1. Critical Reviews in Oncology/Hematology 99 (2016) 37–48
Contents lists available at ScienceDirect
Critical Reviews in Oncology/Hematology
journal homepage: www.elsevier.com/locate/critrevonc
A systematic literature review of the economic implications of
chemotherapy-induced diarrhea and its impact on quality of life
Rosanna Tarriconea,b
, Dana Abu Kousha
, Barbara Nyanzi-Wakholic
,
Antonieta Medina-Laraa,d,∗
a
Centre for Research on Health and Social Care Management (CERGAS), Bocconi University, Milan, Italy
b
Department of Policy Analysis and Public Management, Bocconi University, Milan, Italy
c
Independent Consultant, Kampala, Uganda
d
Health Economics Group, University of Exeter Medical School, Exeter, UK
Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.1. Identification of studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.2. Inclusion and exclusion criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.3. Critical appraisal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38
3. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38
3.1. HRQoL studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.2. Classification of studies included . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.3. Critical appraisal of primary studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.4. Findings from primary research studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.5. Findings from healthcare resource utilization studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44
4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47
Search criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Biography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
a r t i c l e i n f o
Article history:
Received 16 April 2015
Received in revised form
22 December 2015
Accepted 22 December 2015
Keywords:
Chemotherapy-induced diarrhea
Incidence
Health-related quality of life
Healthcare resource utilization
a b s t r a c t
Introduction: Chemotherapy-induced diarrhea (CID) diminishes physical performance, raises anxiety and
depression levels, and increases healthcare resource utilization.
Objective: To understand the impact that CID has on health-related quality of life (HRQoL) and on health-
care resource utilization.
Methods: Systematic searches were conducted in MEDLINE, EMBASE, DARE, and the NHS EED databases.
Results: A total of 22 articles were retrieved for full review (n = 17, HRQoL; n = 5 healthcare resource utiliza-
tion). Only 2 studies had assessed HRQoL in patients experiencing CID, while cost studies demonstrated
that CID episodes are unnecessarily expensive and can be avoided if diagnosed and treated early.
Conclusions: Better management of CID has the potential to reduce overall economic burden and improve
patients’ HRQoL. Available evidence also relays the need to conduct larger studies that assess HRQoL and
consider cost beyond direct medical costs in order to understand the full impact of CID on HRQoL and
healthcare resource utilization.
Crown Copyright © 2016 Published by Elsevier Ireland Ltd. All rights reserved.
∗ Corresponding author at: Health Economics Group, University of Exeter Medical School, Veysey Building, Salmon Pool Lane, Exeter EX2 4SG, UK.
E-mail address: A.Medina-Lara@exeter.ac.uk (A. Medina-Lara).
http://dx.doi.org/10.1016/j.critrevonc.2015.12.012
1040-8428/Crown Copyright © 2016 Published by Elsevier Ireland Ltd. All rights reserved.

2. 38 R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48
1. Introduction
Patients suffering from cancer also report experiencing diar-
rhea. Diarrhea can occur due to radiotherapy, chemotherapeutic
agents, and infections (Stein et al., 2010). Chemotherapy-induced
diarrhea (CID) symptoms include fever, excessive thirst, dizziness,
abdominal cramps, watery stool, bloody stool, and refractory diar-
rhea (Stein et al., 2010). It can also result in dehydration, electrolyte
imbalance, and even death (Maroun et al., 2007; Zachariah et al.,
2010). The worldwide incidence of CID has been reported to be
50%–80% (Benson et al., 2004; Gibson and Stringer, 2009). Episodes
of CID can lead to dose delays, dose reductions, decrease in dose
density, and in some cases, dose discontinuation, all of which
reduce the effectiveness of chemotherapy, leading to worse patient
health outcomes (Zachariah et al., 2010; Arbuckle et al., 2000;
Citron et al., 2003; Arnold et al., 2005).
In the late 1990s, the lack of agreement among oncologists on
the most effective way to treat individuals suffering from CID moti-
vated the development of evidence-based diagnostic and treatment
guidelines. The guidelines were based on clinical evidence from
published trials and unpublished data, and included recommenda-
tions to accurately assess diarrhea, type of pharmacologic agents
(sequence, dose, duration of administration), and type of care
needed by the patients (Wadler et al., 1998). The tool used for
assessing the severity of CID was developed by the National Cancer
Institute (NCI) and is known as the Common Terminology Criteria
(CTC). This tool has several limitations, as it does not consider fac-
tors such as the onset and duration of diarrhea, stool volume and
consistency, current medication, dietary and fluid intake, weight
loss, and the site and stage of cancer (Kornblau et al., 2000; Cope,
2001). Another common criticism of the CTC tool is that diarrhea
diagnosis should be based on the pretreatment baseline bowel
movement of the individual, which is of critical importance for CID
assessment and treatment (Saltz, 2003). A more recent CID clinical
review also reinforced the need for a more comprehensive instru-
ment for assessing CID in which risk factors are also considered
(Richardson and Dobish, 2007).
In the clinical review by Richardson and Dobish, one of the rec-
ommendations for improving CID diagnosis and treatment is to
encourage a closer relationship between the oncology nurse and
the patient, in order for the patient to be well-informed and aware
of diarrhea-inducing drugs, tests, symptoms, and treatment. A
second recommendation is weekly assessments by a nurse or physi-
cian in combination with timely patient reporting of CID symptoms
(eg, diarrhea for the first time during treatment, blood in the stool
or around the anal area, or severe abdominal pain or cramping),
which could help the patient in achieving optimal clinical outcomes
(Richardson and Dobish, 2007).
Alongside the clinical impact of CID, the health-related quality
of life (HRQoL) of individuals with CID has been reported to dete-
riorate significantly (Benson et al., 2004). CID raises the levels of
anxiety and depression among patients and limits, or completely
inhibits, their normal activities, including work, travel, and social
interaction (Viele, 2003). Furthermore, it substantially increases
healthcare resource utilization through an increased number of
hospitalization days, emergency department visits, adoption of
palliative treatment, and by increasing the care-giving burden
(Arbuckle et al., 2000; Dranitsaris et al., 2005a; Nonzee et al., 2008).
This systematic literature review considers 2 specific questions:
(1) What is the impact of CID on HRQoL? This question will be
answered by identifying the tools that are used to assess changes
in HRQoL and by determining which aspects of HRQoL are affected;
and (2) What is the impact of CID on healthcare resource utiliza-
tion? This question will be answered by describing which resource
utilization items are the cost drivers in a CID episode.
2. Methods
2.1. Identification of studies
The principles of the preferred reporting items for systematic
reviews and meta-analyses (PRISMA) were employed in this review
(Moher et al., 2009). Searches were conducted in 4 databases:
MEDLINE, EMBASE, the Database of Abstracts of Reviews of Effects
(DARE), and the National Health Service Economic Evaluation
Database (NHS EED). While the searches had an open starting date,
the end date was week 2 of December 2013. The search strate-
gies used for economic studies were specific for EMBASE (McKinlay
et al., 2006) and for MEDLINE (Sassi et al., 2002; Wilczynski et al.,
2004), while a less restricted search was used for the DARE and
NHS EED databases. Since HRQoL studies do not have a published
specific search strategy, the authors adopted the search strate-
gies used in Health Technology Assessment reports published by
the National Institute of Health Research in the United Kingdom
to identify HRQoL studies (Fitzpatrick et al., 1998). The searches
were used in combination with free-text words (chemotherapy
induced diarrhea/diarrhoea and CID). The search strategy is pre-
sented in Appendix A. Limits were only applied to remove animal
studies. The full text of potentially relevant articles was obtained.
Included references were downloaded in Endnote (X6; Thomson
ISI ResearchSoft) and Microsoft Excel 2010 software for further
assessment and handling.
2.2. Inclusion and exclusion criteria
Articles were considered if they were written in English, Ital-
ian, or Spanish. Only studies that elicited patient preferences from
adults (≥18 years old) were considered. Articles were included
if the abstract mentioned a HRQoL measure (generic or specific),
and/or utilities or health states related to CID. Studies that identi-
fied, measured, and valued healthcare resources were also included
and reviewed. All titles and abstracts of citations retrieved by
the searches were screened independently by 2 reviewers; dis-
agreements about inclusion or exclusion were resolved through
consensus.
Details of the study type, study population, chemotherapy drugs
inducing CID, treatments for CID, health outcomes, HRQoL instru-
ments, and parameters of healthcare resources were extracted by
1 reviewer, and verified by a second reviewer; disagreements were
resolved through discussion.
2.3. Critical appraisal
All included studies were assessed for methodologic quality
using Cochrane recommendations and the criteria suggested by the
Centre for Reviews and Dissemination for conducting systematic
reviews in healthcare (Higgins and Green, 2011; Centre for Reviews
and Dissemination, 2009). These criteria were adapted in order to
address the needs of this review and were extracted by 1 reviewer
and checked by a second reviewer; consensus of disagreement was
derived by discussion. Data were synthesized through narrative
review. Results of the quality checks were used for descriptive pur-
poses and transparency of the overall quality of the studies included
in the analysis. The quality checks of studies included in this report
are available upon request.
3. Results
3.1. HRQoL studies
Of the 209 hits obtained, 135 were identified in MEDLINE,
53 in EMBASE, and 21 in DARE and NHS EED databases (Fig. 1

3. R.Tarriconeetal./CriticalReviewsinOncology/Hematology99(2016)37–4839
Table 1a
A Summary of CID primary experimental research studies.
Type of study Author and year Setting Study participants Intervention Comparison HRQoL measure
Randomized controlled
trials
Gourgou-Bourgade
et al. (2013)
Multicenter,
randomized, Phase II/III
trial conducted at 15
centers during Phase II
and expanded to 48
centers during Phase III
342 adults with
metastatic pancreatic
cancer
FOLFIRINOX, which
consisted of oxaliplatin
85 mg/m2
as a 2-h i.v.
infusion immediately
followed by leucovorin
400 mg/m2
administered as a 2-h
i.v. infusion and, after
30 min, with irinotecan
180 mg/m2
as a
90 -min i.v. infusion;
this was followed by a
5-FU 400 mg/m2
i.v.
bolus and then
continuous i.v. infusion
of2400 mg/m2
over
46 h once every 2 wk
Gemcitabine1000
mg/m2
infused weekly
for 7 wk, followed by a
1-wk rest period, and
then once per wk for 3
wk of a 4-wk cycle
EORTC QLQ-C30
Yang et al. (2013) Details of the LUX-Lung
3 trial were not stated
345 patients with
advanced EGFR
mutation-positive lung
adenocarcinoma
Oral afatinib 40 mg
once daily or i.v.
cisplatin 75 mg/m2
every 21 days for up to
6 cycles
Cisplatin 75 mg/m2
or
pemetrexed
500 mg/m2
every 21
days for up to 6 cycles
EORTC QLQ-C30
QLQ-LC13
Lück et al. (2013) Multicenter,
prospective,
randomized, Phase III
noninferiority trial in
63 centers in Europe
340 women between
18 and 75 years of age
with histologically
confirmed, metastatic
breast cancer
Oral
capecitabine1000 mg/m2
twice daily on days
1–14 plus i.v. paclitaxel
175 mg/m2
as a 3-h
infusion on day 1 of a
3-wk cycle
Epirubicin 60 mg/m2
as
a 1-h infusion plus i.v.
paclitaxel 175 mg/m2
as a 3-h infusion, both
on day 1 of a 3-wk
cycle
EORTC QLQ-C30
QLQ-BR23
Ziefle et al. (2011) Prospective,
randomized,
multicenter Phase III
trials conducted in 44
centers in Europe
282 patients with
malignant melanoma
Adjuvant low-dose
treatment with IFN-␣ 3
times/wk for 18 mo
Adjuvant low-dose
treatment with IFN-␣ 3
times/wk for 60 mo
EORTC QLQ-C30
Phase II open-label trial Reynolds et al. (2013) Conducted in the
oncology network of
community-based
oncology practices
60 evaluable elderly
patients (≥70 years of
age) with metastatic
NSCLC
Sunitinib malate
37.5 mg/day orally on
days 1–42 of each
42-day (6-wk) cycle
Not applicable FACT-Ge FACT-L
Phase I trial Toyama et al. (2013) Teaching hospital 94 patients with
pancreatic cancer
Mild dose-intensity
adjuvant
chemotherapy with
biweekly1000 mg/m2
gemcitabine for at least
12 courses (58
patients)
36 patients who
declined the adjuvant
biweekly gemcitabine
chemotherapy
received traditional
adjuvant 5-FU–based
chemotherapy
consisting of a
20-mg/m2
i.v. bolus of
leucovorin followed by
a 400-mg/m2
i.v. bolus
of 5-FU on 5
consecutive days every
28 days for 6 cycles
EORTC QLQ-C30
QLQ-PAN26

4. 40R.Tarriconeetal./CriticalReviewsinOncology/Hematology99(2016)37–48
Table 1a (Continued)
Type of study Author and year Setting Study participants Intervention Comparison HRQoL measure
Cross-sectional study Bentzen et al. (2013) National database of all
patients diagnosed in
with anal squamous
cell carcinoma
between 1/07/2000
and 30/06/2007
treated with curatively
intended
chemoradiotherapy
128 anal cancer
survivors
To investigate the
HRQoL in the
long-term follow-up of
anal cancer survivors
269 volunteers who
were age and sex
matched from the
general population
EORTC QLQ-C30
QLQ-CR29 version 2.1
Prospective studies Kaptein et al. (2013) Outpatient
departments of clinical
oncology
22 Dutch and 21
Japanese patients with
breast cancer
1) To examine illness
perceptions and QoL in
Japanese and Dutch
women with breast
cancer 2) To explore
the potential
differences between
these groups of
patients 3) To
investigate whether
QoL and illness
perceptions changed
during chemotherapy
Not applicable EORTC QLQ-C30
Zabernigg et al. (2012) The Department of
Internal Medicine of
the Kufstein County
Hospital
80 patients with
pancreatic cancer or
cancer of the bile ducts
To analyze and
compare repeated
electronic
patient-reported QoL
and
physical/psychosocial
symptom burden from
adjuvant treatment to
palliative third-line
therapy
Not applicable EORTC QLQ-C30
Tholstrup et al. (2011) Department of
Hematology
26 patients with DLBCL
undergoing dose-dense
chemotherapy
To investigate to what
extent QoL is affected
in patients with DLBCL,
before treatment,
during dose-dense
chemotherapy, and
after its termination
Not applicable EORTC QLQ-C30
Retrospective study Hurmuzlu et al. (2011) Haukeland University
Hospital
21 esophageal cancer
patients undergoing a
potentially curative
treatment between
1996 and 2007
To compare different
aspects of QoL in
esophageal cancer
patients who had
received high-dose
neoadjuvant
chemoradiotherapy
20 consecutive patients
with nonmetastatic
esophageal cancer; 96
patients (≤80 years
old) with head and
neck squamous cell
carcinoma; 104
patients treated with
laryngectomy, and a
random sample of3000
people from the
general Norwegian
population
EORTC QLQ-C30
QLQ-OES18
5-FU, fluorouracil; CID, chemotherapy-induced diarrhea; DLBCL, diffuse large B-cell lymphoma; EGFR, epidermal growth factor receptor; EORTC QLQ-C30, European Organisation for the Research and Treatment of Cancer Quality
of Life Questionnaire; EPIC-Bowel,14-item Expanded Prostate Cancer Index Bowel; FACIT-D, Functional Assessment of Chronic Illness-Diarrhea; FACT-G, Functional Assessment of Cancer Therapy-General; FACT-L, Functional
Assessment of Cancer Therapy-Lung; HRQoL, health-related quality of life; IFN-␣, interferon-␣; i.v., intravenous; QLQ-BR23, EORTC breast cancer-specific quality of life questionnaire; QLQ-CR29, EORTC colorectal cancer-specific
questionnaire; QLQ-LC13, EORTC lung cancer-specific questionnaire; QLQ-OES18, EORTC esophageal cancer-specific questionnaire; QLQ-PAN26, EORTC pancreatic cancer-specific questionnaire; QOL-RTI, 24-item HRQoL Radiation
Therapy instrument.

5. R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48 41
Health-Related Quality of Life
ScreeningIdentificationEligibilityIncluded
Healthcare Resource Utilization
Hits identified through
database searching
(n = 209b
)
Hits identified and
removed as duplicates
(n = 20)
Hits identified and
removed as duplicates
(n = 29)
Hits screened
(n = 189)
Hits screened
(n = 60)
Full-text articles
assessed for eligibility
(n = 22)
Full-text articles
assessed for eligibility
(n = 10)
Other sourcesd
(n = 3)
Studies included in
qualitative synthesis
(n = 17)
Studies included in
qualitative synthesis
(n = 5)
Hits excluded
(n = 167)
Hits excluded
(n = 50)
Full-text articles excluded
(HRQoL was not
measured in 1 study and
7 articles were not
CID specific)
Full-text articles excluded
(5 articles were not
CID specific)
Hits identified through
database searching
(n = 89c
)
Fig. 1. PRISMA diagrama
.
(Moher et al., 2009; Shabaruddin et al., 2013), left side). After dupli-
cates (n = 20) were removed, 189 hits (titles and abstracts) were
screened. Those that mentioned QoL in the abstract but did not
measure it were excluded (n = 167), leaving a total of 22 studies,
the full text of which was assessed for eligibility. A further 8 stud-
ies were excluded, as HRQoL was not measured in 1 study and 7
papers were not CID specific, leaving 14 studies for data extraction.
Three additional studies were identified from a recent systematic
review of utility values for chemotherapy-related adverse events
(Shabaruddin et al., 2013). Key findings of these studies are sum-
marized in the paragraphs below.
3.2. Classification of studies included
All the studies were classified as primary research studies, these
were subcategorized as experimental clinical studies (n = 13) and
methodologic studies (n = 4) (Table 1a, Table 1b and Table 1c)
(Zachariah et al., 2010; Gourgou-Bourgade et al., 2013; Yang et al.,
2013; Lück et al., 2013; Ziefle et al., 2011; Rosenoff et al., 2006;
Reynolds et al., 2013; Toyama et al., 2013; Bentzen et al., 2013;
Kaptein et al., 2013; Zabernigg et al., 2012; Tholstrup et al., 2011;
Hurmuzlu et al., 2011; Kuchuk et al., 2013; Beusterien et al., 2009,
2010; Nafees et al., 2008). A study that does not fit with the pre-
vious 2 subcategories is the study by Kaptein et al. (Kaptein et al.,
2013), in which the authors used a survey to investigate women’s
perceptions of the impact that chemotherapy has over time on their
QoL.
Ten experimental clinical studies investigated the relationship
between chemotherapy and diarrhea episodes. Of these, 4 were
randomized controlled trials (RCTs) of cytostatic drugs (Gourgou-
Bourgade et al., 2013; Yang et al., 2013; Lück et al., 2013; Ziefle
et al., 2011); 1 was a Phase II open-label trial (Reynolds et al.,
2013); another was a Phase I trial (Toyama et al., 2013); 1 was a
cross-sectional study (Bentzen et al., 2013); 2 were prospective
studies (Zabernigg et al., 2012; Tholstrup et al., 2011) and 1 was
a retrospective study (Hurmuzlu et al., 2011). In addition, 2 RCTs
investigated supportive care for controlling or preventing diarrhea
episodes (Zachariah et al., 2010; Rosenoff et al., 2006).
Three of the methodologic studies were cross-sectional surveys
(Kuchuk et al., 2013; Beusterien et al., 2009, 2010) that attempted
to unravel the perceptions about the chemotherapy side effects,
including diarrhea. The studies elicited preferences using the Stan-
dard Gamble (SG), which is used in economic evaluation studies for
obtaining utilities (Gafni, 1994). The last methodological study was
a prospective study that aimed at eliciting UK societal-based util-
ity values for different stages of non-small cell lung cancer (NSCLC)

6. 42R.Tarriconeetal./CriticalReviewsinOncology/Hematology99(2016)37–48
Table 1b
Randomised controlled trials of supportive care.
Author and year Setting Study participants Intervention Comparison HRQoL measure
Zachariah et al. (2010) Radiation Therapy Oncology Group 215 patients (≥18 years old) with
rectal and anal cancers receiving
concurrent chemotherapy, pelvic
radiation therapy, or with a history
of chemotherapy
Two 30-mg intramuscular
injections of long-acting
octreotide. The first dose of study
drug was given between 4 and 7
days before the start of radiation.
The second dose of study drug was
given on day 22 (±3 days) of
radiation
Placebo 24-item QOL-RTI 14-item
EPIC-Bowel
Rosenoff et al. (2006) Open-label, randomized,
multicenter study
147 cancer patients scheduled for
at least 2 cycles of chemotherapy
over a 2-mo period who had
experienced grade I–IV diarrhea
during previous chemotherapy or
were experiencing diarrhea at
study entry
30 mg octreotide long-acting
release intramuscularly 7–14 days
before day 1 of the next
chemotherapy cycle. The second
dose coincided with the initiation
of the chemotherapy cycle.
Subsequent doses delivered every
28 days up to a total of 6 doses on a
schedule
40 mg octreotide long-acting
release intramuscularly 7–14 days
before day 1 of the next
chemotherapy cycle. The second
dose coincided with the initiation
of the chemotherapy cycle.
Subsequent doses delivered every
28 days up to a total of 6 doses on a
schedule
FACIT-D
Table 1c
Summary of CID primary methodologic research studies.
Type of study Author and year Setting Study participants Intervention Comparison HRQoL measure
Cross-sectional studies Kuchuk et al. (2013) Cancer centers 69 women with breast
cancer
To obtain utility weights from
patients with breast cancer for
common side effects associated
with chemotherapy
Not applicable Preference elicitation methods: SG
Beusterien et al. (2009) Not stated 140 respondents with
health states associated
with melanoma
To elicit utilities values for 13
health states from patients with
melanoma
Not applicable Preference elicitation methods: SG
Beusterien et al. (2010) Not stated 89 participants from
the general population
assessing health states
associated with CLL
To measure preferences for health
states associated with CLL
treatment
Not applicable Preference elicitation methods: SG
Prospective study Nafees et al. (2008) General population 100 participants from
the general population
To elicit UK societal-based utility
values for different stages of NSCLC
and different-grade toxicities
commonly associated with
chemotherapy treatments
Not applicable EQ-5D VAS SG
CID, chemotherapy-induced diarrhea; CLL, chronic lymphocytic leukemia; EQ-5D, EuroQoL 5-Dimension; HRQoL, health-related quality of life; NSCLC, non-small cell lung cancer; SG, Standard Gamble; VAS, Visual Analogue Scale.

7. R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48 43
and for common toxicities (grade III/IV) related to chemotherapy
treatment (Nafees et al., 2008).
3.3. Critical appraisal of primary studies
Overall, the trials (Zachariah et al., 2010; Gourgou-Bourgade
et al., 2013; Yang et al., 2013; Lück et al., 2013; Ziefle et al., 2011;
Rosenoff et al., 2006; Reynolds et al., 2013; Toyama et al., 2013)
showed some degree of homogeneity, although 3 of the 7 failed
to report on intention-to-treat, which is considered to bias the
results. In 3 trials, HRQoL was a secondary outcome and thus these
results were not comprehensively reported. One of the trials failed
to report variability in the primary outcome and if confounding bias
was considered (Hurmuzlu et al., 2011). Other primary research
studies (Reynolds et al., 2013; Kaptein et al., 2013; Zabernigg et al.,
2012; Tholstrup et al., 2011; Kuchuk et al., 2013; Beusterien et al.,
2009, 2010) reported their objectives, methods, and appropriate-
ness of the population under investigation in detail, although they
did not consistently address the question of confounding and bias,
which is a common omission for this type of study.
3.4. Findings from primary research studies
With respect to the HRQoL tools used, 10 studies favored the use
of the European Organisation for the Research and Treatment of
Cancer Quality of Life Questionnaire (EORTC QLQ-C30) irrespective
of their study design, whether used on its own (Gourgou-Bourgade
et al., 2013; Ziefle et al., 2011; Kaptein et al., 2013; Zabernigg et al.,
2012; Tholstrup et al., 2011) or in conjunction with other HRQoL
questionnaires, including the Lung Cancer-13 questionnaire (QLQ-
LC13) (Yang et al., 2013), the breast cancer-specific quality of life
questionnaire (QLQ-BR23) (Lück et al., 2013), the pancreatic cancer-
specific supplemental module (QLQ-PAN26) (Toyama et al., 2013),
the EORTC module for colorectal cancer (QLQ-CR29) (Bentzen et al.,
2013), and the esophageal cancer module (QLQ-OES18) (Hurmuzlu
et al., 2011). Only 2 studies used specific modules from the Func-
tional Assessment of Chronic Illness (FACIT) questionnaire; one
used the module for diarrhea (FACIT-D) (Rosenoff et al., 2006), and
the other employed the Functional Assessment of Cancer Therapy
General (FACT-G) and the Functional Assessment of Cancer Therapy
Lung (FACT-L) (Reynolds et al., 2013). Other HRQoL question-
naires used among the primary studies were the Visual Analogue
Scale (VAS) and the EuroQoL 5-Dimension (EQ-5D) (Nafees et al.,
2008), the 24-item HRQoL Radiation Therapy instrument (QOL-RTI)
(Zachariah et al., 2010), and the 14-item Expanded Prostate Cancer
Index Bowel (EPIC-Bowel) (Zachariah et al., 2010).
As mentioned above, the majority of primary studies looked
at the side effects of chemotherapy, which included diarrhea
episodes. In one of the RCTs, FOLFIRINOX (oxaliplatin, irinote-
can, 5-fluorouracil [5-FU], and leucovorin) was investigated versus
gemcitabine in pancreatic cancer patients, for patients receiving
FOLFIRINOX an increase in diarrhea was observed (Gourgou-
Bourgade et al., 2013). However, no statistical differences in HRQoL
scores were found between the treatment arms at baseline or
in the longitudinal analysis. In the RCT that included patients
with advanced epidermal growth factor receptor mutation-positive
lung adenocarcinoma were randomized to receive afatinib or
cisplatin-pemetrexed (Yang et al., 2013). Patients in the afatinib
arm experienced significantly worse diarrhea, but no significant
difference was found for improvement or deterioration of the
global health status and functional scales between the treatment
arms. However the longitudinal analysis showed that EORTC scores
were significantly better in the afatinib arm. In a trial with cuta-
neous stage II malignant melanoma patients receiving low-dose
interferon-␣, diarrhea was reported to increase after 3 months
(Ziefle et al., 2011). Diarrhea episodes were associated with the low-
est HRQoL scores, and even after 12 months the HRQoL scores were
significantly lower when compared with their respective base-
line values (Ziefle et al., 2011). Metastatic breast cancer patients
reported grade III/IV diarrhea after receiving capecitabine plus
paclitaxel, compared with patients receiving epirubicin plus pacli-
taxel (Lück et al., 2013). Statistically significant differences between
the 2 treatment arms in HRQoL favored epirubicin plus paclitaxel
in items related to long walks, physical conditions or medical treat-
ment interfering with social activities, limitations in hobbies or
leisure activities, and worries over the last week. In a Phase II open-
label trial of sunitinib malate in elderly patients with stage III/IV
NSCLC, changes in HRQoL scores depended on the treatment cycles,
with patients experiencing deterioration in the initial cycles, but
a significant improvement in HRQoL in the later cycles (Reynolds
et al., 2013). Lastly in a Phase I trial, pancreatic cancer patients
receiving adjuvant biweekly 1000 mg/m2 gemcitabine for at least
12 courses had better HRQoL compared with patients receiving
adjuvant 5-FU–based chemotherapy (Toyama et al., 2013).
The findings from prospective studies are consistent with those
from RCTs. In the study by Zabernigg and colleagues, up to 21%
of patients suffering from pancreatic and biliary tract cancer who
received third-line palliative chemotherapy (adjuvant treatment)
experienced a CID episode (Zabernigg et al., 2012). Furthermore,
for first and second line palliative chemotherapy patients, physical
and psychological symptoms and global QoL were stabilized, but
no significant improvement in global QoL was found (Zabernigg
et al., 2012). While a study investigating (R)-CHOP-14 (dose-dense
chemotherapy) showed that during treatment up to 57% of the
patients with diffuse large B-cell lymphoma had an increased num-
ber of diarrhea episodes and fatigue, and experienced significant
decrements in physical and role functioning, whereas emotional
functioning increased; these changes were normalized (pretreat-
ment scores) after 3 months (Tholstrup et al., 2011).
Two studies in which cancer survivors received chemoradio-
therapy found that almost 20% of anal cancer survivors suffered
from diarrhea and from long-term impaired HRQoL, primarily with
respect to social, sexual, and role functioning (Bentzen et al., 2013).
While those esophageal cancer survivors who received high-dose
of (5-FU), their global QoL scores were significantly worse com-
pared with patients who received surgery alone (Hurmuzlu et al.,
2011).
However, key to this review are two RCTs that investigated
treatments for controlling diarrhea (Zachariah et al., 2010; Rosenoff
et al., 2006). The efficacy of long-acting octreotide (LAO) in prevent-
ing the onset of acute diarrhea in patients receiving concurrent
chemoradiotherapy for rectal or anal cancer was assessed in 233
patients (215 received a 30-mg dose of LAO (n = 109) or placebo
(n = 106) via intramuscular injection) (Zachariah et al., 2010).
Assessment of the impact of LAO on number of hospitalizations, use
of other antidiarrheal agents, and HRQoL (measured by the QOL-RTI
and the EPIC-Bowel) was also carried out. Results showed that after
a median follow-up time of 9.64 months, incidence rates of grade
I–IV acute diarrhea were similar in both groups (44% LAO versus 49%
placebo; p = 0.21), and no statistically significant differences were
observed for number of hospitalizations, use of other antidiarrheal
agents, or HRQoL scores. The second RCT recruited a total of 147
cancer patients scheduled for at least 2 cycles of chemotherapy
over a 2-month period, who had experienced grade 1–4 diarrhea
as defined by NCI-CTC. Patients were randomized to 2 dose levels
(30 mg or 40 mg) of LAO release (LAOR) while HRQoL was assess
by the FACIT-D (Rosenoff et al., 2006). Patients in the 40-mg group
experienced fewer severe diarrhea episodes (48.4% versus 61.7%),
required less intravenous (i.v.) fluid (18.8% versus 31.7%), and had
fewer diarrhea-related unscheduled healthcare visits (28.1% versus
41.7%) than those in the 30-mg group. Nevertheless, these dif-

8. 44 R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48
ferences were not statistically significant, and investigators were
unable to recommend the prescription of 40 mg LAOR over 30 mg.
The study by Kuchuk et al. (Kuchuk et al., 2013), utility values
were obtained from 69 women with breast cancer for all disease
stages using the SG preference elicitation method. Utility estimates
were derived for most of the potential side effects of chemotherapy;
however, for the scope of this review, the important side effects
were grade I/II diarrhea, defined as 3–6 episodes of diarrhea per
day, ie, mean utility value of 0.76 (standard deviation ± 16.8; range
0.25–0.95); and grade III/IV diarrhea, more than 6 episodes per day,
requiring i.v. fluids at the hospital, ie, mean utility value of 0.68
(standard deviation ± 22.1; range 0.00–0.95). Grade III/IV diarrhea
was ranked as the second worst side effect after grade III/IV nausea
or vomiting requiring a physician or emergency room visit, while
grade I/II diarrhea was ranked as the most preferred side effect. The
interpretation of the utility values for grades I/II and grades III/IV is
that, on average, patients are willing to take a gamble, even if they
have a 24% or 32% chance of death, in order to avoid having grade
I/II or grade III/IV diarrhea, respectively. The authors’ conclusions
suggested the use of these utility values in cost-effectiveness anal-
yses, although they also acknowledged selection bias by excluding
from their analysis all the illogical responses that accounted for 32%
of the total sample.
The second methodological study used a vignette approach for
obtaining utility values for health states associated with advanced
melanoma using the SG with members of the general population
(Beusterien et al., 2009). A total of 140 participants (n = 77 from
Australia and n = 63 from the UK) were recruited in the study. Utility
values were obtained for 4 clinical response states (partial response
[PR], stable disease [SD], progressive disease [PD], and best sup-
portive care [BSC]), and separately for grade I/II toxicities, which
included hair loss, skin reaction, diarrhea, nausea/vomiting, flu-like
syndrome, and stomatitis. For severe toxicity (grade III/IV), utility
values were grouped into 2 categories: 1-day in/outpatient stay, or
2- to 5-day hospitalizations. In order to facilitate the interpretation
of these results, the overall utility mean values of a patient expe-
riencing diarrhea in the 4 clinical states are presented here. The
lowest utility value (0.43; standard error 0.02) was estimated for
PD and BSC, so on average a patient will be willing to take a gam-
ble even if this involved a 67% chance of death, in order to avoid
being in a PD or BSC state. The chance that a patient will be will-
ing to accept for SD was on average 29% (ie, mean utility value of
0.71; standard error 0.01). Lastly, on average, a patient was willing
to accept a 21% chance of death for the PR state (0.79; standard
error 0.01). The overall results show that utility values were lower
for health states with reduced chemotherapy responsiveness and
with grade III/IV toxicities. In another methodologic study by the
same authors preferences were elicited in 89 individuals from the
general population in England and Scotland related to health states
associated with chronic lymphocytic leukemia, using the SG once
again (Beusterien et al., 2010). The health states were based on
response status (n = 4), treatment-related toxicities on CTC (n = 6),
and line treatment (n = 2). Among the adverse events considered
was diarrhea grade I/II that had a utility value equal to 0.70 (±0.19
standard deviation); for diarrhea grade I/II, there were no statisti-
cal differences between respondents with respect to age (<60 years
old or ≥60 years old), sex, or information about leukemia; how-
ever, participants with knowledge of leukemia reported slightly
lower utility values (0.68; ±0.19 standard deviation). In both stud-
ies, the authors concluded that these utility values could be used in
cost-effectiveness studies.
The study by Nafees et al. (Nafees et al., 2008) elicited utility
values from a UK general population for different stages of NSCLC
and for different grade III/IV toxicities, including diarrhea. Existing
descriptive metastatic breast cancer health states were adapted for
describing NSCLC health states for patients on second-line therapy.
The valuation was done face to face with 100 participants, who
were asked to answer a socio-demographic questionnaire and the
EQ-5D using the VAS for rating their own health, while the health
state utilities were obtained from the SG. The mean utility value for
the base health state with grade III/IV diarrhea was estimated to be
0.606, while for a progressive state it was 0.423, which is similar to
the value reported by Beusterien and colleagues for the progressive
state (Beusterien et al., 2009).
The last methodological study was the one conducted by Kaptein
et al. (Kaptein et al., 2013) aimed primarily to understand the cul-
tural differences and similarities in terms of HRQoL and illness
perception of Japanese and Dutch women receiving chemother-
apy for breast cancer using the EORTC QLQ-C30. The results from
this cross-cultural retrospective study showed that both groups
suffered from diarrhea episodes one week after receiving their
chemotherapy. However, the HRQoL of Japanese women appeared
more affected than that of Dutch women. Nevertheless, the study
has a very small sample (22 Dutch and 21 Japanese women) which
was acknowledge by the authors.
3.5. Findings from healthcare resource utilization studies
A total of 89 hits were obtained; 66 were identified in MED-
LINE, 15 in EMBASE, and 8 in DARE and NHS EED databases (Fig. 1,
right side). After duplicates (n = 29) were removed, 60 hits (titles
and abstracts) were screened and only 5 studies were retrieved for
full review. The results in this section are described chronologi-
cally from the earliest article in 2000 (Arbuckle et al., 2000) to the
most recent in 2010 (Mittmann et al., 2010). Details of these stud-
ies are presented in Table 2 (Arbuckle et al., 2000; Dranitsaris et al.,
2005a,b; Mittmann et al., 2010; Elting and Shih, 2004).
In the retrospective study by Arbuckle et al. (Arbuckle et al.,
2000); the investigators reviewed 100 consecutive records from
patients treated for colorectal cancer between 1995 and 1998.
Healthcare resources consumed for the management of diarrhea
were among the data collected. Of the 673 chemotherapy cycles
that were received, 301 cycles were associated with diarrhea
episodes, and more than half of the patients (52%) experienced
severe diarrhea (grade III/IV). Among the additional health-
care resources were oral antidiarrheal agents (n = 67 patients),
octreotide (n = 7 patients), emergency outpatient visits (n = 14
patients), hospitalization (n = 23 patients), and i.v. fluids (n = 21
patients). The authors concluded that all grades of diarrhea should
be recognized and treated in order to maximize the effectiveness
of chemotherapy.
The article by Elting and Shih (2004) aimed to estimate the
cost of outpatient and inpatient supportive care for cancer patients
using existing literature and Medicare payments; costs are pre-
sented in 2002 US dollars. The costs of common complications
of chemotherapy were estimated, and the hospitalization cost for
managing diarrhea was derived to be $6,616. For most inpatient
complications, the cost per episode was $7,000, while the aver-
age Medicare payments were in the range of $3,000. The authors
emphasized the need for cost-of-illness and cost-utility studies for
supportive care conditions in order to have a better-informed clin-
ical decision-making process.
Dranitsaris and colleagues estimated the impact that grade III/IV
diarrhea has on resource consumption in 2 retrospective cost-of-
illness studies that focused on hospitalizations and outpatient visits
of patients treated with fluoropyrimidines, irinotecan, or oxali-
platin (or any combination of these) (Dranitsaris et al., 2005a;
Dranitsaris et al., 2005b). Diarrhea grade III and IV was defined
according to the NCI-CTC as: 7–9 stools/day, incontinence, or severe
cramping (grade III); and at least 10 stools per day, the need of par-
enteral support for dehydration, or development of glossy bloody
diarrhea (grade IV). In terms of healthcare resource consump-

9. R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48 45
Table 2
Summary of CID economic studies.
Author and year Setting Perspective Cost year Discount rate Type of costs
estimated
Grades of diarrhea
episodes
Costs
(Arbuckle et al. (2000) Cancer Center Not stated Not stated Not stated Antidiarrheal
agents Emergency
outpatient visits
Hospitalization
Intravenous fluids
III and IV Not applicable
Elting and Shih (2004) Hospital Discharge
Database
(population-based
estimates)
Medicare 2002 US dollars Not stated Hospitalization Not applicable $6,616
(Dranitsaris et al. 2005a) Cancer centers Socialized
healthcare system
2004 Canadian
dollars
Not stated Outpatient
(clinic/emergency
depart-
ment/hospital day)
cost per episode
III and IV $2,559a
Dranitsaris et al. (2005b) Cancer centers Socialized
healthcare system
2004 Canadian
dollars
Not stated Hospitalization III and IV $8,320a
Mittmann et al. (2010) Model-based
Breast Cancer
International
Research Group
(BCIRG) 001 trial
(“TAC-FAC”)
Canadian
provincial
government payer
2006 Canadian
dollars
5% Outpatient cost per
episode
III and IV $2,760
CID, chemotherapy-induced diarrhea; FAC, fluorouracil, doxorubicin, and cyclophosphamide; TAC, doxorubicin and cyclophosphamide.
a
Including the costs of febrile neutropenia, emesis, and stomatitis.
tion, the following elements were considered: unscheduled visit to
the oncology clinic or emergency departments; hospitalization for
supportive care; medical interventions for managing diarrhea (eg,
octreotide, antibiotics); laboratory and microbiologic tests; diag-
nostic imagining procedures; nursing time; number of physician
visits to hospitalized patients; and number of specialist consulta-
tions that were directly related to the diarrhea episode. The unit
costs were obtained from the Toronto Sunnybrook Regional Can-
cer Centre and from the University Health Network in Toronto,
Ontario, for 2004, while the cost of hospital stay was acquired
from a Canadian oncology center and was reported to be $644
per day. Physicians’ fees were obtained from the Schedule of Ben-
efits from the Ontario Ministry of Health for 1998 and reflated
to 2004 Canadian dollars. In both studies, the authors reported
that up to 59% (n = 37/63) (Dranitsaris et al., 2005b) and 54%
(n = 52/96) (Dranitsaris et al., 2005a) of the patients developed diar-
rhea grade III or IV after the first cycle of chemotherapy. A total
of 59% (n = 37/63) (Dranitsaris et al., 2005b) and 33% (n = 32/96)
(Dranitsaris et al., 2005a) of the patients attended an unsched-
uled visit to the oncology center; 43% (n = 27/63) (Dranitsaris et al.,
2005b) and 12.5% (n = 12/96) (Dranitsaris et al., 2005a) of the
patients attended the emergency department. Of the 63 patients
studied, 9 (14%) died, 3 (5%) of whom had uncontrolled diarrhea
(Dranitsaris et al., 2005b). The median hospitalization length was
8 days, with a 3-day median duration of i.v. fluids (Dranitsaris
et al., 2005a; Dranitsaris et al., 2005b). Overall, 27% (n = 17/63)
(Dranitsaris et al., 2005b) and 28% (n = 27/96) (Dranitsaris et al.,
2005a) of patients delayed their chemotherapy for 14 days, while
33% (n = 21/63) (Dranitsaris et al., 2005b) and 57% (n = 55/96)
(Dranitsaris et al., 2005a) of patients had their chemotherapy
reduced by 25%. Another 16% (n = 10/63) (Dranitsaris et al., 2005b)
and 8% (n = 8/96) (Dranitsaris et al., 2005a) of patients had their
chemotherapy changed, and 34% (n = 22/63) (Dranitsaris et al.,
2005b) and 14% (n = 13/96) (Dranitsaris et al., 2005a) of patients had
their chemotherapy discontinued. The total cost per hospitalization
per patient with diarrhea grade III or IV was estimated to be $8,230
on average (Dranitsaris et al., 2005b). The authors also estimated
the total costs excluding the costs associated with concomitant
febrile neutropenia, emesis, and stomatitis, which provided the
estimates of $7,576, $8,617, and $7,981, respectively (Dranitsaris
et al., 2005b), while in the other cost-of-illness study, the mean
cost estimate for the overall cost impact of grade III/V diarrhea for
outpatient visits (clinic/emergency department/hospital day vis-
its, supportive care, hospital staff, laboratory and diagnostic tests
for the management of diarrhea) was estimated to be $2,559 per
patient (Dranitsaris et al., 2005a). In a subgroup analysis of grade III
and IV patients, the authors estimated that grade IV episodes were
5 times more costly than grade III ($5,776 versus $1,097, respec-
tively) (Dranitsaris et al., 2005a). They also followed their previous
approach of excluding the cost of febrile neutropenia, emesis, and
stomatitis, the mean cost estimates of which were $1,802, $1,384,
and $2,500, respectively. The authors suggested that aggressive
interventions should be put in place in order to prevent diarrhea
grade III/IV episodes. However, these results should be interpreted
with caution since the number of individuals included in both stud-
ies is very small.
The Markov model analyses by Mittmann and colleagues
(Mittmann et al., 2010) estimated the cost effectiveness of provid-
ing docetaxel (Taxotere®: Sanofi-Aventis, Laval, QC) in combination
with doxorubicin and cyclophosphamide (TAC) compared with 5-
FU, doxorubicin, and cyclophosphamide (FAC), following primary
surgery for breast cancer in women with operable, axillary lymph
node-positive disease. The direct medical costs of adverse events
grades III and IV for febrile neutropenia, stomatitis, diarrhea, and
infections were estimated from the perspective of the Canadian
provincial government. Costs were presented in 2006Canadian dol-
lars and showed that the outpatient cost of a diarrhea grade III/IV
episode was $2,760, which is in line with the study by Dranitsaris
et al. (Dranitsaris et al., 2005a). No further data were extracted from
this article.
4. Discussion
Cancer is among the 10 biggest killers worldwide (World Health
Organization, 2011). The economic burden associated with can-
cer and cancer treatments is increasing at an unsustainable rate
in almost all industrialized countries. In Europe the total economic
burden of cancer was estimated in 2013 to be equivalent to D 126
billion, of which 40% is attributable to healthcare costs and 60%
to nonhealthcare costs (eg, informal care and productivity losses)

10. 46 R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48
(Luengo-Fernandez et al., 2013). In 2004 Medicare spent $7.3 billion
on inpatient cancer care, but this did not include chemothera-
pies, which are usually administered as an outpatient service (The
Hastings Center, 2010). While there are no reliable cost projections
of the overall disease, there is an exponential increase in the cost
of cancer drugs. In 2009 the cost of anticancer drugs in Europe rep-
resented almost 30% of the overall healthcare costs. In the UK, the
cost of diagnosing and treating cancer is likely to raise by almost
two-thirds over the next decade, from D 9.4 billion in 2010 to D 15.3
billion by 2021, an increase of almost 63% (Bupa, 2011). This implies
that, while in 2010 the average cost of treating someone diag-
nosed with cancer was approximately D 30,000, this will increase to
almost D 40,000 by 2021. The increase in the overall cost of cancer
diagnosis and treatment is, in part, the result of the aging popu-
lation, but also of the cost of cancer technologies and treatments,
which will continue to rise significantly over the 10-year period
(Bupa, 2011). In view of future scenarios and in a time of resource
constraints, it is fundamental to have a clear picture of the cost of
illness in order to identify potential areas for improvements with
regard to unnecessary costs and worse health outcomes.
When unmanaged, side effects such as CID can cause life-
threatening dehydration, renal insufficiency, electrolyte imbalance,
and cardiovascular complications, resulting in collapse of the
patient’s health. CID also increases the individual’s level of anxiety,
depression, and diminishes his or her self-esteem (Viele, 2003). It
delays or can result in the discontinuation of principal treatments
(ie, chemotherapy). In addition, CID increases caregivers’ burden,
and impacts on the overall cost of cancer treatment (Dranitsaris
et al., 2005a; Mittmann et al., 2010; Dranitsaris et al., 2005b; Abd
El-Atti et al., 2009).
This systematic literature review is the first aimed at analyz-
ing the impact of CID on QoL and on resource utilization. Overall,
the evidence suggests that grades III and IV CID have a profound
impact on the HRQoL of individuals (Zachariah et al., 2010; Rosenoff
et al., 2006). However, from this work it emerged that QoL, the
most important outcome in oncology research, has not investigated
as the primary outcome on the studies for individuals experienc-
ing CID, with the exception of only 2 studies actually measuring
the HRQoL of individuals experiencing CID (Zachariah et al., 2010;
Rosenoff et al., 2006). In addition, although the study by Zachariah
and colleagues did not find any statistical difference in terms of
improvements in QoL between the groups, the authors empha-
sized that using HRQoL tools with this population provides reliable
and valid data, and that these tools might be used for symptom
management in future studies (Zachariah et al., 2010).
In terms of assessment, it appears that researchers favored
the EORTC QLQ-C30 questionnaire for assessing HRQoL changes.
This might be because the majority of studies attempted to assess
the impact of chemotherapy and not of adverse events, such
as CID. However, how sensitive this tool is for assessing the
impact of CID on HRQoL is an unanswered question. Moreover, of
greater importance for resource allocation are the findings from
the methodologic studies (Kuchuk et al., 2013; Beusterien et al.,
2009, 2010; Nafees et al., 2008), since the utility values obtained in
these studies can be used in cost-effectiveness analysis and decision
analytics models. These studies are indeed a step forward for a bet-
ter understanding and consideration of cancer patient preferences,
although 3 of these studies (Beusterien et al., 2009; Beusterien et al.,
2010; Nafees et al., 2008) used an approach different than those
conventionally adopted and recommended in the UK and Australia
as the reference case for health technology assessment (National
Institute for Health and Care Excellence, 2008), in which changes
in HRQoL, expressed as utility values, should be obtained from the
EQ-5D generic questionnaire.
Understanding the economic impact of CID is important to sup-
port the health-related decision-making process with regard to
preventive strategies. If the incidence of CID is reduced, the addi-
tional costs to treat CID episodes will turn into relevant savings
that could be used elsewhere. However, the economic evidence
in this area is scarce, focusing on healthcare costs and thereby
underestimating the broader societal burden of CID. This disre-
gards, for instance, the impact on informal care and productivity
losses (Arbuckle et al., 2000; Dranitsaris et al., 2005a,b; Mittmann
et al., 2010; Elting and Shih, 2004). Nevertheless, from this work
it clearly emerges that even healthcare costs alone could repre-
sent a large proportion of the total costs of cancer. CID episodes
have been shown to comprise a relevant proportion of avoidable
costs in terms of hospitalizations, unplanned visits, tests, drug con-
sumption, and discontinuation or prolongation of chemotherapy
(Dranitsaris et al., 2005a,b). Hospital admissions undoubtedly rep-
resent the major cost-driver, even though outpatient care costs can
reach as much as almost $6,000 per episode when grade IV episodes
are differentiated from grade III episodes (Dranitsaris et al., 2005a).
If one considers that over 50% of cancer patients suffer from diar-
rhea and that each single patient experiences more than 1 episode
of any grade on average, it becomes evident that the amount of
resources that payers could potentially save and free for alternative
ends (eg, to introduce new technologies) is considerable.
To conclude, this review shows that healthcare providers,
payers, and patients can potentially benefit from a better under-
standing of how to best prevent CID episodes. Further research
is needed to understand the economic and HRQoL impact of pre-
venting and treating CID episodes; this will allow the identification
of resources that can potentially be made available to fund other
treatments. Future studies should consider collecting healthcare
resource utilization data from large cohorts and adopting a soci-
etal perspective in order to provide a more accurate scenario for
resource allocation to policy makers.
Author contributions
This study is the result of a joint effort of all co-authors, and
the paper has been written jointly by them: A.M.-L. contributed
to the design, screening, and extraction of the data; analysis and
interpretation of the results; writing the article; critical revision
of the article; and final approval of the article. D.A.K. and B.N.-W.
contributed to the screening and extraction of the data. R.T. con-
tributed to the design of the study, to the final recommendations,
to the writing of the manuscript, and the final approval of the article.
Conflict of interest
We declare that none of the authors or their organizations have
any conflict of interest in the publication of this paper.
Acknowledgments
This work was supported by an unrestricted grant from Helsinn
Group. The authors thank Dr. Carla Rognoni for providing com-
ments on the manuscript and Leala Watson for re-running the
searches. Nevertheless, the authors are solely responsible for
the content of the present paper. The authors developed the
manuscript without medical writing assistance. Just prior to journal
submission, editorial assistance was provided by Sandra Mendes,
PhD, CMPP (TRM Oncology, The Netherlands), funded by Bocconi
University.

11. R. Tarricone et al. / Critical Reviews in Oncology/Hematology 99 (2016) 37–48 47
Appendix A.
Search criteria
1. exp chemotherapy Induced diarrh?/
2. chemotherapy Induced diarrh?.ti,ab.
3. 1 or 2
4. Economics, Medical/
5. Economics, Nursing/
6. exp economics, hospital/
7. economics pharmaceutical.
8. ec.fs.
9. exp “Costs and Cost Analysis”.
10. exp “Cost-benefit Analysis”.
11. “Value of Life”
12. exp “Models, Economic”.
13. exp “Fees and Charges”.
14. Resource Allocation/
15. exp Budgets/
16. budget*.tw.
17. (economic$or price$or pricing or financ$or fee$or pharma-
coeconomic$or pharma
18. economic$).tw.
19. (expenditure$not energy).tw.
20. (value$5 adj2 (money or monetary or life or lives or cost$2)).tw.
21. (economic adj2 burden).tw.
22. (resource$2 adj2 (use* or utili* or allocat*)).tw.
23. (cost$2 adj2 (benefit$or consequence* or analys* or saving* or
breakdown* or lowering or estimat* or variable* or allocation*
or control* or illness* or affordable* or instrument* or tech-
nolog* or fee* or charge$2 or utilit$or minim$or effective$or
effective* or efficac*)).ab.
24. cost.ti.
25. 19 or 20
26. (animals not humans).sh.
27. AND
28. “Quality of Life”/
29. “Value of Life”/
30. ((qualit$3 or value) adj2 life).tw.
31. quality-adjusted life years/
32. quality adjusted.tw.
33. (qaly* or qald* or qale* or qtime* or qualy).tw.
34. sickness impact profile/
35. (disabilit$3 adj2 life).tw.
36. daly.tw.
37. Health Status Indicators/
38. (euroqol or euro qol or eq5d or eq 5d).tw.
39. (hql or hqol or qol or hrqol).tw.
40. (hye or hyes).tw.
41. health$year$equivalent$.tw.
42. health utilit* or utilities or utility value*).tw.
43. hui$1.tw.
44. disutil$.tw.
45. rosser.tw.
46. (quality adj3 well).tw.
47. quality of wellbeing.tw.
48. willingness to pay.tw.
49. standard gamble$.tw.
50. (time trade off or time tradeoff or tto).tw.
51. (health adj3 (utilit$3 or value$2 or preference$2)).tw.
52. (visual analog$3 scale or VAS).tw.
53. (health adj2 (utilit$3 or value$2 or preference$2)).tw.
54. patient preference$2.tw.
55. or/23–54
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Biographies
Rosanna Tarricone is an associate professor at the Department of Policy Anal-
ysis and Public Management, Bocconi University, Milan, Italy. She graduated in
business administration from Bocconi University, and obtained an MSc in health
services management and a PhD in economics from the University of London. She
is the director of the Centre for Health and Social Care Management (CERGAS)
at Bocconi University and the scientific director of the European Health Technol-
ogy Institute for Socio-Economic Research. Her main areas of research include
healthcare management, health economics, economic analysis of healthcare ser-
vices, health policy, and health technology assessment. Rosanna is a member of the
International Association of Health Economics (iHEA), the International Health Tech-
nology Assessment (HTAi), and the International Society for Pharmacoeconomics
and Outcomes Research (ISPOR). She is the author of numerous papers and books
on healthcare management and economics.
Dana Abu Koush received a BSc in physiology, a postgraduate diploma in general
management from McGill University (Canada), and obtained an MSc in interna-
tional healthcare management, economics, and policy from Bocconi University. She
has experience in survey-based market research and was responsible for setting up
the healthcare research division at Ipsos Jordan, where she worked as a healthcare
project manager for 5 years. As a research fellow at the Centre for Health and Social
Care Management (CERGAS) at Bocconi University, specifically the Pharmaceuti-
cal Observatory (OSVAR), her main areas of research were economic evaluations of
healthcare interventions and budget impact model analysis.
Barbara Nyanzi-Wakholi is an independent social scientist majoring in qualita-
tive research methods. She originally trained as a secondary school teacher and later
obtained an undergraduate degree in humanities and social sciences from Nkumba
University, Entebbe, Uganda. For over 12 years, Barbara worked with the Medi-
cal Research Council/UVRI research unit on AIDS in Uganda, focusing on the use
of community-oriented research and evaluative tools. Her areas of research com-
prise sexual and reproductive health; health-seeking behavior for malaria, HIV/AIDS,
and tuberculosis; delivery of anti-retroviral therapy; and the assessment of health-
related quality of life. Her work has been published in various peer-reviewed
journals.
Antonieta Medina-Lara is a senior lecturer in health economics at the Health
Economics Group at the University of Exeter Medical School in the UK, and an hon-
orary fellow at the Centre for Research on Health and Social Care Management
(CERGAS) in Milan, Italy. She holds a BSc (Hons) in economics and econometrics,
an MSc in health economics from the University of York, and a PhD in experimen-
tal economics applied to health from the University of Liverpool. Her main areas
of expertise are experimental economics, economic modeling, econometrics, health
technology assessment, health-related quality of life assessment, well-being mea-
surement, and discrete choice analysis. She is a review member of the iHEA, the
Health Technology Assessment in the UK, and the International Society of Quality of
Life Research (ISOQOL). Antonieta has worked in Burkina Faso, Ghana, Italy, Kenya,
Malawi, Mexico, South Africa, Tanzania, Uganda, the UK, and Zimbabwe.