Patient preferences for treatment of castration-resistant prostate cancer in Japan: a discrete-choice experiment
Uemura et al. BMC Urology
Patient preferences for treatment of castration-resistant prostate cancer in Japan: a discrete-choice experiment
Dianne Athene Ledesma
Ateesha F. Mohamed
Background: Up to a fifth of patients diagnosed with prostate cancer (PC) will develop castration-resistant prostate cancer (CRPC), which has been associated with a poor prognosis. The aim of this study was to consider the patient perspective as part of the overall treatment decision-making process for CRPC, given that an alignment between patient preference and prescribing has been shown to benefit patient outcomes. This study examines preferences of patients with CRPC in Japan for treatment features associated with treatments like RA-223, abiraterone, and docetaxel and to examine the extent to which treatment preferences may vary between symptomatic and asymptomatic patients. Methods: A two-phase research approach was implemented. In Phase 1, N = 8 patients with CRPC were recruited from a single hospital to complete a qualitative interview to provide feedback on the draft survey. In Phase 2, N = 134 patients with CRPC were recruited from five hospitals to complete a paper survey. The survey included 6 treatment choice questions, each asking patients to choose between two hypothetical treatments for their CRPC. Each treatment alternative was defined by the following attributes: length of overall survival (OS), time to a symptomatic skeletal event (SSE), method of administration, reduction in the risk of bone pain, treatment-associated risk of fatigue and lost work days. A hierarchical Bayesian logistic regression was used to estimate relative preference weights for each attribute level and mean relative importance. Results: A total of N = 133 patients with CRPC completed the survey and were included in the final analysis. Patients had a mean age of 75.4 years (SD = 7.4) and had been diagnosed with PC a mean of 6.5 years prior (SD = 4.4). Over the attribute levels shown, fatigue (relative importance [RI] = 24.9 %, 95 % CI: 24.7 %, 25.1 %) was the most important attribute, followed by reduction in the risk of bone pain (RI = 23.2 %, 95 % CI: 23.0 %, 23.5 %), and OS (RI = 19.2 %, 95 % CI: 19.0 %, 19.4 %). Although symptomatic patients placed significantly more importance on delaying an SSE (p < .05), no other preference differences were observed. Conclusions: CRPC patients were more concerned about reduced quality of life from side effects of treatment rather than extension of survival, which may have implications for shared decision-making between patients and physicians.
Castration-resistant prostate cancer; Patient preferences; Fatigue; Bone pain; Symptomatic
Prostate cancer (PC) is the fourth-most common cancer
in Japan, with most patients being diagnosed at 70 years
or older . Since the middle of 2014, there have been a
number of advancements in the treatment options for
PC, specifically in metastatic castration-resistant PC
(mCRPC) (e.g., abiraterone, enzalutamide, cabazitaxel,
Ra-223) in Japan, which has extended overall survival
(OS) significantly based on available clinical data [2–7].
Yet, these treatment options can vary substantially with
respect to their effectiveness, safety profile and method
of administration, among other characteristics ,
complicating treatment decision-making for patients and
In an extensive review of patient preferences and
decision-making aids in the context of PC, Aning and
colleagues reiterated the importance of medical care that
seeks to adopt shared decision-making and aligns
treatment decisions with patient goals and values . As the
complexity of cancer treatment increases globally, the
role of patient preferences in guiding medical care will
become increasingly critical [9–13].
Research has suggested that patient preferences, in the
context of cancer, possess implications for adherence,
persistence and follow-up care . If patient
preferences and prescribed treatment regimens are misaligned,
patients can be at an increased risk for discontinuation
and non-adherence, which could affect symptom
management and survival . As a result, it is important to
understand how patients value different treatments to
best inform overall disease management.
Studies in the United States and Europe have been
conducted to explore patient preferences among patients
with PC, with a focus on the treatment of bone
metastases [15–17]. The results from these studies suggest that
patients place substantial value on the delay of bone
complications; indeed, in one study, patients were
willing to sacrifice 3–5 months of survival in the interest of
avoiding them .
Critically, however, no study has examined how
patients in Japan value differences in the characteristics of
CRPC treatment options and how these preferences
differ based on the symptomatic status of the patient. As
research suggests significant variation in patient
preferences across countries and cultures, there is a need for
more Japan-specific studies . Therefore, the objective
of this study was to fill this important gap in the
literature by enhancing the understanding of treatment
preferences among patients with CRPC in Japan.
willingness to accept tradeoffs among hypothetical
treatment profiles described by treatment attributes of varying
levels. In a healthcare context, the attractiveness of a
treatment to patients depends on patients’ relative preferences
for treatment attributes expressed by their willingness to
accept tradeoffs among them.
This study was designed to follow the good practice
guidelines for conjoint analysis associated with the
International Society of Pharmacoeconomics and Outcomes
Research . A two-phase approach was conducted. In
the first phase (Phase 1), a draft paper-and-pencil survey
was piloted on a small group of Japanese patients with
CRPC (N = 8) in a qualitative research setting to solicit
feedback and to determine the content validity of the
survey (i.e., ensuring the DCE materials were
appropriate and sufficiently clear to patients). Specifically, a
participating physician from one hospital in Japan identified
patients with CRPC who met eligibility criteria and were
willing to participate. Inclusion criteria were as follows:
(1) aged 20 years or older, (2) diagnosed with CRPC, (3)
chemotherapy-naïve, (4) able to read and understand
Japanese, and (5) provided written informed consent.
Patients were excluded if they were currently
participating in a clinical trial, unable to complete the survey by
themselves due to physical or psychological reasons, or
were otherwise deemed ineligible by the referring
In the second phase (Phase 2), the paper-and-pencil
survey was distributed to N = 134 pre-selected CRPC
patients at four participating sites, who were identified
by various hospital-based clinicians/investigators. The
inclusion and exclusion criteria, as well as the
sequencing of the items in the questionnaire, were fixed
across respondents and were the same as those used in
Phase 1. Patients completed the survey in their home
and called a researcher to provide their responses,
which were then entered into an electronic database.
The researcher ensured that patients’ responses were
recorded for all components of the questionnaire.
Basic clinical measures (as described below), provided
by the patients’ respective physicians, were also
entered into this same database and integrated into the
The experimental design in a choice-exercise survey
involves a careful selection, achieving statistical properties
of balance and orthogonality, of possible combinations
among the full set of theoretical combinations of
attributes and levels. An orthogonal design implies attributes
and levels tested independently from one another,
ensuring that importance contributions of individual features
can be isolated from the remaining (possibly
confounding) effects presented simultaneously as part of the DCE.
A balanced design implies that all attributes and levels
are being exposed an equal number of times in the DCE.
Equal exposure implies that each level has an equal
chance of being selected.
Given the expected number of possible
combinations and the information necessary to complete each
task, a full profile, fractional, factorial, balanced,
incomplete block design was used to maximize the
number of exposures of the attribute levels in each
choice task and across the experimental design.
Defficiency values range from 0 to 100, with higher
values reflecting a more balanced and orthogonal
design, with minimized variability of estimates obtained
through the DCE and consequently more accurate
results for main effects and interactions . Assuming
one 5-level and five 3-level attributes (with the
expected achievable sample size of 134 noted above),
the number of possible combinations was computed
The D-efficiency is determined by the number of cards
included and the ability to achieve balance and
orthogonality. Warren Kuhfeld’s macro %MktRuns was used to
calculate reasonable design sizes . The selection of
the total number of cards was based on maximizing the
accuracy of the model results: namely, choosing the
most cards possible to maximize observed design points
for analysis, while also choosing the fewest cards
possible per respondent to minimize fatigue and the fewest
choice sets possible that are not divisible by any 2-way
combination of the attributes and levels considered (i.e.,
“violations”). Based on these selection criteria, a design
containing 45 cards in 9 blocks was chosen, keeping the
number of cards per respondent and the number of
violations to a minimum.
An additional holdout card was then inserted in all
blocks containing the head-to-head comparison between
the absolute best case scenario (i.e., the hypothetical
profile containing all the most desirable features of the
treatment) and the absolute worst case scenario (i.e., the
hypothetical profile containing the least desirable
features of the treatment). This card was inserted in order
to determine the respondents’ ability to identify the profile
with dominant characteristics over the one with the least
desirable characteristics. Respondents who did not choose
the profile with clearly dominant characteristics were
flagged and then reported as a “risk ratio” (see Validity
Assessments section). Hence, the total number of cards
seen by a given respondent was six, for a final
(augmented) design containing 54 cards in 9 blocks.
The appropriate selection of the design size is key to
maximize the efficiency of the design. Kuhfeld’s macro
%MktEx was then used to create the combinations that
could maximize the efficiency of the design for a
resulting D-efficiency of 90.51 .
As previously noted, the survey itself included six
preference-elicitation questions, each asking respondents
to choose between two hypothetical treatments for their
PC (no real treatments or treatment names were used or
mentioned in the survey; instead they were presented as
“Medicine A” and “Medicine B”). Each hypothetical
treatment alternative shown in the preference-elicitation
questions was defined by six attributes, which were
identified through literature search and expert medical
opinion (urologists who treat mCRPC patients). The specific
attributes were as follows: (1) method of administration,
(2) OS, (3) time to a symptomatic skeletal event (SSE),
(4) reduction in the risk of bone pain, (5) risk of fatigue
and (6) lost work days following treatment. The specific
levels of each attribute, which were developed by
extracting data from the clinical studies provided in the
labels for RA-223, abiraterone and docetaxel, are shown
in Table 1.
The experimental design ensured a sufficient number
of patients saw the different combinations of attributes
Table 1 Attributes and levels represented in the DCE
Six 1-min IV injections (requiring 5 h in the
hospital) every 4 weeks; no radiation emitted
Six 1-min IV injections (requiring 5 h in the
hospital) every 4 weeks; minor radiation emitted
Six 1-min IV injections (requiring 5 h in the
hospital) every 4 weeks; some radiation emitted
Four pills taken orally once a day; 1 h at the
hospital every 2 weeks
Six 1-h IV infusions (requiring 1–2 weeks in the
hospital the first time and 7–8 h each other time)
every 3 weeks
Reduction in the
risk of bone pain
25 % chance of suppressing bone pain
50 % chance of suppressing bone pain
75 % chance of suppressing bone pain
0 % chance of fatigue
30 % chance of fatigue
60 % chance of fatigue
and levels. All attribute levels varied independently
according to this experimental design, which dictated the
number and types of choice questions presented to each
respondent when assigned to a specific block. Figure 1
represents an example of a single preference-elicitation
question that was presented to respondents. After
reviewing the information in the two presented profiles,
the patient was asked to select which of the two profiles
(Medicine A or B) he would prefer as his PC treatment.
As previously discussed, a holdout card containing the
head-to-head comparison between the absolute best and
worst case scenarios was inserted in all blocks in order
to determine the respondents’ ability to choose the
profile with dominant characteristics over the one with the
least desirable characteristics. Respondents who did not
choose the profile options with dominant characteristics
were flagged and reported as a “risk ratio.” The
withinset risk ratio, referring to the percentage of respondents
who selected the worst possible profile over the best
one, was found to be 1.5 % (i.e., two respondents).
Moreover, respondents were presented with other holdout
cards in which one of the profiles had dominant
characteristics on all attributes. For the across-set
monotonicity risk ratio, the percentage of respondents making
at least one incorrect selection in these other holdout
cards was found to be 4.5 % (i.e., six respondents). The
overall root likelihood was equal to 852, which meant
that with six alternatives in each preference-elicitation
question, the model was 5.1 times better at predicting the
preference that respondents would have had for the
alternatives presented, compared with chance. Goodness of fit
of these models was also reflected in the observed 95 %
confidence intervals ranging from +/−1 to 5 %, where the
lowest margins were found at the extremes and the
highest margins around the middle of the preference
continuum. Based on these analyses, one patient was
excluded due to inconsistent responding, yielding a final
sample of 133 patients included in the main analyses.
Patient demographics and disease history
Physicians reported patient characteristics, including
years since diagnosis, symptomatic status
(“symptomatic” being defined based on regular analgesic/opioid use
or external beam radiation therapy for bone pain),
presence and number of metastases, Eastern Cooperative
Oncology Group (ECOG) performance status, and
(1) How you take the medicine
(4) Reduction in the risk of bone pain
(6) Risk of fatigue
1-minute IV injection every 4
weeks (no radiation)
14 months until a complication
of bone metastases
10 months until a complication
of bone metastases
Fig. 1 Example preference elicitation task
history of an SSE. Patients self-reported their
demographics (age, region of residence, education, household
income, employment status, insurance status, etc.),
comorbidities (which were used to calculate a Charlson
comorbidity index [CCI] score for each patient [21, 22],
height and weight (which were used to derive a body
mass index [BMI] category), and level of pain in the past
24 h and in the past week.
The study sample was described with respect to
demographics, disease history and comorbidity variables using
frequencies and percentages for categorical variables and
counts, means and standard deviations (SDs) for
Data from the DCE were analyzed using a hierarchical
Bayesian logistic regression model. The outcome variable
of this model was choice (“Medicine A” vs. “Medicine
B”) and the predictor variables were the levels within
each attribute (i.e., method of administration, OS, time
to an SSE, reduction in the risk of bone pain, risk of
fatigue and lost work days following treatment). Effects
coding was used for each level within each attribute.
The resulting parameter estimate for each attribute level
represents the preference weight, which is defined as the
marginal utility of a change in that attribute. With the
exception of method of administration, interpolations
were made to determine the marginal utilities for the
values contained within the numeric range tested for
each attribute. Parameter estimates for the levels tested
were reported, along with their standard errors, 95 %
confidence intervals (CIs), and statistical significance.
These parameter estimates were also used to calculate
relative importance weights using the MSS approach
. Attributes with higher relative importance weights
hold stronger relationships with treatment choice than
other attributes, and these weights are on a ratio scale
(e.g., an attribute with a relative importance of 50 % is
twice as important as an attribute with a relative
importance of 25 %). Ninety-five percent CIs for these
estimates were also reported.
A total of N = 134 patients with CRPC completed the
survey. One respondent (N = 1) was excluded from the
analysis, as his responses to the DCE suggested he may
not have fully understood the task, based on the validity
assessments described above. The remaining N = 133
respondents had a mean age of 75.4 years (SD = 7.4)
(Table 2), and most were retired (74.4 %), married
(82.7 %), and from the Kanto region (83.5 %).
Patients had been diagnosed with PC a mean of
6.5 years prior (SD = 4.4) (Table 3). Over two-thirds
(69.9 %) had metastatic disease, and over a quarter of
these patients (25.8 %) had visceral metastases. A total
of 45.1 % of patients had at least one bone metastasis,
with 15.0 % of patients having 4 or more metastases.
Over a fifth (20.3 %) of patients were symptomatic.
Patients self-reported a high comorbidity burden (mean
CCI = 5.2, SD = 3.2). Nearly 25 % of the patients reported
experiencing pain in the past day and pain in the past
The full hierarchical Bayesian logistic regression model
results are reported in Table 4. All levels of all attributes
were significantly associated with choice (all p < .05).
Four-year university (%)
Less than ¥2,500,000 (%)
¥2,500,000 to ¥4,999,999 (%)
¥5,000,000 to ¥7,499,999 (%)
¥7,500,000 or more (%)
Decline to answer (%)
National Health Insurance (%)
Late Stage Elderly Insurance (%)
Other (Company/Social Insurance) (%)
None of the above (all treatment
costs paid by patient) (%)
Body mass index (BMI) category
Underweight (<18.5 kg/m2) (%)
Acceptable risk (≥18.5 kg/m2 to <23 kg/m2) (%)
Increased risk (≥23 kg/m2 to <27.5 kg/m2) (%)
High risk (≥27.5 kg/m2) (%)
Charlson comorbidity index (CCI) (Mean ± SD)
Years diagnosed with PC
Metastatic disease (%)
(of those with metastatic disease) (%)
Number of bone metastases
Spinal cord compression (%)
Radiation to the bone (%)
ECOG performance status
Total (N = 133)
The preference weights and their 95 % confidence
intervals are also displayed in Fig. 2. The greater the vertical
changes within an attribute (as illustrated for risk of
fatigue, reduction in risk of bone pain, and OS), the
stronger is the relationship between that attribute and
treatment choice. This is further illustrated in the
relative importance weights in Fig. 3. Over the range of
attributes and levels included in the survey, risk of fatigue
(relative importance [RI] = 24.9 %, 95 % CI: 24.7 %,
25.1 %) was the most important attribute, followed by
reduction in the risk of bone pain (RI = 23.2 %, 95 % CI:
23.0 %, 23.5 %), and OS (RI = 19.2 %, 95 % CI: 19.0 %,
19.4 %). Both risk of fatigue and reduction in the risk of
bone pain were at least 50 % more important to choice
than method of administration (RI = 14.5 %), time to an
SSE (RI = 13.1 %), and lost work days following
treatment (RI = 5.1 %).
Upon examining specific levels of the attributes
(Table 4 and Fig. 2), the results suggest that the risk of
fatigue held a linear relationship with patient preference,
with each increasing 1 % of fatigue having a uniform
effect on treatment choice. With respect to method of
administration, oral pills were strongly preferred over any
IV injection and infusion; IV injection was strongly
preferred over infusion (all p < .05). Also, an IV injection
with no radiation was preferred over an IV injection
with some radiation which, in turn, was preferred over
an IV injection with minor radiation (all p < .05). The
relationship between OS and preference was non-linear: a
patient values a 4-month OS extension (16-20 months)
higher than a 2-month OS extension (14–16 months).
The relationship between time to an SSE and preference
was also non-linear, such that an additional 1-month
delay in an SSE was more important when the overall
delay was 10–14 months, compared with an additional
1-month delay when the overall delay was 14–16 months
(all p < .05).
The reduction in the risk of bone pain was also
nonlinear, such that each increasing 1 % of risk reduction
was far less important to patients when the overall risk
reduction was between 25 and 50 % than when the
overall risk reduction was between 50 and 75 %. Indeed, the
differences between 25 and 50 % in risk reduction were
quite trivial and had little effect on treatment choice.
Finally, lost work days also exhibited a similar pattern to
reduction in the risk of bone pain. Although patients
had a strong preference for 0 days lost, the difference in
days lost between 3 and 5 days was relatively negligible.
Patient preferences by symptomatic status
A final analysis compared differences in preference
weights between patients who were symptomatic
versus asymptomatic. With the exception of time to an
SSE, no differences were observed. Symptomatic
patients placed significantly more importance on
delaying an SSE, as shown by a greater preference weight
for 16 months to an SSE (b = 1.1 vs. 0.9, p < .05) and
a lower preference weight for 10 months to an SSE
(b = −2.1 vs. -1.7, p < .05).
Patient preferences by demographic and health history
Additional comparisons of preference weights were
made across demographic and health history variables.
Given the lack of a priori hypotheses for these variables,
a Bonferroni correction (ranging from α = 0.0083 for
comparisons across four-category measures to an
unadjusted α = 0.05 for comparisons across two-category
measures) was made to minimize the possibility of a
spurious finding. No significant differences in
preferences weights were observed.
The findings suggest that patients with CRPC in Japan
primarily value the risk of fatigue and reduction in the
risk of bone pain when considering potential treatment
options for their PC. Indeed, these characteristics were
even more important (approximately 20 % to 30 % more
important) than OS across the attributes and levels used
in this study. Interestingly, although the risk of fatigue
had a relatively linear relationship with preference,
reduction in the risk of bone pain did not. Specifically, the
benefit of a 30 % reduction was seen as relatively
comparable to a 0 % reduction. A 60 % reduction, however,
Fig. 2 Patient preference weights (N = 133). Footnote: Bars represent 95 % confidence intervals. “Minor radiation” was described as radiation that
can be stopped by a thin sheet of paper without any risk of contaminating others with the patient’s bodily fluids; “some radiation” was described
as radiation which can be stopped by aluminum or lead and care must be taken not to contaminate others with bodily fluids for one week
was considerably more valued by patients. Although this
suggests a floor effort, in that only substantial risk
reductions are valued by patients, it is unclear why this
may be the case. Additional research is necessary.
The emphasis on minimizing risks, particularly
symptomatic risks, over survival somewhat diverges from past
research. Although symptomatic events (pain, SSEs, etc.)
have been extremely important to patients with solid
tumors , most studies conducted in cancer have found
patients value OS or progression-free survival as the
most important attribute when considering treatment
options [17, 24–26]. It is possible that the differences
between our findings and those of the literature could be a
function of tumor type (CRPC vs. other tumors),
geography (Japan vs. the West), or another aspect of the
methods (e.g., a more restricted range of OS levels vs. a
wider range of OS levels; older, late-stage patients vs.
younger, earlier-stage patients). However, the results do
suggest that patients with CRPC in Japan place
considerable value on their symptom experience when expressing
a treatment preference.
Of course, OS was still viewed as an important
attribute. Indeed, it was considered 30–40 % more important
than the method of administration and time to an SSE.
Consistent with many studies conducted in cancer [16,
17, 25, 26], method of administration held only a modest
association with medication choice. Oral administration
was most positively associated with choice, while a 1-h
IV infusion every 3 weeks was most negatively associated
with choice. Interestingly, patients had a slight
preference for “some radiation” over “minor radiation,” even
though “some radiation” would require extra effort on
the part of the patient to ensure his bodily fluids do not
contaminate others. It is unclear why this might be. It is
possible the most salient aspect of these administration
options is the injection itself (rather than the
accompanying radiation). If so, the differences between “some
radiation” and “minor radiation” may be merely due to
chance. Additional research would be necessary to
examine this issue.
A plateau effect was observed with respect to time to
an SSE. Particularly, there seemed to be little benefit to
extending time to an SSE from 14 to 16 months. In
contrast, there was a considerable benefit to extending time
to an SSE from 10 to 14 months.
Work impairment was most weakly associated with
medication choice. In part, this may be due to the fact
less than 25 % of patients held some form of
employment. The effect of 3 lost days and 5 lost days on
preference was similar; having to miss work at all mattered
more to patients than the number of days missed.
Although difficult to draw firm conclusions given the
small sample size, differences in preferences were
examined as a function of demographic and health
characteristics. Few differences were observed, suggesting the
potential homogeneity of treatment preferences among
those with CRPC in Japan. Of primary interest was the
comparison between symptomatic and asymptomatic
patients. Symptomatic patients placed significantly
more importance on delaying time to an SSE,
suggesting that patients’ actual experience with an SSE makes
them appreciate the value in delaying these events,
which may not be the case for patients who have not
experienced an SSE. No other differences in preferences
were observed between symptomatic and asymptomatic
These study results help to provide insight into the
patient experience with CRPC treatments in Japan. A
recent American Society of Clinical Oncology
statement paper reinforced the importance of capturing the
patient perspective in defining the value of a treatment
option in oncology . Because preferences can be
unique to each person, it is important to present the
various clinical benefits and risks to ensure patients
are kept informed throughout the treatment
decisionmaking process. Our results help to identify clear
trends in the treatment attributes that matter most to
CRPC patients, which can facilitate discussions
between physicians and their patients to select the best
A few limitations should be noted. Due to sample
selection during recruitment, we were only able to analyze
data from patients who had already been pre-screened
by their physicians, and the total number of patients
who were initially screened to obtain our final sample
could not be verified. Hence, patients who were healthy
enough to participate and were interested in research
may be over-represented in our sample, thereby raising
the possibility of selection bias. While we could not
confirm the extent to which the current study’s sample
represented the broader Japanese population of CRPC
patients, we made sure to recruit patients from
institutions in both east and west Japan, and the clinical and
demographic features of our sample (e.g., age, ECOG,
BMI) were generally in line with those reported in prior
studies [28, 29]. Although efforts were made to ensure a
representative sample, we could not control the precise
ratio of subgroups that may appear in the CRPC
population. Therefore, the results may not generalize to the
entire CRPC population.
The data collected in the DCE were based on
responses to hypothetical choice profiles. These choices
were intended to simulate possible clinical decisions, but
obviously do not have the same clinical, financial or
emotional consequences of actual decisions. Although
we identified the key clinical features that differ across
PC treatment options, there are a multitude of other
factors (e.g., presentation of treatment options by the
physician, Internet research, family/friend opinion, etc.) that
would be present in a real-world choice selection that
could not reasonably be accounted for in our controlled
experiment. As a result, when confronted with a real
choice, preferences may differ from our DCE results.
Thus, differences can arise between stated and actual
choices. Finally, duration of treatment and patient
burden may also have affected patient preferences, although
subgroup analysis using patient clinical background did
not show any significant differences in preference.
CRPC patients were more concerned about reduced
quality of life derived from side effects of treatment than
extension of survival, which may impact shared
decisionmaking between patients and physicians. In particular,
CRPC patients in Japan place particular importance on
the risk of fatigue, reducing the risk of bone pain, and OS
when expressing a preference for a hypothetical PC
treatment. Treatment preference largely did not vary as a
function of symptomatic status except in the case of time to
an SSE. Patients who were asymptomatic placed
significantly more importance on delaying an SSE when
expressing medication preferences.
BMI: Body mass index; CCI: Charlson comorbidity index; CI: Confidence
interval; CRPC: Castration-resistant prostate cancer; DCE: Discrete-choice
experiment; ECOG: Eastern Cooperative Oncology Group; IV: Intravenous;
mCRPC: Metastatic castration-resistant prostate cancer; OS: Overall survival;
PC: Prostate cancer; RI: Relative importance; SD: Standard deviation;
SSE: Symptomatic skeletal event
The authors would like to thank Dr. Hirotsugu Uemura of The Department of
Urology, Kinki University Faculty of Medicine for his invaluable support of
this research. The authors would also like to thank Atsuko Matsumoto and
Yoshihito Chiba, employees of Kantar Japan and PD Research for field
support, as well as Yusuke Hikichi, Masaaki Jitsu and Shigetaka Hyodo
employees of Bayer Yakuhin, Ltd. for operational and logistical support.
This study was funded by Bayer Yakuhin, Ltd. Employees of the study sponsor
(DA Ledesma, AF Mohamed, E Wang, A Narimatsu, Y Aitoku) appear as
coauthors on this paper and were involved in the study design, interpretation
and manuscript writing.
Availability of data and materials
Requests for the study materials and dataset used to support the
conclusions of this article should be directed to the corresponding author.
HU contributed to the study design, data collection, interpretation and
manuscript writing. G Kimura contributed to the study design, data
collection, interpretation and manuscript writing. AY contributed to the
study design, data collection, interpretation and manuscript writing. NM
contributed to the study design, data collection, interpretation and
manuscript writing. DAL contributed to the study design, interpretation and
manuscript writing. MDiB contributed to the study design, analysis,
interpretation and manuscript writing. AFM contributed to the study design,
interpretation and manuscript writing. EB contributed to the study design,
analysis, interpretation and manuscript writing. IMcK contributed to the
study design, interpretation and manuscript writing. EW contributed to the
study design, interpretation and manuscript writing. KC contributed to the
study design, data collection and manuscript writing. AN contributed to the
study design, interpretation and manuscript writing. YA contributed to the
study design, interpretation and manuscript writing. All authors read and
approved the final manuscript.
This study was funded by Bayer Yakuhin, Ltd. H Uemura received funding
from Bayer Yakuhin, Ltd. during the conduct of this study, G Kimura and A
Yamaguchi declare no conflicts of interest. N Matsubara received funding
from Janssen Pharmaceutical, Sanofi, Taiho Pharmaceutical, AstraZeneca and
Bayer Yakuhin, Ltd. DA Ledesma is a full-time employee of Bayer Yakuhin,
Ltd. M DiBonaventura was a full-time employee of Kantar Health, the
institution which received funding from Bayer Yakuhin, Ltd., at the time the
study was conducted. AF Mohamed is a full-time employee of Bayer
Healthcare. E Basurto is a full-time employee of Kantar Health, the institution
which received funding from Bayer Yakuhin, Ltd. I McKinnon is a full-time
employee of Kantar Health, the institution which received funding from
Bayer Yakuhin, Ltd. E Wang is a full-time employee of Bayer Healthcare. K
Concialdi is a full-time employee of Kantar Health, the institution which
received funding from Bayer Yakuhin, Ltd. A Narimatsu is a full-time employee
of Bayer Yakuhin, Ltd. Y Aitoku is a full-time employee of Bayer Yakuhin, Ltd.
Consent for publication
Ethics approval and consent to participate
The protocol and study materials were reviewed and approved by each of
the four study sites including Yokohama City University Hospital, National
Cancer Center Hospital East, Nippon Medical School and Harasanshin
General Hospital. All respondents provided written informed consent prior to
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