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1. A META-ANALYSIS OF FIBROMYALGIA TREATMENT INTERVENTIONS 1,2
Lynn A. Rossy, M.A. and Susan P. Buckelew, Ph.D.
University of Missouri-Columbia
Nancy Dorr, Ph.D.
Jamestown College
Kristofer J. Hagglund, Ph.D., Julian F. Thayer, Ph.D., Matthew J. McIntosh, M.A.,
John E. Hewett, Ph.D., and Jane C. Johnson, M.A.
University of Missouri-Columbia
ABSTRACT
Objective: Toevaluate and compare the efficacy ofpharmaco-
logical and nonpharmacological treatments of fibromyalgia syn-
drome (FMS). Methods: This meta-analysis of 49 fibromyalgia
treatment outcome studies assessed the efficacy of pharmacologi-
cal and nonpharmacological treatment across four types of
outcome measures--physical status, self-report of FMS symptoms,
psychological status, and dailyfunctioning. Results: After control-
ling for study design, antidepressants resulted in improvements on
physical status and self-report of FMS symptoms. All nonpharma-
cological treatments were associated with significant improve-
ments in all four categories of outcome measures with the
exception that physically-based treatment (primarily exercise) did
not significantly improve daily functioning. When compared,
nonpharmacological treatment appears to be more efficacious in
improving self-report of FMS symptoms than pharmacological
treatment alone. A similar trend was suggested for functional
measures. Conclusion: The optimal intervention for FMS would
include nonpharmacological treatments, specifically exercise and
cognitive-behavioral therapy, in addition to appropriate medica-
tion management as neededfor sleep and pain symptoms.
(Ann Behav Med 1999, 21(2):180-191)
INTRODUCTION
Fibromyalgia syndrome (FMS) is one of the most common
disorders seen by rheumatologists and perhaps the most enigmatic.
The prevalence of FMS is estimated to be 2% (3.4% for women
and .5% for men) (1). The etiology of FMS is still not understood,
but symptoms include sleep disturbance, fatigue, pain (especially
at tender points), impairment in daily functioning, and often
affective distress. Therefore, treatment studies have focused on the
efficacy of pharmacologic and nonpharmacologic interventions to
relieve the multiple physical and psychological symptoms of FMS.
Over the last 10 years, there has been a marked increase in
published research of fibromyalgia. While some reviews of the
a Preparation of this manuscript was supported in part by grants from the
NationalInstitute of Health (DHHS 1T32 HD 07460-02) and the National
Institute on Disability and Rehabilitation Research (H133B30039-96).
2 The authors would like to acknowledge the assistance ofChristy Mueller
in coding studies for this analysis.
Reprint Address: L. A. Rossy, M.A., Department of Psychology, 210
McAlester Hall, University of Missouri, Columbia, MO 65211.
91999by The Society of Behavioral Medicine.
FMS literature have been conducted, with one exception (2), these
reviews have been qualitative in nature. The one published
quantitative review (2) examined the results of 24 controlled
clinical trials of FMS treatments, evaluating methodological issues
including type of outcome measures, the ability of each outcome
measure to distinguish between individuals in treatment and
placebo groups, and study design. Results indicated that a diversity
of outcome constructs and measurement instruments have been
used and no two trials have used the same outcome measures. As
many as nine different instruments have been used for a single
outcome measure. Also, clinically important outcomes such as
psychological and functional status were infrequently included in
data collection. Moreover, the authors concluded that limitations in
study design, such as incomplete blinding of outcome evaluators,
inadequate randomization, flaws in participant selection and group
allocation, and inappropriate analysis of data render valid interpre-
tation of findings untenable. This review thoroughly addressed the
methodological aspects of research in FMS, but did not examine
treatment efficacy.
The objective of the current meta-analysis was to provide a
quantitative review of the efficacy of pharmacological and nonphar-
macological FMS treatment across four outcome domains com-
monly used in clinical practice including physical status, self-
report of FMS symptoms, psychological status, and daily
functioning. This study answered five main questions: (a) With
regard to pharmacological treatment of FMS, do antidepressants,
muscle relaxants, nonsteroidal anti-inflammatory drugs (NSAIDs),
or other medications result in improvement in the four outcome
domains? (b) If so, which of these pharmacological treatments
have the greatest effect? (c) With regard to nonpharmacological
treatment of FMS, does physically-based treatment, psychologi-
cally-based treatment, or a combination of physically-based and
psychologically-based treatments produce symptom reduction? (d)
Which of these nonpharmacological treatments has the greatest
effect? and (e) Does pharmacological or nonpharmacological
treatment demonstrate the most improvement?
METHOD
Literature Search
Computerized and manual methods were used to identify
studies to be included in the meta-analysis. The computer search
was conducted using MEDLINE (1966-November 1996),
PsycINFO (1967-October 1996), CINAHL The Nursing and
Allied Health database (1982-September 1996), and Dissertation
Abstracts (1861-September 1996). Reference sections were manu-
ally searched in all of the identified treatment outcome study
180

2. Fibromyalgia Treatment VOLUME 21, NUMBER 2, 1999 181
articles and in major review papers (3-13). A manual search was
conducted of 1995 and 1996 issues of four journals from which the
greatest number of treatment outcome studies had been identified
(i.e. Arthritis and Rheumatism, Clinical Rheumatology, Journal of
Rheumatology, and Scandinavian Journal of Rheumatology). Ab-
stracts from Supplements to the Journal of Musculoskeletal Pain,
Scandinavian Journal ofRheumatology, andArthritis andRheuma-
tism were manually searched over the past 4 years. Solicitation
letters were sent to primary authors requesting copies of other
outcome studies that they had conducted, published or unpub-
lished. Solicitation letters were also sent to the primary authors of
studies or abstracts to request additional data when effect sizes
could not be calculated from published results. Only studies or
abstracts written in English were retained for review.
Inclusion and Exclusion Criteria
Studies were included in the meta-analysis if: (a) at least one
treatment group was exclusively comprised of adult participants
with fibromyalgia; (b) major outcome variables included physical
status, self-report of FMS symptoms, psychological status, and/or
daily functioning; and (c) they contained sufficient statistical
information to calculate effect sizes on outcome variables.
Thirty-three of the 48 identified pharmacological treatment
studies and abstracts and 16 of the 38 identified nonpharmacologi-
cal treatment studies and abstracts met the inclusion criteria and
were included in the meta-analysis. The main reason studies or
abstracts were excluded from the meta-analysis was insufficient
data available to calculate effect sizes (i.e. no statistics or
insufficient statistics were reported) (14-21,11,22-36). Studies
included in the final sample are listed in the Appendix.
Coding
Sample size, multiple effect size information, methodology,
control and treatment group characteristics, treatment characteris-
tics, and outcome measures with statistics necessary to calculate
effect sizes were coded by one of two independent raters. Each fifth
study was coded by both independent raters. A 98% mean rate of
agreement was attained for studies coded by both raters with a
range from 98% to 100% agreement. Discrepancies in coding were
resolved by discussing the criteria and refining them if necessary.
Treatment-Related Variables:Pharmacological treatments were
categorized as antidepressants, muscle relaxants, NSAIDs, and
other. The "other" category included all pharmacological treat-
ments not included in the antidepressants, muscle relaxants, and
NSAIDs categories, as well as treatments that combined two or
more categories. Nonpharmacological treatments were categorized
as physically-based treatment (e.g. aerobic exercise, muscle
strengthening, and stretching), psychologically-based treatment
(e.g. biofeedback, relaxation, and cognitive-behavioral), and com-
bination treatment (i.e. treatment which included a combination of
physically-based and psychologically-based interventions).
Outcome-Related Variables: Four different categories of out-
come variables included physical status, self-report of FMS
symptoms, psychological status, and daily functioning. Examples
of physical status measures included tender point index, myalgic
score, grip strength, and physician global rating of pain symptoms.
Examples of self-report of FMS symptoms included participants'
report of symptoms such as fatigue, pain, and morning stiffness as
measured by questionnaires such as the McGill Pain Questionnaire
and visual analog scales. Examples of psychological status in-
cluded self-report of depression and anxiety as measured by ques-
tionnaires such as the Arthritis Impact Measurement Scales (AIMS)
of Depression and Anxiety, the Hamilton Depression and Anxiety
Scales, and the Symptom Cbecklist-90-Revised. Examples of daily
functioning included self-report of physical activity and daily
activities as measured by questionnaires such as the Sickness
Impact Profile and the Fibromyalgia Impact Questionnaire.
Methodology-Related Variables: Including methodology-
related variables in the meta-analysis is critical for controlling
potential effect size inflation due to different types of designs,
particularly those associated with uncontrolled research. There-
fore, the major methodology-related variable in this analysis was
the type of control group used in each study. For pharmacological
treatment studies, all studies used either a placebo control group or
a no control group design. For nonpharmacological treatment
studies, three types of control group designs were used--no
control group, placebo/attention control group, and walt list
control group. The two other methodology-related variables that
were included in the analysis were whether participants were
requested to washout or abstain from drug treatment (i.e. antidepres-
sant, tranquilizing, and/or hypnotic drugs) during the study and
whether the 1990 American College of Rheumatology (ACR)
criteria (37) or an earlier type of criteria was used to classify
participants with fibromyalgia.
Calculation of Effect Sizes
We initially used g as the effect size index. The g is calculated
by subtracting the control group mean from the treatment group
mean and dividing by the pooled standard deviation. Therefore, the
results from all studies are expressed in a common metric. For
example, a g of +.50 indicates that outcomes from individuals in
the treatment condition were one-half of a standard deviation better
than outcomes for individuals in the control condition. Alterna-
tively, a negative g indicates that outcomes for individuals in the
control condition were better than outcomes for individuals in the
treatment condition. Because g can overestimate the population
effect size, especially for studies with small samples, each g was
converted into an adjusted Cohen's d which corrects for this bias
(38,39). All effect sizes were calculated by the recta-analytic
program DSTAT (40).
Means and standard deviations were used to calculate d-in-
dexes when they were provided in the primary report. If it was
specifically reported in the article that there were no pretest
differences between the treatment and control groups, posttreat-
ment means and standard deviations for each condition were used
to calculate effect sizes. Otherwise, in order to control for pretest
differences between treatment conditions, change scores (posttreat-
ment means minus pretreatment means) and pooled standard
deviations were used in computing effect sizes. For studies not
employing a control group or only reporting within treatment
group results, effect sizes were computed by comparing posttreat-
merit to pretreatment means and standard deviations.
When means and standard deviations were not reported in the
primary report, but the F-statistic was associated with a test of
differences between the treatment and control conditions, the
d-index was calculated using the F-statistic and degrees of
freedom. When only the significance level (p-value) of the
difference between treatment and control conditions was reported,
d-indexes were computed by transforming p into z (41), then z into
Pearson's r, and r into d (42). When a comparison between the
treatment and control conditions was only described as non-
significant and the F or p-value was not reported, an effect size of
zero was used as a conservative estimate (43).

3. 182 ANNALS OF BEHAVIORAL MEDICINE Rossy et al.
Statistical Analysis
In order to examine each research question, effect sizes were
combined to create average d-indexes within each class of
treatment by outcome measure. Because effect sizes from studies
with larger samples are more likely to accurately represent the true
population effect size, weighted average effect sizes were com-
puted that gave more weight to the more reliable effect sizes
obtained from larger samples (39). To weight each d-index
according to sample size, separate formulas were used for between-
groups designs (39) and within-groups designs (44).
In addition to computing average effect sizes, the 95%
confidence interval (CI) for each category of interest (e.g. treat-
ment group or outcome measure) was also computed. If the 95%
confidence interval included zero, it was concluded that across all
studies there was no relationship between the independent and
dependent measures. If the 95 % confidence interval did not include
zero, it was concluded that the effect size was greater than would
be expected due to sampling error alone.
In addition to examining whether effect sizes differed signifi-
cantly from zero, we examined also whether effect sizes were
significantly different from each other. To do this, we conducted
homogeneity analyses (Qb) (45) which examine whether sample
error alone accounts for the variation in effect sizes, or whether
moderator variables, such as type of treatment or type of outcome,
also contribute to variation.
We were frequently able to calculate multiple effect sizes from
each primary report. For example, a particular study may have
included several self-reports of FMS symptoms (e.g. fatigue,
morning stiffness, and pain) and several physical status measures
(e.g. tender point index and myalgic score). In these instances, we
calculated separate effect sizes for each measure that was avail-
able. However, allowing all effect sizes to enter into statistical
analyses would seriously violate the independence of data points
assumption required to conduct the analyses. Following the
recommendations of Cooper (46), we used the independent sample
as the unit of analysis and averaged across all outcome measures
within each category of interest (i.e. physical status, self-report of
FMS symptoms, psychological status, and dally functioning).
Thus, average effect sizes within any given outcome measure
category have only one effect size from any independent sample.
RESULTS
Summary Effect Sizes
Table 1 presents a summary of the effect sizes for each
independent sample that used a pharmacological treatment. Table 2
presents a summary of the effect sizes for each independent sample
that used a nonpharmacological treatment. In each table, the type
of design for each study indicates whether outcomes were reported
by comparing a treatment group to a control group (between-
groups design and crossover design) or whether pretreatment and
posttreatment outcomes were compared within each treatment
group (within-groups design). If an article reported that a between-
groups study or a crossover study had been designed but statistics
reflected a comparison between pretreatment and posttreatment
within-group outcomes (47-49), a within-groups design is listed
for the corresponding independent sample(s). Within the four
outcome categories (physical status, self-report of FMS symptoms,
psychological status, and daily functioning), effect sizes for each
type of treatment were averaged across dependent measures.
Pharmacological Treatments
For measures of physical status and FMS symptoms (see
Table 3), treatment with antidepressants and muscle relaxants was
significantly associated with improved outcomes. However, treat-
ment with muscle relaxants was superior to treatment with
antidepressants, X2(1) = 12.96, p = .0003, for physical status
measures) Although treatment with muscle relaxants was signifi-
cantly associated with improved psychological status and treat-
ment with antidepressants and was not associated with a significant
effect on this measure, there was no statistically significant
difference between the two treatments, X2(1) = .04, p = .82. No
pharmacological treatment was associated with significantly im-
proved daily functioning. However, the small number of observa-
tions for treatment with muscle relaxants and NSAIDs limit the
generalizability of these results. Treatment with NSAIDs was not
significantly associated with improved outcomes on any measure.
While the effect sizes of the treatment interventions in the
"other" category were the most reliable (due to sample size and
size of effect) and resulted in positive outcomes across all outcome
measures except dally functioning, the heterogeneous nature of
this category warranted further investigation. First, a comparison
of treatments using one drug, d = .58, 95% CI = (.44, ,72), k = 15,
and treatments using a combination of drugs, d = .52, 95% CI =
(.26, .78), k = 4, found that both were significantly associated with
improved outcome and there was no significant difference between
the two treatments, X2(1) = .29, p = .59.
Second, the only types of treatment that were repeated in more
than one study were S-adensyl-L-methionine (SAMe), an anti-
inflammatory drug with analgesic and antidepressant effects, (six
studies) and 5-hydroxytryptophan (two studies) (see Table 1). A
comparison of the combination of all six studies using SAMe
treatments, d = .61, 95% CI = (.41, .81), k = 6, to the rest of the
treatments in the "other" category, d = .47, 95% CI = (.29, .65),
k = 10, found both groups were significantly associated with
improved outcome and there was no statistically significant
difference between the two groups, X2(1) = 1.35, p = .25. SAMe
was associated with improvements in physical status, self-report of
FMS symptoms, and psychological status (47,49-52), except for
one study that found a decline in psychological status (53). Both
studies using 5-hydroxytryptophan were associated with a signifi-
cant improvement on physical status, self-reported FMS symp-
toms, and psychological status (54,55).
Out of the remaining treatments in the "other" category,
cyclobenzaprine and ibuprofen (56), amitriptyline and naproxen
(57), and ibuprofen and alprazolam (58) were associated with
significant improvements on physical status and self-report of
FMS symptoms. A pilot study of topical capsalcin, applied four
times dally, demonstrated its efficacy at reducing tenderness of
3 Three independent samples contributed an effect size to more than one
pharmacological treatment category (50,51,71). For example, Goldenberg
(50) compared outcomes for a treatment group receivingantidepressants, a
treatment group receiving NSAIDs, and a control group. Thus, an effect
size comparing the antidepressant and control condition contributes to the
average effect sizes for antidepressants, and an effect size comparing the
NSAIDs and control condition contributes to the average effect sizes for
NSAIDs. Although any one independent sample within the antidepressant
and NSAIDs categories contributes only one effect size, homogeneity
analyses comparing these categories may be biaseddue to violations of the
independence of data points assumption. To examine the impact of
violating this assumption on results, we randomly discarded one effect size
from each of the three independent samples and reconducted the homoge-
neity analyses. Results from all analyses remained the same. Thus, we
reportresults from analysis with all effect sizes included in the text.

4. Fibromyalgia Treatment VOLUME 21, NUMBER 2, 1999 183
TABLE 1
Summary of Effect Sizes (ES) by Outcome Measures for Pharmacological Treatment
Source of Type of Group PS SR PSY DF
Independent Sample Design Type of Treatment n ES ES ES ES
Bennett et al. (1988) between
Carette, McCain, Bell, and Fam (1986) between
Carette et al. (1994) between
Carette, Oakson, Guimont, and Steriade
(1995)
Caruso et al. (1987)
Caruso, Puttini, Cazzola, and Azzolini
(1990)
Clark, Tindall, and Bennett (1985)
Di Benedetto, Iona, and Zidarich (1993)
Fossaluzza and De Vita (1992)
Goldenberg, Felson, and Dinerman
(1986)
Goldenberg, Mayskiy, Mossey, Ruthazer,
and Schmid (1996)
Grassetto and Varotto (1994)
Ianniello et al. (1994)
Jacobsen, Danneskiold-Samsoe, and
Andersen (1991)
Karoliussen and Kvalheim (1995)
Kempenaers et al. (1994)
McCarty, Csuka, McCarthy, and Trotter
(1994)
Moldofsky, Lue, Mously, Roth-Schechter,
and Reynolds (1996)
Norregaard, Volkmann, and Darmeskiold-
Samsoe (1995)
Ostuni et al. (1995)
Pattrick, Swarmell, and Doherty (1993)
Puttini and Caruso (1992)
Quimby, Gratwick, Whituey, and Block
(1989)
Reynolds, Moldofsky, Saskin, and Lue
(1991)
Russell, Fletcher, Michalek, McBroom,
and Hester (1991)
Russell, Michalek, Flechas, and Abraham
(1995)
Santandrea, Montrone, Sarzi-Puttini, Boc-
cassini, and Caruso (1993)
Scudds, McCain, Rollman, and Harth
(1989)
Tavoni, Vitali, Bombardieri, and Pasero
(1987)
Vaeroy, Abrahamsen, Forte, and Kass
(1989)
Volkmann et al. (1997)
Wolfe, Cathey, and Hawley (1994)
Yunus, Masi, and Aldag (1989)
crossover
cyclobenzaprine 40 .09 .26
amitriptyline 27 .12 .24
amitriptyline 78 .23 .20
cyclobenzaprine 70 .25 .30
amitriptyline 22 .32 .74*
between dothiepin 26 .74* .74*
between 5-hydroxytryptophan 24 1.06" .96* 1.06"
crossover prednisone 20 0 0
within s-adenosyl-l-methionine 15 1.01" .34 .71"
within cyclobenzaprine 15 1.96" 1.68"
within cyclobenzaprine and ibuprofen 17 1.71" 1.72"
between amitriptyline and naproxen 15 .89* .82*
between naproxen 15 0 0
between amitriptyline 15 .47 .55
crossover amitriptyline 19 .28 .44 .09
crossover fluoxetine 19 .08 .50 .26
crossover amitriptyline and fluoxetine 19 .61 .97* .33
within s-adenosyl-l-methionine 47 .79* .25 .76*
within s-adenosyl-l-methionine 10 1.41" 1.08" .62
between s-adenosyl-l-methionine 17 .31 .55 .70*
between mexiletine 16 .29 .16
between SER282 9 -.47 -.30
between topical capsaicin 20 .35 .03
crossover zolpidem(5mg) 16 .04 -.10
crossover zolpidem(10mg) 16 .26 .06
crossover zolpidem(15mg) 16 -.34 .03
between citalopram 21 .63* -.04
within myanserine 10 .38 .89*
between chlormezanone 18 - .33 0
within 5-hydroxy-l-tryptophan 43 1.51* .97*
between cyclobenzaprine 21 .87* .38
crossover cyclobenzaprine 9 -. 14 .23
.01
1.96"
between ibuprofen and alprazolam 15 .29 .24 .12
between ibuprofen 17 .04 .13 .49
between alprazolam 17 .14 .18 -. 16
within ibuprofen and alprazolam 52 .33* .62* -.49*
crossover supermalicR 20 -. 17 .06 .10
within supermalicR 16 1.08" .79* .56*
within cyclobenzaprine (10 mg) 35 1.33" .48* 0
within cyclobenzaprine (30 mg) 25 1.48" .64* .60*
crossover amitriptyline 36 .47 .65*
within s-adenosyl-l-methionine 17 .83* .85*
between carisoprodol, paracetamol, and caffeine 20 .12
crossover s-adenosyl-l-methionine 29 .30 .32 -.14
between fluoxetine 15 -.27 .05 .67
between ibuprofen 20 .15 .06
.04
.24
.30
.57
1.04*
-.51
-.25
-.25
.14
.55
.32
.17
Notes: PS = Physical Status; SR = Self-Report of FMS Symptoms; PSY = Psychological Status; DF = Daily Functioning; * = denotes significant effect
size (95 % confidence interval does not encompass zero).

5. 184 ANNALS OF BEHAVIORAL MEDICINE Rossy et al.
Burckhardt, Mannerkorpi, Hedenberb,
and Bjelle (1994)
TABLE 2
Summary of Effect Sizes (ES) by Outcome Measures for Nonpharmacological Treatment
Source of Type of Group
Independent Sample Design Type of Treatment n
Banwell and Fiechtner (1992)
Buckelew et al. (1998)
Deluze, Bosia, Zirbs, Chantraine, and
Vischer (1992)
Ferraccioli et al. (1987)
Ferraccioli et al. (1987)
Goldenberg et al. (1994)
Haanen et al. (1991)
McCain, Bell, Mai, and Halliday (1988)
Martin et al. (1996)
Mengshoel, Komnaes, and Forre (1992)
Mengshoel, Forseth, Haugen, Walle-
Hansen, and Forre (1995)
Mikkelsson, Isomeri, and Kautianen
(1994)
Nichols and Glenn (1994)
Nielson, Walker, and McCain (1992)
within exercise and education 17
between biofeedback and relaxation 27
between walking, strengthening, and stretching 28
between biofeedback and exercise 26
between education 28
education and physical therapy (stretch- 28
ing, pool therapy, and walking, cycling,
or swimming)
between electroacupuncture 28 .69*
Ostuni et al, (1995)
Wigers, Stiles, and Vogel (1996)
within biofeedback 15 4.33*
between biofeedback 6 3.18*
between cognitive-behavioral 79
between hypnotherapy 20 -.09
between bicycle ergometer 18 1.11"
between walking and stretching 18 1.10*
between aerobics 11 .26
within exercise (nonaerobic) and 16
cognitive-behavioral
within cycling and strengthening 10
between walking and strengthening 8
within cycling or treadmill, stretching, and cog- 25 1.13"
nitive-behavioral
within acupuncture 14 .51
between aerobics 16 .96"
between cognitive-behavioral 15 .63
PS SR
ES ES
.... .,.. ...... ,,,,
.40
.58* .40
.53 .48
.41 .19
.18
.10
.50
1.46"
1.30"
.40*
.76*
.67
0
.37
.15
• . . . . • .,.
PSY DF
ES ES
.32 .31
.49 .51
.23 .75
.38 .44
.27 .07
.86* .39
.78*
.36 .23
.34
0 .29 -.44
1.15" 1.02" .63*
1.74"
.77* .31
,43 .56
" Noies: PS = Physical Status; SR = Self-Report of FMS symptoms. PsY = Psychological Status; D'F Daily Functioning; * = denotes significant effect
size (95% confidence interval does not encompass zero).
TABLE 3
Effect Sizes by Outcome Measure for Pharmacological Treatment
Antidepressants Muscle Relaxants NSAIDs Other
k ES k ES k ES k ES
Physical Status 11 .37a* 7 .89b* 3 .08a 17 .73b*
FMS Symptoms 12 .49a* 8 .47a* 3 .06b 17 .50a*
Psychological Status 4 .22a 3 .26a* 1 .49a.b 10 .68b*
Daily Functioning 4 .15~ 1 .24~ 1 -.25~ 2 .15~
, ||, ,,, , ,, 9 ,
Notes: For each outcome measure, treatment groups with the same letter subscript do not differ significantly; k = number of independent samples
contributing to effect size estimate; ES = weighted effect size; * = denotes significant effect size (95% confidence interval does not encompass zero).
tender points, but not subjective pain and sleep measurements (59).
Super Malic R, a proprietary tablet of malic acid (200 mg) and
magnesium (50 rag), produced improvement across outcomes,
particularly measurements of pain and tenderness, when looking at
results from an open label trial, but failed to show significant
improvement in the blinded, placebo controlled trial (60). Alpra-
zolam, a benzodiazepine approved for the treatment of anxiety
and/or anxiety associated with depressive symptoms, appeared to
be of greater benefit when used in conjunction with ibuprofen than
when used alone (58). However, modest short-term effects of
benzodiazepines are generally outweighed by the dangerous side
effects of long-term use (61) and most physicians caution against
their long-term use.
Nonpharmacologieal Treatments
Each type of nonphannacological treatment (physically-based,
psychologically-based, and combination) was associated with
significant improvements on each of the four outcome measures,
with one exceptionmfunctional outcome after physically-based
treatment (see Table 4). Pairwise comparisons conducted to test
for significant differences in effect sizes between the types of
treatment for each outcome measure revealed no significant
differences.4
Comparison of Nonpharmacological and Pharmacological
Treatments
Overall, both pharmacological and nonpharmacological treat-
ments were associated with improved outcomes for all categories
4 Three independent samples contributed an effect size to both physically-
based and psychologically-based categories (55,59,61). As was done with
pharmacological treatment, we randomly deleted one effect size from one
category and reconducted the homogeneity analysis. All results remained
the same and we report results from the entire data set in the text.

6. Fibromyalgia Treatment
TABLE 4
Effect Sizes by Outcome Measures for Nonpharmacological 1~reatment
Physically-Based Pychologically-Based Combination
Outcome Measure k ES k ES k ES
Physical Status 7 .71a* 6 .60a* 4 .55a*
FMS Symptoms 8 .56a* 6 .63a* 3 .63a*
Psychological Status 5 .38~* 5 .60a* 3 .56a*
Daily Functioning 3 .29~ 3 .38~* 3 .49a*
Notes: For each outcome measure, treatment groups with the same letter
subscript do not differ significantly;k = number of independent samples
contributingto effect size estimate; ES = weighted effect size; * = denotes
significanteffect size (95% confidence interval does not encompass zero).
TABLE 5
Comparison of Pharmacological and Nonpharmacological Treatment
Effect Sizes by Outcome Measure
Pharmacological Nonpharmacological
k ES k ES p
Physical Status 34 .66* 13 .69* .67
FMS Symptoms 35 .49* 14 .65* .03
Psychological Status 16 .52* 9 .61" .53
Daily Functioning 6 .19 6 .40* .10
Notes: k = number of independent samples contributing to effect size
estimate; ES = weighted effect size;p = significancelevel for comparison
of nonpharmacologicai and pharmacological treatment; * = denotes
significanteffect size (95% confidence interval does not encompass zero).
of outcome measures, except for daily functioning measured after
pharmacological treatment (see Table 5). However, nonpharmaco-
logical treatment was superior to pharmacological treatment on
self-report of FMS symptoms, X2(1) = 4.87, p = .03, and the same
trend was found for functional measures, • = 2.72, p = .10.
There were no significant differences between nonpharmacological
and pharmacological treatments for measures of physical status,
• = .18, p = .67, and psychological status, X2(1) = .38,
p = .53.
Methodological Characteristics
Three methodological moderator variables (study design,
existing drug treatment washout, and criteria used to classify
fibromyalgia participants) were examined. If effect sizes remained
the same across these methodological characteristics, we could
have more confidence in the validity of the conclusions drawn
from the meta-analysis.
To examine whether the magnitude of effect sizes reported
previously was moderated by the type of design employed by the
primary researchers, we examined the design of pharmacological
and nonpharmacological treatment studies separately. For pharma-
cological treatments, all studies reported results that either re-
flected a comparison between active medication and a placebo
control group or between pretreatment and posttreatment using
active medication (no control group). Because individual differ-
ences are controlled for in studies using a no control groups design
where each participant serves as their own control, we anticipated
that effect sizes from no control group studies would show a
stronger effect of treatment on outcome measure than studies that
compared a treatment group to a control group. Therefore, study
design was used as a moderator to determine whether it was
systematically related to the magnitude of the effect sizes. A
breakdown of effect sizes that were averaged over each type of
pharmacological treatment for each type of outcome measure were
VOLUME 21, NUMBER 2, 1999 185
TABLE 6
Comparison of Effect Sizes for Placebo Control and No Control Group
Designs by Outcome Measure and Pharmacological Treatment
Placebo Control No Control
Group Design Group Design
k ES k ES p
Antidepressants
Physical Status 9 .37* 2 .42 .81
FMS Symptoms 10 .41" 2 1.14" .0003
Psychological Status 4 .22 0 --
Daily Functioning 4 .15 0 --
Muscle Relaxants
Physical Status 4 .15 3 1.48" <.0001
FMS Symptoms 5 .23 3 .70* <.0001
Psychological Status 1 .30 2 .24 .73
Daily Functioning 1 .24 0 --
NSAIDs
Physical Status 3 .08 0 --
FMS Symptoms 3 .06 0 --
Psychological Status 1 .49 0 --
Daily Functioning 1 -.25 0 --
Other
Physical Status 11 .29* 8 .88* <.0001
FMS Symptoms 12 .27* 7 .66* <.0001
Psychological Status 5 .31 7 .52* .006
Dally Functioning 2 .15 0 --
Notes: k = number of independent samples contributing to effect size
estimate; ES = weighted effect size;p = significancelevel for comparison
of placebo control and no control group designs; * = denotes significant
effect size (95% confidenceintervaldoes not encompass zero).
computed according to whether a study used no control group or a
placebo control group (see Table 6).
With regard to pharmacological treatments, antidepressants
resulted in modest improvements across study design. In studies
using a no control group design, treatment with antidepressants
was not associated with a statistically significant improvement in
physical status measures, however, the effect did not differ
significantly from the statistically significant effect found in the
studies using a placebo group design. Therefore, we attribute the
nonsignificant finding in no control group designs to be due to the
very small number of studies in this category and do not question,
based on our results, the efficacy of treatment with antidepressants
for physical status measures. Muscle relaxants resulted in improve-
ments in both physical status and self-report of FMS symptoms in
studies utilizing a no control group design only. No significant
improvements were found on these two measures in studies using a
placebo control group, a more stringent design. The large discrep-
ancy between type of design for treatment with muscle relaxants
on physical status and self-report of FMS symptoms precludes any
definite conclusions about the efficacy of this treatment.
For nonpharmacological treatments, studies utilized three
types of control group designs--no control group, placebo/
attention control group, and wait list control group. Placebo/
attention control interventions included placebo (62,63), education
(64), physical therapy (65), flexibility (66), and relaxation (67).
The groups in the wait list control category were described as wait
list (68,69), treatment as usual (70), sedentary (71), and no change
in physical activity (72). All three types of control group designs
were associated with significant improvements across outcome
measures, no-control group d = .74, 95% CI = (.52, .96), k = 6;
placebo/attention control d = .61, 94% CI = (.34, .88), k = 6; and
wait list control d -- .36, 95% CI = (.10, .62), k = 5. Although
analyses examining study design show that wait list control studies

7. 186 ANNALS OF BEHAVIORAL MEDICINE Rossy et al.
were associated with smaller effects than studies using no control
group and placebo/attention control group designs, wait list control
group studies still showed a significant effect. Thus, we have
confidence in the efficacy of nonpharmacological treatment across
study design.
With regard to the methodological question as to whether
individuals were asked to washout or abstain from existing drug
treatment strategies before participation in a study, only 4 of the 33
pharmacological studies explicitly stated they did not require a
washout period (52,53,59,73), and no further analysis of pharmaco-
logical studies was considered useful. Although nonpharmaco-
logical treatment studies that did not require a washout (62,64,
67-69,74), d = .56, 95% CI = (.36, .76), k = 6, as well as
nonpharmacological studies that did require a washout or absten-
tion from drugs (63,66,71,75), d = 1.14, 95% CI = (.78, 1.50), k =
5, were associated with significant overall outcomes, nonpharma-
cological studies that did require a washout showed a significantly
larger effect, • = 19.93, p < .00001.
The magnitude of effect sizes may have been moderated by
the type of classification criteria used, since not all of the studies
used the 1990 ACR criteria. Therefore, an analysis was completed
using this variable. The studies using the 1990 ACR criteria, d =
.43, 95% CI = (.48, .82), k = 20, and studies using criteria
previous to the 1990 ACR criteria, d = .61, 95% CI = (.51, .71),
k = 34, were both associated with significant overall outcomes,
and there were no significant differences between the two groups,
X2(1) = .57, p = .45. Because of these results, no further
investigation of differences based on type of criteria were performed.
DISCUSSION
Our analysis of 49 clinical trials including 2,066 participants
demonstrates that many pharmacological and nonpharmacological
treatments are beneficial for individuals with FMS. Before examin-
ing differences due to study design, all broad classes of pharmaco-
logical treatments defined in this study, except NSAIDs alone,
were associated with significant improvements in physical status
and self-report of FMS symptoms. However, when effect sizes
were separated by whether a study used a no control group or a
placebo control group, several differences in effect sizes emerged
within the same treatment. Across study design, antidepressants
and muscle relaxants did not result in meaningful improvements in
psychological status and daily functioning in the few studies
including these outcome measures. This may not be surprising,
because the dosages for antidepressants commonly used in these
studies are lower than the therapeutic dosages for depression
(48,76-78). No pharmacological treatment alone resulted in im-
proved dally functioning (58,60,76,78). However, one trial using a
combination of amitriptyline and fluoxetine (77) resulted in
improved functional ability as measured by the Fibromyalgia
Impact Questionnaire (FIQ). Future research may look at other
combinations of selective serotonin reuptake inhibitors in conjunc-
tion with tricyclics. NSAIDs are not effective on any dimension of
measured outcome except in conjunction with another treatment
(e.g. cyclobenzaprine and amiWiptyline) (56-58).
All classes of nonpharmacological treatments were associated
with significant improvements in all four categories of outcome
measures with the exception that physically-based treatment was
not associated with significant improvement of daily functioning.
However, this result may be explained by the self-report nature of
this measure reflecting self-efficacy of function (a psychological
variable) rather than actual physical functioning. When comparing
the two types of treatment, nonpharmacological treatment is more
efficacious in improving self-report of FMS symptoms than
pharmacological treatment alone. A similar trend is suggested for
functional measures.
Results of the analyses of study design highlight the difference
between placebo-controlled pharmacological studies and those that
did not utilize a placebo. There are several factors that could
produce this difference. First, because no control group designs
control for individual differences among participants, the design
itself is more sensitive to changes in outcome. However, no control
group designs (as included in our data set) are open to a host of
threats to internal validity that cannot be ruled out in assessing
whether posttreatment change is actually due to treatment versus
some other factor (e.g. social desirability, experimenter demand).
Alternatively, participants receiving the placebo in a placebo
control group study could be showing improvement because of the
attention paid to them and/or expectancy effects (76,79), and thus,
those studies would detect less of a difference between treatment
and placebo. Therefore, it is likely that the amount of improvement
in participants receiving active medication in placebo control
group studies is primarily due to treatment and not attention
(placebo). Conversely, the level of improvement in clinical situa-
tions may be better estimated by no control group studies, which
better simulate a clinic condition.
Analyses of nonpharmacological treatment did not result in
significantly different effects between different types of study
design. These consistent findings across study design suggest
evidence of value added by treatment beyond that attained with
placebo, even though, by nature, nonpharmacological treatment is
often thought to work through those mechanisms of social
interaction, expectations, and attitude change that constitute the
key elements of the placebo effect.
The classification of treatment as nonpharmacological, how-
ever, is somewhat misleading, since many of these studies
(62,64,67-69,74) allowed participants to remain on their current
pharmacologic treatments of FMS. When effect sizes were sepa-
rated by whether or not current pharmacological treatments were
allowed during a nonpharmacological treatment intervention,
nonpharmacological treatments after washout from medication
produced sighificantly larger effect sizes. However, a significant
effect was still found for nonpharmacological treatment used in
conjunction with medication. The fact that both strategies were
associated with significant effects constitutes one of the most
important findings of this study and underlines the value of
nonpharmacological treatment both with and without concurrent
medication. The real life significance of these findings is illustrated
by two recent studies and highlights the need for future research
that examines the combination of treatments that are being used
both inside and outside a medical setting. The first study (80) found
that 91% of the patients with FMS had adopted an alternative
treatment within the preceding year. The second study's findings
also suggest a high degree of complementary treatment use among
patients with FMS and, specifically, that poor clinical status is a
major predictor of such use (81). The term "complementary" is
used because patients tend to use alternative treatments in conjunc-
tion with traditional medical care (82). Using empirical research to
validate the use of such treatments and then disseminate this
information to FMS patients who are seeking complementary
treatment should be a priority for future research and educational
endeavors.
To date, the one published study that explicitly set out to
examine the combination of pharmacological and nonpharmacologi-
cal treatment utilized a 6-month group treatment outpatient

8. Fibromyalgia Treatment VOLUME 21, NUMBER 2, 1999 187
program (83) and concluded that a program limited to education,
cognitive-behavioral therapy, and supervised stretching/aerobic
training would be the optimal treatment strategy. Those conclu-
sions are further validated by a recent study that examined
differences between a cognitive treatment group, an attention
control group using a discussion format, and a wait list control
group on self-report measures of pain and affective distress (84).
Both the cognitive treatment and the attention control groups
received the same educational program which included a physical
exercise component. Significant within-group changes were found
for both the cognitive treatment and the attention control groups,
but not the wait list control group. The cognitive treatment group
and the attention control group interventions may have been too
similar to create differences in outcomes between the groups at
posttreatment on coping and pain control, the two primary
variables that distinguish the cognitive treatment and the attention
control groups from the wait list control group. Again, the
combination of education, physical exercise, and some type of
psychological intervention appears to be effacacious in the treat-
ment of FMS. Further research is needed that examines different
combinations of treatment and their differential effects on sub-
groups of individuals.
Although the results of this analysis did not find any
significant differences between studies using the currently recom-
mended 1990 ACR criteria and studies which used older criteria,
there are a number of reasons to recommend the 1990 ACR criteria
for future treatment outcome studies. Given the diagnostic ambig-
uity and historical confusion surrounding FMS, this empirically-
defined criteria provides a method for researchers to evaluate their
treatment on a more distinct and similar population of fibromyalgia
patients.
As FMS is a chronic illness, it is important to gain an
understanding of the long-term efficacy of treatment. However, all
studies conducted to date have used relatively short-term treatment
interventions. In the current review, pharmacological treatment
studies ranged from 1 week to 6 months, and nonpharmacological
treatment studies ranged from 4 to 20 weeks in length. The longest
and one of the most well-designed studies of pharmacological
treatment of FMS confirmed the short-term (1-month) efficacy of
amitriptyline and cyclobenzaprine. Continued treatment over the
next 5 months produced an increase in improvement in both the
amitriptyline group and the cyclobenzaprine group, but a similar
phenomenon observed in the placebo group resulted in no statisti-
cal difference between the three groups at the end of treatment
(79). No long-term follow-up studies have been conducted on
pharmacological treatments that could imply long-term efficacy
from their modest short-term effects. Because only five long-term
follow-up studies have been conducted on nonpharmacological
treatments, they are not included in our analysis. However, they
add further support for their use in the treatment of FMS. A
30-month follow-up of cognitive-behavioral therapy suggests its
role in the long-term treatment of FMS (85); a 6-month follow-up
of electromyograph (EMG) biofeedback found a long-term benefit
was observed in 56% of patients (63); a 24-week follow-up of
hypnotherapy (12 weeks after treatment ended) found improve-
ment in subjective measurements of FMS (65); and a 6-month
follow-up of exercise and cognitive-behavioral therapy found that
pain intensity was still reduced from baseline measurements (86).
Another recent study that conducted a 6-month follow-up of
behavioral and educational interventions found maintenance of
significant improvements in depression, self-reported pain behav-
ior, observed pain behavior, and myalgia scores that were reported
at the end of the initial 10-week treatment period (87). This study
also examined the role of intervening variables that may serve as
active agents of change in clinical outcome. Their findings suggest
that the reduction of helplessness beliefs and maladaptive coping
strategies should be explicitly targeted in psychosocial interven-
tions of FMS based on their ability to predict improvement in pain,
depression, and self-reported pain behavior.
As in any review of the literature, this study is subject to the
same recruitment and retention bias that exists in the primary
research from which this analysis was conducted. Patients included
in these studies were typically recruited from rheumatologists or a
registry from a rheumatology clinic, and persons with FMS who
seek treatment frequently exhibit multiple psychiatric disorders
and high levels of pain and fatigue (88). The prevalence of
psychiatric disorders, particularly mood and panic disorders, and
psychological disturbance associated with FMS has been high-
lighted in a number of studies (88-92). In fact, patients with FMS
indicated that the management of psychosocial aspects of their
illness is significantly more important to them than to their
rheumatologists (93). As this study reveals, a large number of
treatment outcome studies neglect to include measurement of these
clinically important variables. Thus, identifying treatments with
the ability to improve psychological and functional outcome is an
important facet of future FMS research. Selection bias can also be
introduced into a study by a large dropout rate, which often occurs
in medication studies, as well as the different types of diagnostic
criteria for FMS. Although not the subject of this review, a recent
recta-analysis of treatments in areas as diverse as education to
health-related concerns concluded that methodological artifacts, as
listed above, are almost as likely to produce an underestimate as an
overestimate of effects (94).
The practical and clinical significance of an effect is depen-
dent on the nature of the outcome and its importance to patients or
clients. Across treatment groups, the current review found signifi-
cant effect sizes ranging from .26 to .89 for pharmacological
treatments and .38 to .71 for nonpharmacological treatments. A
meta-analysis of drug treatment judged effective for arthritis
reported effect sizes between .45 and .77 (95) and a meta-analysis
of biofeedback and relaxation training for migraine and tension
headaches reported a mean effect size of .63 (96). The magnitude
of effect sizes in the current review seems sufficiently large, by
comparison to similar medical domains, to support the claim that
treatment is generally efficacious in practical as well as statistical
terms.
Despite all that we know to date, fibromyalgia continues to be
a challenging disorder to treat. This is due, in part, to the
incomplete understanding of the biological underpinnings as well
as the multiple symptoms that characterize FMS. Therefore,
treatment has been approached empirically rather than theoreti-
cally, focusing on symptom reduction rather than control of the
disorder. Moreover, no clear guidelines exist that translate statisti-
cally significant research findings into a statement about correspond-
ing significant clinical improvement. The results of this meta-
analysis suggest that nonpharmacological treatments are particularly
more helpful in managing self-reported FMS symptoms (i.e. pain,
fatigue, and morning stiffness) and daily functioning than pharma-
cological treatment alone. Therefore, the recommendation for
optimal treatment of FMS would include nonpharmacological
interventions, specifically exercise and cognitive-behavioral
therapy, in addition to appropriate medication management as
needed for sleep and pain symptoms.

9. 188 ANNALS OF BEHAVIORAL MEDICINE Rossy et al.
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