Download Validation and real-world assessment of the Functional

Support Care Cancer (2015) 23:2341–2347
DOI 10.1007/s00520-015-2606-z
ORIGINAL ARTICLE
Validation and real-world assessment of the Functional
Assessment of Anorexia-Cachexia Therapy (FAACT) scale
in patients with advanced non-small cell lung cancer
and the cancer anorexia-cachexia syndrome (CACS)
Thomas W. LeBlanc & Greg P. Samsa & Steven P. Wolf &
Susan C. Locke & David F. Cella & Amy P. Abernethy
Received: 6 November 2014 / Accepted: 5 January 2015 / Published online: 14 January 2015
# Springer-Verlag Berlin Heidelberg 2015
Abstract
Purpose Patients with cancer anorexia-cachexia syndrome
(CACS) suffer a significant symptom burden, impaired quality of life (QoL), and shorter survival. Measurement of QoL
impairments related to CACS is thereby important both in
clinical practice and in research. We aimed to further validate
the Functional Assessment of Anorexia-Cachexia Therapy
(FAACT) scale in an advanced lung cancer population.
Methods We tested the performance of the FAACT and its
anorexia-cachexia subscale (ACS) within a dataset of patients
This work was funded in part by a research grant from Helsinn to Duke
University Medical Center.
T. W. LeBlanc : A. P. Abernethy
Duke Cancer Institute, Duke University School of Medicine,
Durham, NC 27710, USA
T. W. LeBlanc : G. P. Samsa : S. P. Wolf : S. C. Locke :
A. P. Abernethy
Center for Learning Health Care, Duke Clinical Research Institute,
Durham, NC 27710, USA
T. W. LeBlanc
Division of Hematologic Malignancies and Cellular Therapy,
Department of Medicine, Duke University School of Medicine,
Durham, NC 27710, USA
D. F. Cella
Department of Medical Social Sciences, Northwestern University
Feinberg School of Medicine, Chicago, IL 60611, USA
A. P. Abernethy
Division of Medical Oncology, Department of Medicine, Duke
University School of Medicine, Durham, NC 27710, USA
T. W. LeBlanc (*)
2400 Pratt Street, Suite 9000, Durham, NC 27705, USA
e-mail: [email protected]
with advanced non-small cell lung cancer (aNSCLC), using
standard statistical methods. We then compared the performance of commonly used QoL measures stratified by CACS
status and by patient self-report of appetite and weight loss.
Results The FAACT and its ACS demonstrate internal validity consistent with acceptable published ranges for other QoL
scales (Cronbach alpha=0.9 and 0.79, respectively). Correlation coefficients demonstrate moderate correlations in the expected directions between FAACT and ACS and scales that
measure related constructs. Comparing patients with and without CACS, the ACS is more sensitive to change than other
QoL instruments (mean score 33.1 vs. 37.2, p=0.011, ES=
0.58).
Conclusion In patients with aNSCLC, the FAACT and its
ACS performed well compared with other instruments, further
supporting their validity and value in clinical research.
FAACT and ACS scores covaried with symptoms and other
QoL changes that are typical hallmarks of CACS, lending
further support to their use as QoL endpoints in clinical trials
among patients with CACS.
Keywords Cancer anorexia cachexia syndrome . Quality of
life instruments . Validity
Introduction
Patients with advanced lung cancer often experience anorexia
(i.e., the subjective sense of poor appetite) and cachexia (i.e.,
the physiologic state of muscle catabolism and weight loss)
[1]. These often occur together and constitute the “cancer
anorexia-cachexia syndrome” or CACS [2, 3]. In an effort to
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promote standardization, a 2011 international consensus defined CACS, as “weight loss greater than 5 %, or weight loss
greater than 2 % in individuals already showing depletion
according to current bodyweight and height (body-mass index
<20 kg/m2) or skeletal muscle mass (sarcopenia) [4].” We
have previously shown that when using these criteria, patients
with overt CACS suffer a significant burden of symptoms,
marked impairments in quality of life (QoL) [5], and shorter
overall survival [6]. The measurement of QoL impairments
related to CACS is therefore important both in clinical practice
and in research efforts [7] that seek to improve patients’ lived
experience with advanced lung cancer.
The Functional Assessment of Cancer Therapy
(FACT) is a family of scales designed to measure
health-related QoL and is among the best-validated set
of instruments developed for use specifically among patients with cancer [8]. The FACT family is organized
around the FACT-General (FACT-G) core instrument
and its four subscales: physical well-being, emotional
well-being, functional well-being, and social well-being.
Often, the FACT-G is combined with additional subscales that include additional items of relevance to particular clinical contexts. For patients with lung cancer,
for example, there is a “lung cancer subscale” (LCS);
when scored together with the FACT-G, this yields the
FACT-L [9]. Similarly, there is an anorexia and cachexia
subscale (ACS) [10]. When combined with the FACT-G,
this yields the Functional Assessment of AnorexiaCachexia Therapy (FAACT). While these scales are purported to capture important domains of health-related
QoL among patients with cancer, some questions have
been posed about the utility and validity of the FAACT
scale [11].
The FACT-L has been extensively validated among
patients with lung cancer. For example, a review article
published in 2005 references 25 papers from 15 data
sets including over 4000 patients [12]. Additional evidence has accumulated since then. The FAACT has also
been widely studied, yet many validation studies do not
report the proportion of patients with lung cancer and
questions have emerged about whether the FAACT captures relevant domains regarding the psychosocial impact of cancer cachexia on patients’ experiences [11].
Furthermore, to our knowledge, none of these validation
studies applied the recent consensus-based CACS definition to explore the performance of the FAACT scale
among patients with overt cancer cachexia.
Since the FAACT and its anorexia-cachexia subscale
(ACS) are important markers of QoL in patients with advanced lung cancer and CACS, we sought to further explore
their performance specifically in this population. This validation effort is unique for three reasons: (1) its exclusive focus
on patients with advanced lung cancer, (2) the application of
Support Care Cancer (2015) 23:2341–2347
the recent international consensus definition of CACS to stratify the sample, and (3) the comparative performance of
FAACT with other instruments vis-à-vis responsiveness to
symptoms and clinical anchors.
Methods
Design and participants
From December 2007 through 2008, we screened patients in
the Duke Oncology clinics who had a confirmed diagnosis of
stage IIIB or stage IV non-small cell lung cancer. Eligible
subjects were English-speaking, able to provide informed
consent, and receiving cancer care at Duke University Medical Center. Ninety-nine patients were enrolled, and 97 patients
completed at least the first study visit. The study was aimed at
providing a broad understanding of the longitudinal experience of patients with advanced non-small cell lung cancer
(aNSCLC) including their symptom burden, quality of life,
physical function, and overall well-being [13].
Patients completed up to 4 study visits, in accordance
with their scheduled routine outpatient cancer care. At
each visit, they were asked to complete a battery of
electronic patient-reported assessments including a detailed review of symptoms via the Patient Care Monitor
version 2.0 and a quality of life assessment by several
of the FACT questionnaires (including the FAACT and
its anorexia-cachexia subscale). For this analysis, we
utilized data only from the first visit, to maximize the
available sample size, and to avoid bias due to nonrandom missingness of data at subsequent visits.
We also grouped patients based on the weight-based
international consensus CACS definition. Most patients
had available weight data at 30, 60, 90, and 180 days
prior to the first study visit. They were categorized as
having CACS if adequate weight loss occurred within
the 6 months prior to enrollment or as not having
CACS if weight loss had not occurred during this period. Those with incomplete weight data who nevertheless
clearly had at least 5 % weight loss were counted as
meeting CACS criteria. Those with incomplete weight
data who did not clearly lose over 5 % of their weight
were considered as having an uncertain CACS classification and were excluded from analysis to minimize
bias. Twenty-six patients were definitively identified as
having CACS, 53 were definitively identified as not
having CACS, and 18 had uncertain CACS status. These 18 patients could not be reliably categorized, as their
weight data were not available for the 6 months prior to
enrollment in the study. Therefore, data from 79 patients
were included in the analysis.
Support Care Cancer (2015) 23:2341–2347
Data elements
The Patient Care Monitor Version 2.0 (PCM) is an instrument
that primarily focuses on physical symptoms for patients with
cancer [14]. Among its items (80 for males, 86 with females)
are some that closely correspond to the symptom-based items
used in the FAACT. Each item is scored on a 0–10 scale;
higher scores are associated with more severe symptoms.
The PCM can also generate 6 summated subscales (i.e., despair, distress, impaired ambulation, impaired performance,
general physical symptoms, and treatment side effects), which
we used as comparators in our analyses here.
The Functional Assessment of Cancer Therapy-General
(FACT-G) is a summated score of 27 items pertaining to physical well-being (7 items), emotional well-being (6 items), functional well-being (7 items), and social well-being (7 items).
Each of the items uses a 5-point (0 to 4) scale. The FACT-G
is typically used as a primary measure of general health status
among patients with cancer, with its 4 subscales sometimes
(albeit not always) used to provide additional detail. Higher
scores are associated with better health-related quality of life.
The lung cancer subscale (LCS) is a 9-item summated scale
containing items specific to lung cancer (only 7 of these items
are scored, however). Each item uses the same 5-point scale as
above. Adding the 9 LCS items to the FACT-G produces the
36-item FACT-L. The Anorexia-Cachexia Subscale (ACS) is
a 12-item summated scale containing items specific to patients’ perceptions of appetite and weight, also using the 5point scale. Adding the 12 ACS items to the FACT-G produces the 39-item Functional Assessment of AnorexiaCachexia Therapy (FAACT). Higher scores are associated
with a higher QoL.
Statistical analysis
Patient characteristics were summarized using routine
descriptive statistics. We then applied a multifaceted approach to instrument validation, combining traditional
methods as follows. First, we assessed internal consistency with standardized Cronbach alpha coefficients.
Next, we assessed convergent and divergent validity
by calculating bivariate correlation coefficients between
the FAACT (including the ACS), various versions of the
FACT, and also the 6 subscales of the PCM. We divided patients into subgroups and compared their various
summary scores to examine convergent and divergent
validity, and used independent t tests to compare mean
differences. For example, when comparing CACS and
non-CACS patients, we expected a greater difference
(in effect size comparisons) in the FAACT than in the
other measures. Effect sizes were determined so that the
group differences on the different scales could be easily
compared using a common scale. Similarly, we repeated
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this comparison after dividing patients by their selfreport of weight loss, obtained from the PCM questionnaire. We repeated this comparison using patients’ selfreport of poor appetite, as well.
Results
Descriptive analysis
Table 1 presents selected demographic and clinical characteristics of the patient population at baseline. Most patients were
under the age of 65 (53 %), male (63 %), married (68 %), and
Caucasian (78 %), with at least some college education
(58 %). Of particular note is the distribution of functional
status; 49 % had Karnofsky performance status (KPS) ratings
of 80 and above. Patients with CACS, however, had lower
(worse) KPS scores than those without CACS; this was expected given the known association between cancer cachexia,
loss of lean body mass, and declining physical function. At
enrollment, 35 % of CACS patients were receiving chemotherapy, compared to 45 % of control patients (P=0.47).
Table 2 presents descriptive statistics for various scales
derived from the FACT and the PCM. Of particular note is
that the largest separation between the CACS and non-CACS
group means occurs for the anorexia-cachexia specific (ACS)
subscale of the FAACT (effect size=0.58). This suggests that
among the instruments compared, the ACS-12 is uniquely
suited to distinguish patients divided into those with or without CACS. There were no other statistically significant differences between the CACS and non-CACS groups for any of
the other scales. Comparison of effect sizes also suggests a
trend in differences between the PCM scales for despair (P=
0.12, ES=0.46) and distress (P=0.11, ES=0.38) among the
CACS vs. non-CACS groups.
Internal consistency
Table 3 presents standardized Cronbach alpha coefficients,
which quantify the internal consistency of the various scales
within the FACT family. Coefficients were 0.79 and 0.90 for
the ACS and the FAACT total, respectively. This is consistent
with, even exceeding, values present in other published literature [10]. The other alpha coefficients are included to facilitate comparison to other published values.
Correlations
Table 4 presents correlations between the FAACT and various
scales from the FACT and PCM. As anticipated, these correlations are of moderate magnitude (mostly ranging from about
0.3 to 0.6) and in the anticipated direction (note that high
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Support Care Cancer (2015) 23:2341–2347
scores are bad for the PCM and good for the FACT scales;
thus, the correlations between the two instruments are expected to be negative). None of the correlations were adjusted for
overlapping items. This explains the value of 0.96 between the
FAACT and FACT-G, since the former contains all the items
from the latter, plus the 12 additional ACS items.
We also expected to see correlation among scales that measure related concepts, and there is indeed evidence of at least
moderate correlation in several items that one would expect to
be related. For example, the ACS correlates moderately with
the FACT-functional subscale (0.35) and the FACT-physical
subscale (0.54), as does the FAACT (at 0.85 and 0.62, respectively). Patients with CACS are known to have worse function
and significant physical symptoms. Thus, if ACS and FAACT
track with CACS status, they should also be at least moderately correlated with the FACT subscales that measure function and physical symptoms (such as fatigue). This is indeed
what we found. Similarly, we would expect to see less correlation among items that are not directly related. For example,
there is no evidence of appreciable correlation between the
ACS and FACT-social (coefficient=0.06). The ACS focuses
on specific questions about appetite, weight, food intake,
Table 1 Patient characteristics at
baseline
Age under 65 years
Female gender
Marital status
Married
Widowed/divorced/separated
Single
Education
Less than high school
High school graduate
Some college
College graduate
Ethnicity
White/Caucasian
Black/African-American
Chinese
Korean
Spanish/Hispanic/Latino
Ever smoked
Currently smoke
Karnofsky performance status
50 %
60 %
70 %
80 %
90 %
Receiving chemotherapy
physical appearance, interest in food, vomiting, early satiety,
and pain. To the contrary, the FACT-social subscale focuses
on relationships and closeness with friends and family, along
with support derived from these relationships, so it makes
sense that these would be essentially uncorrelated.
Symptom-based grouping
Tables 5 and 6 present additional analyses based on patientreported symptoms from the PCM that we expected to correlate
with items measured in the FAACT and ACS scales. We
grouped patients based on their responses to the two specific
PCM questions about weight loss and appetite. The PCM items
for weight loss (Table 5) and appetite loss (Table 6) were classified into “no problem” or “some problem,” based on whether
the score for the item in question exceeded 0. This served to
divide the sample into approximately equal halves. Grouping
patients by the PCM item pertaining to weight loss (Table 5),
the ACS was one of the two most sensitive instruments (the
other being the PCM treatment side effects scale). Similarly,
dividing the patients by the PCM item pertaining to appetite
(Table 6), the ACS was again the most sensitive instrument.
CACS (n=26)
Non-CACS (n=53)
Overall (n=79)
P
46.2 % (12)
42.3 % (11)
56.6 % (30)
34.0 % (18)
53.2 % (42)
36.7 % (29)
0.38
0.47
0.65
73.1 % (19)
23.1 % (6)
3.8 % (1)
66.0 % (35)
24.5 % (13)
9.4 % (5)
68.4 % (54)
24.1 % (19)
7.6 % (6)
30.8
15.4
30.8
23.1
11.5 % (6)
28.8 % (15)
36.5 % (19)
23.1 % (12)
17.9
24.4
34.6
23.1
69.2 % (18)
23.1 % (6)
3.8 % (1)
0.0 % (0)
3.8 % (1)
88.5 % (23)
83.0 % (44)
15.1 % (8)
0.0 % (0)
1.9 % (1)
0.0 % (0)
84.9 % (45)
78.5 % (62)
17.7 % (14)
1.3 % (1)
1.3 % (1)
1.3 % (2)
86.1 % (68)
21.7 % (5)
13.6 % (6)
16.4 % (11)
3.8 % (1)
46.2 % (12)
23.1 % (6)
19.2 % (5)
7.7 % (2)
34.6 % (9)
0.0 % (0)
9.6 % (5)
30.8 % (16)
38.5 % (20)
21.2 % (11)
45.3 % (24)
1.3 % (1)
21.8 % (17)
28.2 % (22)
32.1 % (25)
16.7 % (13)
41.8 % (33)
0.17
% (8)
% (4)
% (8)
% (6)
% (14)
% (19)
% (27)
% (18)
0.23
0.67
0.40
0.002
0.47
Support Care Cancer (2015) 23:2341–2347
Table 2
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Means (standard deviation) of the symptom and quality of life instruments by CACS category, at baseline
Instrument
CACS (n=26)
Non-CACS (n=53)
Total (n=79)
P
Effect sizea
ACS
FAACT total score
FACT-social
FACT-emotional
FACT-physical
FACT-functional
FACT-G total score
LCS
FACT-L
PCM despair
PCM distress
PCM impaired ambulation
PCM impaired performance
PCM general physical symptoms
PCM treatment side effects
33.1 (7.7)
111.0 (17.4)
21.4 (6.1)
19.4 (4.1)
20.5 (5.3)
15.2 (6.3)
76.5 (14.3)
18.2 (4.7)
95.1 (17.0)
3.2 (5.0)
3.9 (6.5)
4.2 (6.2)
14.4 (12.7)
20.0 (13.2)
12.1 (8.4)
37.2 (6.5)
113.7 (20.9)
21.2 (5.5)
18.6 (5.0)
21.4 (4.4)
15.3 (6.7)
76.5 (17.0)
19.0 (3.9)
95.5 (20.1)
9.1 (15.0)
7.1 (9.1)
3.8 (6.1)
13.1 (10.0)
22.7 (14.2)
12.0 (9.2)
35.9 (7.1)
112.5 (19.8)
21.3 (5.7)
18.8 (4.7)
21.1 (4.7)
15.3 (6.5)
76.5 (16.0)
18.8 (4.2)
95.4 (19.0)
7.2 (12.9)
6.0 (8.4)
3.9 (6.1)
13.5 (10.8)
21.8 (13.8)
12.1 (8.9)
0.011
0.399
0.77
0.66
0.57
0.88
0.80
0.55
0.85
0.12
0.11
0.84
0.84
0.43
0.78
0.58
0.14
−0.04
−0.17
0.19
0.02
0.00
0.19
0.02
0.46
0.38
−0.07
−0.12
0.20
−0.01
a
Effect size was calculated as (non-CACS mean–CACS mean)/SD of total sample
Italicized numbers denote statistical significance at a threshold of p<0.05
Discussion
Patients with advanced non-small cell lung cancer face a significant symptom burden and many such patients will develop
overt CACS. While QoL assessment is an increasingly standard and important approach, assessment of QoL in the context of CACS is less established as a meaningful endpoint in
clinical trials. Amidst recent positive interventional drug trials
aimed at improving CACS [15], our efforts to further validate
the FAACT and ACS in a lung cancer population, stratified by
CACS status, are timely.
The FACT family contains several well-validated instruments that are relevant to patients with advanced lung cancer;
however, some questions have been posed about the validity
of the FAACT scale and the ACS [11]. As such, we explored
the cross-sectional validity of these scales. Our findings are
Table 3
Cronbach’s alpha coefficients (standardized)
Module
Standardized alpha
ACS (12-item anorexia and cachexia subscale)
FAACT (ACS+FACT-G)
FACT-G emotional well-being (6 item subscale)
FACT-G functional well-being (7 item subscale)
FACT-G physical well-being (7 item subscale)
FACT-G family/social well-being (7 item subscale)
FACT-G (27 item base FACT scale)
LCS (9-item lung cancer subscale; only 7 items
are scored)
FACT-L (LCS+FACT-G)
0.79
0.90
0.84
0.87
0.78
0.87
0.90
0.49
0.91
encouraging—both scales demonstrate reasonable degrees of
internal consistency, convergent validity, and divergent validity, consistent with those of the other FACT family of instruments. These results, when combined with the extensive validation of the FACT instruments outside the current context,
provide reassurance about applying the FAACT and the ACS
to patients with advanced lung cancer.
Furthermore, by stratifying patients according to CACS
status, we were able to test the ability of the FAACT scale
and the ACS to detect meaningful differences known to exist
among patients suffering with CACS (such as weight, appetite, and physical function, each of which is assessed through
specific items in these scales). Our findings, highlighted in
Table 2, suggest that the ACS tracks nicely with CACS status,
being the only QoL measure in this analysis that was significantly different between the two groups. It is important to
explicitly point out that we defined CACS by objective weight
loss prior to study enrollment, whereas QoL was patient-reported. As such, these differences in ACS scores among
CACS patients suggest that they were indeed aware of the
weight, appetite, and functional considerations that define
the syndrome. Our prior analyses of differences in survival,
function, and symptoms among these patients lend further
support to the notion that the two groups used in this analysis
are quite meaningfully different [6] and are thus an appropriate validation set for these scales.
Similarly, when we grouped patients by their responses to
the PCM questions about appetite and weight loss (Tables 5
and 6), again there were significant differences in the ACS and
FAACT scores by group. These differences are of sufficient
magnitude to reach clinical significance as well. This suggests
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Support Care Cancer (2015) 23:2341–2347
Table 4 Correlation coefficients of the ACS and FAACT with the
various FACT and PCM Scales at baseline
ACS
FAACT
FACT-social
FACT-emotional
FACT-physical
FACT-functional
0.06
0.33
0.54
0.35
0.56
0.74
0.62
0.85
FACT-G
LCS
FACT-L
PCM despair
PCM distress
PCM impaired ambulation
PCM impaired performance
PCM general physical symptoms
PCM treatment side effects
0.41
0.55
0.47
−0.34
−0.29
−0.41
−0.31
−0.34
−0.45
0.96a
0.76
0.97a
−0.60
−0.52
−0.48
−0.45
−0.55
−0.29
Table 6 Means (standard deviation) of the symptom and quality of life
instruments by response to the PCM decreased appetite question at
baseline
Instrument
a
Since the FAACT includes all items from the FACT-G, plus 12 additional questions from the ACS, and the FACT-L includes all items from
the FACT-G, plus 9 additional questions from the LCS, a high correlation
among these items is expected
that the FAACT and ACS appropriately measure appetite,
weight, or related constructs. Of further interest is the observation that a few additional QoL scales also differed based on
responses to these PCM questions, including the FACTphysical subscale and the LCS (when grouped by the PCM
weight responses), and the FACT-physical, FACT-functional,
FACT-G, LCS, and FACT-L (when grouped by PCM appetite
responses). These associations between physical and functional subscale changes along with changes in ACS and FAACT
lend further support to the notion that the ACS and FAACT
indeed track along with other QoL changes that we should
Table 5 Means (standard
deviation) of the symptom and
quality of life instruments by
response to the PCM weight loss
question at baseline
Italicized numbers denote
statistical significance at a
threshold of p<0.05
No decrease in Decreased
appetite
appetite
(n=53)
(n=26)
P
ACS
37.7 (7.2)
32.3 (5.5)
0.0001
FAACT
FACT-social
FACT-emotional
FACT-physical
FACT-functional
FACT-G
LCS
FACT-L
PCM despair
PCM distress
PCM impaired ambulation
PCM impaired performance
PCM general physical symptoms
PCM treatment side effects
116.8 (20.6)
21.0 (6.0)
19.3 (4.6)
22.2 (4.5)
16.2 (6.9)
78.8 (16.9)
19.7 (4.2)
98.8 (20.0)
6.0 (12.2)
5.2 (8.0)
2.3 (4.1)
10.7 (9.5)
18.9 (11.3)
9.9 (7.0)
104.1 (14.9)
21.7 (5.1)
17.8 (4.8)
18.9 (4.5)
13.4 (5.2)
71.8 (13.1)
17.0 (3.6)
88.8 (15.1)
9.5 (14.2)
7.6 (9.3)
7.2 (7.9)
19.2 (11.1)
27.8 (16.7)
16.4 (10.7)
0.002
0.68
0.14
0.001
0.043
0.015
0.009
0.007
0.12
0.20
0.001
0.002
0.024
0.004
Italicized numbers denote statistical significance at a threshold of p<0.05
expect to find among patients with CACS. While these differences are statistically significant, however, it is worth noting
that several of them do not reach clinical significance at published minimally interpretable difference levels for these
scales, whereas the differences noted in ACS and FAACT
are all clinically significant.
There are a few limitations to our approach. While this study
yielded broad and deep data about the experience of patients
with aNSCLC, the relatively small sample size limited our
Instrument
No weight loss (n=52)
Weight loss (n=27)
P
ACS
FAACT
FACT-social
FACT-emotional
FACT-physical
FACT-functional
FACT-G
38.3 (5.4)
115.8 (19.3)
20.5 (5.9)
19.3 (4.5)
21.8 (4.7)
15.7 (7.0)
77.3 (16.9)
31.4 (7.9)
106.4 (19.5)
22.7 (4.9)
18.0 (5.0)
19.7 (4.4)
14.5 (5.6)
75.0 (14.5)
0.0001
0.040
0.07
0.33
0.027
0.38
0.36
LCS
FACT-L
PCM despair
PCM distress
PCM impaired ambulation
PCM impaired performance
PCM general physical symptoms
PCM treatment side effects
19.7 (4.0)
97.2 (19.9)
6.1 (11.4)
5.3 (7.3)
3.2 (5.4)
12.6 (10.5)
19.9 (12.6)
9.5 (7.0)
17.1 (4.0)
92.1 (17.0)
9.2 (15.5)
7.4 (10.4)
5.4 (7.1)
15.3 (11.3)
25.4 (15.5)
17.0 (10.2)
0.018
0.14
0.59
0.88
0.10
0.33
0.15
0.0002
Support Care Cancer (2015) 23:2341–2347
ability to detect significant differences between subsets of patients. As such, a larger study might yield additional insights
about the performance of the FAACT and the ACS across the
spectrum of those patients with or without CACS. This may
explain why we did not see more striking QoL differences by
CACS status. In addition, our ability to use all 97 patients was
limited by the absence of weight data for some subjects prior to
enrollment; this resulted in 18 patients who we could not classify by CACS status and were excluded from analysis. A larger
sample size may have yielded additional findings.
In conclusion, in a population of patients with aNSCLC, the
ACS and FAACT demonstrate many hallmarks of instrument
validity including good internal consistency, convergent validity, and divergent validity. Furthermore, when analyzed by patients’ CACS status, the ACS in particular appears to perform
well in its ability to discriminate between groups. The performance of the ACS and FAACT in this analysis suggests that
they track nicely with symptoms and other QoL changes that
are typical hallmarks of CACS including weakness, poor appetite, weight loss, and declining physical function. These results lend further support to the notion that the ACS or FAACT
are valid QoL endpoints for patients with CACS.
Acknowledgments Dr. Abernethy reports personal fees (as ownership
or employment) from Advoset, Orange Leaf Associates, Athena Health
and Flatiron Health, Inc. Grants from Alliance for Clinical Trials in Oncology, American Cancer Society, Bristol-Myers Squibb, Celgene,
DARA, Denderon, GlaxoSmithKline, Helsinn Healthcare, Helsinn Therapeutics, Kanglaite, Mayo Clinic, Medical College of Wisconsin, Memorial Sloan Kettering Cancer Center, Pfizer, University of North Carolina at
Chapel HIll, University of South Florida and federal grants from NIH,
National Cancer Institute, AHRA, National Institute for Nursing Research, National Institutes on Aging; personal fees from American Academy of Hospice and Palliative Medicine (as immediate past president),
Pfizer, and ACORN Research. Dr. LeBlanc is a recipient of a Junior
Career Development Award from the National Palliative Care Research
Center (NPCRC), has received research support (paid to Duke University
Medical Center) from Celgene and Helsinn Therapeutics, and honoraria
from Helsinn (<$5000). The authors acknowledge the editorial assistance
of Donald T. Kirkendall, ELS, a Duke-employed medical editor.
Conflicts of interest The remaining co-authors have no disclosures or
conflicts of interest to report.
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