Patient preferences for whole-body MRI or conventional staging pathways in lung and colorectal cancer: a discrete choice experiment

Abstract

Objectives To determine the importance placed by patients on attributes associated with whole-body MRI (WB-MRI) and standard cancer staging pathways and ascertain drivers of preference. Methods Patients recruited to two multi-centre diagnostic accuracy trials comparing WB-MRI with standard staging pathways in lung and colorectal cancer were invited to complete a discrete choice experiment (DCE), choosing between a series of alternate pathways in which 6 attributes (accuracy, time to diagnosis, scan duration, whole-body enclosure, radiation exposure, total scan number) were varied systematically. Data were analysed using a conditional logit regression model and marginal rates of substitution computed. The relative importance of each attribute and probabilities of choosing WB-MRI-based pathways were estimated. Results A total of 138 patients (mean age 65, 61% male, lung n = 72, colorectal n = 66) participated (May 2015 to September 2016). Lung cancer patients valued time to diagnosis most highly, followed by accuracy, radiation exposure, number of scans, and time in the scanner. Colorectal cancer patients valued accuracy most highly, followed by time to diagnosis, radiation exposure, and number of scans. Patients were willing to wait 0.29 (lung) and 0.45 (colorectal) weeks for a 1% increase in pathway accuracy. Patients preferred WB-MRI-based pathways (probability 0.64 [lung], 0.66 [colorectal]) if they were equivalent in accuracy, total scan number, and time to diagnosis compared with a standard staging pathway. Conclusions Staging pathways based on first-line WB-MRI are preferred by the majority of patients if they at least match standard pathways for diagnostic accuracy, time to diagnosis, and total scan number.

Full text

ONCOLOGY
Patient preferences for whole-body MRI or conventional staging
pathways in lung and colorectal cancer: a discrete choice experiment
Anne Miles
1
&Stuart A. Taylor
2
&Ruth E. C. Evans
1
&Steve Halligan
2
&Sandy Beare
3
&John Bridgewater
4
&Vicky Goh
5
&
Sam Janes
6
&Neil Navani
7
&Alf Oliver
8
&Alison Morton
8
&Andrea Rockall
9,10
&Caroline S. Clarke
11
&Stephen Morris
12
&
on behalf of the STREAMLINE investigators
Received: 31 October 2018 / Revised: 22 February 2019 / Accepte d: 11 March 2019 / Published online: 1 April 2019
#The Author(s) 2019
Abstract
Objectives To determine the importance placed by patients on attributes associated with whole-body MRI (WB-MRI) and
standard cancer staging pathways and ascertain drivers of preference.
Methods Patients recruited to two multi-centre diagnostic accuracy trials comparing WB-MRI with standard staging pathways in
lung and colorectal cancer were invited to complete a discrete choice experiment (DCE), choosing between a series of alternate
pathways in which 6 attributes (accuracy, time to diagnosis, scan duration, whole-body enclosure, radiation exposure, total scan
number) were varied systematically. Data were analysed using a conditional logit regression model and marginal rates of
substitution computed. The relative importance of each attribute and probabilities of choosing WB-MRI-based pathways were
estimated.
Results A total of 138 patients (mean age 65, 61% male, lung n= 72, colorectal n= 66) participated (May 2015 to September
2016). Lung cancer patients valued time to diagnosis most highly, followed by accuracy, radiation exposure, number of scans,
and time in the scanner. Colorectal cancer patients valued accuracy most highly, followed by time to diagnosis, radiation
exposure, and number of scans. Patients were willing to wait 0.29 (lung) and 0.45 (colorectal) weeks for a 1% increase in
pathway accuracy. Patients preferred WB-MRI-based pathways (probability 0.64 [lung], 0.66 [colorectal]) if they were equiv-
alent in accuracy, total scan number, and time to diagnosis compared with a standard staging pathway.
Conclusions Staging pathways based on first-line WB-MRI are preferred by the majority of patients if they at least match
standard pathways for diagnostic accuracy, time to diagnosis, and total scan number.
Key Points
•WB-MRI staging pathways are preferred to standard pathways by the majority of patients provided they at least match standard
staging pathways for accuracy, total scan number, and time to diagnosis.
•For patients with lung cancer, time to diagnosis was the attribute valued most highly, followed by accuracy, radiation dose,
number of additional scans, and time in a scanner. Preference for patients with colorectal cancer was similar.
•Most (63%) patients were willing to trade attributes, such as faster diagnosis, for improvements in pathway accuracy and
reduced radiation exposure.
Keywords Magnetic resonance imaging .Cancer .Patient preference .Positron emission tomography .Tomography, X-ray
computed
Abbreviations
CT Computed tomography
DCE Discrete choice experiment
MRI Magnetic resonance imaging
PET-CT Positron emission tomography
WB-MRI Whole-body MRI
Anne Miles and Stuart A Taylor are joint first authors because both
authors were equally involved in the design, analysis, and write-up of the
results.
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s00330-019-06153-4) contains supplementary
material, which is available to authorized users.
*Anne Miles
ae.miles@bbk.ac.uk
Extended author information available on the last page of the article
European Radiology (2019) 29:3889–3900
https://doi.org/10.1007/s00330-019-06153-4

Introduction
Cancer staging pathways are complex, typically comprising a
variety of imaging modalities including ultrasound, computed
tomography (CT), and positron emission tomography (PET)
CT. Multi-modality pathways are inconvenient for patients
and prolong time to treatment. Conversely, whole-body mag-
netic resonance imaging (WB-MRI) may facilitate staging
with a single investigation, while simultaneously achieving
greater accuracy for metastatic disease, without imparting i-
onising radiation [1,2]. However, patients perceive WB-MRI
as more challenging than conventional staging scans [3], par-
ticularly among those with coexisting physical conditions
and/or high anxiety levels [4]. MRI scan acquisition is noisy
and whole-body imaging can take up to 1 h, much longer
than standard CT or PET-CT. In addition, WB-MRI elicits
claustrophobia in a substantial proportion of patients, which
can terminate the scan prematurely [5]. Furthermore, WB-
MRI may itself generate future tests such as PET-CT for
equivocal findings.
Patients value staging accuracy highly [6]aswellasrapid
diagnosis [7].Therelativeimportanceplacedbypatientson
the comparative attributes of WB-MRI and standard staging
pathways is unknown currently. For example, it is unclear
what improvement in diagnostic accuracy patients would
trade for lengthier scan times, or a longer wait before final
diagnosis.
The aim of this study was to determine the relative impor-
tance placed by patients on a range of attributes associated
with WB-MRI and standard staging pathways by performing
a discrete choice experiment and to ascertain which of these
attributes govern patient preferences for one pathway over the
other.
Materials and methods
Discrete choice experiments (DCE) elicit preferences by ask-
ing individuals to indicate their choice between two or more
options, where each option contains characteristics or attri-
butes (e.g. scan accuracy, scan duration) that are varied and
are differentiated by values or levels of each attribute. By
analysing the choices people make, the relative importance
of different attributes can be determined. The international
DCE guidelines were followed for study design and analysis
[8–10].
Patients and recruitment
Recruitment took place within the context of two prospec-
tive, multi-centred cohort trials investigating the diagnos-
tic accuracy and cost-effectiveness of WB-MRI compared
with standard pathways for staging newly diagnosed lung
and colorectal cancers (‘Streamline L’and ‘Streamline
C’). The trial protocols have been published previously
[11]. For Streamline L, patients were recruited from 16
hospitals and underwent WB-MRI at one of seven centres.
For Streamline C, patients were recruited from 16 hospi-
tals and underwent WB-MRI at one of eight centres.
Across both trials, WB-MRI was performed on scanners
from three major vendors.
Recruits underwent WB-MRI (the research interven-
tion) in addition to conventional staging scans. The
WB-MRI scans were performed according to a mini-
mum dataset, including axial whole-body (vertex to
mid-thigh) axial diffusion and axial T2- and T1 (pre-
and post-intravenous gadolinium-containing contrast me-
dium)-weighted imaging. A Dixon sequence was used if
available on the scanner. Slice thickness was between 5
and 7 mm and post gadolinium images were acquired at
a minimum through the liver (portal phase), lung (equi-
librium phase), and brain. Exact parameters differed be-
tween sites, but all sites utilised protocols that could be
completedin1horless.
Patients recruited to the Streamline trials were initially in-
vited to either an interview [3] or questionnaire study (both
aimed at assessing patients’experience of staging scans) [4]
(Fig. 1). Once recruitment to these studies was complete, pa-
tients were exclusively invited to complete the current DCE
study [11].
Ethical approval for this study was granted by the Camden
and Islington NRES committee on 03/10/2012, project num-
bers: 12/LO/1176 (StreamlineC) and 12/LO/1177 (Streamline
L). Participants gave written informed consent for participa-
tion in the DCE study.
DCE questionnaires were posted to patients by the Clinical
Trials Unit within 1–2 days of consenting to trial participation
and while they were still undergoing staging. Patients were
provided with stamped addressed reply envelopes and were
paid £20 upon receipt of a completed questionnaire.
Consecutive patients were approached to participate until a
minimum of 42 patients had returned a questionnaire for each
cancer type cohort (see power calculation supplementary
data).
Attributes and levels
DCE attributes were selected by study investigators to
capture known or potential important differences between
WB-MRI and standard staging pathways; these were in-
formed by findings from the patient interview and ques-
tionnaire studies described above [3,4]. The Streamline
trials were designed to determine whether WB-MRI is
more accurate than standard staging pathways for detect-
ing metastatic disease, while simultaneously decreasing
thenumberofindividualscans, thereby reducing time to
3890 Eur Radiol (2019) 29:3889–3900

diagnosis. Accordingly, accuracy, scan number, and time
to diagnosis were selected as potentially important attri-
butes. In addition, the following attributes were also in-
cluded, having also been identified as potentially impor-
tant: scan duration, need for the whole body and head to
be enclosed by the scanner, and increased cancer risk due
to exposure to ionising radiation.
Credible levels for each attribute were chosen based on
either known characteristics, such as scan duration, or after
appropriate literature review, for example radiation exposure
and scan/pathway accuracy [12–14]. The number of scans in
each pathway required to reaching a final diagnosis was based
on typical staging pathways, supported by data accrued during
the main trials.
Attributes and levels are summarised in Table 1.
Questionnaire design
Of the six attributes, five had three levels and one had two
levels. The total number of attribute combinations was there-
fore 486 (= 3
5
×2
1
). Each question presented patients with a
binary choice set (pathway A vs. pathway B), resulting in a
possible 235,710 choices (= 486 × 485). To reducethe number
of choices to a manageable number, an orthogonal fractional
main effects design was applied for pathway A [15]. Pathway
B was generated by shifting the attribute level up by one
category for each attribute (e.g. if the time in a scanner was
10 [30] {60} min in Pathway A then it was shifted to 30 [60]
{10} min in Pathway B). We reduced the number of choice
sets to 18, which were split into two blocks of nine, and half
the respondents in each group were assigned to each block.
Patients were randomly assigned to complete either choice
Fig. 1 Flow diagram of
participants through the study
(May 2015–September 2016)
Table 1 Attributes and attribute levels
Attributes Attribute levels
Time in a scanner 10 min 30 min 60 min
Time to reach a final diagnosis 1 week 3 weeks 5 weeks
Associated increase in cancer risk due to radiation exposure None 1 in 1000 risk of cancer 2 in 1000 risk of cancer
Number of additional staging scans before final diagnosis 0 1 2
Accuracy for metastatic disease (%) 85 90 95
Need for whole body and head to be in a scanner No Yes –
Eur Radiol (2019) 29:3889–3900 3891

sets 1 to 9 (Questionnaire A) or 10 to 18 (Questionnaire B) and
asked to complete all 9 choice sets. A similar approach has
been used in previous DCE studies, balancing the desire to
include more choice sets to cover a wider number of attribute
combinations against respondent burden [16]. The choice sets
were presented in a random order within each questionnaire.
We did not include an opt-out or ‘neither’option as patients
recruited tothe Streamline trials were unlikely to choose not to
undergo staging. Prior to administering the DCE question-
naire, its burden and content were reviewed and modified
for clarity by the Streamline trial management group, which
included 2 patient representatives.
An example of a choice set is shown in Fig. 2.
A range of demographic and health-related variables were
also collected from participants (see Questionnaire
supplementary data), along with self-rated health, presence
of comorbidities, and positive and negative mood (using the
PANAS, phrased to ask about current mood [17,18]and
whether patients had already had a WB-MRI at the time of
completing the questionnaire). Missing data for age and gen-
der were populated with data from the main trial (with patient
consent).
Participants were also asked whether they preferred WB-
MRIorstandardtests(“If you had to have JUST ONE of the
tests which one would you prefer?”).
An example administered questionnaire (Questionnaire A
for lung cancer patients) is shown in supplementary data.
Analysis
The analysis is described in detail in supplementary data.
In brief, DCE data were analysed using a conditional logit
regression model (fixed effects logit) where the outcome was
the test preference (scan A or B) and the variables in the
equation were the individual attributes. We undertook explor-
atory analyses to investigate whether within each cohort pref-
erences varied by sample sub-groups. We conducted likeli-
hood ratio tests to test the null hypothesis that none of the
attributes were related to preferences.
The relative importance of each attribute was calculated as
the difference in preference weights between the best or most
preferred level of each attribute and the worst or least preferred
level of the same attribute [19].
We used the regression coefficients to compute marginal
rates of substitution (MRS). The MRS allows direct assess-
ment of how much of one attribute participants are willing to
trade for one unit of another attribute and therefore enables a
comparison of different attributes on a common scale.
We also used the regression analysis results to calculate
the predicted probabilities of choosing alternative path-
ways (for example based on WB-MRI), compared with a
default standard staging pathway The selected default
standard pathway was PET-CT plus one additional scan
(lung cancer), or CT plus 1 additional scan (colorectal
cancer) (Figs. 3and 4).
Fig. 2 Example of a choice set
3892 Eur Radiol (2019) 29:3889–3900

We compared default staging pathways to alternative path-
ways with varying attribute levels based around PET-CT, CT,
and WB-MRI. We considered several scenarios for WB-MRI-
based pathways, although fixed the following attributes: (i)
60 min in the scanner, (ii) no risk of cancer from radiation
exposure, and (iii) requirement for the whole body and head
to be enclosed. We then varied combinations of time to diag-
nosis, number of additional scans, and accuracy of WB-MRI
individually and jointly. Non-traders were included in the
analysis.
All data were analysed using SPSS version 24 and Stata
version 13.
Results
Participants
One hundred thirty-eight patients completed part or all of the
questionnaires, 72 recruited to Streamline L, and 66 recruited to
Streamline C. A total of 128 completed all 9 choice sets (66 in
Streamline L, 62 in Streamline C). Demographic data are shown
in Table 2. Most patients had already undergone WB-MRI at the
time of completing the DCE (113 [86%] of 131 answering the
question), with no significant difference between the cohorts
(Streamline C, 55/64, 86%; Streamline L, 58/67, 87%).
Regression analysis
Likelihood ratio tests rejected the null hypothesis that none of
the attributes were related to preferences (Table 3). Overall,
participants preferred (i) to wait less time for a diagnosis, (ii) a
lower dose of radiation exposure, (iii) fewer additional scans,
and (iv) greater test accuracy. Conditional on these factors,
preferences were not influenced significantly by time in the
scanner or the need for the whole body and head to be
enclosed. Preferences differed significantly between lung can-
cer and colorectal cancer patients. Time in the scanner did
significantly influence the preferences of lung cancer patients.
Both cohorts preferred tests with higher accuracy, but the
preference was significantly greater for patients with colorec-
tal cancer (p= 0.03). For the other attributes, preferences were
not significantly different between the two cohorts.
Relative importance of the attributes
Over the range of levels included in the study, for patients with
lung cancer, time to diagnosis was the attribute valued most
highly, followed by accuracy, radiation dose, number of addi-
tional scans, and time in a scanner (Table 3). For patients with
colorectal cancer, accuracy was valued most highly, followed
by time to diagnosis, radiation dose, and number of additional
scans.
In exploratory analyses, within each cohort, there
were no significant differences in preferences according
to sub-groups stratified by gender, age, comorbidities,
employment status, marital status, and positive mood.
For patients with lung cancer (but not colorectal), there
were significant variations when patients were stratified
by home ownership, education, and self-rated health
(supplementary data, Tables A1 to A3). For example,
the influence of diagnostic accuracy on preferences
was greater for lung cancer patients who were home-
owning or had higher self-rated health.
Overall, 32/59 (54.2%) lung cancer patients and 45/
61 (73.8%) colon cancer patients who answered the
question selected WB-MRI over standard scans. There
were no significant differences in attribute preferences
between colorectal cancer patients who preferred WB-
MRIcomparedwiththosewhostatedapreferencefor
standard staging scans. Conversely, in patients with lung
cancer, those stating an overall preference for standard
staging scans preferred less time in a scanner and to not
have their whole body and head enclosed (supplementa-
ry data, Table A4).
Traders vs non-traders
Thirty-seven percent (n= 51/138) of patients were ‘non-
traders’(non-traders are participants whose preferences
are determined by a single attribute, which they do not
trade-off against any of the other attributes presented;
suppose for example that a respondent was a non-
trader with respect to the ‘time to reach a final diagno-
sis’attribute, this would mean they would always select
the pathway with the lowest time to reach a final diag-
nosis, irrespective of the levels of any of the other at-
tributes). The most common attributes patients would
not trade were higher accuracy, faster time to diagnosis,
and reduced cancer risk due to scan-related radiation
exposure (see supplementary data, Table A5).
Marginal rates of substitution
Tab le 4shows results of the MRS analysis. Lung cancer pa-
tients were willing to wait just over 1 extra week (MRS =
−1.11) in return for a 1 in 1000 reduction in the risk of cancer
from radiation exposure. They were willing to wait around an
extra half a week (MRS = −0.48) to avoid an additional scan
and around a third of a week (MRS = 0.29) for every 1%
increase in accuracy (i.e. 1.45 weeks for a 5% increase in
accuracy). The willingness to wait longer for a diagnosis for
a reduction in the time in a scanner was negligible (−0.02).
These figures were broadly similar to colorectal cancer pa-
tients. For example, they were willing to wait just under half
Eur Radiol (2019) 29:3889–3900 3893

a week (MRS = 0.45) for every 1% increase in accuracy (i.e.
2.25 weeks for a 5% increase in accuracy).
Predicted probabilities
Figures 3and 4detail the predicted probabilities of choos-
ing alternative pathways, compared with a default standard
staging pathway for lung (PET-CT plus one additional
scan) and colorectal cancer (CT plus one additional scan),
respectively. Lung cancer patients were more likely to pre-
fer a WB-MRI-based pathway (probability 0.64) if it was
as accurate, required the same total number of scans, and
had the same time to diagnosis as the default staging path-
way. If the WB-MRI pathway was more accurate, reduced
time to diagnosis and/or required fewer scans than the de-
fault staging pathway, then the preference for WB-MRI
was even stronger. For example, the probability of choos-
ing WB-MRI if it was more accurate than the default path-
waywas0.76,risingto0.89ifWB-MRIwasmoreaccu-
rate, reduced time to diagnosis and meant fewer scans. The
same patterns were also found for colorectal cancer pa-
tients compared with their default staging pathway.
Fig. 3 Predicted probabilities of choosing an alternate staging pathways
in comparison to a default staging pathway (PET-CT plus one additional
scan) (lungcancer patients). Description of tests: Default staging pathway
(PET-CT plus 1 additional scan) in every case: 30-min time in a scanner,
3 weeks to diagnosis, 2/1000 cancer risk due to radiation dose, 1
additional scan, 90% accuracy, no need for whole body and head to be
in a scanner. Worst possible test: 60-min time in a scanner, 5 weeks to
diagnosis, 2/1000 cancer risk due to radiation dose, 2 additional scans,
85% accuracy, need for whole body and head to be in a scanner. PET-CT
plus 2 additional scans: 30-min time in a scanner, 5 weeks to diagnosis,
2/1000 cancer risk due to radiation dose, 2 additional scans, 90%
accuracy, no need for whole body and head to be in a scanner. CT plus
2 additional scans: 10-min time in a scanner, 5 weeks to diagnosis, 2/1000
cancer risk due to radiation dose, 2 additional scans, 90% accuracy, no
need for whole body and head to be in a scanner. WB-MRI scenario 1:
longer scan time, no radiation, whole body enclosed, longer time to
diagnosis, more scans= 60-min time in a scanner, 5 weeks to diagnosis,
0/1000 cancer risk due to radiation dose, 2 additional scans, 90%
accuracy, need for whole body and head to be in a scanner. CT plus 1
additional scan: 10 min time in a scanner, 3 weeks to diagnosis, 1/1000
cancer risk due to radiation dose, 1 additional scan, 90% accuracy, no
need for whole body and head to be in a scanner. WB-MRI scenario 2:
longer scan time, no radiation, whole body enclosed = 60-min time in a
scanner, 3 weeks to diagnosis, 0/1000 cancer risk due to radiation dose, 1
additional scan, 90% accuracy, need for whole body and head to be in a
scanner. WB-MRI scenario 3: longer scan time, no radiation, whole body
enclosed, more accurate = 60-min time in a scanner, 3 weeks to diagnosis,
0/1000 cancer risk due to radiation dose, 1 additional scan, 95% accuracy,
need for whole body and head to be in a scanner. WB-MRI scenario 4: longer
scan time, no radiation, whole body enclosed, quicker time to diagnosis,
fewer scans = 60-min time in a scanner, 1 week to diagnosis, 0/1000 cancer
risk due to radiation dose, 0 additional scans, 90% accuracy, need for
whole body and head to be in a scanner. WB-MRI scenario 5: longer
scan time, no radiation, whole body enclosed, more accurate, quicker
time to diagnosis, fewer scans = 60-min time in a scanner, 1 week to
diagnosis, 0/1000 cancer risk due to radiation dose, 0 additional scans,
95% accuracy, need for whole body and head to be in a scanner. Best
possible pathway: 10-min time in a scanner, 1 week to diagnosis, 0/1000
cancer risk due to radiation dose, 0 additional scans, 95% accuracy, no
need for whole body and head to be in a scanner. The comparison
indicated by the dashed box (WB-MRI scenario 2) is one in which
WB-MRI differs from the default staging pathway according to
established differences (time in a scanner, exposure to ionising
radiation, need for the whole body and head to be inside the scanner)
but for which other attributes (time to diagnosis, number of additional
scans, accuracy) are assumed to be the same between the two pathways
3894 Eur Radiol (2019) 29:3889–3900

Discussion
The acceptability or otherwise of WB-MRI as a replacement
for current multi-modality pathways is dependent on many
factors, most notably diagnostic accuracy and patient accept-
ability, the latter governed by the contrasting attributes of al-
ternative staging pathways. Using a DCE, we identified those
desirable attributes that most influence patient preferences and
identified circumstances in which WB-MRI pathways would
be preferred by the majority over current staging pathways.
As would be expected, we found that patients generally pre-
fer to wait less time for staging, reduce the cancer risk due to
radiation exposure, and undergo fewer scans with greater accu-
racy. For patients with lung cancer, time to diagnosis was the
attribute valued most highly, followed by accuracy, cancer risk
from radiation exposure, number of additional scans, and time
in a scanner. For patients with colorectal cancer, accuracy was
valued most highly, followed by time to diagnosis, cancer risk
from radiation exposure, and number of additional scans.
Diagnostic accuracy however had a greater influence on the
preferences of lung cancer patients who were home-owning
or had higher self-rated health. Differences between the two
cohorts could therefore reflect demographic and health differ-
ences, with colorectal cancer patients reporting lower
Fig. 4 Predicted probabilities of choosing an alternate staging pathways
in comparison to a default staging pathway (CT plus one additional scan)
(colorectal cancer patients). Description of tests: Default staging pathway
(CT plus 1 additional scan) in every case: 10-min time in a scanner,
3 weeks to diagnosis, 1/1000 cancer risk due to radiation dose, 1
additional scan, 90% accuracy, no need for whole body and head to be
in a scanner. Worst possible pathway: 60-min time in a scanner, 5 weeks
to diagnosis, 2/1000 cancer risk due to radiation dose, 2 additional scans,
85% accuracy, need for whole body and head to be in a scanner. PET-CT
plus 2 additional scans: 30-min time in a scanner, 5 weeks to diagnosis,
2/1000 cancer risk due to radiation dose, 2 additional scans, 90%
accuracy, no need for whole body and head to be in a scanner. CT plus
2 additional scans: 10-min time in a scanner, 5 weeks to diagnosis, 2/1000
cancer risk due to radiation dose, 2 additional scans, 90% accuracy, no
need for whole body and head to be in a scanner. WB-MRI scenario 1:
longer scan time, no radiation, whole body enclosed, longer time to
diagnosis, more scans= 60-min time in a scanner, 5 weeks to diagnosis,
0/1000 cancer risk due to radiation dose, 2 additional scans, 90%
accuracy, need for whole body and head to be in a scanner. PET-CT
plus 1 additional scan: 30-min time in a scanner, 3 weeks to diagnosis,
2/1000 cancer risk due to radiation dose, 1 additional scan, 90% accuracy,
no need for whole body and head to be in a scanner. WB-MRI scenario 2:
longer scan time, no radiation, whole body enclosed = 60-min time in a
scanner, 3 weeks to diagnosis, 0/1000 cancer risk due to radiation dose, 1
additional scan, 90% accuracy, need for whole body and head to be in a
scanner. WB-MRI scenario 3: longer scan time, no radiation, whole body
enclosed, more accurate = 60-min time in a scanner, 3 weeks to diagnosis,
0/1000 cancer risk due to radiation dose, 1 additional scan, 95% accuracy,
need for whole body and head to be in a scanner. WB-MRI scenario 4:
longer scan time, no radiation, whole body enclosed, quicker time to
diagnosis, fewer scans= 60-min time in a scanner, 1 week to diagnosis,
0/1000 cancer risk due to radiation dose, 0 additional scans, 90%
accuracy, need for whole body and head to be in a scanner. WB-MRI
scenario 5: longer scan time, no radiation, whole body enclosed, more
accurate, quicker time to diagnosis, fewer scans = 60-min time in a
scanner, 1 week to diagnosis, 0/1000 cancer risk due to radiation dose,
0 additional scans, 95% accuracy, need for whole body and head to be in a
scanner. Best possible pathway: 10-min time in a scanner, 1 week to
diagnosis, 0/1000 cancer risk due to radiation dose, 0 additional scans,
95% accuracy, no need for whole body and head to be in a scanner. The
comparison indicated by the dashed box (WB-MRI scenario 2) is one in
which WB-MRI differs from the default staging pathway according to
established differences (time in a scanner, exposure to ionising radiation,
need for the whole body and head to be inside the scanner) but for which
other attributes (time to diagnosis, number of additional scans, accuracy)
are assumed to be the same between the two pathways
Eur Radiol (2019) 29:3889–3900 3895

deprivation, higher educational level, and better health than
lung cancer patients. However, the analyses by sub-group with-
in each cohort were exploratory and further research to explore
the observed variations would be beneficial.
The length of time in the scanner was a significant factor
affecting preferences for patients with lung cancer only, likely
because this group finds prolonged scans more challenging. In
support, previous data from patients recruited to the Streamline
trials have shown that in general, patients with lung cancer find
WB-MRI more demanding, often because they cannot hold
their breath easily or lie flat for long periods [3].
Cancer risk from radiation exposure significantly influ-
enced the preferences of both cohorts, although was deemed
less important than test accuracy and time to diagnosis. The
long-term prognosis of the recruited cohort is clearly heavily
dependent on their age and underlying primary cancer diag-
nosis rather than the theoretical small additional cancer risk
due to staging investigations. It is likely improved patient
education would reduce their perceived importance of ionis-
ing radiation exposure, but, nonetheless, long-term survivor-
ship is common for both cancers (particularly colorectal) and
exposure to radiation is clearly a legitimate patient concern.
Just over a third of participants were ‘non-traders’,with
preferences anchored to a single attribute, most commonly
diagnostic accuracy. Traders (who formed the majority) were
willing to accept inferior levels of one attribute in turn for
Table 2 Demographic and psychological characteristics of the sample. Numbers are N(percent) unless stated otherwise
All patients Lung cancer patients Colorectal cancer
patients
Group
differences
1
Demographics
Age
a
(mean (SD)) 64.7 (10.9) (n= 138) 66.0 (10.8) (n= 72) 63.2 (10.9) (n=66) p=0.122
Male gender
a
84 (60.9) (n=138) 42(59.2) (n= 72) 41 (62.1) (n=66) p=0.723
White ethnicity
b
112 (84.2 ) (n=133) 59(85.5) (n= 69) 53 (82.8) (n=64) p=0.670
Educational qualifications
c
None 35 (28.2) 28 (44.4) 7 (11.5) p<0.001
Below degree level 39 (31.5) 17 (27.0) 22 (36.1)
Degree level or equivalent 50 (40.3) (n=124) 18(28.6) (n= 63) 32 (52.5) (n=61)
Home ownership (yes)
c
82 (64.6) (n=127) 34(50.0) (n= 68) 48 (81.4) (n=59) p<0.001
Car ownership (yes)
c
114 (87.0 ) (n=131) 61(88.4) (n= 69) 53 (85.5) (n=62) p=0.619
Marital status
b
Married/cohabiting 85 (63.4) 42 (58.3) 43 (69.4) p=0.403
Single 22 (16.4) 13 (18.1) 9 (14.5)
Divorced, separated, widowed 27 (20.1) (n=134) 17(23.6) (n= 72) 10 (16.1) (n=62)
Employment status
b
Employed full-time, part-time, self-employed, full-time
homemaker
46 (34.1) 17 (23.9) 29 (45.3) p=0.018
Retired 74(54.8) 43(60.6) 31(48.4)
Unemployed, disabled, or too ill to work 15 (11.1) (n=135) 11(15.5)(n= 71) 4 (6.3) (n=64)
Health
Self-rated health
b
Very bad, bad, or fair 60 (44.1) 41 (57.7) 19 (29.2) p=0.001
Good or very good 76 (55.9) (n=136) 30 (42.3) (n= 71) 46 (70.8) (n=65)
Presence of comorbidities
a
77 (55.8) (n=138) 48(66.7) (n= 72) 29 (43.9) (n=66) p=0.007
Psychological variables
Negative mood
b
(mean (SD)) 18.01 (7.45) (n= 136) 18.76 (7.62) (n= 71) 17.20 (7.23) (n=65) p=0.224
Positive mood
b
(mean (SD)) 27.32 (7.92) (n= 137) 25.73 (7.72) (n= 71) 29.03 (7.84) (n=66) p=0.014
a
No missing data
b
Missing data less than 5%
c
Missing data greater than 5%
1
Patients recruited to Streamline C were more likely to have educational qualifications, own a home, and be in employment than patients recruited to
Streamline L. They were less likely to report comorbidities and more likely to rate their current health as good or very good and report higher levels of
positive mood than Streamline L patients
3896 Eur Radiol (2019) 29:3889–3900

Table 3 Results of conditional logit regression analysis by group
All patients Lung cancer patients Colorectal cancer patients
Attributes Levels Coefficient (95% CI) RI Coefficient (95% CI) RI Coefficient (95% CI) RI pvalue
b
Time in a scanner Minutes −0.002 (−0.007, 0.002)
a
–−0.008 (−0.014, −0.002) 0.04 0.005 (−0.002, 0.012)
a
–0.01
Time to diagnosis Weeks −0.355 (−0.411, −0.300) 1.42 −0.372 (−0.449, −0.295) 1.49 −0.349 (−0.432, −0.265) 1.40 0.70
Radiation dose Risk of cancer (/1000) −0.421 (−0.521, −0.320) 0.84 −0.413 (−0.551, −0.274) 0.83 −0.436 (−0.587, −0.286) 0.87 0.83
Number of additional scans Number −0.192 (−0.299, −0.084) 0.38 −0.179 (−0.330, −0.028) 0.36 −0.224 (−0.382, −0.067) 0.45 0.69
Accuracy Percentage 0.128 (0.107, 0.150) 1.28 0.109 (0.079, 0.138) 1.09 0.156 (0.122, 0.190) 1.56 0.03
Needforwholebodyandheadtobeinascanner No ––––––
Yes 0. 0 20 (−0.129, 0.170)
a
0.017 (−0.190, 0.224)
a
−0.007 (−0.233, 0.220)
a
0.88
Observations/respondents 2362/138 1230/72 1132/66 0.02
Likelihood ratio χ
2
(pvalue) 445.5 (< 0.01) 221.9 (< 0.01) 238.9 (< 0.01)
NB: Different attributes do not have the same unit of change so cannot be directly compared with one another
CI, confidence interval; RI, relative importance (see text); RI is calculated for attributes with coefficients that were significantly different from zero
a
Coefficient not significantly different from zero; all other coefficients significant at pvalue < 0.05
b
pvalues are from χ
2
tests that coefficients are equal for lung cancer and colorectal cancer patients. pvalues < 0.05 indicate coefficients are significantly different between groups. pvalue in the bottom row
is for joint test across all coefficients
Table 4 Marginal rates of substitution across all attributes
Lung cancer patients Colorectal cancer patients
Time in a
scanner
Time to
diagnosis
Radiation dose Number of
additional
scans
Accuracy Time to
diagnosis
Radiation dose Number of
additional
scans
Accuracy
Numerator of MRS Willingness
to wait in
scan (min)
Willingness to
wait for
diagnosis
(weeks)
Willingness to have an
additional 1/1000 cancer risk
due to radiation exposure
Willingness
to have an
extra scan
Willingness for
a1%increasein
accuracy
Willingness to
wait for
diagnosis
(weeks)
Willingness to have an
additional 1/1000 cancer risk
due to radiation exposure
Willingness
to have an
extra scan
Willingness for
a1%increasein
accuracy
Time in the scanner –−0.02 −0.02 −0.05 0.08 NS NS NS NS
Time to diagnosis −45.23 –−0.90 −2.08 3.42 –−0.80 −1.55 2.23
Radiation exposure −50.20 −1.11 –−2.31 3.80 −1.25 –−1.94 2.79
Number of
additional scans
−21.77 −0.48 −0.43 –1.65 −0.64 −0.51 –1.44
Accuracy 13.21 0.29 0.26 0.61 –0.45 0.36 0.70 –
NS indicates that the coefficient on time in a scanner is non-significant so the MRS is not computed. The MRS for the willingness for time on the scanner for colorectal cancer patients is not reported because
the coefficient on time in a scanner in this group is non-significant. The MRS with regards need for whole body and head to be in a scanner is not reported for either group because in both cases, the
coefficient is non-significant
Eur Radiol (2019) 29:3889–3900 3897

improvement in another. For example, the marginal rates of
substitution suggest that in return for a 5% improvement in
accuracy, patients with colorectal cancer would be prepared to
wait an additional 2.25 weeks for their final staging diagnosis
and undergo an additional 3.5 scans. Similarly, patients with
lung cancer are willing to wait 1.45 weeks for their final stag-
ing diagnosis or undergo an additional 3.05 scans for the same
5% accuracy improvement. Many patients were also willing
to trade for a reduction in cancer risk due to radiation expo-
sure. For example, to avoid a 1/1000 increase in cancer risk
from scan-related radiation exposure, lung cancer patients
would wait around 1.11 weeks more for their final diagnosis,
despite its likely limited impact on overall prognosis.
This trading of attributes is reflected in overall patient pref-
erences for the various pathway scenarios presented. Patients
with lung or colorectal cancer were more likely to prefer a
WB-MRI pathway compared with default staging as long as
it was as accurate and results in the same scan number and
time to diagnosis. As noted above, this suggests that a lack of
radiation exposure is believed important by patients. If, how-
ever, WB-MRI is more accurate than the standard pathway,
reduces time to diagnosis, and/or results in fewer scans, then
the preference for WB-MRI is even stronger. Indeed, if WB-
MRI is more accurate, reduces time to diagnosis, and results in
fewer scans, the probability of preferring it over the standard
staging pathway is 0.89 in patients with lung cancer and 0.99
in patients CRC.
Likelihood ratio tests rejected the null hypothesis that none
of the attributes were related to preferences. This also provides
some reassurance that the problem of multiple comparisons
did not arise in our analyses.
Our results were very similar between patients with lung and
colorectal cancer, and so we envisage the data could potentially
be extrapolated to staging other cancers. However, there were
some differences between lung and colorectal cancer patients,
which may be in part due to underlying differing comorbidities.
It is possible, for example, that patients with pain due to bony
metastasis (for example in myeloma) may find prolonged WB-
MRI protocols more challenging and this should be investigat-
ed. Furthermore, research on patient preferences for WB-MRI
vs CT in patients undergoing lymphoma staging showed pa-
tients found WB-MRI less unpleasant and less worrisome than
CT [20]. The authors attributed their findings to the more inva-
sive preparation required for CT in their scan protocol (patients
required intravenous lines and had to consume oral contrast). In
our study, WB-MRI protocols required IV gadolinium which
may help explain discrepant findings.
The study has limitations. It was powered to detect differ-
ences between the two cancer cohorts, but not to detect differ-
ences within each cancer type. This may explain non-significant
effects across a number of different demographics. The need to
enclose the whole body and head did not influence scan prefer-
ences when balanced against other test attributes. Previous work
has demonstrated that claustrophobia is problematic for many
patients undergoing MRI [5,21]. Patients recruited to the
Streamline trials were, by definition, willing to undergo WB-
MRI and may therefore not be representative of an unselected
cancer patient cohort, particularly given the general prevalence
of claustrophobia. Indeed, the majority of participants had al-
ready had the WB-MRI scan prior to completing the study. Of
note, however, when given a binary choice, lung cancer patients
stating an overall preference for standard staging scans preferred
less time in a scanner and not to have their whole body and head
enclosed compared with those preferring WB-MRI.
Future research could assess what attributes WB-MRI
would need to possess in order to appeal to people who are
more reluctant to undergo a full body scan.
In conclusion, patients with cancer are willing to trade stag-
ing pathway attributes, for example prolonging time to diag-
nosis, in return for increased accuracy and/or reduced diagnos-
tic radiation exposure. Staging pathways based on first-line
WB-MRI are preferred by most patients if they at least match
standard pathways for diagnostic accuracy, time to diagnosis,
and total scan number. If WB-MRI staging improves any or all
these attributes, patient preference is stronger.
Acknowledgements Study collaborators
*STREAMLINE investigators
The authors of this paper are part of a wider group that form the
Streamline trials investigators and include the following collaborators: A
Aboagye, L Agoramoorthy, S Ahmed, A Amadi, G Anand, G Atkin, A
Austria, S Ball, F Bazari, R Beable, H Beedham, T Beeston, N Bharwani, G
Bhatnagar, A Bhowmik, L Blakeway, D Blunt, P Boavida, D Boisfer, D
Breen, S Burke, R Butawan, Y Campbell, E Chang, D Chao, S Chukundah,
B Collins, C Collins, V Conteh, J Couture, J Crosbie, H Curtis, A Daniel, L
Davis, K Desai, M Duggan, S Ellis, C Elton, A Engledow, C Everitt, S
Ferdous, A Frow, M Furneaux, N Gibbons, R Glynne-Jones, A
Gogbashian, S Gourtsoyianni, A Green, Laura Green, Liz Green, A
Groves, A Guthrie, E Hadley, A Hameeduddin, G Hanid, S Hans, B
Hans, A Higginson, L Honeyfield, H Hughes, J Hughes, L Hurl, E Isaac,
M Jackson, A Jalloh, R Jannapureddy, A Jayme, A Johnson, E Johnson, P
Julka, J Kalasthry, E Karapanagiotou, S Karp, C Kay, J Kellaway, S Khan,
D-M Koh, T Light, P Limbu, S Lock, I Locke, T Loke, A Lowe, N Lucas, S
Maheswaran, S Mallett, E Marwood, J McGowan, F Mckirdy, T Mills-
Baldock, T Moon, V Morgan, S Nasseri, P Nichols, C Norman, E Ntala, A
Nunes, A Obichere, J O’Donohue, I Olaleye, A Onajobi, T O’Shaughnessy,
A Padhani, H Pardoe, W Partridge, U Patel, K Perry, W Piga, D Prezzi, K
Prior, S Punwani, J Pyers, H Rafiee, F Rahman, I Rajanpandian, S Ramesh,
S Raouf, K Reczko, A Reinhardt, D Robinson, P Russell, K Sargus, E
Scurr, K Shahabuddin, A Sharp, B Shepherd, K Shiu, H Sidhu, I
Simcock, C Simeon, A Smith, D Smith, D Snell, J Spence, R
Srirajaskanthan, V Stachini, S Stegner, J Stirling, N Strickland, K Tarver,
J Teague, M Thaha, M Train, S Tulmuntaha, N Tunariu, K van Ree, A
Verjee, C Wanstall, S Weir, S Wijeyekoon, J Wilson, S Wilson, T Win, L
Woodrow, D Yu.
Funding This work was supported by the National Institute of Health
Research health technology assessment NIHR HTA programme (project
number 10/68/01) and will be published in full in Health Technology
Assessment. The project is supported by researchers at the National
Institute for Health Research University College London Hospitals
Biomedical Research Centre. S. Janes is a Wellcome Trust Senior
Fellow in Clinical Science. Stephen Morris was in part supported by the
3898 Eur Radiol (2019) 29:3889–3900

National Institute for Health Research (NIHR) Collaboration for
Leadership in Applied Health Research and Care (CLAHRC), North
Thames at Bart’s Health NHS Trust. Department of Health disclaimer:
This report presents independent research commissioned by the National
Institute for Health Research (NIHR). The views and opinions expressed
by authors in this publication are those of the authors and do not neces-
sarily reflect those of the NHS, the NIHR, NETSCC or the HTA pro-
gramme or the Department of Health.
Compliance with ethical standards
Conflict of interest Stuart Taylor is a research consultant to Robarts.
Guarantor The scientific guarantor of this publication is Professor
Stuart Taylor.
Statistics and biometry One of the authors has significant statistical
expertise.
Informed consent Written informed consent was obtained from all sub-
jects (patients) in this study.
Ethical approval Institutional Review Board approval was obtained.
Study subjects or cohorts overlap There is no overlap with study sub-
jects, but this study is one ofthree looking at patient experience ofstaging
scans within the context of the STREAMLINE trials.
Methodology
•prospective
•cross-sectional study
•multi-centre study
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a link
to the Creative Commons license, and indicate if changes were made.
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Eur Radiol (2019) 29:3889–3900 3899

Affiliations
Anne Miles
1
&Stuart A. Taylor
2
&Ruth E. C. Evans
1
&Steve Halligan
2
&Sandy Beare
3
&John Bridgewater
4
&Vicky Goh
5
&
Sam Janes
6
&Neil Navani
7
&Alf Oliver
8
&Alison Morton
8
&Andrea Rockall
9,10
&Caroline S. Clarke
11
&Stephen Morris
12
1
Department of Psychological Sciences, Birkbeck, University of
London, Malet Street, London WC1E 7HX, UK
2
Centre for Medical Imaging, University College London, Charles
Bell House, 43-45 Foley Street, London W1W 7TS, UK
3
Cancer Research UK and University College London Clinical Trials
Centre, 90 Tottenham Court Road, London W1T 4TJ, UK
4
UCL Cancer Institute, Paul O Gorman Building, 72 Huntley Street
London, London WC1E 6DD, UK
5
Cancer Imaging, School of Biomedical Engineering and Imaging
Sciences, King’s College London, Strand, London WC2R 2LS, UK
6
Lungs for Living Research Centre, Division of Medicine, University
College London, Gower Street, London WC1E 6BT, UK
7
Department of Thoracic Medicine, UCLH and Lungs for Living
Research Centre, University College London, London WC1E 6BT,
UK
8
National Cancer Research Institute, Angel Building, 407 St John
Street, London EC1V 4AD, UK
9
Department of Surgery and Cancer, Imperial College London,
Kensington, London SW7 2AZ, UK
10
Department of Radiology, Royal Marsden NHS Foundation
Hospital Trust, Fulham Road, London SW3 6JJ, UK
11
Research Department of Primary Care and Population Health,
University College London, Upper Third Floor, UCL Medical
School (Royal Free Campus), Rowland Hill Street, London NW3
2PF, UK
12
Research Department of Applied Health Research, University
College London, 1-19 Torrington Place, London WC1E 6BT, UK
3900 Eur Radiol (2019) 29:3889–3900