Cancer patient preferences for quality and length of life

Cancer Patient Preferences for Qualityand Length of Life

Neal J. Meropol, MD1

Brian L. Egleston, MPP, PhD2

Joanne S. Buzaglo, PhD2

Al B. Benson, III, MD3

Donald J. Cegala, PhD4,5

Michael A. Diefenbach, PhD6

Linda Fleisher, MPH2

Suzanne M. Miller, PhD2

Daniel P. Sulmasy, OFM, MD, PhD7

Kevin P. Weinfurt, PhD8

CONNECT Study Research Group

1 Divisions of Medical Science and PopulationScience, Fox Chase Cancer Center, Philadelphia,Pennsylvania.

2 Division of Population Science, Fox Chase Can-cer Center, Philadelphia, Pennsylvania.

3 Division of Hematology/Oncology, Robert H.Lurie Comprehensive Cancer Center, Northwes-tern University, Chicago, Illinois.

4 Department of Communication, Ohio State Uni-versity, Columbus, Ohio.

5 Department of Family Medicine, College ofMedicine, Ohio State University, Columbus, Ohio.

6 Department of Urology, Mount Sinai MedicalCenter, New York, New York.

7 Bioethics Institute, New York Medical College,Valhalla, New York.

8 Department of Psychology and Neuroscience,Duke University School of Medicine, Duke Univer-sity, Durham, North Carolina.

BACKGROUND. Optimal patient decision making requires integration of patient

values, goals, and preferences with information received from the physician. In

the case of a life-threatening illness such as cancer, the weights placed on quality

of life (QOL) and length of life (LOL) represent critical values. The objective of

the current study was to describe cancer patient values regarding QOL and LOL

and explore associations with communication preferences.

METHODS. Patients with advanced cancer completed a computer-based survey

before the initial consultation with a medical oncologist. Assessments included

sociodemographics, physical and mental health state, values regarding quality

and length of life, communication preferences, and cancer-related distress.

RESULTS. Among 459 patients with advanced cancer, 55% placed equal valued on

QOL and LOL, 27% preferred QOL, and 18% preferred LOL. Patients with a QOL

preference had lower levels of cancer-related distress (P < .001). A QOL preference

was also associated with older age (P 5 .001), male sex (P 5 .003), and higher edu-

cational level (P 5 .062). Patients who preferred LOL over QOL desired a more sup-

portive and less pessimistic communication style from their oncologists.

CONCLUSIONS. These data indicate that a values preference for LOL versus QOL

may be simply measured, and is associated with wishes regarding the nature of

oncologist communication. Awareness of these values during the clinical encoun-

ter could improve decision making by influencing the style and content of

the communication between oncologists and their patients. Cancer 2008;113:

3459–66. � 2008 American Cancer Society.

KEYWORDS: quality of life, cancer communication, physician-patient communication,patient preferences, communication preferences, cancer-related distress, length of lifepreferences, patient decision making, cancer communication aid, patient values.

Supported by R01CA082085 and Fox Chase Can-cer Center Population Studies Facility and Behav-ioral Research Core Facility (P30CA06927) fromthe National Cancer Institute.

Clinicaltrials.gov registration ID: NCT00244868.Available at: http://www.clinicaltrials.gov/ct/show/NCT00244868?order56

We thank the following clinical sites and indivi-duals for enrolling patients in this study: FoxChase Cancer Center (Principal Investigator: Neal

J. Meropol, MD; Research Assistants: NicholasSolarino and Jonathan Trinastic); Robert H. LurieComprehensive Cancer Center, NorthwesternUniversity (Principal Investigator: Al B. BensonIII, MD; Research Assistants: Sheano Gold andLisa Stucky-Marshall); and Meharry Medical Col-lege (Principal Investigator: Steven N. Wolff, MD;Research Assistants: Kim Burlison and RoslynHatchett-Pope).

The CONNECT Study Research Group includes:Andrew Balshem, BA (Fox Chase Cancer Center,Philadelphia, Penn); Ellyn Micco, MS (Fox ChaseCancer Center, Philadelphia, Penn); Jennifer L.Millard, BS (Fox Chase Cancer Center, Philadel-phia, Penn); Eric A. Ross, PhD (Fox Chase Can-cer Center, Philadelphia, Penn); Kevin A.

Schulman, MD (Duke University School of Medi-cine, Durham, NC); Elyse Slater, MS (Fox ChaseCancer Center, Philadelphia, Penn); NicholasSolarino, MS (Fox Chase Cancer Center, Phila-delphia, Penn); and Jonathan Trinastic, BS (FoxChase Cancer Center, Philadelphia, Penn), all ofwhom contributed to the authorship of this arti-cle.

Address for reprints: Neal J. Meropol, MD,Department of Medical Oncology, Fox ChaseCancer Center, 333 Cottman Avenue, Philadel-phia, PA 19111; Fax: (215) 728-3639; E-mail:[email protected]

Received April 11, 2008; revision received June11, 2008; accepted June 30, 2008.

ª 2008 American Cancer SocietyDOI 10.1002/cncr.23968Published online 5 November 2008 in Wiley InterScience (www.interscience.wiley.com).

3459

P atients with advanced cancer exist in a unique

medical context in which they are facing mortal-

ity and may be considering treatment options that

have significant potential for toxicity. In addition,

therapeutic choices are characterized by uncertain

outcomes, and may be varied and complex, includ-

ing supportive care alone, standard treatments (eg,

chemotherapy, radiotherapy, and biologic therapy),

and investigational approaches. Quality patient deci-

sion making requires an adequate patient under-

standing of treatment options, including potential

benefit and harm. The physician serves as the pri-

mary source of medical information for cancer

patients1,2; as such, the communication between

physician and patient is of critical importance to

quality decision making.3-5

In a survey of cancer patients who were consid-

ering participation in phase 1 trials, we observed dis-

cordance between patient and oncologist perceptions

regarding the content of their consultations.6 In par-

ticular, patients were far less likely to report discus-

sion of quality of life (QOL) issues than their

physicians. This lack of agreement is a potential

source of concern insofar as nearly all of the patients

taking part in the survey valued QOL at least as

highly as length of life (LOL).

Adequate communication regarding the impact

of treatment on QOL is of particular importance

given that patient preference for either QOL or LOL

can influence patient treatment decision making. For

example, among cancer patients with advanced dis-

ease, an individual’s preference for LOL over QOL is

associated with treatment preference for chemother-

apy over watchful waiting.7 Furthermore, several

sociodemographic factors are reported to be asso-

ciated with a preference for QOL or LOL. A prefer-

ence for QOL is associated with older age8,9 and

having no children.7,8 In contrast, a preference for

LOL is associated with being young, having children,

and good functional health status.8,10 Despite its im-

portance for cancer patient decision making regard-

ing treatment, to our knowledge few studies to date

have explored how an individual’s preference for

QOL or LOL influences the way in which patients

wish their physicians to present prognostic and treat-

ment-related information.

To approach the understanding of how patient

preferences impact decision making, we applied the

Cognitive-Social Health Information Processing (C-

SHIP) model.11,12 This is a comprehensive framework

that delineates the cognitive and affective factors

involved in health information processing.11,12 These

factors include the individual’s self-construals (eg,

perceived vulnerability to disease), affect (eg, anxious

preoccupation with cancer), and values and goals

(eg, concerning the physician-patient encounter and

the importance of QOL), as well as goals related to

achieving desired treatment outcomes (eg, expressing

one’s concerns and values).11 The C-SHIP model

emphasizes the role of distress in information proc-

essing and decision making.13 Because distress can

impact a patient’s ability to process critical prognos-

tic and treatment-related information relevant to

treatment choice,14 examination of its relation to an

individual’s values (eg, importance of QOL and LOL)

and communication preferences is essential.

In an effort to improve the matching of consulta-

tion content with individual patient values, we devel-

oped a computer-based communication aid. We

currently are conducting a randomized clinical trial

to assess the impact of this intervention on the con-

tent of oncology consultations and patient satisfac-

tion with physician communication. In this study, we

describe the baseline characteristics of the study

population in an effort to define the cognitive-affec-

tive profiles and communication preferences among

those cancer patients who prefer QOL and those who

prefer LOL.

MATERIALS AND METHODSPatient SelectionThis report describes baseline survey data obtained

as part of an intervention study to evaluate the effi-

cacy of a computer-based communication aid on

treatment decision making in patients with advanced

cancer. The parent study is a 3-arm randomized clin-

ical trial. Two of the arms include the survey items

that form the basis for this report.

Participants were patients with advanced cancer

being treated at 3 academic cancer centers in the

US. Eligibility criteria included: 1) first outpatient

consultation with a medical oncologist; 2) documen-

ted metastatic malignancy; 3) aged �18 years; 4)

ability to read and verbally communicate in English;

and 5) ability to provide written informed consent to

participate. Potential study participants were ascer-

tained between January 2005 and January 2007

through a review of new patient schedules and medi-

cal information forwarded at the time of scheduling,

before the initial medical oncologist consultation.

ProcedureAfter ascertainment, consent to contact potential

participants was obtained from the physician with

whom the patient was scheduled. A research assist-

ant then contacted patients by telephone to explain

the study. After providing verbal consent, participants

3460 CANCER December 15, 2008 / Volume 113 / Number 12

were given the option to complete the computer-

based survey at home, using a secure web-inter-

face,15 or arrive 1 hour before their appointment to

complete the survey at the clinical site. Participants

using the secure website to complete the survey

signed informed consent documents electronically.

Participants were given a toll-free number for techni-

cal support and to ask any questions regarding the

study. All participants provided written consent at

the time of their arrival for their physician appoint-

ments. The study was approved by the Institutional

Review Boards at the participating centers.

MeasuresPatient characteristics included sex, age, marital sta-

tus, education, employment status, race, ethnicity,

cancer diagnosis, and treatment history.

Physical and emotional health state was assessed

using the Short-Form (SF)-12 and the Revised Impact

of Events Scale (RIES). The SF-1216 is a highly reli-

able shortened version of the SF-3617 and is intended

to provide indices of QOL similar to the longer

instrument while reducing participant burden. Sub-

scales include a Physical Component Scale (PCS)

and Mental Component Scale (MCS). Cancer-related

distress was measured using the RIES, a well-vali-

dated 15-item questionnaire measuring event-related

intrusion and avoidance.18

QOL and LOL preferences were assessed with 3

items to determine the relative value that an indivi-

dual assigns to QOL and LOL. This instrument,

designed and refined based on prior research6,19 with

the target population, asked participants to select

from among 4 choices regarding whether QOL or

LOL was more important (QOL is all that matters,

QOL is more important but LOL matters, LOL is

more important but QOL matters, LOL is all that

matters). Participants were also asked to rate the im-

portance of QOL and LOL as independent domains

on 5-point scales (not at all, somewhat, moderately,

quite a bit, very important).

Communication preferences were assessed using

an 8-item survey developed based on a review of rel-

evant literature and existing physician-communica-

tion assessments.20-24 Participants were asked to rank

their agreement with each of these 8 preferences

regarding physician communication about prognos-

tic and probabilistic information on a 5-point scale

from ‘‘Strongly Agree’’ to ‘‘Strongly Disagree.’’

Statistical ConsiderationsWe defined QOL and LOL preferences in 2 ways. We

initially defined QOL versus LOL preference based

on the single 4-point survey item that required

patients to prioritize QOL and LOL. In an effort to

discriminate patient preferences further given infre-

quent selection of the extreme values of this single-

item measure, we defined 3 preference groups based

on independent rating of QOL and LOL on the 2 5-

point scales. For this composite analysis, we categor-

ized patients with regard to whether they selected

equal ratings for QOL and LOL on the independent

measures, or whether they rated 1 of these prefer-

ences higher on 1 of the measures. The analyses

described below use the composite measure.

For unadjusted analyses comparing the QOL

preference groups with potential confounders, we

used multiple linear regressions with robust standard

errors of the continuous confounders to assess statis-

tically significant differences among groups. We used

robust standard errors to weaken the analysis of var-

iance (ANOVA) assumption of normally distributed

errors. We used Wald tests of the regression parame-

ters to test the null hypothesis that there were no dif-

ferences in mean responses among the 3 QOL

preference groups. For categoric confounders, we

used the Fisher exact test. We used correlations to

assess the relation between the communication pref-

erence variables and the RIES distress score.

To adjust for age, education, sex, race, SF-12

PCS, and MCS scores in analyses relating QOL pre-

ferences with communication preferences and dis-

tress, we used propensity score adjustment through

propensity score-based weighting with doubly robust

estimation.25 We calculated robust standard errors

using the sandwich estimator of Huber26; our stand-

ard errors account for the uncertainty associated

with the estimation of the propensity scores. Propen-

sity score-based weighting is an effective means of

adjusting for potential confounders because it allows

for the creation of an adjusted population in which

the balance of confounders between QOL preference

groups can be assessed directly. If the average covari-

ate characteristics between QOL preference groups

in the adjusted population are similar, then it is unli-

kely that the covariates are confounding the adjusted

inferences.

The adjusted mean communication preference

scores presented in Table 1 and adjusted mean dis-

tress scores presented in Figure 1 represent estimates

of mean responses in the adjusted population.

To develop the propensity score model, we used

a multinomial logistic regression of the nominal 3-

category QOL variable. The age, SF-12, education,

sex, and race terms were entered into the model

using restricted cubic splines for age, SF-12 PCS, and

SF-12 MCS27 and interactions of sex with age and

education. The appropriateness of the model was

Cancer Patient Preferences/Meropol et al 3461

measured by it ability to balance the covariates

among the 3 groups.

RESULTSParticipant CharacteristicsA total of 1932 patients were contacted and 1101

(57%) agreed to be assigned a password to consider

participation in this 3-arm study; 743 patients (68%)provided informed consent and completed baselinesurveys. In all, 471 patients were randomized tothe 2 intervention arms, and 12 patients with miss-ing data were not included in these analyses.Therefore, 459 patients form the basis of the cur-rent study. Although all 459 patients were used toderive propensity scores, each communicationpreference response had an additional 1 or 2 miss-ing values. Patient demographics are shown inTable 2. The sample was primarily white (91%),51% male, and well-educated (70% with somecollege or more).

Preferences regarding QOL and LOL are summar-

ized in Table 3. Approximately half of the patient

participants (55%) equally valued QOL and LOL

based on the composite measure. Of those patients

with a preference, QOL was selected more often

than LOL (27% vs 18%). This finding is consistent

with the selection of QOL as more important on the

single-item scale (80% of patients) in which patients

were required to commit to a preference. Older age

(P < .001) and male sex (P < .003) were found to

be positively associated with a preference for QOL

(Table 4). To remove possible confounding by these

variables in the subsequent communication prefer-

ence analyses, we used propensity score adjustment.

In the propensity-weighted population, older age and

male sex were no longer associated with a preference

for QOL, indicating successful adjustment. In the

adjusted population, all P values were >.20. Com-

TABLE 1Relation Between Communication Preferences, Distress, and LOL/QOL Preference*

Total RIES Adjusted Mean (SE) P

Correlation P QOL Equal LOL P

I want the doctor to speak in a positive manner 0.096 3.65 4.03 4.19 <.001

.040 (.09) (.05) (.09)

I want to hear general terms (for example, ‘‘the treatment is likely to work’’) rather than

statistics (for example, ‘‘the treatment has a 75% likelihood of working’’).

0.034 3.22 3.63 3.76 .002

.468 (.12) (.07) (.12)

I want the doctor to soften the blow when giving me bad news 0.321 2.17 2.74 2.93 <.001

<.001 (.10) (.08) (.16)

I want the doctor to speak to me in an emotionally supportive way 0.289 3.83 4.15 4.24 <.001

<.001 (.08) (.04) (.07)

I want to hear detailed statistics 0.074 3.87 3.96 3.81 .358

.112 (.10) (.06) (.10)

I want the doctor to speak matter-of-factly (for example, give me the cold hard facts) 20.217 3.92 3.82 3.88 .721

<.001 (.10) (.07) (.10)

I want to hear averages about people like me 0.034 4.05 4.01 4.01 .910

.463 (.07) (.05) (.10)

I want to hear the doctor’s opinion about my case in particular 20.087 4.70 4.66 4.64 .788

.064 (.05) (.04) (.07)

LOL indicates length of life preferred; QOL, quality of life preferred; RIES, Revised Impact of Events Scale; SE, standard error.

*Scores represent average responses. A score of 1 indicates Strongly Disagree and a score of 5 indicates Strongly Agree (standard deviation).

FIGURE 1. Cancer-related distress and quality of life (QOL) versus lengthof life (LOL) preferences. The center bars represent the means of the pro-

pensity score-adjusted total Revised Impact of Events Scale (RIES) measure-

ments, whereas the whiskers represent the 95% confidence intervals.

P < .001 for a hypothesis test of the equality of the 3 means.


pared with patients with other diseases, those with

prostate cancer preferred QOL (P 5 .021) (Fig. 2).

Given a potential relation between affect and

values, an association between patient distress and

QOL versus LOL preferences was investigated. As

shown in Figure 1, those patients with a preference

for QOL had lower levels of cancer-related distress

than those patients with an LOL preference or no

preference. There was a marginally significant asso-

ciation noted between the mental health component

summary score of the SF–12 (P 5 .069) and the phys-

ical health component summary score of the SF–12

(P 5 .073), and preferences for QOL or LOL, with in-

ferior QOL on these measures associated with a pref-

erence for LOL (Table 4). There was no association

noted between length of time since diagnosis or pre-

vious receipt of systemic therapy, and QOL versus

LOL preferences.

We next explored whether QOL/LOL preferences

are associated with preferences for communication

with the physician. As shown in Table 1, after propen-

sity score-weighted adjustment, analyses indicate sig-

nificant differences in preferences for the style of

communication between those patients preferring

QOL and those preferring LOL. Specifically, compared

with the other groups, individuals who indicated that

they prefer LOL over QOL (testing for the equality of 3

means) were more likely to indicate that they would

like the physician to speak more positively (P < .001), to

want the physician to use general terms (P < .002), to

want the physician to soften bad news (P < .001), and

to want the physician to speak in an emotionally sup-

portive way (P < .001).

TABLE 2Patient Demographics (N5459)

No. %

Median age (range), y 60 (26-89)

Male 232 51%

Race

White 416 91%

Black 29 6%

Other 14 3%

Ethnicity

Non-Hispanic 452 99%

Hispanic 6 1%

Education

High school 136 30%

Some college 145 32%

�College degree 178 39%

Cancer diagnosis

Lung 83 18%

Colorectal 68 15%

Breast 53 12%

Pancreas 32 7%

Prostate 33 7%

Renal 24 5%

Ovarian 21 5%

Other* 145 32%

Y since diagnosis

Median 1

Mean (SD) 3.1 (4.3)

Range 0-41

Prior systemic therapy 276 60%

SD indicates standard deviation.

*‘‘Other’’ includes cancers accounting for <5% of all diagnoses within the study population, includ-

ing bladder, bone, cervical, endometrial, esophageal, head and neck cancers, lymphoma, melanoma,

stomach, and thyroid.

TABLE 3Preferences for Quality and Length of Life

Single-Item Measure No. %

Quality of life is all that matters 67 15%

Quality of life is more important, but length of life matters 299 65%

Length of life is more important, but quality of life matters 89 19%

Length of life is all that matters 4 1%

Composite Measure Mean SD

How important is quality of life to you? 4.4 0.8

How important is length of life to you? 4.2 1.0

No. %

Quality of life more important 123 27%

Equally important 252 55%

Length of life more important 84 18%

SD indicates standard deviation.

TABLE 4Relation Between Patient Characteristics and Values Preferences

Values Preference

QOL Equal LOL P

No. 123 252 84

Mean age (SD), y 62.6 (10.5) 59.2 (11.9) 57.3 (11.9) .001

PCS-12 43.6 (10.6) 44.7 (11.1) 41.7 (10.4) .073

MCS-12 46.1 (6.8) 44.6 (7.5) 43.9 (9.2) .069

Male 34% 49% 17% .003

Female 20% 61% 19%

Race .67

Black 17% 59% 24%

White 27% 55% 18%

Other 35% 50% 14%

Education .062

�High school 18% 62% 19%

Some college 28% 51% 21%

�College 32% 52% 16%

QOL indicates quality of life preferred; LOL, length of life preferred; SD, standard deviation; PCS,

Physical Component Scale; MCS, Mental Component Scale.


DISCUSSIONThere is great variability reported in cancer patients’

preferences regarding the content and format of

communication from their physicians.28-31 Matching

communication to patient preferences contributes to

quality patient decision making and satisfaction.23,32

Thus, tools to assist physicians in identifying relevant

patient preferences and guiding communication

accordingly could improve clinical outcomes. The

data we present indicate that a values preference for

LOL versus QOL may be simply measured, and is

associated with a desire for more supportive and less

pessimistic communication from the oncologist.

Communication skill in the cancer context is par-

ticularly critical given that patients are commonly

facing mortality and ‘bad news,’ treatment outcomes

are characterized by uncertainty, and treatment is

associated with the significant potential for morbidity.

Previous reports have identified a variety of patient

characteristics that bear on their wishes regarding

physician communication. For example, women and

patients with higher levels of educational attainment

have been shown to want more detailed information

regarding their prognosis.31,33,34 Female sex is also

associated with a desire for a supportive communica-

tion style over a blunter approach, whereas patients

with more education31 and older patients35 have

been shown to prefer a more fact-oriented style of

communication. The data we present support the hy-

pothesis that a preference for QOL versus LOL is a

key value that impacts treatment goals and desires

regarding physician communication. We also ob-

served that older age (P 5 .001), male sex (P 5 .003),

and higher educational level (P 5 .063) were asso-

ciated with a preference for QOL. Even after propen-

sity score adjustment, the QOL/LOL preference was

predictive of patient communication preferences.

It is notable that patients with less cancer-related

distress were more likely to favor QOL over LOL. The

direction of causation in this relationship cannot be

concluded from these data. It is possible that

increased distress is associated with greater difficulty

in processing QOL issues when faced with a life-

threatening illness, and therefore a focus on LOL is

preferred. It is also plausible that a greater concern

for one’s LOL leads to greater anxiety in the context

of an immediate threat to longevity. In either case,

high levels of distress can negatively impact risk in-

formation processing and communication, and, ulti-

mately, decision making. The finding that those

patients who favor LOL seek a more supportive com-

munication style and content is consistent with a

desire to minimize additional distress in this patient

subgroup. Furthermore, an alternative explanation

exists: patients who rely more heavily on blunting or

denial as a way to manage their distress may be

more inclined to avoid thinking about the end of life

and report a preference for LOL without fully consid-

ering the range of options, namely, shorter but

enhanced QOL. This subgroup of individuals may be

more inclined to prefer provider communications

that ‘soften the blow’ and avoid discussion of a diffi-

cult reality, and experience heightened distress when

provided with too much threat-relevant informa-

tion.36 Further research is required to more finely

delineate the relation between these cognitive and

affective influences on downstream events.

Although patients who value LOL over QOL pre-

fer a more supportive communication style, this does

not suggest that communication of ‘bad news’ should

be avoided. The withholding of negative prognostic

information may result in a loss of trust in the physi-

cian, decreased compliance, communication barriers

between partners, patient isolation and loss of con-

trol, and a lost opportunity to adapt to new circum-

stances.37-39 Furthermore, recent data suggest that

prognostic disclosure may be associated with

increased hope, even in the face of a poor progno-

sis.40 The data from the current study support the

recommendation that communication must be tai-

lored such that medical information is conveyed in a

manner that serves the cognitive and affective needs

of individual patients.28,37-39

The current study findings also demonstrate that

patients who value LOL over QOL have lower scores

on indicators of mental health, with a trend for these

patients to score lower on indicators of physical

health. We previously reported that the decision to

FIGURE 2. Quality of life (QOL)-length of life (LOL) preferences amongpatients with different types of cancer.


take part in an experimental therapy program (per-

haps indicative of an LOL focus) was related to a

patient’s reference point regarding the threat that

their cancer posed to their quality–adjusted sur-

vival.41 Further exploration of the relation between

health status and preferences regarding QOL and

LOL is warranted.

Because the study population in this report is

racially homogenous and relatively well–educated, it

is difficult to generalize these results to a more

diverse population. It is possible that the relation-

ships we observed between distress, QOL and LOL

preferences, and communication preferences may

differ in various socioeconomic or racial groups.

Furthermore, this study is limited in that the assess-

ment was conducted at a single timepoint, and does

not capture potential variations in values and goals

over the course of illness. Finally, the method we

used to classify patients’ preferences for LOL versus

QOL assumed that a 1-point difference on a 5-point

scale represents a precise, meaningful difference. If

such differences were not meaningful, there would

be greater noise in our classification of patients’ pref-

erence, thus leading to an underestimation of the

relationships reported here. It is important to note

that before this classification method is adopted as a

component of routine care, further work to establish

its discriminant ability is appropriate. Nevertheless,

to our knowledge this study represents 1 of the lar-

gest surveys of cancer patient preferences reported

to date, and patient ascertainment procedures sought

to identify and enroll all eligible subjects.

In summary, the results of the current study pro-

vide evidence that patient differences in the value

placed on QOL and LOL can be easily assessed, and

these values are associated with preferences for the

content and format of physician communication. We

currently are conducting a prospective randomized

clinical trial (NCT00244868) to assess whether pro-

viding patients with communication skills training,

and reporting patient values and preferences to the

oncologist before the initial consultation will impact

communication content and format, and improve

patient satisfaction with the consultation.

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Cancer patient preferences for quality and length of life

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