three clusters best
fit the data. The symptom profiles of the 3 clusters are
displayed in Figure 1, and corresponding values for the
neurobiologic (tenderness on evoked-pain testing), psy-
chosocial, and cognitive variables are displayed in
Table 2. Multivariate ANOVAs confirmed that each
variable was differentiated by the cluster solution
(Wilks? H9261 [degrees of freedom 6,89] H11005 0.123, P H11021
0.0001). Furthermore, univariate ANOVAs confirmed
that each variable in the analysis significantly differenti-
ated the clusters (all P H11021 0.05).
As shown in Figure 2, cluster 1 contained the
highest number of patients (n H11005 50), with 41 women
(82%) and 9 men (18%). This cluster consisted of 39
whites (78%), 7 African Americans (14%), 1 Asian
Figure 1. Symptom profiles of patient subgroups, as detected by
cluster analysis. Cluster 1 (n H11005 50; long broken line) displayed
moderate levels of anxiety, depression, and catastrophizing, moderate
control over pain, as well as moderate to low tenderness. Cluster 2
(n H11005 31; solid line) was characterized by high levels of anxiety,
depression, and catastrophizing, the lowest control over pain, and
considerable tenderness. Cluster 3 (n H11005 16; short broken line) dis-
played the lowest levels of anxiety, depression, and catastrophizing and
the highest control over pain, but also the lowest pain thresholds.
Values for anxiety, depression, and catastrophizing have been rescaled
(divided by 5) to facilitate meaningful simultaneous display. MRS H11005
multiple random-staircase pressure-pain sensitivity determination.
Table 1. Patient characteristics and variables used for clustering of
the whole study population (n H11005 97; 85 female, 12 male)*
Variable
Maximum
possible range Mean SD
Age, years 18?60 44.94 10.37
No. of tender points 11?18 14? ?
Biologic pressure-pain?
MRS, kg 0?10 5.12 2.29
Dolorimeter, kg 0?10 4.81 2.16
Psychosocial/cognitive
CES-D 0?60 17.23 9.39
STPI?trait anxiety 20?80 22.43 8.19
Catastrophizing on CSQ 0?36 10.81 7.30
Control over pain on CSQ 0?6 3.08 1.29
SF-36 physical functioning 0?100 36.55 9.28
* MRS H11005 multiple random-staircase pressure-pain sensitivity determi-
nation; CES-D H11005 Center for Epidemiologic Studies Depression ques-
tionnaire (scores H1102216 indicate probable depression); STPI H11005 Stait-
Trait Personality Inventory (scores H1102222 on trait anxiety correspond to
the 75th percentile for normal adults); CSQ H11005 Coping Strategies
Questionnaire (high catastrophizing scores indicate that catastrophiz-
ing is an important element of an individual?s means of coping, while
higher control over pain scores indicates that the individual is more
able to use coping strategies to control pain); SF-36 H11005 Short Form 36
(higher scores indicate better functioning).
? Tender point counts are not normally distributed, and therefore the
median is displayed, without SD (geometric mean).
? Lower pain threshold values on MRS and dolorimetry are equivalent
to higher tenderness.
Table 2. Cluster characteristics*
Variable Cluster 1 Cluster 2 Cluster 3
Age, years 46.1 H11006 10.0 42.8 H11006 11.3 45.5 H11006 9.6
MRS, kg 6.63 H11006 1.7 3.22 H110061.4 2.24 H11006 1.3
Dolorimeter, kg 4.81 H11006 2.2 3.21 H11006 1.7 2.73 H11006 1.3
CES-D score 14.16 H11006 7.5 25.74 H11006 7.3 9.63 H11006 4.6
STPI?trait anxiety
score
19.36 H11006 4.9 29.13 H11006 8.5 17.06 H11006 6.3
Catastrophizing score 8.76 H11006 6.1 17.52 H11006 6.0 4.86 H11006 3.0
Control over pain
score
3.16 H11006 1.3 2.71 H11006 1.2 3.69 H11006 1.1
SF-36 physical
functioning score
37.44 H11006 9.2 35.74 H11006 7.7 34.56 H11006 10.2
* Values are the mean H11006 SD. Multivariate analysis of variance
confirmed that each variable was differentiated by the cluster solution
(Wilks? H9261 [degrees of freedom 6,89] H11005 0.123, P H11021 0.0001), and
univariate analysis of variance confirmed that each variable signifi-
cantly differentiated the clusters (all P H11021 0.05). See Table 1 for
definitions.
SUBGROUPING FM PATIENTS BY NEUROBIOLOGIC AND PSYCHOSOCIAL FACTORS 2919
(2%), 1 Hispanic (2%), and 2 of other ethnicity (4%).
These patients were characterized by moderate anxiety
on the STPI trait anxiety questionnaire (mean H11006 SD
score 19.4 H11006 4.9), moderate levels of depression on the
CES-D (mean H11006 SD score 14.2 H11006 7.5), moderate levels
of catastrophizing and control over pain on the CSQ
(mean H11006 SD scores 8.8 H11006 6.1 and 3.2 H11006 1.3, respective-
ly), as well as the highest pain threshold by dolorimetry
(4.8 H11006 2.2 kg) and the lowest suprathreshold pain-
sensitivity level by the MRS method (6.6 H11006 1.7 kg), i.e.,
a low level of tenderness. This mean value for pain
threshold is plausible because a positive tender point
count is not equivalent to a pressure-pain threshold of 4
kg.
Cluster 2 comprised 31 patients, of which 28 were
female (90.3%) and 3 were male (9.7%). This cluster
consisted of 24 whites (77%), 4 African Americans
(13%), 2 Asians (6%), and 1 Hispanic (3%). These
patients were characterized by the highest levels of
anxiety and depressive symptoms (mean H11006 SD scores
29.1 H11006 8.5 and 25.7 H11006 7.3, respectively) and the highest
level of catastrophizing (mean H11006 SD score 17.5 H11006 6.0)
combined with the lowest levels of control over pain
(mean H11006 SD score 2.7 H11006 1.2). They also displayed
considerable tenderness, with a mean H11006 SD pain thresh-
old of 3.2 H11006 1.7 kg and a suprathreshold pain-sensitivity
level of 3.2 H11006 1.4 kg.
Cluster 3 was the smallest cluster (n H11005 16) and
consisted solely of women. Fifteen women were white
(94%) and 1 was of other ethnicity (6%). These patients
were characterized by the lowest levels of anxiety
(mean H11006 SD score 17.1 H11006 6.3), depressive symptoms
(mean H11006 SD score 9.6 H11006 4.6), and catastrophizing
(mean H11006 SD score 4.9 H11006 3.0) and had the highest level
of control over pain (mean H11006 SD score 3.7 H11006 1.1).
Nevertheless, they had, by far, the lowest pain threshold
and the highest suprathreshold pain-sensitivity level
(mean H11006SD 2.7 H110061.3 kg and 2.2 H110061.3 kg, respectively),
i.e., the highest level of tenderness.
Tender points, pain, and physical functioning
among subgroups. The mean H11006 SD tender point counts
in clusters 1, 2, and 3 were 13 H11006 3, 13 H11006 4, and 16 H11006 3,
respectively. Self-reported mean H11006 SD pain scores on a
regular 0?100 VAS in clusters 1, 2, and 3 were 52 H11006 26,
53 H11006 27, and 62 H11006 20, respectively. Values for perceived
physical functioning, as determined by the SF-36 for
clusters 1, 2, and 3, are displayed in Table 2. There were
no significant differences between the clusters with
regard to the number of tender points, extent of self-
reported pain, and perceived level of physical functioning.
To facilitate the task of assigning individual pa-
tients to our clusters, we performed a discriminative
analysis (results shown in Table 3). A constant and a set
of 6 coefficients for the 6 variables are given for each
cluster. After multiplying the coefficient and the actual
value of each variable, the sum of the constant and these
6 products is calculated. Application of the 3 formulas
provides 3 values for every patient. The highest value
determines the cluster to which the patient is assigned.
DISCUSSION
Our study showed that within a group composed
entirely of individuals with FM, there are subgroups of
patients who can be identified on the basis of their
patterns of pressure-pain sensitivity, mood, and cogni-
tion. Over half of the patients in our sample were in
cluster 1, in which patients had moderately increased
pressure-pain sensitivity and mood ratings and average
cognitive factors. This might represent the ?typical? FM
patient, especially those seen in a primary care setting.
The next largest group had highly elevated pressure-pain
sensitivity and had significantly high values in terms of
Figure 2. Subgroups of fibromyalgia patients, based on a psychosocial
domain (depression/anxiety), a cognitive domain (catastrophizing/
control over pain), and a neurobiologic domain (tenderness).
Table 3. Discriminative analysis of cluster characteristics*
Variable Cluster 1 Cluster 2 Cluster 3
Constant H1100218.19352 H1100222.53864 H1100210.12578
MRS 2.17562 0.06690 0.26735
Dolorimeter 1.16519 0.64933 0.47685
CES-D 0.07713 0.30474 0.07287
STPI?trait anxiety 0.36064 0.59625 0.37779
Catastrophizing 0.24672 0.61229 0.27448
Control over pain 1.93189 2.52485 2.67505
* Values are the coefficients for discriminant functions for each cluster
(relative to the constants) (see text for details on assignment of
patients to clusters). Values in boldface indicate that the variable loads
highest for that particular cluster. See Table 1 for definitions.
2920 GIESECKE ET AL
the presence of mood and cognitive factors. This might
characterize the presentation of FM common in tertiary
care settings. The smallest group, cluster 3, had ex-
tremely elevated pressure-pain sensitivity, but had no
identifiable psychological or cognitive factors that ap-
peared to be contributing to increased symptom report-
ing. This group may characterize the neurobiologic
presentation of FM when it is unconfounded by common
psychological factors. In summary, these results add to
existing data and further the clinical impression that FM
is a heterogeneous disorder.
With regard to the measures of tender points
(tender point counts), physical functioning (SF-36), and
self-reported pain, a comparison of these 3 measures
among the 3 clusters showed that none was associated
with subgroup membership. Studies comparing the ten-
der point count with other measures of tenderness have
found that the tender point count is significantly influ-
enced by various measures of psychological distress
(2,14,15). Petzke et al also found a relationship between
the tender point count and self-reported pain (15). In
contrast, in accordance with other results from this
study, tender point counts in our 3 subgroups were not
significantly associated with the other, ?purer? measures
of pressure-pain sensitivity. The tender point count may
serve as a tool to attain an overall evaluation of physi-
ologic and psychological dysfunction, but as a compound
measure of many factors, it does not reflect differences
in distress or pressure-pain sensitivity or provide help in
subgrouping FM patients.
The similarity of self-reported pain among the 3
subgroups demonstrates once more that the relationship
between pain and depression is still very unclear. Al-
though the severity of pain has been shown to be
associated with the severity of depression in FM patients
(27), the cross-sectional relationship of pain and depres-
sion may become nonsignificant once other disease-
related variables are controlled (28).
This study also sheds new light on the relation-
ship between pressure-pain sensitivity and distress. Dis-
tress is typically operationalized as some combination of
somatic symptoms and symptoms of anxiety/depression.
Until recently it had been assumed that because tender
point counts measure pressure-pain sensitivity, and be-
cause the presence of tender points is associated with
distress, an individual?s sensitivity to mechanical pres-
sure was associated with distress (29,30). However, as
already pointed out, in a study of evoked-pain measures
by Petzke et al (15), this is not necessarily the case.
Tender points are a flawed measure of ?pure? pressure-
pain sensitivity, because, in large part, they are influ-
enced considerably by distress. More sophisticated
measures of pressure-pain sensitivity appear to be inde-
pendent of psychological status. Dolorimetry results are
only mildly influenced by distress, thus being a purer
measure than is the tender point count, but even dolo-
rimetry is not as independent of distress as are the more
sophisticated measures (14,15). As a result, in this study,
we see 2 groups of patients with high levels of pressure-
pain sensitivity, of which one displayed high levels of
distress (cluster 2) and the other displayed very low
levels of distress (cluster 3).
The implications of these results with regard to
treatment of FM are not yet clear. It might be expected
that cluster 1, in which patients had moderate mood
difficulties and already had very adaptive cognitive
factors, might be less likely to need or respond to
cognitive behavioral approaches, whereas cluster 2, in
which patients had extremely high levels of distress,
might benefit most from this type of program. Pharma-
cologic therapy using antidepressant drugs, selective
serotonin reuptake inhibitors, and other psychotropic
medications might also be expected to be more effective
in cluster 2, since mood appeared to play a greater role
in driving symptom expression. However, cluster 3 may
possibly respond best to symptom-based pharmacologic
therapy, including antidepressant agents with analgesic
properties. Further studies need to replicate these find-
ings, and additional testing should be done to determine
whether these FM subgroupings can, in fact, be used to
identify optimal treatment strategies.
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