Copyright 2017 American Medical Association. All rights reserved.
Effect of a Patient-Centered Communication Intervention
on Oncologist-Patient Communication, Quality of Life,
and Health Care Utilization in Advanced Cancer
The VOICE Randomized Clinical Trial
Ronald M. Epstein, MD; Paul R. Duberstein, PhD; Joshua J. Fenton, MD, MPH; Kevin Fiscella, MD, MPH; Michael Hoerger, PhD; Daniel J. Tancredi, PhD;
Guibo Xing, PhD; Robert Gramling, MD, DSc; Supriya Mohile, MD, MS; Peter Franks, MD; Paul Kaesberg, MD; Sandy Plumb, BS; Camille S. Cipri, BS;
Richard L. Street Jr, PhD; Cleveland G. Shields, PhD; Anthony L. Back, MD; Phyllis Butow, PhD, MPH; Adam Walczak, PhD; Martin Tattersall, MD, ScD;
Alison Venuti, BS; Peter Sullivan, MSW; Mark Robinson, MSW; Beth Hoh, MSW; Linda Lewis, RN; Richard L. Kravitz, MD, MSPH
IMPORTANCE
Observational studies demonstrate links between patient-centered
communication, quality of life (QOL), and aggressive treatments in advanced cancer, yet few
randomized clinical trials (RCTs) of communication inter ventions have been repor ted.
OBJECTIVE To determine whether a combined intervention involving oncologists, patients
with advanced cancer, and caregivers would promote patient-centered communication, and
to estimate intervention effects on shared understanding, patient-physician relationships,
QOL, and ag gressive treatments in the last 30 days of life.
DESIGN, SETTING, AND PARTICIPANTS Cluster RCT at community- and hospital-based cancer
clinics in Western New York and Northern California; 38 medical oncologists (mean age
44.6 years; 11 (29%) female) and 265 community-dwelling adult patients with advanced
nonhematologic cancer participated (mean age, 64.4 years, 146 [55.0%] female, 235 [89%]
white; enrolled August 2012 to June 2014; followed for 3 years); 194 patients had
participating caregivers.
INTERVENTIONS Oncologists received individualized communication training using
standardized patient instructors while patients received question prompt lists and
individualized communication coaching to identify issues to address during an upcoming
oncologist visit. Both interventions focused on engaging patients in consultations,
responding to emotions, informing patients about prognosis and treatment choices, and
balanced framing of information. Control participants received no training.
MAIN OUTCOMES AND MEASURES The prespecified primar y outcome was a composite
measure of patient-centered communication coded from audio recordings of the first
oncologist visit following patient coaching (intervention group) or enrollment (control).
Secondary outcomes included the patient-physician relationship, shared understanding of
prognosis, QOL, and aggressive treatments and hospice use in the last 30 days of life.
RESULTS Data from 38 oncologists (19 randomized to intervention) and 265 patients
(130 intervention) were analyzed. In fully adjusted models, the intervention resulted in
clinically and statistically significant improvements in the primary physician-patient
communication end point (adjusted intervention effect, 0.34; 95% CI, 0.06-0.62; P = .02).
Differences in secondary outcome s were not statistically significant.
CONCLUSIONS AND RELEVANCE A combined intervention that included oncologist
communication training and coaching for patients with advanced cancer was effective in
improving patient-centered communication but did not affect secondary outcomes.
TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01485627
JAMA Oncol. 2017;3(1):92-100. doi:10.1001/jamaoncol.2016.4373
Published online September 9, 2016.
Supplemental content
Author Affiliations: Author
affiliations are listed at the end of this
article.
Corresponding Author: Ronald M.
Epstein, MD, Center for
Communication and Disparities
Research, Department of Family
Medicine, University of Rochester
Medical Center, 1381 South Ave,
Rochester, NY 14620 (ronald_epstein
@urmc.rochester.edu).
Research
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T
he National Cancer Institute, the National Academy of
Medicine, the American Society for Clinical Oncology,
and the National Priorities Partnership all call for im-
proved patient-physician communication in the context of se-
rious and life-limiting illnesses, citing effects of good commu-
nication on quality of care and quality of life (QOL) and an
ethical mandate that patients be offered participation in in-
formed decisions regarding their care.
1-4
In advanced cancer,
inadequate communication about prognosis and treatment
choices is common
5-7
and is associated with unrealistic pa-
tient expectations regarding curability,
8
provision of aggres-
sive treatment that is not concordant with patients’ wishes and
enrollment in hospice too late to deliver discernable benefit.
8-12
Critical conversations typically do not happen, or happen in
hospital shortly before a patient’s death.
13
Making high-quality conversations happen is difficult.
More than 90% of patients with advanced cancer say they want
to be actively involved in their care and value frank and sen-
sitive conversations about QOL, prognosis, and treatment
choices.
10,14,15
Yet patients are often reluctant to be assertive,
ask questions, request clarification, express emotions
directly, or state opinions and preferences.
16
As death ap-
proaches, patients express considerable ambivalence about
end-of-life discussions, often indicating that now is “not the
right time.”
17-20
Similarly, while most clinicians indicate will-
ingness to have these discussions “now,” few follow
through.
21,22
More typically, clinicians wait for patients to sig-
nal interest, then offer prognostic information that is optimis-
tically biased.
23,24
Prior attempts to improve patient-physician communi-
cation in advanced cancer have had limited impact. Inten-
sive workshops inconsistently improve trainee communica-
tion behaviors
25,26
and are impractical for busy clinicians.
Brief individualized in-office interventions using expert
feedback on video recorded encounters improved oncolo-
gists’ empathy and patient-reported trust,
27
but this
approach has not been applied to other communication
behaviors, such as delivery of prognostic information.
Patient coaching increased discussion of cancer pain,
28
and,
in palliative care, question prompt lists (QPLs) have
increased question-asking
29
—but only when physicians
encouraged patients to ask questions.
The Values and Options in Cancer Care (VOICE) study
30
combined 2 interventions, a brief individualized oncologist
skill-based training, and individualized patient and caregiver
coaching incorporating a QPL. Based on an ecological model
of patient-clinician communication, both interventions were
designed to promote the involvement in care that patients
and families desire but rarely request and emphasized the
same communication skills and topics identified in prior
research: engaging patients to participate in the consulta-
tion, responding to patients’ emotions, informing patients
about prognosis and treatment choices, and framing infor-
mation in a balanced manner.
6,18,29,31-35
The primary out-
come was patient-centered communication in these
domains. Secondary outcomes were shared understanding,
patient-physician relationships, QOL, and health care utili-
zation at the end of life.
33
Methods
Overview
We conducted a multisite cluster randomized clinical trial (RCT)
of an intervention to improve communication between pa-
tients (and caregivers when available) and oncologists. On-
cologists randomized to the intervention arm participated in
individualized communication training using standardized pa-
tient-instructors (SPIs), while their patients (with caregivers)
participated in an individualized communication coaching ses-
sion with follow-up telephone calls. After a prerandomiza-
tion phase designed to assess baseline communication pat-
terns of participating oncologists, we enrolled participants
(from August 2012 through June 2014) and followed them un-
til October 2015. We obtained institutional review board ap-
proval for all study sites, and participants provided written in-
formed consent and received $15 per questionnaire completed.
See the published study description
36
and the eAppendix in
Supplement 1 for the study protocol and descriptions of the
interventionsand Supplement 2 for the statistical analysis plan.
Settings and Participants
We conducted the study in community-based cancer clinics
(4), academic medical centers (3) and community hospitals (3)
in Western New York and Sacramento, California.
Physicians
We recruited medical oncologists who care for patients with
nonhematologic cancers at practice meetings at participating
clinics. The mean physician age was 44 years; 27 (71%) were
male; 17 (45%) were white, 16 (42%) were Asian, and 5 (13%)
were of other race.
Patients
With clinic staff, research assistants reviewed clinic rosters of
enrolled physicians to contact potentially eligible patients age
21 years or older, able to understand spoken English and pro-
vide written informed consent, and who had either stage IV
nonhematologic cancer or stage III cancer and whose physi-
cian “would not be surprised” if the patient were to die within
12 months.
37,38
We excluded inpatients and those in hospice.
Key Points
Question Can communication between patients with advanced
cancer and their oncologists be improved?
Findings This cluster randomized clinical trial of communication
training for oncologists paired with previsit coaching for patients
showed clinically and statistically significant improvement in
patient-centered communication.
Meaning Paired communication training for patients and
oncologists helps achieve patient-centered care in advanced
cancer: engaging patients in consultations (asking questions,
expressing preferences), responding to emotions, and providing
information about prognosis and treatment choices.
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We first recruited 3 to 4 “prerandomization” patients per phy-
sician who agreed to have 1 office visit audio recorded and com-
plete questionnaires before and after the office visit. After phy-
sician randomization, we recruited a new cohort of patients,
up to 10 per physician, for the cluster RCT (eTable 1 in
Supplement 3) until we reached the target sample size of 265
patients. Cluster RCT patients also agreed to an audio re-
corded office visit and previsit and postvisit questionnaires;
in addition, they agreed to participate in intervention or con-
trol conditions, complete questionnaires quarterly for 3 years,
and to have their medical records abstracted. Patients were
blinded to study arm assignment until completion of base-
line measures.
Caregivers
Research assistants asked patients to identify “a family mem-
ber, partner, friend, or other individual involved with your
health care issues, preferably someone who comes to physi-
cian appointments with you.” Eligible caregivers were 21 years
or older and able to understand spoken English and provide
written informed consent.
Interventions
The experimental intervention
36
included (1) a 2-session
in-office physician training (1.75hours) using a brief video, feed-
back from standardized patients portraying roles of patients with
advanced cancer who also critiqued up to 2 audio recorded study
patient visits, and (2) a single 1-hour patient and caregiver coach-
ing session incorporating a question prompt list to help pa-
tients bring their most important concerns to their oncolo-
gist’s attention at an upcoming office visit, plus up to 3 follow-up
phone calls (Table 1;eTable2inSupplement 3). Trainers and
coaches underwent 3-day on-site trainings. To promote patient-
centered communication about disease course, prognosis, treat-
ment decisions and end-of-life care, physician and patient
interventions focused on the same 4 key domains of patient-
centered communication.
36
Intervention sessions were audio
recorded and reviewed by lead trainers and investigators using
a fidelity checklist. Fidelity was 94% or higher.
All intervention physicians completed both training ses-
sions. All intervention patients received in-person coaching;
of the 52% who responded to a mailed survey, 87% “would rec-
ommend coaching to other patients with cancer”; and 85%
Table 1. Communication Domains That Promote Patient Involvement in Care Through Being Better Engaged, Responded to, Informed, and Debiased
Communication
Domain Goal of Intervention
Examples of Physician
and Patient Behaviors Measure What Is Measured Reliability and Validation
Engaging Engaging patients and CGs
to be more active
participants in clinical care.
Oncologists acknowledge
and endorse the use of
QPLs, encourage questions,
and encourage participation
in decision-making.
Patients ask relevant
questions that clarify their
values and preferences and
are emboldened to
participate in decisions to
the degree they wish.
Physician: Asking patients
what questions are most
important to them.
Bringing attention to
the QPL.
APPC
39
Absolute number of active
patient communication
behaviors (eg, asking
questions, requesting
clarification, expressing
opinions) and facilitative
physician behaviors
(partnership-building and
supportive talk, eg,
empathy, reassurance and
praise), coded from audio
recordings
Intraclass correlations for
patient behaviors were
0.91-0.97 and for physician
behaviors were 0.82-0.91
Patient: Asking questions,
expressing concerns and
opinions, requesting
clarification
Higher scores associated with
patient preference for a
shared, patient-centered
model of care
40
Responding Responding to patients’
emotions (expressed as
direct concerns and indirect
cues) by listening and
offering acknowledgment,
legitimation, empathy and
support. Patients are
comfortable participating
more actively in the
consultation.
Physician: Identif ying
patient emotions, opening
the door for further
exploration, expressing
empathy
Verona
VR-CoDES
system
41,42
Percentage of physician
responses to patients’
emotional cues and
concerns that were coded
as “opening space” (eg,
acknowledgment, support)
vs “closing space” (eg,
cutoff, change of topic),
coded from transcripts
Discrepancies were
adjudicated first by consulting
the coding manual then by
1 of the investigators (R.G.)
(all discrepancies were in
identifying indirect “cues”;
there was agreement on all
“concerns” and “responses”)
Patient/CG: expressing
emotions, eg, fear and
sadness
Informing Informing patients about
disease, prognosis and
treatments; assessing
desire for information;
checking understanding.
Patients and CGs ask for
information and
clarification.
Physician: Asking patient
what he or she wants to
know about prognosis and
treatment choices.
Explicitly checking
patient understanding
using an “ask-tell-ask”
approach.
43
PTCC,
44
Informing
subscale
The number of statements
discussing curability,
survival, future quality of
life and future functional
status, coded from
transcripts
Developed by Shields et al
44
for an unannounced
standardized patient study of
physician communication in
cancer settings and adapted
and divided into 2 subscales
for this study. Informing
subscale contains 9 items.
Patient: asking specific
questions about the
disease, treatment
choices, prognosis, QOL
Intraclass correlation was
0.75
Balanced framing Framing positive and
negative aspects of a
decision to reduce biases
introduced by 1-sided
presentation of data.
Physician: Indicating
percentage of patients
likely to benefit from a
treatment and percentage
who are unlikely to
benefit
PTCC,
44
Balanced
Framing subscale
Number of (1) expressions
of probabilities in a
balanced fashion (eg, 60%
chance of cure and 40%
chance of relapse) or
(2) occurrences of “best
case/worst case” framing
of future probabilities,
coded from transcripts
Based on recommendations
for debiasing decisions,
45,46
this scale represents 2 items
that are part of the PTCC
scale.
Patient: Asking about the
pros and cons of
important choices
Intraclass correlation was
0.75
Abbreviations: APPC, Active Patient Participation Coding; CG, caregiver; PTCC, Prognostic and Treatment Choices; QPL, question prompt list.
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were able to ask “all” or “most” of their “most important”
questions. Of the 130 coached patients, 94% participated in
≥1 follow-up call (≥2 calls, 78.7%; 3 calls, 58.3%); reasons for
nonparticipation were death and/or illness (47.1%), unre-
turned phone calls (47.1%) and refusal and/or withdrawal
(5.8%). Control physicians and patients received no training.
Data Collection and Outcome Measures
We audio recorded the first physician visit after the coaching
session (for intervention) or after study entry (control). The pri-
mary outcome was a composite of 4 prespecified communi-
cation measures matched to the goals of communication train-
ing, described in detail in Table 1—engaging patients in
consultations (Active Patient Participation Coding [APPC]
39
),
responding to patients’ emotions (Verona VR-CoDES
41,42
), in-
forming patients about prognosis and treatment choices (Prog-
nostic and Treatment Choices [PTCC] Informing subscale
44
)
and balanced framing of decisions (PTCC Balanced Framing
subscale
44
). The composite score derived from these scales
were designed to capture key elements of 6 interrelated func-
tions of communication outlined by the National Cancer In-
stitute: fostering healing relationships (APPC), exchanging in-
formation (PTCC), managing uncertainty (PTCC), making
decisions (APPC, PTCC), responding to emotions (Verona), and
enabling patient self-management (APPC).
47
Coding of the 4
measures was performed by teams of trained university stu-
dents who were audited continuously and blinded to study hy-
potheses and group assignment. We transformed each of the
4 component scores to z scores based on the prerandomiza-
tion phase sample means (SDs):
z = (Raw Score – Prerandomization Phase
Mean)/Prerandomization Phase SD
The 4-component z-scores were averaged to form the pri-
mary outcome, a composite measure with better overall
precision and sensitivity than the individual components for
assessing intervention effects on the multiple targeted com-
munication goals.
We assessed patient-physician relationships using The
Human Connection (THC) scale,
48
the Health Care Climate
Questionnaire (HCCQ),
49
and the Perceived Efficacy in Patient-
Physician Interactions (PEPPI) scale
50
shortly after the audio
recorded visit. Physicians and patients were also asked to es-
timate 2-year survival and curability of the patient’s cancer on
a 7-point scale (100%, about 90%, about 75%, about 50/50,
about 25%, about 10%, 0%, don’t know); discordance was de-
fined as 2 or more categories of difference.
We administered QOL questionnaires at 3-month intervals
from study entry for up to 3 years and prespecified a composite
QOL score to be the average of 5 z-scored subscales: McGill QOL
scale single item, McGill Psychological Well-Being subscale,
McGill Existential Well-Being subscale, FACT-G Physical Func-
tioning subscale, and FACT-G Social Functioning subscale
51,52
;
all are widely used in research in advanced cancer. Fewer than
3% of follow-up questionnaires were missing.
Trained nurses and physicians abstracted utilization data
from medical records at relevant hospitals, offices, and hos-
pice organizations. Based on a review of the literature,
9,53-55
we prespecified a composite utilization score of 3 indicators
of aggressive treatment in the last 30 days of life (chemo-
therapy, potentially burdensome interventions, emergency
department [ED]/hospital admission) and hospice utilization
(eTable 3 in Supplement 3).
Randomization and Blinding
We randomized by physician and stratified by site (New York
or California) and oncologist subspecialty (≥50% vs <50% of
patients with breast cancer) to balance sex and other unmea-
sured patient characteristics that might be associated with the
communication outcomes. Within strata, we randomly as-
signed physicians at a 1:1 ratio to intervention or control. We
recruited, obtained consent, and enrolled patients based on
the arm to which their physician was assigned. We over-
sampled patients with caregivers to achieve recruitment goals
for a companion study of caregiver bereavement. Only the
study statisticians were aware of the random number se-
quences and treatment assignment, preserving blinding among
transcriptionists, coders, and abstractors.
Sample Size
To affect utilization and patient outcomes meaningfully, we
felt a moderately large effect on communication would be
needed. To account for attrition and variance inflation aris-
ing from cluster randomization, we used standard formula as
well as simulation studies using SAS statistical software to de-
termine that a target sample size of 38 physicians and 265 pa-
tients would yield the effective sample needed to provide at
least 80% power (2-sided testing, α = .05) to detect standard-
ized effects of 0.50 for the primary communication outcome.
36
Statistical Analysis
Between-group comparisons on communication and utilization
outcomes were conducted using Wald-type tests from prespeci-
fied mixed-effects linear regression models (for continuous out-
comes) and generalized estimating equations for binary out-
comes, specified to account for the nesting of patients (the units
of analysis) within physicians (the units of randomization). For
all regression analyses, covariates for study site and breast can-
cer subspecialty were included to account for the stratified ran-
domization, as well as patient-level covariatesto adjust for demo-
graphic and cancer characteristics. Between-group comparisons
of QOL trajectories were performed using the terminal decline
model (TDM) of Li et al
56
that accounts for mortality by jointly
modeling QOL and survival using piecewise linear regression and
exponential hazards regression models, respectively. The TDM
parameterizes time countingbackwardfrom patienttimeof death
and is specified with 2 periods for each component, the “termi-
nal decline” period nearest death and the more remote period
before then; our model extends on Li et al
56
to permit the inclu-
sion of study covariates. We chose 9 months and 12 months as
the duration of the terminal decline period for QOL and mortal-
ity, respectively, based on the observed change point in the data.
For the analysis of communication outcomes, we used the
prerandomization data to adjust for between-physician dif-
ferences among the 38 physician clusters. Hence, the data sets
for these mixed models analyses included observations from
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prerandomization and postrandomization audio recordings,
and the models included fixed-effects terms for phase (pre-
randomization vs postrandomization), study arm, and the in-
teraction of phase and arm. Intervention effects were esti-
mated as the between-arm difference in adjusted mean
difference from prerandomization to postrandomization
samples. For the other continuous outcomes, only postran-
domization data were included, and intervention effects were
estimated as adjusted mean differences. In model validation
and exploratory analysis, heterogeneity of treatment effects
was assessed by adding interaction terms to regression mod-
els to compare intervention effects across prespecified sub-
groups. Residual plots were also used for model validation.
Statistical analyses (Supplement 2) were conducted in
version 9.4 of the SAS System.
Results
Study Participants
Of 52 physicians contacted, 43 enrolled and 38 participated in
the cluster RCT (eFigure 1 in Supplement 3). Of the 265 par-
ticipating patients, 194 (73.0%) had an enrolled caregiver. Pa-
tient characteristics across study arms were well matched
(eTable 1 in Supplement 3); mean age was 64.4 years, 55.0%
were female, 11.5% were nonwhite, 28.0% had high school edu-
cation or less, and 19.0% reported income of $20 000 or less.
The mean follow-up for patients was 15 months; by study clos-
ing (October 1, 2015), 151 patients had died, 18 had with-
drawn, and 1 was lost to follow-up (eFigure 1 in Supplement
3). We abstracted all decedents’ medical records.
Primary Outcome
In fully adjusted models, the composite communication
score showed a significant intervention effect (estimated
adjusted intervention effect, 0.34; 95% CI, 0.06-0.62;
P =.02)(Table 2; eTable 4 in Supplement 3). The sample
standard deviation of the composite from the prerandomiza-
tion cohort was 0.53, hence the estimated intervention
effect of 0.34 corresponds to a standardized effect of 0.64,
corresponding to 5.7 additional “engaging” statements (a
44% increase), 0.6 additional responses to emotion (a 71%
increase), and 1.4 additional statements regarding prognosis
and treatment choices (a 38% increase).
Secondary Outcomes
Of the individual communication component measures,
only the engaging measure (APPC) was statistically signifi-
cant. There were no statistically significant effects of the
intervention on the PEPPI, THC, or HCCQ scales, or on 2-year
survival and curability estimates; 2-year survival discor-
dance was 59% in the intervention group vs 62% for control;
corresponding figures for curability discordance were 39%
and 44%. Quality of life was stable until 6 to 9 months prior
to death, with a terminal decline (eFigure 2 in Supplement
3); overall, QOL differences between intervention and con-
trol were not statistically significant. We observed no inter-
vention effects on health care utilization.
Exploratory Outcomes
None of the prespecified candidate effect modifiers were as-
sociated with heterogeneity in treatment effects on commu-
nication outcomes. Median survival was 16 months: 19 months
in the intervention group and 14 months in the control (haz-
ard ratio, 0.84; 95% CI, 0.61-1.15) (eFigure 3 in Supplement 3).
Discussion
In this study, a brief combined intervention targeting physi-
cians, patients with advanced cancer, and their caregivers
(when available) promoted patient-centered communication
in the near term, with clinically meaningful increases in
engaging patients in discussions, responding to emotions
and discussions of prognosis and treatment choices. These
communication domains are linked; provision of informa-
tion or emotional support, for example, may depend on a
patient cue or request as well as a clinician’s willingness and
capacity to respond. Of the 4 communication domains, the
most fundamental, engaging patients as active partners in
care—being assertive, asking questions, requesting clarifica-
tion, expressing opinions and preferences to a greater degree
than control patients—was independently significant in sec-
ondary analyses. Our approach was individualized and tai-
lored to participants’ educational needs; it was theory-
based, highly rated by patients, caregivers, and oncologists,
and focused on important domains of patient-centered com-
munication but whose incorporation into practice remains
elusive.
1,9-11
While prior reports suggest that activated
patients and those receiving bad news may rate their physi-
cians more harshly,
8,57
we did not observe these effects, per-
haps because our intervention focused on aligning patient,
caregiver, and physician expectations.
Despite calls for improved patient-centered communica-
tion between oncologists and their patients and evidence that
linking end-of-life discussions with more realistic prognosis
estimates, better QOL and reduced utilization of aggressive
treatments,
8-12
there has been little headway over the past 20
years. Many patients hold unrealistically optimistic prognos-
tic estimates,
8,11,21,58,59
which they mistakenly believe their
physicians share
60
; future studies can unravel how to inter-
rupt the temporarily adaptive but ultimately dysfunctional pas
de deux, in which physicians, caregivers, and patients avoid,
euphemize, or misinterpret these discussions.
61-64
Oncolo-
gists need better training in the provision of information to pa-
tients with varying levels of health numeracy and literacy as
well as “terror management,” a defense mechanism that may
prompt some patients (and physicians) to respond to fear of
death through avoidance and selective attention.
65-67
Venues
already exist for communication and awareness training dur-
ing residency and fellowship,
25,68,69
and interventions such as
ours are feasible for practicing oncologists.
Consistent with prior data,
70,71
QOL is remarkably stable
during the course of cancer, until the terminal decline. It is pos-
sible that the timing of the intervention may have not have been
optimized to affect QOL trajectories. Future patient and care-
giver interventions might be targeted to key junctures in the
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