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R E S E A R C H Open Access
Psychometric assessment of the PROMIS
Fatigue Short Form 6a in women with
moderate-to-severe endometriosis-
associated pain
Robin Pokrzywinski
1*
, Ahmed M. Soliman
2
, Eric Surrey
3
, Michael C. Snabes
2
and Karin S. Coyne
1
Abstract
Background: Endometriosis is a common problem in women of reproductive age and has impacts on health-
related quality of life and productivity. Fatigue is an important part of the burden of endometriosis, it is not often
included as an endpoint in clinical trials.
Objectives: The study assessed the psychometric properties of the PROMIS Fatigue Short Form 6a in women with
moderate-to-severe endometriosis-associated pain.
Methods: In a phase III double-blind, placebo-controlled clinical trial (NCT01620528), women aged 18–49 years with
moderate-to-severe endometriosis-related pain were randomized to elagolix 150 mg once daily, elagolix 200 mg
twice daily, or placebo for 6 months. PROMIS Fatigue and dysmenorrhea and non-menstrual pelvic pain (NMPP)
scores were assessed at baseline and months 1, 3, and 6, and Patient Global Impression of Change (PGIC) was
assessed at months 1, 3, and 6. Reliability (internal consistency and test-retest reliability), construct validity
(convergent and known groups validity), and responsiveness were evaluated.
Results: The analysis included 871 women, mean age 31.5 years. Internal consistency supported a single concept
(Cronbach’s alpha 0.93). For the 238 patients with no change in PGIC at month 1, the intraclass correlation
coefficient for the PROMIS Fatigue T-score was 0.7 and paired t-test statistically significant (2.84, p= 0.0049).
Correlations with other measures were expected to be fairly low as concepts were not redundant. The PROMIS
Fatigue discriminated among known groups with mean scores of 55.3, 62.3, and 65.8 at month 3 (PGIC
improvement, no change, worsening, respectively). Statically significant discrimination, and change score
responsiveness, were seen using clinically relevant anchors (dysmenorrhea and NMPP) at months 3 and 6 between
responders and non-responders. Anchor-based (PGIC) responsiveness showed significant improvement from
baseline to months 3 and 6 (p< 0.0001).
Conclusions: PROMIS Fatigue has good reliability, validity, and responsiveness in women with moderate-to-severe
endometriosis-associated pain.
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* Correspondence: robin.pokrzywinski@evidera.com
1
Evidera Inc., 7101 Wisconsin Ave., Suite 1400, Bethesda, MD 20814, USA
Full list of author information is available at the end of the article
Journal of Patient-
Reported Outcomes
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86
https://doi.org/10.1186/s41687-020-00257-y
Background
Endometriosis is a common problem in women of repro-
ductive age [1,2]. In the Unites States, endometriosis af-
fects approximately 6%–10% of women at some time in
their life. Symptoms include intermenstrual bleeding,
non-menstrual pelvic pain (NMPP), and pain during men-
struation, intercourse, urination, and defecation. In
addition to pain and bleeding, fatigue is experienced by
50%–87% of women with endometriosis and is considered
by women to be one of the most burdensome symptoms
[3–5]. Due to these symptoms, and their association with
infertility, endometriosis has far-reaching consequences
on a woman’s health-related quality of life, interfering with
marital and sexual relationships, social life, employment,
physical activities, and psychological function [4–11].
Although fatigue is an important part of the burden of
endometriosis, it is not often included as an endpoint in
clinical trials. Several options are available to assess
patient-reported fatigue, including the Fatigue Severity
Scale [12], Fatigue Impact Scale [13], or Brief Fatigue In-
ventory [14], but these have not been developed specific-
ally for or been assessed for use among women with
endometriosis. The Patient-Reported Outcome Measure-
ment Information System (PROMIS), includes fatigue-
related item banks and several fatigue short forms that
have been developed and assessed for performance in
chronic conditions [15].
A recent qualitative study in women with moderate-to-
severe endometriosis-associated pain supported the con-
cept of fatigue as important in this population [16]. In
addition, PROMIS Fatigue SF-6a was used as a secondary
endpoint to measure patient-reported fatigue in EM-I, a
phase III randomized, placebo-controlled clinical trial that
assessed the safety and efficacy of elagolix in 871 women
with moderate-to-severe endometriosis-related pain [17].
At baseline, 54%–74% of the patients reported frequently
having fatigue-related issues. The study also showed that
at 6 months, PROMIS Fatigue SF-6a T-scores decreased
significantly more in women treated with either dose of
elagolix than in women who received placebo, and de-
creased more in women reporting clinically meaningful
reductions in dysmenorrhea, NMPP, and dyspareunia
than in women who did not [18].
These findings support the possibility of using PRO-
MIS Fatigue SF-6a as an appropriate endpoint in clinical
trials of endometriosis treatments. Here, we describe the
psychometric characteristics of PROMIS Fatigue SF-6a
in this sample of women with endometriosis based on
data collected during the EM-I trial.
Methods
Data source and sample
This analysis was based on data collected during the
EM-I phase III clinical trial (NCT01620528) [17].
Participants in the trial were premenopausal women
from the United States and Canada aged 18–49 years
with a surgical diagnosis of endometriosis in the previ-
ous 10 years and enrolled from July 2012 to May 2014.
Women were excluded if they had clinically significant
gynecological conditions other than endometriosis; or
chronic pain unrelated to endometriosis [17].
The study ran from May 22, 2012 to September 28,
2015. Participants were randomized 3:2:2 to placebo, ela-
golix 150 mg once daily, or elagolix 200 mg twice daily.
The study included a washout period for women receiv-
ing hormonal therapies, a screening period of up to 100
days, and a 6-month treatment period. The co-primary
endpoints were the proportions of women with a clinical
response for dysmenorrhea and a clinical response for
NMPP at 3 months. Secondary endpoints assessed in the
current analysis included PROMIS Fatigue SF-6a, Endo-
metriosis Health Profile-30 (EHP-30), the Health Related
Productivity Questionnaire (HRPQ), severity of dysmen-
orrhea and NMPP, and the Patient Global Impression of
Change (PGIC) at months 1, 3, and 6. Data on daily an-
algesic medication use was collected using an electronic
diary.
PROMIS Fatigue SF-6a
PROMIS Fatigue SF-6a is a 6-item instrument with a re-
call period of last 7 days [19]. Items include (1) “I feel fa-
tigued”; (2) “I have trouble starting things because I am
tired”; (3) “How run-down did you feel on average”; (4)
“How fatigued were you on average?”; (5) “How much
were you bothered by your fatigue on average?”; (6) “To
what degree did your fatigue interfere with your physical
functioning”. Response options for each item range from
“Not at all”(1 point) to “Very much”(5 points). The raw
overall (range 6–30) and can be converted to a T-score;
higher scores indicate greater fatigue [20]. A T-score
more than one standard deviation (10 points) higher
than the standardized mean of 50 for the United States
population indicates worse than average fatigue than the
United States norm.
EHP-30
EHP-30 is a 30-item disease-specific health-related qual-
ity of life instrument comprising five core domains (pain,
control and powerlessness, emotional well-being, social
support, and self-image) with a recall period of 4 weeks
[21]. In addition to the core domains, the clinical study
included the optional 5-item sexual relationship module
of the EHP-30. Women were able to report if the whole
sexual relationship module, or individual items, were not
relevant. The EHP-30 was scored according to the devel-
oper’s manual where item responses map 0 = Never to
4 = Always and domain scores are standardized to a 0
(best health status) to 100 (worst health status) range.
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 2 of 10
Domain scores were calculated from the sum of the raw
scores per domain divided by the maximum possible
raw score of items in the domain, multiplied by 100
[22]. The measure was used to characterize the sample’s
health-related quality of life impact and the pain domain
used to assess construct validity and used as a respon-
siveness anchor.
HRPQ
HRPQ is a 9-item questionnaire to assess loss of product-
ivity due to absenteeism and presenteeism [23]assessed
for use in women with endometriosis [24]. The question-
naire uses skip patterns to ensure that items are applicable
to those who work outside the home (e.g. in full- or part-
time employment) and those who work at home.
Dysmenorrhea and NMPP
During the trial, participants completed a daily elec-
tronic diary. Dysmenorrhea was assessed with the item
“Choose the item that best describes your pain during
the last 24 hours you had your period”and NMPP with
the item “Choose the item that best describes your pain
during the last 24 hours without your period”. Possible
responses included “None”(No discomfort), “Mild”
(Mild discomfort but I was easily able to do the things I
usually do.), “Moderate”(Moderate discomfort or pain. I
had some difficulty doing the things I usually do.), and
“Severe”(Severe pain. I had great difficulty doing the
things I usually do.). Responses were assigned scores as
follows: 0, none; 1, mild, 2; moderate; 3, severe. Scores
were averaged over the 35 calendar days immediately
prior to and including the date of the first dose of study
drug, as well as over the 28 days before each post-
baseline assessment. As reported by Taylor and col-
leagues [17], a dysmenorrhea response was defined as no
increase in analgesic use and a score change from base-
line of at least −0.81 (dysmenorrhea responder; if not
reached then dysmenorrhea non-responder) and a
NMPP response was defined as no increase in analgesic
use and a score change from baseline of at least −0.36
(NMPP responder; if not reached then NMPP non-
responder). The thresholds were identified using receiver
operating characteristic analysis using the PGIC as an
anchor and evaluating changes in analgesic use.
PGIC
PGIC was assessed using the question “Since I started
taking the study medication, my endometriosis related
pain has: very much improved (1), much improved (2),
minimally improved (3), no change (4), minimally worse
(5), much worse (6), very much worse (7).”
Statistical analyses: general considerations
All analyses were performed in all randomized subjects
who received at least one dose of treatment or placebo.
Missing data were not imputed. SAS version 9.4 (SAS
Institute, Cary, NC, USA) and Mplus version 7.11 (Los
Angeles, CA) were used to perform analyses.
Assessment of ceiling and floor effects
Ceiling effects were explored based a highest response
option and floor effects based on a lowest response
option.
Confirmatory factor analysis
A categorical confirmatory factor analysis using polyto-
mous response options was performed to evaluate the fit
of the PROMIS Fatigue SF-6a as a unidimensional fa-
tigue scale. Model fit was assessed using recommenda-
tions by Reeve and colleagues [25]. Specifically, the
model fit was evaluated by considering the comparative
fit index (suggested cut point > 0.95); Tucker-Lewis
Index (suggested cut point > 0.95); weighted root mean
square residual (suggested cut point < 1.0); average abso-
lute residual correlations (suggested cut point < 0.10);
root mean square error of approximation (suggested cut
point < 0.06).
Assessment of reliability
Internal consistency reliability of the PROMIS Fatigue
was assessed by calculating Cronbach’s alpha for data
collected at baseline. Values above 0.70 are generally
considered acceptable for aggregate data [26]. Item per-
formance for the PROMIS Fatigue SF-6a was evaluated
by calculating Cronbach’s alpha with individual items
deleted. Test-retest reliability (reproducibility) of PRO-
MIS Fatigue SF-6a was assessed in patients with no
change in PGIC at month 1; T-scores were compared
between baseline and month 1 by paired t-test and
intra-class correlations.
Assessment of construct validity
Convergent validity was assessed by calculating Pearson
product-moment and Spearman’s rank correlation coef-
ficients at baseline, month 3, and month 6 for PROMIS
Fatigue SF-6a versus dysmenorrhea, NMPP, HRPQ, and
EHP-30. Because the concepts being measured are not
redundant, rather hypothesized to be distally related, the
expectation is that positive, low to moderate correlations
are expected. Cohen’s conventions were used when
interpreting correlation coefficients as 0.10 small, 0.30
moderate, and 0.50 large [27].
Known groups validity was assessed by comparing
PROMIS Fatigue SF-6a T-score at months 3 and 6 be-
tween the following subgroups: dysmenorrhea and
NMPP responders versus non-responders; and PGIC
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 3 of 10
(improved; no change; worsened). Responder status (re-
sponder or non-responder) for dysmenorrhea and
NMPP was from the Endometriosis Daily Pain Impact
diary score as noted in the clinical study [17]. General
linear models (Proc GLM) were used to calculate F sta-
tistics and p-values; for multiple group pairwise compar-
isons Scheffe’s test was used to adjust for the multiple
comparisons.
Assessment of responsiveness
The PROMIS Fatigue SF-6a was explored using a tri-
angulation approach comprising anchor-based analyses,
difference between means analyses, and use of clinically
relevant indicators to test the instrument’s ability to de-
tect change during the clinical study. Responsiveness is
the ability of a measure to detect change when change is
present [28].
In anchor-based analyses, the least-squares (LS)-mean
change from baseline in PROMIS Fatigue SF-6a T-score
at months 3 and 6 were compared for the following sub-
groups: PGIC (improved, no change, worsened) and
EHP-30 pain domain responders (≥30-point decrease in
EHP-30 pain domain score from baseline) versus non-
responders. General linear models controlling for age
and baseline PROMIS Fatigue score were used to calcu-
late F statistics and p-values using Scheffe’s test to ad-
justment for multiple comparisons.
In the assessment of standardized difference be-
tween two means, effect size (Cohen’sd),wascalcu-
lated for PROMIS Fatigue SF-6a at months 3 and 6.
The analyses do not include direct patient feedback,
thus cannot serve as the primary assessment for
within-patient clinical meaningfulness, and should be
considered only as supportive [29]. Effect size was
calculated by subtracting the baseline score from the
post-baseline (month 3 or 6) score and dividing the
result by the baseline standard deviation. As described
by Cohen [27], effect sizes were classified as small
(0.20), moderate (0.50), or large (0.80). Change from
baseline was analyzed by paired t-test.
Clinically relevant indicators were used to explore the
responder threshold, which was defined as the LS-mean
change in PROMIS Fatigue SF-6a score from baseline
that indicated a meaningful response to treatment. Re-
sponder thresholds for PROMIS Fatigue SF-6a T-score
at 3 and 6 months were calculated for dysmenorrhea and
NMPP responders and non-responders.
Results
Sample characteristics
This analysis included the 871 participants enrolled in
the EM-I trial who received at least one dose of study
treatment or placebo (Table 1). Mean age was 31.5 years
and most were White (87.1%) and not Latino (84.0%).
The majority of the women were employed (60.2% full
time; 17.0% part-time). For the EHP-30 domains, mean
scores at baseline were 58.2 (14.3) for pain, 49.3 (19.3)
for emotional well-being, 69.8 (19.5) for control and
powerlessness, 54.8 (25.6) for social support, 51.0 (27.6)
for self-image, and 64.5 (24.7) for sexual relationships.
The mean PROMIS Fatigue T-score at baseline was 63.3
(7.7) (range, 33.4–76.8).
Ceiling and floor effects
A ceiling effect was observed for one PROMIS Fatigue
SF-6a item at baseline, “How much were you bothered
by your fatigue on average?”, with 32.6% responding
“Very much”. No other ceiling or floor effects were de-
tected at baseline or at months 3 or 6.
Table 1 Sociodemographic characteristics and patient-reported
data at baseline
Characteristic Total (N= 871)
Age (Mean, SD) 31.5 (6.2)
Race (n, %)
White 759 (87.1%)
Black or African American 76 (8.7%)
Asian 9 (1.0%)
American Indian or Alaska Native 6 (0.7%)
Multi Race 18 (2.1%)
Native Hawaiian or Other Pacific Islander 3 (0.3%)
Ethnicity (n, %)
Hispanic or Latino 139 (16.0%)
Not Hispanic or Latino 732 (84.0%)
Employment Status
a
Employed full-time 524 (60.2%)
Employed part-time 148 (17.0%)
Non-Employed 193 (22.2%)
Missing 6 (0.7%)
EHP-30 Domain Scores
b
Pain 58.2 (14.3) [0.0–100.0]
Control and Powerlessness 69.8 (19.5) [0.0–100.0]
Emotional Well-being 49.3 (19.9) [0.0–100.0]
Social Support 54.8 (25.6) [0.0–100.0]
Self-image 51.0 (27.6) [0.0–100.0]
Sexual Relationship 64.5 (24.7) [0.0–100.0]
PROMIS Fatigue Short Form 6a
c
63.3 (7.7) [33.4–76.8]
EHP-30 Indicates Endometriosis Health Profile-30, PROMIS Patient-Reported
Outcome Measurement Information System, SD Standard deviation
a
Reported in the HRPQ first item
b
Each domain has a 0–100 scale range where 0 indicates the best
health status
c
T-score Higher scores indicating more fatigue; population mean is 50 and 10
is one standard deviation from the general population
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 4 of 10
Confirmatory factor analysis
Confirmatory factor analysis demonstrated strong fit for
a unidimensional scale with item factor loadings ranging
between 0.808–0.942 (Table 2). Model fit was supported
by the comparative fit index, Tucker-Lewis index, and
all absolute residual correlations less than 0.10. The data
were nonnormative and the weighted root mean square
residual and RMSEA estimate was 0.112 (90% confi-
dence interval, 0.093–0.132) which is higher than the ac-
ceptable value but not uncommon for small degrees of
freedom [30,31].
Reliability
Cronbach’s alpha was 0.93 at baseline and 0.91–0.92
when individual items were deleted, indicating that the
items comprising PROMIS Fatigue SF-6a measured the
same construct. In the 238 patients with no change in
PGIC at month 1, the interclass correlation for baseline
versus month 1 was 0.7 and paired t-test were statisti-
cally significant (t-value 2.84, p= 0.0049) for the PRO-
MIS Fatigue T-score indicating stable test-retest
reliability.
Construct validity
Spearman’s rank correlation coefficients indicated a
moderate correlation at baseline between PROMIS Fa-
tigue SF-6a and the EHP-30 pain domain (0.34) and
weak correlations between PROMIS Fatigue SF-6a and
HRPQ work absenteeism (0.22), HRPQ work
presenteeism (0.23), dysmenorrhea (0.17), and NMPP
(0.17) (Table 3). At month 3, Spearman’s rank correl-
ation coefficients ranged from 0.27 (dysmenorrhea) to
0.49 (EHP-30 pain domain), and at month 6, they ranged
from 0.35 (HRPQ work absenteeism) to 0.60 (EHP-30
pain domain). Pearson product-moment correlations
were found to be similar to the Spearman’s rank correl-
ation coefficients (Table 3).
Known groups validity
The mean PROMIS Fatigue T-scores at month 3 were
significantly lower for dysmenorrhea and NMPP re-
sponders than for non-responders (Table 4). At month 3
the dysmenorrhea responders mean score was 54.5 and
the non-responders was 59.1; the DYS responder mean
was 54.4 and the non-responders was 59.8. Similar re-
sults for mean PROMIS Fatigue T-score between clinical
responders and non-responders were seen at month 6.
The mean PROMIS Fatigue T-score was also signifi-
cantly lower in participants for whom PGIC showed im-
provement than in those for whom PGIC did not change
(55.3 vs. 62.3, p< 0.001) or worsened (55.3 vs. 65.8, p<
0.001) at month 3; results at month 6 were similar
(Table 5).
Responsiveness
Two anchor-based approaches were used to evaluate
PROMIS Fatigue SF-6a responsiveness, the patient-
reported changes in PGIC (improved, no change, wors-
ened) and responder status on the EHP-30 pain domain.
At month 3 the mean changes in the PROMIS Fatigue
SF-6a T-score were −7.9 (0.4) for participants who re-
ported an improvement, −0.9 (0.8) for participants who
reported no change, and 2.3 (1.3) for participants who
reported a worsening using the PGIC (Table 5). The
findings demonstrate a PROMIS Fatigue SF-6a score re-
sponse when a change is identified. Similar findings were
seen at month 6 using the PGIC as an anchor. At month
3 and 6 the PROMIS Fatigue SF-6a T-scores were sig-
nificantly different for those who were a responder ver-
sus not a responder on the EHP-30 pain domain (p<
0.0001 at both timepoints). The mean T-score difference
for the EHP-30 responders versus non-responders was
−10.3 (0.5) and −3.5 (0.4) at month 3 and −11.8 (0.5)
and −3.3 (0.5) at month 6.
The responsiveness in distribution-based analyses uses
only the PROMIS Fatigue SF-6a data to look for changes
over time and does not include outside sources of data
such as the PGIC or clinical indicator. The treatment
groups should have a change, an improvement, between
baseline and month 3 and month 6. It is also expected
that the placebo group may have an improvement in
PROMIS Fatigue SF-6a scores over time due to placebo
effect. Table 6reports the responsiveness findings for
Table 2 Confirmatory factor analysis PROMIS Fatigue 6a at
baseline
PROMIS Fatigue Items Factor
Loadings
1. I feel fatigued 0.863
2. I have trouble starting things because I am tired 0.808
3. How run-down did you feel on average? 0.879
4. How fatigued were you on average? 0.942
5. How much were you bothered by your fatigue on
average?
0.867
6. To what degree did your fatigue interfere with
your physical functioning?
0.842
Model Fit Statistic
Comparative Fit Index 0.994
Tucker-Lewis Index 0.991
Weighted Root Mean Square Residual 1.074
Absolute Residual Correlations all < 0.10
RMSEA Estimate 0.112
RMSEA Lower 90% Confidence Limit 0.093
RMSEA Upper 90% Confidence Limit 0.132
PROMIS Indicates Patient-Reported Outcome Measurement Information
System, RMSEA Root mean square error of approximation
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 5 of 10
the total sample then by treatment arms. For all group-
ings, at both timepoints, there is a reduction in fatigue
indicating less fatigue. The total sample of participants
had a −6.2 (9.8) change from baseline to month 3 in
their mean PROMIS Fatigue SF-6a T-score the change
was a significant decrease (p< 0.0001); at month 6 the
total sample score changed −6.8 (10.4) and was also a
significant decrease (p< 0.0001).
Clinically relevant indicators were used to assess the
responsiveness of the PROMIS Fatigue SF-6a. For dys-
menorrhea responders, the LS-mean change from base-
line in PROMIS Fatigue SF-6a T-score was significantly
greater than those who did not have a response to treat-
ment in dysmenorrhea (Fig. 1). Dysmenorrhea re-
sponders had a score change of −8.8 (0.5) versus
dysmenorrhea non-responders having a change of −4.0
(0.4) at month 3 and −10.4 (0.5) versus dysmenorrhea
non-responders change of −3.2 (0.5) at month 6 (both
comparisons p< 0.0001). NMPP responders versus non-
responders had significant score changes for the re-
sponders versus the non-responders at both timepoints
too (Fig. 1).
Discussion
This analysis showed that for women with moderate-to-
severe endometriosis-associated pain, PROMIS Fatigue
SF-6a performs well, with evidence of reliability, con-
struct validity, and responsiveness to change. The instru-
ment measures a single construct, and the resulting
scores could discriminate between pain severity groups,
between responders and non-responders for clinically
relevant endpoints (dysmenorrhea and NMPP), and be-
tween levels of patient self-assessed global change. Cor-
relations with other patient-reported outcomes were
moderate to weak at baseline, indicating that PROMIS
Fatigue SF-6a is not redundant with other patient-
reported outcomes.
For a patient-reported outcome measure to be fit
for purpose there needs to be evidence that the con-
cept being measured is appropriate and applicable to
the target population and that the measure performs
well in the target population. The current findings
compliment the results of a previous study demon-
strating content validity and appropriateness of PRO-
MIS Fatigue SF-6a in this population [16]. They also
Table 3 Correlations (Spearman and Pearson) between PROMIS Fatigue Short Form 6a and patient-reported outcome measures at
baseline, month 3, and month 6
Measure Baseline Month 3 Month 6
N PROMIS Fatigue
(Spearman,
Pearson)
N PROMIS Fatigue
(Spearman,
Pearson)
N PROMIS Fatigue
(Spearman,
Pearson)
EHP-30 pain domain 851 (0.34, 0.34) 719 (0.49, 0.51) 576 (0.60, 0.60)
Dysmenorrhea over the last 28 days 860 (0.17, 0.17) 732 (0.27, 0.28) 573 (0.39, 0.38)
NMPP over the last 28 days 860 (0.17, 0.17) 732 (0.36, 0.37) 573 (0.49, 0.46)
HRPQ hours of absenteeism from work due to endometriosis 656 (0.22, 0.17) 498 (0.33, 0.30) 373 (0.35, 0.30)
HRPQ hours of presenteeism from work due to
endometriosis
623 (0.23, 0.20) 491 (0.41, 0.36) 368 (0.45, 0.37)
EHP-30 Indicates Endometriosis Health Profile-30, HRPQ Health Related Productivity Questionnaire, NMPP Non-menstrual pelvic pain, PROMIS Indicates Patient-
Reported Outcome Measurement Information System, SD Standard deviation
Table 4 Known groups validity: PROMIS Fatigue Short Form 6a T-score by dysmenorrhea and NMPP responder status at months 3
and 6
Time Outcome Responders Non-responders F-test
a
N Mean (SD) N Mean (SD) F P-value
Month 3 Dysmenorrhea
b
351 54.5 (10.0) 381 59.1 (8.8) 42.78 < 0.0001
NMPP
c
397 54.4 (9.5) 335 59.8 (9.0) 62.62 < 0.0001
Month 6 Dysmenorrhea
b
292 52.9 (10.2) 281 59.7 (8.8) 73.64 < 0.0001
NMPP
c
321 53.2 (10.0) 252 60.2 (8.8) 78.10 < 0.0001
NMPP Non-menstrual pelvic pain, PROMIS Patient-Reported Outcome Measurement Information System, SD Standard deviation
a
General linear model controlling for age and baseline Fatigue score
b
Pain due to endome triosis over the last 28 days during menstruation
c
Pain due to endometriosis over the last 28 days when the patient was not menstruating
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 6 of 10
provide quantitative evidence about the positive per-
formance (reliability, validity, and responsiveness) of
the instrument, therefore supporting a recent study
basedonPROMISFatigueSF-6adatafromtheEM-I
trial, which showed that the women in the trial fre-
quently experienced severe fatigue at baseline and
that elagolix significantly improved fatigue after 6
months of treatment [18].
The mean T-score at baseline in this study was more
than one standard deviation higher than the standard-
ized mean for the United States population, indicating
that the women included in this analysis experienced
significantly greater fatigue than the US norm at study
baseline. To put this in context, the baseline T-scores in
this study were higher than reported for back pain, can-
cer, chronic heart failure, chronic obstructive pulmonary
disease exacerbation, stable chronic obstructive pulmon-
ary disease, major depressive disorder, and rheumatoid
arthritis, muscular dystrophy, multiple sclerosis, post-
polio syndrome, spinal cord injury, and chronic pelvic
pain [32–34]. The baseline T-score in the present ana-
lysis was also close to the T-score obtained using the
PROMIS Fatigue Short Form 7a in a recent study of
adults with myalgic encephalomyelitis and chronic fa-
tigue [35].
PROMIS Fatigue Short Form 7a has been similarly
shown to have sound psychometric properties in preg-
nant women and patients with fibromyalgia, sickle cell
disease, and cardio-metabolic risk [36].
The patient-focused drug development guidance series
from the US Food and Drug Administration has pro-
vided insight to the Agency’s views about the develop-
ment and use of patient-reported outcome measures as
clinical study endpoints. The first draft guidance focuses
on the comprehensive and representative input during
product development [37]. The guidance details the pa-
tient experience data includes information about the ex-
perience and impact a condition has on the patient. The
concept of fatigue has been shown to be important to
this target population and the use of a measure that as-
sesses the concept is appropriate. Having the ability to
reliably measure fatigue among women with moderate-
to-severe endometriosis-related pain can be an import-
ant from a clinical and humanistic perspective. The
Table 5 PROMIS Fatigue Short Form 6a by PGIC: improved, no change, and worsened
Time Value PGIC improved
a
No change in PGIC PGIC worsened
b
Overall F-test
c
P-value for pairwise comparisons
d
N Mean (SD) N Mean (SD) N Mean (SD) F P-value Improved vs.
no change
Improved vs.
worsened
Month 3 Score 571 55.3 (9.2) 111 62.3 (7.8) 44 65.8 (10.6) 49.8 < 0.0001 < 0.001 < 0.001
Change from baseline 565 −7.9 (0.4) 109 −0.9 (0.8) 44 2.3 (1.3) 69.20 < 0.0001 < 0.001 < 0.001
Month 6 Score 404 54.3 (9.9) 81 60.6 (7.6) 58 63.9 (9.2) 35.2 < 0.0001 < 0.001 < 0.001
Change from baseline 398 −8.9 (0.4) 79 −3.1 (1.0) 58 0.6 (1.2) 48.54 <.0001 < 0.001 < 0.001
PGIC Indicates Patient Global Impression of Change, PROMIS Patient-Reported Outcome Measurement Information System, SD Standard deviation
a
Very much improved, much improved, or minimally improved
b
Minimally worse, much worse, or very much worse
c
General linear model, controlling for age and baseline PROMIS Fatigue SF 6a score for change values
d
Scheffe’s test adjusting for multiple comparisons
Table 6 Responsiveness of PROMIS Fatigue Short Form 6a at months 3 and 6
Time Sample N Mean (SD) t-value (p-
value)
†
Effect
size
(Cohen’s
d)
b
Baseline Post-baseline
a
Change (SD)
Month 3 Total Sample 728 63.2 (7.5) 57.0 (9.7) −6.2 (9.8) 17.12 (< 0.0001) −0.83
Placebo 314 62.4 (7.4) 58.2 (9.7) −4.2 (9.3) 8.02 (<.0001) −0.57
150 mg 216 64.0 (7.8) 57.4 (9.5) −6.7 (10.0) 9.79 (<.0001) −0.85
200 mg 198 63.6 (7.3) 54.6 (9.5) −9.0 (9.9) 12.90 (<.0001) −1.25
Month 6 Total Sample 577 63.1 (7.5) 56.3 (10.1) −6.8 (10.4) 15.76 (< 0.0001) −0.91
Placebo 246 62.5 (7.7) 58.3 (10.0) −4.2 (9.8) 6.73 (<.0001) −0.55
150 mg 170 63.6 (7.7) 56.6 (9.4) −7.0 (9.9) 9.24 (<.0001) −0.91
200 mg 161 63.5 (7.2) 52.9 (10.0) −10.6 (10.7) 12.64 (<.0001) −1.48
PROMIS Indicates Patient-Reported Outcome Measurement Information System, SD Half standard deviation, SEM Standard error of the mean
†
Paired t-test
a
Month 3 or month 6
b
Calculated as mean change / SD for baseline score
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 7 of 10
PROMIS Fatigue SF-6a can measure changes in fatigue
and add value in clinical practice and research. This re-
search is an example of how an existing measure can be
assessed for use in a new population. The assessment of
the psychometric properties and responsiveness support
the use of the PROMIS Fatigue SF-6a among women
with moderate-to-severe endometriosis-related pain. The
findings from this research could be used to identify a
responder threshold that would indicate a treatment
benefit among this target sample. Previous research with
different versions of the Short Form of the PROMIS (e.g.
17 item Short form) has suggested a change of 3–5
points to indicate a responder [38].
A strength of this study is that the data were from a
large randomized, controlled trial and were therefore of
high quality. At the same time, the results may not be
generalizable outside of the selected population, which
may have a different racial makeup than the overall
population of women in the US with endometriosis, or
to women with more mild endometriosis-associated
pain. In addition, the results may not be generalizable to
other PROMIS Fatigue measures for this population or
to the use of PROMS Fatigue SF-6a in other women’s
health conditions.
Conclusion
In conclusion, this study showed that PROMIS Fatigue
SF-6a performs well in women with moderate-to-severe
endometriosis-related pain, with good reliability, validity,
and responsiveness to change. The study also confirmed
that fatigue is a common and severe problem in women
with endometriosis, highlighting the need for a high-
quality instrument for assessing fatigue as a treatment
outcome in this population.
Abbreviations
EHP-30: Endometriosis Health Profile-30; HRPQ: Health Related Productivity
Questionnaire; LS: Least-squares; NMPP: Non-menstrual pelvic pain;
PGIC: Patient Global Impression of Change; Proc GLM: General linear models;
PROMIS: Patient-Reported Outcome Measurement Information System;
RMSEA: Root mean square error of approximation; SD: Standard deviation;
SEM: Standard error of the mean; SF-6a: ROMIS Fatigue Short Form 6a
Acknowledgments
Medical writing was provided by Phillip S. Leventhal, PhD and Stephen
Gilliver, PhD (Evidera) and paid for by AbbVie. AbbVie, Inc. funded the study
and participated in the study design, research, analysis, data collection,
interpretation of data, reviewing, and approval of the publication.
Authors’contributions
In accordance with ICMJE guidelines all authors made substantive
intellectual contributions to this manuscript. RP and KSC contributed to the
analytic design, analysis, interpretation, and reporting of the data. AMS, MCS
and ES contributed to the trial design, acquisition of the data, and
interpretation of the data. The author(s) read and approved the final
manuscript.
Funding
This study was funded by AbbVie, Inc. AbbVie sponsored the study;
contributed to the design; participated in collection, analysis, and
interpretation of data; and participated in in writing, reviewing, and approval
of the final version. No honoraria or payments were made for authorship.
Availability of data and materials
AbbVie is committed to responsible data sharing regarding the clinical trials
we sponsor. This includes access to anonymized, individual and trial-level
data (analysis data sets), as well as other information (e.g., protocols and Clin-
ical Study Reports), as long as the trials are not part of an ongoing or
planned regulatory submission. This includes requests for clinical trial data
for unlicensed products and indications.
Fig. 1 Clinically Relevant Responsiveness for PROMIS Fatigue Short Form 6a Change for Dysmenorrhea and NMPP Responders at Month 3 and
Month 6. LS-mean indicates least-squares mean; NMPP, non-menstrual pelvic pain; PROMIS, Patient-Reported Outcome Measurement Information
System; SE, standard error. * Pvalue between responder and non-responder is p< 0.0001
Pokrzywinski et al. Journal of Patient-Reported Outcomes (2020) 4:86 Page 8 of 10
This clinical trial data can be requested by any qualified researchers who
engage in rigorous, independent scientific research, and will be provided
following review and approval of a research proposal and Statistical Analysis
Plan (SAP) and execution of a Data Sharing Agreement (DSA). Data requests
can be submitted at any time and the data will be accessible for 12 months,
with possible extensions considered. For more information on the process,
or to submit a request, visit the following link: https://www.abbvie.com/our-
science/clinical-trials/clinical-trials-data-and-information-sharing/data-and-
information-sharing-with-qualified-researchers.html
Ethics approval and consent to participate
The studies were conducted in accordance with the Declaration of Helsinki,
local independent ethics committee/institutional review board requirements,
and good clinical practice guidelines. Shulman Associates IRB conducted the
majority of the IRB approvals (M12–665 IRB approval number 201202559
approval date April 11, 2012; M12–671 IRB approval number 201208471,
approval date on November 16, 2012). Informed consent was obtained from
all individual participants included in the study. AbbVie is committed to
responsible data sharing regarding the clinical trials we sponsor. This
includes access to anonymized, individual and trial-level data (analysis data
sets), as well as other information (e.g., protocols and Clinical Study Reports),
as long as the trials are not part of an ongoing or planned regulatory sub-
mission. This includes requests for clinical trial data for unlicensed products
and indications.
Consent for publication
Not applicable.
Competing interests
A. Soliman and M. Snabes are employees of and own stock/stock options in
AbbVie. R. Pokrzywinski and KS. Coyne are employees of Evidera, who were
paid consultants to AbbVie in connection with this study. Eric Surrey is
Medical Director at Colorado Center for Reproductive Medicine, has served
in a consulting role for AbbVie and DOT Laboratories, received research
grants from AbbVie, and served on the speaker bureau for AbbVie and
Ferring Laboratories. Evidera received funding from AbbVie to conduct the
study and for medical writing.
Author details
1
Evidera Inc., 7101 Wisconsin Ave., Suite 1400, Bethesda, MD 20814, USA.
2
AbbVie Inc., North Chicago, IL, USA.
3
Colorado Center for Reproductive
Medicine, Lone Tree, CO, USA.
Received: 9 March 2020 Accepted: 13 October 2020
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