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Original article
Cancer patients’ acceptance, understanding, and willingness-to-pay for pharmacogenomic testing Sinead Cuffea, Henrique Hona, Xin Qiub, Kimberly Tobrosa, Chung-Kwun Amy Wonga, Bradley De Souzaa, Graham McFarlanea, Sohaib Masroora, Abul K. Azada, Ekta Hasania, Natalie Rozaneca, Natasha Leighla, Shabbir Alibhaic, Wei Xub, Amalia M. Issad and Geoffrey Liua Background Pharmacogenomics is gaining increasing importance in the therapeutics of cancer; yet, there is little knowledge of cancer patients’ attitudes toward the use of pharmacogenomic testing in clinical practice. We carried out this study to explore cancer patients’ acceptance, understanding, and willingness-to-pay for pharmacogenomic testing. Materials and methods A broad cross-section of gastrointestinal, lung, breast, and other cancer patients were interviewed in terms of their acceptance of pharmacogenomic testing using hypothetical time, efficacy, and toxicity trade-off and willingness-to-pay scenarios. Results Among the 96% of 123 adjuvant patients accepting chemotherapy under optimal conditions, 99% wanted pharmacogenomic testing that could identify a subset of patients benefiting from chemotherapy, accepting median incurred costs of $2000 (range $0–25 000) and turnaround time for test results of 16 days (range 0–90 days). Among the 97% of 121 metastatic patients accepting chemotherapy, 97.4% wanted pharmacogenomic testing that could detect the risk of severe toxicity, accepting median incurred costs of $1000 (range $0–10 000) and turnaround time for results of 14 days (range 1–90 days). The majority of patients wanted to be involved in decision-
Introduction Pharmacogenomic testing of a patient’s inherited genetic variation and/or tumor molecular changes is increasingly being used to stratify patients to receive preferentially specific therapies, with the goal of improving outcomes and minimizing toxicity. There are many challenges to its implementation in clinical practice, however [1,2]. Pharmacogenomic tests can be expensive [3] and have a turnaround time of several days to weeks [4], with the potential to cause increased psychological stress [5]. In addition, not everyone who undergoes pharmacogenomic testing will derive a change in therapy nor does receiving the test guarantee a response to therapy or reduced toxicity. Moreover, there is significant uncertainty in the Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.pharmacogeneticsandgenomics.com). 1744-6872 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
making on pharmacogenomic testing; however, one in five patients lacked a basic understanding of pharmacogenomic testing. Conclusion Among cancer patients willing to undergo chemotherapy, almost all wanted pharmacogenomic testing and were willing-to-pay for it, waiting several weeks for results. Although patients had a strong desire to be involved in decision-making on pharmacogenomic testing, a considerable proportion lacked the necessary knowledge to make informed choices. Pharmacogenetics and Genomics 24:348–355 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Pharmacogenetics and Genomics 2014, 24:348–355 Keywords: patient preference, personalised medicine, pharmacogenomics Departments of aMedical Oncology, bBiostatistics, Princess Margaret Cancer Centre, University of Toronto, cDepartment of Medicine, University Health Network, Toronto, Ontario, Canada and dProgram in Personalized Medicine and Targeted Therapeutics, Department of Health Policy and Public Health, University of the Sciences, Philadelphia, Pennsylvania, USA Correspondence to Geoffrey Liu, MD, Princess Margaret Cancer Centre, Room 7-124, 610 University Ave, Toronto, ON, Canada M5G 2M9 Tel: + 1 416 946 3428; fax: + 1 416 946 6546; e-mail: [email protected] Received 4 October 2013 Accepted 22 April 2014
clinical utility of many pharmacogenomic tests because of a lack of large-scale prospective clinical trials to validate the impact of genetic variability on drug response. Finally, there may be additional privacy, security, and ethical concerns related to testing [1,6]. Despite these challenges, pharmacogenomics is being endorsed increasingly by professional organizations in oncology: both the American Society of Clinical Oncology and the National Comprehensive Cancer Network guidelines now include the Oncotype DX assay as an option to predict whether certain breast cancer patients will benefit from chemotherapy [7,8]. Pharmacogenomic information is currently incorporated into the labeling of ∼ 10% of all drug approved by the US Food and Drug Administration [9]. Moreover, significant resources have been invested into the research and development of pharmacogenomics, with the National DOI: 10.1097/FPC.0000000000000061
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Cancer patients and pharmacogenomic testing Cuffe et al. 349
Institute of Health budgeting $161.3 million over 5 years to expand its Pharmacogenomics Research Network [10]. As the clinical applications for pharmacogenomic-based diagnostics in cancer therapy expand, it is important to understand how patients perceive this technology, and in particular, their readiness to accept and adopt testing in the clinical setting. This is especially true when we consider that patients increasingly want to be involved in decision-making on their medical treatment [11–13], including cancer therapy [14–16], and experience greater satisfaction as a result [16]. Already, there are concerns that patients may lack awareness and understanding of pharmacogenomics [17–19] or have issues relating to privacy, cost, and accuracy of testing [17–22], which could significantly impact on their readiness to adopt this technology. However, there is comparatively little knowledge of cancer patients’ actual willingness to accept and pay for pharmacogenomic testing in the clinical setting or their associated preferences therein. Other analyses have focused on specific pharmacogenomic tests currently available, such as KRAS mutation or HER2 testing, which limit the generalizability of the results. This has prompted several experts to call for further research in this area [3,21–24]. In this study, we seek to address this gap in knowledge by providing a detailed overview of cancer patients’ understanding, desire, and willingness to accept and pay for pharmacogenomic testing, and further highlight the clinical characteristics and patient values underlying such preferences.
Materials and methods Study population
The study population included cancer patients attending the Princess Margaret Cancer Centre, Toronto, Canada, between April and October 2010. Eligibility criteria were as follows: (a) established diagnosis of malignancy; (b) life expectancy of at least 30 days; (c) potential that systemic therapy could be offered or has been offered previously; (d) age of at least 18 years; (e) ability to communicate effectively in English; and (f) no significant cognitive impairment. The study population was subdivided into an adjuvant group (patients undergoing curative intent treatment) and a metastatic group (incurable patients) on the basis of cancer patients’ self-reported perception of the stage of their disease. The study was approved by the institution’s Research Ethics Board. Study design
Eligible patients provided informed consent during their clinic visit and completed a questionnaire of patient demographics, health status, and associated health values. Patients were then interviewed on their preferences for pharmacogenomic testing using hypothetical trade-off clinical scenarios outlining the use of chemotherapy in either a curative (adjuvant group) or a
palliative (metastatic group) setting. Cancer diagnoses and treatments were confirmed using electronic health records. Any patient determined to have received a scenario type inconsistent with their curative/palliative intent was excluded from analyses.
Questionnaire
The questionnaire encompassed four domains: (a) Sociodemographic characteristics: age; sex; ethnicity; marital status; number of household members; annual household income; highest educational level; occupational status; (b) Health status: primary cancer diagnosis; previous receipt of chemotherapy or targeted therapy; previous participation in a clinical trial; previous experience of genomic testing; patients’ own assessment of personal health; (c) Patient preference for who should decide on need for pharmacogenomic testing; and (d) Level of agreement (Likert scales) with a series of novel statements designed to elicit patients’ values on chemotherapy and pharmacogenomics.
Trade-off technique
Patient preferences for chemotherapy and pharmacogenomic testing were evaluated using intervieweradministered, scenario-based questionnaires, and probability trade-off testing (Supplementary Appendix 1a and b, Supplemental digital content 1, http://links.lww.com/ FPC/A732) similar to our previous research [25]. Patients were presented with a theoretical scenario in which they were recommended to undergo a course of chemotherapy, and questioned whether, faced with that scenario, they would opt to undergo chemotherapy with its stated risks and benefits. If patients opted against chemotherapy, the scenario was then modified by systematically altering the risks and benefits of chemotherapy to determine under which circumstances, if any, patients would be willing to accept treatment. Patients accepting chemotherapy were then presented with a follow-on scenario outlining the availability of a hypothetical pharmacogenomic test that could predict the likely efficacy (adjuvant group) or the risk of toxicity (metastatic group) of chemotherapy. Patients expressing a preference for pharmacogenomic testing were asked to trade off their preference against the burden of testing by systematically modifying the levels of various attributes associated with testing until the patient opted against testing. The primary attribute was either response to therapy or the risk of adverse events. Other attributes included (a) cost of testing; (b) wait time for test results; and (c) prevalence of the genetic variation of interest. Finally, patients’ and interviewers’ assessment of the level of understanding of the scenario were measured using Likert scales.
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350 Pharmacogenetics and Genomics 2014, Vol 24 No 7
Statistical analyses
Descriptive statistics were used to characterize patient demographics, their preferences for chemotherapy, their desire for pharmacogenomic testing, and their preferences for who should decide on need for pharmacogenomic testing. Comparisons between the adjuvant and metastatic groups were performed using Pearson’s χ2-test and Wilcoxon rank-sum tests. Multivariate logistic regression models of patients’ desire for pharmacogenomic testing were performed using stepwise selection among clinically important and/or significant variables in univariate analysis (P < 0.1). Multivariate linear regression model of patients’ willingness-to-pay and willingness to wait for test results were assessed using a stepwise selection, with a log transformation on outcome for willingness-to-pay. All multivariate analyses were stratified or adjusted by cohort. Results were considered significant if the P-value was 0.05 or less. Statistical analyses were carried out using SAS version 9.2 (SAS Institute, Cary, North Carolina, USA).
Results Baseline demographics
The overall participation rate was 92%. Of 278 study participants, 153 (55%) received the adjuvant scenario and 125 (45%) received the metastatic scenario; 34 patients (12%) were subsequently determined on chart review to have received a scenario type incongruous to their disease stage (30 in the adjuvant group; four in the metastatic group) and were excluded from analyses. Baseline demographics of the final study population (n = 244) are presented in Table 1. The distribution of adjuvant and metastatic patients was in keeping with the underlying patient population of the Princess Margaret Cancer Centre. Metastatic patients were older (P = 0.04) and more likely to be male (P = 0.003) compared with their adjuvant counterparts. Metastatic patients were more likely to be retired (P = 0.02), to have received previous chemotherapy (P = 0.01), and/or targeted therapy (P < 0.001), to have participated in a treatment clinical trial (P < 0.001), and had a lower annual household income (P = 0.04) and lower median personal health rating (6; range 0–10) compared with adjuvant patients (7; range 3–10; P < 0.001).
Table 1
Patient demographics Adjuvant Metastatic (N = 123) [N (%)] (N = 121) [N (%)]
Sex Male Female Age Median Range Ethnicity White Non-White Marital status Married Other Education Secondary or less Postsecondary Employment Professional and white collar Retired All other Household income (CAD$) < 50 000 50 000–100 000 > 100 000 Unknown Cancer type Lung and head and neck Gastrointestinal and hepatobiliary Breast Other Previous chemotherapy No Yes Previous targeted therapy No Yes Clinical trial experience No Yes Previous genetic testing No Yes Personal health rating (0–10)a Median Range
P-value
56 (46) 67 (54)
78 (64) 43 (36)
0.003
58 21–90
62 27–82
0.04
99 (80) 24 (20)
100 (83) 21 (17)
0.66
90 (73) 33 (27)
83 (69) 38 (31)
0.43
46 (37) 77 (63)
44 (36) 77 (64)
0.87
42 (34)
28 (23)
41 (33) 40 (33)
62 (51) 31 (26)
31 34 49 9
47 35 29 10
(25) (28) (40) (7)
(39) (29) (24) (8)
0.02
0.04
29 (24) 47 (38)
42 (35) 39 (32)
24 (20) 23 (18)
8 (7) 32 (26)
22 (18) 101 (82)
9 (7) 112 (93)
0.01
102 (83) 21 (17)
55 (45) 66 (55)
< 0.001
100 (81) 23 (19)
75 (62) 46 (38)
< 0.001
119 (97) 4 (3)
110 (91) 11 (9)
0.06
7 3–10
6 0–10
< 0.001
0.006
a Linear Likert scale, where 0 signifies worst possible health and 10 signifies best possible health.
Acceptance of chemotherapy and pharmacogenomic testing
accept pharmacogenomic testing that could improve the prediction of response to chemotherapy when the test was free, had a 1-day turnaround time for results, and the prevalence of the genetic variation associated with lack of response to chemotherapy was 50%.
Eighty-nine percent of the study participants answered each of the main outcome questions in the survey; thus, 82% of all patients approached were included in the final analyses. Among the adjuvant group, 72% were willing to accept chemotherapy for a 5% absolute improvement in cure rate and risk of severe side effects of less than 5%. A further 24% of patients would accept chemotherapy for a higher cure rate (median 15%; range 10–50%); thus, only 4% refused chemotherapy at any level of benefit. Of the patients accepting chemotherapy, 99% were willing to
Among the metastatic group, 92% were willing to accept chemotherapy for an 80% benefit (shrinkage or stable disease) and risk of severe side effects of less than 5%. A further 2.5% would accept chemotherapy for a higher response rate (median 95%; range 85–100%), whereas 2.5% would accept chemotherapy for a lower risk of side effects (median 0%; range 0–1%). Of the 97% of patients accepting chemotherapy, 97.4% were willing to accept pharmacogenomic testing that could stratify risk of
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Cancer patients and pharmacogenomic testing Cuffe et al. 351
toxicity when the test was free, had a 1-day turnaround time for results, and the prevalence of the genetic variation associated with severe side effects was 5%.
diagnosis (P = 0.01) and those agreeable to an additional blood test (P = 0.006) were more accepting (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/FPC/A733).
Willingness-to-pay
The median out-of-pocket cost at which patients would no longer opt to undergo pharmacogenomic testing (acceptable price) and the median cost that patients considered reasonable for testing are presented in Table 2. Patients’ perceptions of acceptable and reasonable prices were significantly correlated (r = 0.44, P < 0.0001). Willingness-to-pay was higher among patients who better understood genetic testing (P = 0.01), and those with annual household income > CAD$50 000 (P < 0.001), and declined among patients who did not understand the scenario completely (P = 0.01; Table 3).
The majority of patients wanted decision-making on pharmacogenomic testing to be shared between the patient and the physician (Table 5). Patients who admitted to worrying about how to finance pharmacogenomic testing were more likely to favor a shared decisionmaking process versus a physician-only process (P = 0.02). In contrast, patients who indicated that they would be distressed by the need for an additional blood draw preferred to make their own decisions (P = 0.03). Patient understanding
Other preferences
The median acceptable wait time for pharmacogenomic test results was 16 days (range 0–90 days) for the adjuvant group and 14 days (range 1–90 days) for the metastatic group. Patients’ preferences for pharmacogenomic testing were not significantly influenced by the prevalence of the genetic variation of interest (likelihood of test results influencing a treatment change). The median lowest prevalence of the genetic variation at which patients would no longer opt for pharmacogenomic testing was just 5% (range 0–80%) and 1.5% (range 0–10%) for the adjuvant and metastatic groups, respectively. Among adjuvant patients, 37% would accept testing even when the prevalence of the genetic variation of interest varied from 5 to 95%. Patient attitudes toward pharmacogenomic testing
Over 85% of patients agreed that reducing the chance of receiving ineffective treatment was a high priority (Table 4). Interestingly, 77% believed that any additional test offered by the medical profession must be of benefit. Fewer than 15% would accept pharmacogenomic testing only if they could be reassured that it would not detect the inheritability of their cancer, whereas one-third of patients worried about finding money to pay for testing. Ninety-two percent of patients were agreeable to an additional blood draw to facilitate testing, whereas just over half (55%) were agreeable to biopsy. Women (P < 0.001) and chemotherapy-naïve patients (P = 0.002) were significantly less likely to agree to an additional biopsy, whereas patients with more than one cancer Table 2
Decision-making
Using a five-point Likert scale, more than 75% of patients rated the clinical scenario trade-off testing as easy or very easy to understand, with just 9.5% rating it as difficult/very difficult. Patient and interviewer assessments of patient understanding were highly correlated (P < 0.0001). One-fifth of patients indicated that they did not fully understand genetic testing and were worried about its implications. Understanding was lower among patients who were concerned about the potential of pharmacogenomic testing to predict for inheritability of cancer (P = 0.001), whereas patients who were willing to undergo an additional biopsy better understood testing (P = 0.05; Table 6). Level of understanding had no impact on strength of desire for pharmacogenomic testing.
Discussion Despite several professional organizations in oncology now endorsing pharmacogenomic testing [7,8,26], the translation of pharmacogenomic testing into clinical practice has been relatively slow. Increasingly, it is being recognized that successful implementation of pharmacogenomic testing into clinical practice is reliant on patients’ acceptance of and willingness-to-pay for testing [3,23]. We report that adjuvant and metastatic cancer patients in a North American academic center are overwhelmingly willing to accept, pay for, and wait for pharmacogenomic testing when such testing had been deemed clinically useful by their healthcare provider.
Willingness-to-pay for pharmacogenomic testing and acceptable wait time for results Adjuvant
Willingness-to-pay/acceptable price for test (CAD$) Patients’ perception of reasonable price for test (CAD$) Acceptable waiting time for test results (days)
Metastatic
Median
Range
Median
Range
P-value
2000 200 16
0–25 000 0–25 000 0–90
1000 100 14
0–10 000 0–5000 1–90
0.23 0.18 0.27
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352 Pharmacogenetics and Genomics 2014, Vol 24 No 7
Table 3
Significant factors associated with patients’ willingness-to-pay for pharmacogenomic testing
Patient group Adjuvant
Metastatic
Combined
Number of patientsa
Predictors
Mean acceptable cost
SEM
P-value
1953 3588 4821
527 877 746
< 0.001
3632 1696
439 519
0.02
3588 1052
421 389
0.01
1493 3173 4904
370 654 789
2290 3336
763 421
1682 3384 4854
306 542 546
3688 2173
308 623
0.01
1465 3587
500 299
0.06
3781 2309
342 431
0.06
2336 3764
495 347
0.01
Household income per year (CAD$) < 50 000 31 50 000–100 000 33 > 100 0000 45 Marital status Married 81 Others 36 ‘Don’t understand genetic testing and would worry about implications’ 1–3 (strongly disagree–neutral) 91 4–5 (somewhat–strongly agree) 26 Household income per year (CAD$) < 50 000 44 50 000–100 000 35 > 100 000 28 Understood scenario – patient assessment 1–3 (strongly disagree–neutral) 20 4–5 (somewhat–strongly agree) 87 Household income per year (CAD$) < 50 000 75 50 000–100 000 68 > 100 000 73 ‘Don’t understand genetic testing and would worry about implications’ 1–3 (strongly disagree–neutral) 183 4–5 (somewhat–strongly agree) 50 ‘Measures to prolong life are of utmost importance to me’ 1–3 (strongly disagree–neutral) 23 4–5 (somewhat–strongly agree) 211 Marital status Married 168 Others 66 Understood scenario – patient assessment 1–3 (strongly disagree–neutral) 45 167 4–5 (somewhat–strongly agree)
0.001
0.05
< 0.001
a
Includes only those patients accepting chemotherapy; totals may vary because of missing data.
Table 4
Cancer patients’ agreement with statements designed to elicit patients’ values on chemotherapy and pharmacogenomic testing
Patient values Would be distressed by having to undergo an additional blood draw If test caused a change in treatment, would worry about receiving inferior treatment Delay in starting treatment would cause additional anxiety If the test was available but not offered, it would cause additional anxiety Worry about finding money to pay for test Believe any additional tests offered by the medical profession must be of benefit Measures to prolong life are of utmost importance to me Quality of life is of utmost importance Do not understand genetic testing and would worry about implications If test did not cause a change in treatment, would be reassured that getting correct treatment Reducing chance of getting ineffective treatment is important Prefer if testing was performed on existing tumor sample rather than extra blood draw Agreeable to additional blood draw to facilitate testing Agreeable to additional biopsy to facilitate testing Agreeable to have testing provided that it did not look at inheritability of cancer
Adjuvant % of patients
Metastatic % of patients
Combined % of patients
11 16 52 0 26 79 87 93 20 74
5 16 45 42 39 75 91 91 22 72
9 16 48 42 32 77 89 92 22 73
89 20 88 54 11
85 25 95 56 16
87 23 92 55 14
No significant difference was found between the adjuvant and the metastatic groups.
Patients’ opinion on who should decide on the need for pharmacogenomic testing
Table 5
Adjuvant [N (%)] Physician Patient Both physician and patient Unsure
22 6 90 5
(18) (5) (73) (4)
Metastatic [N (%)] 12 11 94 4
(10) (9) (78) (3)
P-value 0.20
P-value represents any differences in opinion between the adjuvant and the metastatic groups on who should decide on the need for pharmacogenomic testing.
The strength of patients’ desire for pharmacogenomic testing was evidenced by the considerable out-of-pocket costs that patients were willing-to-pay, especially as our patients derive from a universal healthcare system, and are familiar with healthcare that is mostly reimbursed at point of use. Importantly, several studies have shown that willingness-to-pay may be a surrogate measure not only of patients’ perception of the worth or benefit of a test but also of their willingness to adopt novel technologies [27,28].
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Cancer patients and pharmacogenomic testing Cuffe et al. 353
Table 6
Significant factors associated with patients’ understanding of pharmacogenomic testing
Patient group Adjuvant
Metastatic
Combined
Predictors
Number of patientsa
Patients who understand (%)
‘Agreeable to have testing provided that it did not look at inheritability of cancer’ 4–5 (somewhat–strongly agree) 13 1–3 (strongly disagree–neutral) 104 ‘Agreeable to additional biopsy to facilitate testing’ 4–5 (somewhat–strongly agree) 66 1–3 (strongly disagree–neutral) 51 Ethnicity Non-Caucasian 42 Caucasian 192 ‘If test didn’t cause a change in treatment, would be reassured that getting correct 1–3 (strongly disagree–neutral) 63 4–5 (somewhat–strongly agree) 167 ‘Agreeable to additional biopsy to facilitate testing’ 4–5 (somewhat–strongly agree) 129 1–3 (strongly disagree–neutral) 105 ‘Agreeable to have testing provided that it did not look at inheritability of cancer’ 4–5 (somewhat–strongly agree) 32 1–3 (strongly disagree–neutral) 202
Odds ratio (95% CI)b
P-value
54 82
4.10 (1.23–13.6)
0.02
88 65
0.25 (0.10–0.65)
0.004
67 81 treatment’ 87 75
2.09 (0.95–4.62)
0.07
0.46 (0.20–1.04)
0.06
84 71
0.51 (0.26–1.01)
0.05
53 82
3.94 (1.74–8.92)
0.001
CI, confidence interval. Totals may vary due to missing data. b Odds ratio >1 signifies that patients are less likely to understand pharmacogenomic testing when compared to the reference group. a
The median willingness-to-pay for pharmacogenomic testing (CAD$1000–2000) was higher than that reported in a discrete–choice experiment study in depression in which the median willingness-to-pay for avoidance of one change in antidepressant medication was 1571 Danish Krone (CAD$264) [29]. Although a possible reason for this discrepancy may relate to patients’ perception of a cancer diagnosis as being more severe than that of other chronic conditions [22], other reasons include socio-cultural and economic factors and perception of the role of public versus private healthcare. However, one-third of the study participants worried about finding money to fund testing, raising concerns as to whether patients would actually pay such large amounts in clinical practice. Indeed, the median cost that patients considered reasonable for testing was, on average, one-tenth of the willing-to-pay amounts, significantly lower than the current market value of many pharmacogenomic tests. Reimbursement policies will, therefore, be of importance in integrating pharmacogenomic testing into clinical practice [30], and are most influenced by strength of clinical evidence, endorsement by professional guidelines, and cost-effective analyses [31]. However, although there is mounting evidence for the clinical benefit of many pharmacogenomic tests, considerably fewer cost-effective analyses have been carried out [32], highlighting the importance of integrating such analyses into future pharmacogenomic studies. Cancer patients’ enthusiasm for pharmacogenomic testing was further evidenced by their willingness to accept considerable delays in initiating treatment to avail of testing. The median acceptable wait time for results of 14–16 days exceeded the 2–7-day preferred turnaround time reported in a previous study involving noncancer patients receiving azathioprine [33]. This is important
given that one in five physicians admit to ‘assuming patient priorities and preferences for pace of treatment’ and would consider omitting what they regard as clinically relevant pharmacogenomic tests to avoid treatment delays [34]. In contrast, our findings support the converse view of patient advocates who report that patients do not necessarily prefer the speediest time to treatment, but instead welcome the opportunity to discuss all treatment options [34]. Finally, although one-quarter of Canadian physicians cite lack of patient demand for pharmacogenomic testing as a potential barrier to its use in clinical practice [35], our findings provide empiric data to the contrary. Although we have shown that cancer patients are overwhelmingly willing to accept, pay for, and wait for pharmacogenomic testing, we also identified significant deficiencies in patients’ understanding of pharmacogenomics. Despite our highly educated and potentially select study population, of whom two-thirds had higher education, more than one in five patients did not fully understand genetic testing and worried about its implications. The degree of misunderstanding may even be higher, given that 14% of patients equated pharmacogenomic testing to fears of its potential to predict for inheritability of cancer, whereas patients’ acceptance of testing was relatively insensitive to the prevalence of the genetic variation affecting treatment efficacy/toxicity. In addition, despite strongly wanting pharmacogenomic testing, only half were willing to undergo an additional biopsy to facilitate testing, implying possible lack of conviction behind their stated beliefs. Moreover, there appeared to be blind acceptance that any test offered by the medical profession must be of benefit. These findings all point to the urgent need for improved patient education.
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354 Pharmacogenetics and Genomics 2014, Vol 24 No 7
The strengths of our study include its high response rate and the inclusion of patients with a diverse range of cancer diagnoses. Nonetheless, our study has limitations. To simplify matters, this study involved two different hypothetical scenarios depending on patients’ selfreported cancer stage. In the adjuvant group, we focused on the impact of pharmacogenetic testing on the efficacy, but not toxicity, of chemotherapy, whereas in the metastatic group, we focused only on its influence on the toxicity of chemotherapy. Although ideally it would have been useful to examine the influence of pharmacogenomic testing on both the efficacy and the toxicity of chemotherapy in each population group, this would have made the hypothetical scenarios and subsequent analyses overcomplicated. Indeed, hypothetical scenarios can never fully show the actual complexity of decisionmaking in the real world [36,37]. Thus, it is likely that the interest reported in this study may be an overestimate of actual uptake rates and willingness-to-pay if translated into clinical practice [36,37]. This is especially true when we consider the level of uncertainty in understanding of pharmacogenomic testing in one-fifth of our population. Our goal was to evaluate patient attitudes, preferences, and understanding; thus, we did not address broader pharmacogenomic issues such as clinical utility, physician resistance, and insurance reimbursement issues as this would have made the scenarios overly complicated. Nonetheless, we are cognizant of the fact that the ‘level of evidence’ for genetic testing may particularly impact on patients’ willingness to adopt pharmacogenomic testing in clinical practice; thus, we recommend that future studies address this. We also did not address patient perceptions of whether pharmacogenomic tests were considered part of their standard care as the scenarios assumed that the tests were validated, but were not reimbursed by insurance or medical providers. Our questions do not fully focus on the attribute differences between testing for germline versus somatic mutations, where familial implications are important for the former, but not for the latter; these will form the basis of one of our follow-up studies. Certainly, willingness to provide a blood draw (generally for genetic testing) was higher than a second biopsy specimen. Finally, our patient population was derived from a single tertiary cancer center within a universal healthcare system, and was therefore potentially select, which may impact on the generalizability of our results. Conclusion
Despite significant advances in pharmacogenomics in recent years, the diffusion of pharmacogenomic testing into patient care has been variable [38–41]. Although the reasons underlying this are multifactorial and include a relative lack of large-scale prospective trials validating the impact of genomic variability on drug response, several authors have expressed concern that the cost of testing
may be prohibitive and/or that patients may be resistant to adopting this technology [42,43]. In this study, we found the opposite. While acknowledging the limitations of our study, we have shown that among cancer patients accepting chemotherapy, the vast majority were accepting of pharmacogenomic testing and were willing to accept considerable out-of-pocket costs and delays in treatment to avail of testing. However, in line with previous studies, we observed a self-perceived lack of clarity of understanding of pharmacogenomics in a substantial minority of our cancer patients that could potentially impact on the actual utilization of pharmacogenomic testing in clinical practice. Although the majority of cancer patients want to participate in decision-making on pharmacogenomic testing, a considerable proportion lacked the necessary knowledge to make fully informed choices. Significant efforts to improve patient education are therefore warranted.
Acknowledgements This work was supported by the Princess Margaret Hospital Foundation and the Posluns Family Foundation. Amalia M. Issa’s work is partially funded by In Health, the Institute for Health Technology Studies. Previous presentations: (a) Poster presentation ‘Cancer Patients’ and Physicians’ Preferences for DecisionMaking Regarding Pharmacogenomic Testing (PGT)’, American Society of Clinical Oncology Quality Care Symposium, San Diego, 2012 (Conquer Cancer Foundation of ASCO Merit Award recipient). (b) Oral presentation ‘Cancer Patient Acceptance, Understanding, and Willingness to Pay for Pharmacogenetic Testing (PGT)’, American Society of Clinical Oncology Annual Meeting, Chicago, 2012. (c) Poster presentation ‘Patient Attitudes toward Receiving Chemotherapy and Pharmacogenetic Testing in Curative and Palliative Cancer Patients’, 27th International Conference on Pharmacoepidemiology & Therapeutic Risk Management, Chicago, 2011. Conflicts of interest
Geoffrey Liu holds the Alan B. Brown Chair in Molecular Genomics and the Cancer Care Ontario Chair in Experimental Therapeutics and Population Studies and is a member of the Canadian Pharmacogenetic Network for Drug Safety. For the remaining authors there are no conflicts of interest.
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Original article
Cancer patients’ acceptance, understanding, and willingness-to-pay for pharmacogenomic testing Sinead Cuffea, Henrique Hona, Xin Qiub, Kimberly Tobrosa, Chung-Kwun Amy Wonga, Bradley De Souzaa, Graham McFarlanea, Sohaib Masroora, Abul K. Azada, Ekta Hasania, Natalie Rozaneca, Natasha Leighla, Shabbir Alibhaic, Wei Xub, Amalia M. Issad and Geoffrey Liua Background Pharmacogenomics is gaining increasing importance in the therapeutics of cancer; yet, there is little knowledge of cancer patients’ attitudes toward the use of pharmacogenomic testing in clinical practice. We carried out this study to explore cancer patients’ acceptance, understanding, and willingness-to-pay for pharmacogenomic testing. Materials and methods A broad cross-section of gastrointestinal, lung, breast, and other cancer patients were interviewed in terms of their acceptance of pharmacogenomic testing using hypothetical time, efficacy, and toxicity trade-off and willingness-to-pay scenarios. Results Among the 96% of 123 adjuvant patients accepting chemotherapy under optimal conditions, 99% wanted pharmacogenomic testing that could identify a subset of patients benefiting from chemotherapy, accepting median incurred costs of $2000 (range $0–25 000) and turnaround time for test results of 16 days (range 0–90 days). Among the 97% of 121 metastatic patients accepting chemotherapy, 97.4% wanted pharmacogenomic testing that could detect the risk of severe toxicity, accepting median incurred costs of $1000 (range $0–10 000) and turnaround time for results of 14 days (range 1–90 days). The majority of patients wanted to be involved in decision-
Introduction Pharmacogenomic testing of a patient’s inherited genetic variation and/or tumor molecular changes is increasingly being used to stratify patients to receive preferentially specific therapies, with the goal of improving outcomes and minimizing toxicity. There are many challenges to its implementation in clinical practice, however [1,2]. Pharmacogenomic tests can be expensive [3] and have a turnaround time of several days to weeks [4], with the potential to cause increased psychological stress [5]. In addition, not everyone who undergoes pharmacogenomic testing will derive a change in therapy nor does receiving the test guarantee a response to therapy or reduced toxicity. Moreover, there is significant uncertainty in the Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.pharmacogeneticsandgenomics.com). 1744-6872 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
making on pharmacogenomic testing; however, one in five patients lacked a basic understanding of pharmacogenomic testing. Conclusion Among cancer patients willing to undergo chemotherapy, almost all wanted pharmacogenomic testing and were willing-to-pay for it, waiting several weeks for results. Although patients had a strong desire to be involved in decision-making on pharmacogenomic testing, a considerable proportion lacked the necessary knowledge to make informed choices. Pharmacogenetics and Genomics 24:348–355 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Pharmacogenetics and Genomics 2014, 24:348–355 Keywords: patient preference, personalised medicine, pharmacogenomics Departments of aMedical Oncology, bBiostatistics, Princess Margaret Cancer Centre, University of Toronto, cDepartment of Medicine, University Health Network, Toronto, Ontario, Canada and dProgram in Personalized Medicine and Targeted Therapeutics, Department of Health Policy and Public Health, University of the Sciences, Philadelphia, Pennsylvania, USA Correspondence to Geoffrey Liu, MD, Princess Margaret Cancer Centre, Room 7-124, 610 University Ave, Toronto, ON, Canada M5G 2M9 Tel: + 1 416 946 3428; fax: + 1 416 946 6546; e-mail: [email protected] Received 4 October 2013 Accepted 22 April 2014
clinical utility of many pharmacogenomic tests because of a lack of large-scale prospective clinical trials to validate the impact of genetic variability on drug response. Finally, there may be additional privacy, security, and ethical concerns related to testing [1,6]. Despite these challenges, pharmacogenomics is being endorsed increasingly by professional organizations in oncology: both the American Society of Clinical Oncology and the National Comprehensive Cancer Network guidelines now include the Oncotype DX assay as an option to predict whether certain breast cancer patients will benefit from chemotherapy [7,8]. Pharmacogenomic information is currently incorporated into the labeling of ∼ 10% of all drug approved by the US Food and Drug Administration [9]. Moreover, significant resources have been invested into the research and development of pharmacogenomics, with the National DOI: 10.1097/FPC.0000000000000061
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Cancer patients and pharmacogenomic testing Cuffe et al. 349
Institute of Health budgeting $161.3 million over 5 years to expand its Pharmacogenomics Research Network [10]. As the clinical applications for pharmacogenomic-based diagnostics in cancer therapy expand, it is important to understand how patients perceive this technology, and in particular, their readiness to accept and adopt testing in the clinical setting. This is especially true when we consider that patients increasingly want to be involved in decision-making on their medical treatment [11–13], including cancer therapy [14–16], and experience greater satisfaction as a result [16]. Already, there are concerns that patients may lack awareness and understanding of pharmacogenomics [17–19] or have issues relating to privacy, cost, and accuracy of testing [17–22], which could significantly impact on their readiness to adopt this technology. However, there is comparatively little knowledge of cancer patients’ actual willingness to accept and pay for pharmacogenomic testing in the clinical setting or their associated preferences therein. Other analyses have focused on specific pharmacogenomic tests currently available, such as KRAS mutation or HER2 testing, which limit the generalizability of the results. This has prompted several experts to call for further research in this area [3,21–24]. In this study, we seek to address this gap in knowledge by providing a detailed overview of cancer patients’ understanding, desire, and willingness to accept and pay for pharmacogenomic testing, and further highlight the clinical characteristics and patient values underlying such preferences.
Materials and methods Study population
The study population included cancer patients attending the Princess Margaret Cancer Centre, Toronto, Canada, between April and October 2010. Eligibility criteria were as follows: (a) established diagnosis of malignancy; (b) life expectancy of at least 30 days; (c) potential that systemic therapy could be offered or has been offered previously; (d) age of at least 18 years; (e) ability to communicate effectively in English; and (f) no significant cognitive impairment. The study population was subdivided into an adjuvant group (patients undergoing curative intent treatment) and a metastatic group (incurable patients) on the basis of cancer patients’ self-reported perception of the stage of their disease. The study was approved by the institution’s Research Ethics Board. Study design
Eligible patients provided informed consent during their clinic visit and completed a questionnaire of patient demographics, health status, and associated health values. Patients were then interviewed on their preferences for pharmacogenomic testing using hypothetical trade-off clinical scenarios outlining the use of chemotherapy in either a curative (adjuvant group) or a
palliative (metastatic group) setting. Cancer diagnoses and treatments were confirmed using electronic health records. Any patient determined to have received a scenario type inconsistent with their curative/palliative intent was excluded from analyses.
Questionnaire
The questionnaire encompassed four domains: (a) Sociodemographic characteristics: age; sex; ethnicity; marital status; number of household members; annual household income; highest educational level; occupational status; (b) Health status: primary cancer diagnosis; previous receipt of chemotherapy or targeted therapy; previous participation in a clinical trial; previous experience of genomic testing; patients’ own assessment of personal health; (c) Patient preference for who should decide on need for pharmacogenomic testing; and (d) Level of agreement (Likert scales) with a series of novel statements designed to elicit patients’ values on chemotherapy and pharmacogenomics.
Trade-off technique
Patient preferences for chemotherapy and pharmacogenomic testing were evaluated using intervieweradministered, scenario-based questionnaires, and probability trade-off testing (Supplementary Appendix 1a and b, Supplemental digital content 1, http://links.lww.com/ FPC/A732) similar to our previous research [25]. Patients were presented with a theoretical scenario in which they were recommended to undergo a course of chemotherapy, and questioned whether, faced with that scenario, they would opt to undergo chemotherapy with its stated risks and benefits. If patients opted against chemotherapy, the scenario was then modified by systematically altering the risks and benefits of chemotherapy to determine under which circumstances, if any, patients would be willing to accept treatment. Patients accepting chemotherapy were then presented with a follow-on scenario outlining the availability of a hypothetical pharmacogenomic test that could predict the likely efficacy (adjuvant group) or the risk of toxicity (metastatic group) of chemotherapy. Patients expressing a preference for pharmacogenomic testing were asked to trade off their preference against the burden of testing by systematically modifying the levels of various attributes associated with testing until the patient opted against testing. The primary attribute was either response to therapy or the risk of adverse events. Other attributes included (a) cost of testing; (b) wait time for test results; and (c) prevalence of the genetic variation of interest. Finally, patients’ and interviewers’ assessment of the level of understanding of the scenario were measured using Likert scales.
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350 Pharmacogenetics and Genomics 2014, Vol 24 No 7
Statistical analyses
Descriptive statistics were used to characterize patient demographics, their preferences for chemotherapy, their desire for pharmacogenomic testing, and their preferences for who should decide on need for pharmacogenomic testing. Comparisons between the adjuvant and metastatic groups were performed using Pearson’s χ2-test and Wilcoxon rank-sum tests. Multivariate logistic regression models of patients’ desire for pharmacogenomic testing were performed using stepwise selection among clinically important and/or significant variables in univariate analysis (P < 0.1). Multivariate linear regression model of patients’ willingness-to-pay and willingness to wait for test results were assessed using a stepwise selection, with a log transformation on outcome for willingness-to-pay. All multivariate analyses were stratified or adjusted by cohort. Results were considered significant if the P-value was 0.05 or less. Statistical analyses were carried out using SAS version 9.2 (SAS Institute, Cary, North Carolina, USA).
Results Baseline demographics
The overall participation rate was 92%. Of 278 study participants, 153 (55%) received the adjuvant scenario and 125 (45%) received the metastatic scenario; 34 patients (12%) were subsequently determined on chart review to have received a scenario type incongruous to their disease stage (30 in the adjuvant group; four in the metastatic group) and were excluded from analyses. Baseline demographics of the final study population (n = 244) are presented in Table 1. The distribution of adjuvant and metastatic patients was in keeping with the underlying patient population of the Princess Margaret Cancer Centre. Metastatic patients were older (P = 0.04) and more likely to be male (P = 0.003) compared with their adjuvant counterparts. Metastatic patients were more likely to be retired (P = 0.02), to have received previous chemotherapy (P = 0.01), and/or targeted therapy (P < 0.001), to have participated in a treatment clinical trial (P < 0.001), and had a lower annual household income (P = 0.04) and lower median personal health rating (6; range 0–10) compared with adjuvant patients (7; range 3–10; P < 0.001).
Table 1
Patient demographics Adjuvant Metastatic (N = 123) [N (%)] (N = 121) [N (%)]
Sex Male Female Age Median Range Ethnicity White Non-White Marital status Married Other Education Secondary or less Postsecondary Employment Professional and white collar Retired All other Household income (CAD$) < 50 000 50 000–100 000 > 100 000 Unknown Cancer type Lung and head and neck Gastrointestinal and hepatobiliary Breast Other Previous chemotherapy No Yes Previous targeted therapy No Yes Clinical trial experience No Yes Previous genetic testing No Yes Personal health rating (0–10)a Median Range
P-value
56 (46) 67 (54)
78 (64) 43 (36)
0.003
58 21–90
62 27–82
0.04
99 (80) 24 (20)
100 (83) 21 (17)
0.66
90 (73) 33 (27)
83 (69) 38 (31)
0.43
46 (37) 77 (63)
44 (36) 77 (64)
0.87
42 (34)
28 (23)
41 (33) 40 (33)
62 (51) 31 (26)
31 34 49 9
47 35 29 10
(25) (28) (40) (7)
(39) (29) (24) (8)
0.02
0.04
29 (24) 47 (38)
42 (35) 39 (32)
24 (20) 23 (18)
8 (7) 32 (26)
22 (18) 101 (82)
9 (7) 112 (93)
0.01
102 (83) 21 (17)
55 (45) 66 (55)
< 0.001
100 (81) 23 (19)
75 (62) 46 (38)
< 0.001
119 (97) 4 (3)
110 (91) 11 (9)
0.06
7 3–10
6 0–10
< 0.001
0.006
a Linear Likert scale, where 0 signifies worst possible health and 10 signifies best possible health.
Acceptance of chemotherapy and pharmacogenomic testing
accept pharmacogenomic testing that could improve the prediction of response to chemotherapy when the test was free, had a 1-day turnaround time for results, and the prevalence of the genetic variation associated with lack of response to chemotherapy was 50%.
Eighty-nine percent of the study participants answered each of the main outcome questions in the survey; thus, 82% of all patients approached were included in the final analyses. Among the adjuvant group, 72% were willing to accept chemotherapy for a 5% absolute improvement in cure rate and risk of severe side effects of less than 5%. A further 24% of patients would accept chemotherapy for a higher cure rate (median 15%; range 10–50%); thus, only 4% refused chemotherapy at any level of benefit. Of the patients accepting chemotherapy, 99% were willing to
Among the metastatic group, 92% were willing to accept chemotherapy for an 80% benefit (shrinkage or stable disease) and risk of severe side effects of less than 5%. A further 2.5% would accept chemotherapy for a higher response rate (median 95%; range 85–100%), whereas 2.5% would accept chemotherapy for a lower risk of side effects (median 0%; range 0–1%). Of the 97% of patients accepting chemotherapy, 97.4% were willing to accept pharmacogenomic testing that could stratify risk of
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Cancer patients and pharmacogenomic testing Cuffe et al. 351
toxicity when the test was free, had a 1-day turnaround time for results, and the prevalence of the genetic variation associated with severe side effects was 5%.
diagnosis (P = 0.01) and those agreeable to an additional blood test (P = 0.006) were more accepting (Supplementary Table 1, Supplemental digital content 2, http://links.lww.com/FPC/A733).
Willingness-to-pay
The median out-of-pocket cost at which patients would no longer opt to undergo pharmacogenomic testing (acceptable price) and the median cost that patients considered reasonable for testing are presented in Table 2. Patients’ perceptions of acceptable and reasonable prices were significantly correlated (r = 0.44, P < 0.0001). Willingness-to-pay was higher among patients who better understood genetic testing (P = 0.01), and those with annual household income > CAD$50 000 (P < 0.001), and declined among patients who did not understand the scenario completely (P = 0.01; Table 3).
The majority of patients wanted decision-making on pharmacogenomic testing to be shared between the patient and the physician (Table 5). Patients who admitted to worrying about how to finance pharmacogenomic testing were more likely to favor a shared decisionmaking process versus a physician-only process (P = 0.02). In contrast, patients who indicated that they would be distressed by the need for an additional blood draw preferred to make their own decisions (P = 0.03). Patient understanding
Other preferences
The median acceptable wait time for pharmacogenomic test results was 16 days (range 0–90 days) for the adjuvant group and 14 days (range 1–90 days) for the metastatic group. Patients’ preferences for pharmacogenomic testing were not significantly influenced by the prevalence of the genetic variation of interest (likelihood of test results influencing a treatment change). The median lowest prevalence of the genetic variation at which patients would no longer opt for pharmacogenomic testing was just 5% (range 0–80%) and 1.5% (range 0–10%) for the adjuvant and metastatic groups, respectively. Among adjuvant patients, 37% would accept testing even when the prevalence of the genetic variation of interest varied from 5 to 95%. Patient attitudes toward pharmacogenomic testing
Over 85% of patients agreed that reducing the chance of receiving ineffective treatment was a high priority (Table 4). Interestingly, 77% believed that any additional test offered by the medical profession must be of benefit. Fewer than 15% would accept pharmacogenomic testing only if they could be reassured that it would not detect the inheritability of their cancer, whereas one-third of patients worried about finding money to pay for testing. Ninety-two percent of patients were agreeable to an additional blood draw to facilitate testing, whereas just over half (55%) were agreeable to biopsy. Women (P < 0.001) and chemotherapy-naïve patients (P = 0.002) were significantly less likely to agree to an additional biopsy, whereas patients with more than one cancer Table 2
Decision-making
Using a five-point Likert scale, more than 75% of patients rated the clinical scenario trade-off testing as easy or very easy to understand, with just 9.5% rating it as difficult/very difficult. Patient and interviewer assessments of patient understanding were highly correlated (P < 0.0001). One-fifth of patients indicated that they did not fully understand genetic testing and were worried about its implications. Understanding was lower among patients who were concerned about the potential of pharmacogenomic testing to predict for inheritability of cancer (P = 0.001), whereas patients who were willing to undergo an additional biopsy better understood testing (P = 0.05; Table 6). Level of understanding had no impact on strength of desire for pharmacogenomic testing.
Discussion Despite several professional organizations in oncology now endorsing pharmacogenomic testing [7,8,26], the translation of pharmacogenomic testing into clinical practice has been relatively slow. Increasingly, it is being recognized that successful implementation of pharmacogenomic testing into clinical practice is reliant on patients’ acceptance of and willingness-to-pay for testing [3,23]. We report that adjuvant and metastatic cancer patients in a North American academic center are overwhelmingly willing to accept, pay for, and wait for pharmacogenomic testing when such testing had been deemed clinically useful by their healthcare provider.
Willingness-to-pay for pharmacogenomic testing and acceptable wait time for results Adjuvant
Willingness-to-pay/acceptable price for test (CAD$) Patients’ perception of reasonable price for test (CAD$) Acceptable waiting time for test results (days)
Metastatic
Median
Range
Median
Range
P-value
2000 200 16
0–25 000 0–25 000 0–90
1000 100 14
0–10 000 0–5000 1–90
0.23 0.18 0.27
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352 Pharmacogenetics and Genomics 2014, Vol 24 No 7
Table 3
Significant factors associated with patients’ willingness-to-pay for pharmacogenomic testing
Patient group Adjuvant
Metastatic
Combined
Number of patientsa
Predictors
Mean acceptable cost
SEM
P-value
1953 3588 4821
527 877 746
< 0.001
3632 1696
439 519
0.02
3588 1052
421 389
0.01
1493 3173 4904
370 654 789
2290 3336
763 421
1682 3384 4854
306 542 546
3688 2173
308 623
0.01
1465 3587
500 299
0.06
3781 2309
342 431
0.06
2336 3764
495 347
0.01
Household income per year (CAD$) < 50 000 31 50 000–100 000 33 > 100 0000 45 Marital status Married 81 Others 36 ‘Don’t understand genetic testing and would worry about implications’ 1–3 (strongly disagree–neutral) 91 4–5 (somewhat–strongly agree) 26 Household income per year (CAD$) < 50 000 44 50 000–100 000 35 > 100 000 28 Understood scenario – patient assessment 1–3 (strongly disagree–neutral) 20 4–5 (somewhat–strongly agree) 87 Household income per year (CAD$) < 50 000 75 50 000–100 000 68 > 100 000 73 ‘Don’t understand genetic testing and would worry about implications’ 1–3 (strongly disagree–neutral) 183 4–5 (somewhat–strongly agree) 50 ‘Measures to prolong life are of utmost importance to me’ 1–3 (strongly disagree–neutral) 23 4–5 (somewhat–strongly agree) 211 Marital status Married 168 Others 66 Understood scenario – patient assessment 1–3 (strongly disagree–neutral) 45 167 4–5 (somewhat–strongly agree)
0.001
0.05
< 0.001
a
Includes only those patients accepting chemotherapy; totals may vary because of missing data.
Table 4
Cancer patients’ agreement with statements designed to elicit patients’ values on chemotherapy and pharmacogenomic testing
Patient values Would be distressed by having to undergo an additional blood draw If test caused a change in treatment, would worry about receiving inferior treatment Delay in starting treatment would cause additional anxiety If the test was available but not offered, it would cause additional anxiety Worry about finding money to pay for test Believe any additional tests offered by the medical profession must be of benefit Measures to prolong life are of utmost importance to me Quality of life is of utmost importance Do not understand genetic testing and would worry about implications If test did not cause a change in treatment, would be reassured that getting correct treatment Reducing chance of getting ineffective treatment is important Prefer if testing was performed on existing tumor sample rather than extra blood draw Agreeable to additional blood draw to facilitate testing Agreeable to additional biopsy to facilitate testing Agreeable to have testing provided that it did not look at inheritability of cancer
Adjuvant % of patients
Metastatic % of patients
Combined % of patients
11 16 52 0 26 79 87 93 20 74
5 16 45 42 39 75 91 91 22 72
9 16 48 42 32 77 89 92 22 73
89 20 88 54 11
85 25 95 56 16
87 23 92 55 14
No significant difference was found between the adjuvant and the metastatic groups.
Patients’ opinion on who should decide on the need for pharmacogenomic testing
Table 5
Adjuvant [N (%)] Physician Patient Both physician and patient Unsure
22 6 90 5
(18) (5) (73) (4)
Metastatic [N (%)] 12 11 94 4
(10) (9) (78) (3)
P-value 0.20
P-value represents any differences in opinion between the adjuvant and the metastatic groups on who should decide on the need for pharmacogenomic testing.
The strength of patients’ desire for pharmacogenomic testing was evidenced by the considerable out-of-pocket costs that patients were willing-to-pay, especially as our patients derive from a universal healthcare system, and are familiar with healthcare that is mostly reimbursed at point of use. Importantly, several studies have shown that willingness-to-pay may be a surrogate measure not only of patients’ perception of the worth or benefit of a test but also of their willingness to adopt novel technologies [27,28].
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Cancer patients and pharmacogenomic testing Cuffe et al. 353
Table 6
Significant factors associated with patients’ understanding of pharmacogenomic testing
Patient group Adjuvant
Metastatic
Combined
Predictors
Number of patientsa
Patients who understand (%)
‘Agreeable to have testing provided that it did not look at inheritability of cancer’ 4–5 (somewhat–strongly agree) 13 1–3 (strongly disagree–neutral) 104 ‘Agreeable to additional biopsy to facilitate testing’ 4–5 (somewhat–strongly agree) 66 1–3 (strongly disagree–neutral) 51 Ethnicity Non-Caucasian 42 Caucasian 192 ‘If test didn’t cause a change in treatment, would be reassured that getting correct 1–3 (strongly disagree–neutral) 63 4–5 (somewhat–strongly agree) 167 ‘Agreeable to additional biopsy to facilitate testing’ 4–5 (somewhat–strongly agree) 129 1–3 (strongly disagree–neutral) 105 ‘Agreeable to have testing provided that it did not look at inheritability of cancer’ 4–5 (somewhat–strongly agree) 32 1–3 (strongly disagree–neutral) 202
Odds ratio (95% CI)b
P-value
54 82
4.10 (1.23–13.6)
0.02
88 65
0.25 (0.10–0.65)
0.004
67 81 treatment’ 87 75
2.09 (0.95–4.62)
0.07
0.46 (0.20–1.04)
0.06
84 71
0.51 (0.26–1.01)
0.05
53 82
3.94 (1.74–8.92)
0.001
CI, confidence interval. Totals may vary due to missing data. b Odds ratio >1 signifies that patients are less likely to understand pharmacogenomic testing when compared to the reference group. a
The median willingness-to-pay for pharmacogenomic testing (CAD$1000–2000) was higher than that reported in a discrete–choice experiment study in depression in which the median willingness-to-pay for avoidance of one change in antidepressant medication was 1571 Danish Krone (CAD$264) [29]. Although a possible reason for this discrepancy may relate to patients’ perception of a cancer diagnosis as being more severe than that of other chronic conditions [22], other reasons include socio-cultural and economic factors and perception of the role of public versus private healthcare. However, one-third of the study participants worried about finding money to fund testing, raising concerns as to whether patients would actually pay such large amounts in clinical practice. Indeed, the median cost that patients considered reasonable for testing was, on average, one-tenth of the willing-to-pay amounts, significantly lower than the current market value of many pharmacogenomic tests. Reimbursement policies will, therefore, be of importance in integrating pharmacogenomic testing into clinical practice [30], and are most influenced by strength of clinical evidence, endorsement by professional guidelines, and cost-effective analyses [31]. However, although there is mounting evidence for the clinical benefit of many pharmacogenomic tests, considerably fewer cost-effective analyses have been carried out [32], highlighting the importance of integrating such analyses into future pharmacogenomic studies. Cancer patients’ enthusiasm for pharmacogenomic testing was further evidenced by their willingness to accept considerable delays in initiating treatment to avail of testing. The median acceptable wait time for results of 14–16 days exceeded the 2–7-day preferred turnaround time reported in a previous study involving noncancer patients receiving azathioprine [33]. This is important
given that one in five physicians admit to ‘assuming patient priorities and preferences for pace of treatment’ and would consider omitting what they regard as clinically relevant pharmacogenomic tests to avoid treatment delays [34]. In contrast, our findings support the converse view of patient advocates who report that patients do not necessarily prefer the speediest time to treatment, but instead welcome the opportunity to discuss all treatment options [34]. Finally, although one-quarter of Canadian physicians cite lack of patient demand for pharmacogenomic testing as a potential barrier to its use in clinical practice [35], our findings provide empiric data to the contrary. Although we have shown that cancer patients are overwhelmingly willing to accept, pay for, and wait for pharmacogenomic testing, we also identified significant deficiencies in patients’ understanding of pharmacogenomics. Despite our highly educated and potentially select study population, of whom two-thirds had higher education, more than one in five patients did not fully understand genetic testing and worried about its implications. The degree of misunderstanding may even be higher, given that 14% of patients equated pharmacogenomic testing to fears of its potential to predict for inheritability of cancer, whereas patients’ acceptance of testing was relatively insensitive to the prevalence of the genetic variation affecting treatment efficacy/toxicity. In addition, despite strongly wanting pharmacogenomic testing, only half were willing to undergo an additional biopsy to facilitate testing, implying possible lack of conviction behind their stated beliefs. Moreover, there appeared to be blind acceptance that any test offered by the medical profession must be of benefit. These findings all point to the urgent need for improved patient education.
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354 Pharmacogenetics and Genomics 2014, Vol 24 No 7
The strengths of our study include its high response rate and the inclusion of patients with a diverse range of cancer diagnoses. Nonetheless, our study has limitations. To simplify matters, this study involved two different hypothetical scenarios depending on patients’ selfreported cancer stage. In the adjuvant group, we focused on the impact of pharmacogenetic testing on the efficacy, but not toxicity, of chemotherapy, whereas in the metastatic group, we focused only on its influence on the toxicity of chemotherapy. Although ideally it would have been useful to examine the influence of pharmacogenomic testing on both the efficacy and the toxicity of chemotherapy in each population group, this would have made the hypothetical scenarios and subsequent analyses overcomplicated. Indeed, hypothetical scenarios can never fully show the actual complexity of decisionmaking in the real world [36,37]. Thus, it is likely that the interest reported in this study may be an overestimate of actual uptake rates and willingness-to-pay if translated into clinical practice [36,37]. This is especially true when we consider the level of uncertainty in understanding of pharmacogenomic testing in one-fifth of our population. Our goal was to evaluate patient attitudes, preferences, and understanding; thus, we did not address broader pharmacogenomic issues such as clinical utility, physician resistance, and insurance reimbursement issues as this would have made the scenarios overly complicated. Nonetheless, we are cognizant of the fact that the ‘level of evidence’ for genetic testing may particularly impact on patients’ willingness to adopt pharmacogenomic testing in clinical practice; thus, we recommend that future studies address this. We also did not address patient perceptions of whether pharmacogenomic tests were considered part of their standard care as the scenarios assumed that the tests were validated, but were not reimbursed by insurance or medical providers. Our questions do not fully focus on the attribute differences between testing for germline versus somatic mutations, where familial implications are important for the former, but not for the latter; these will form the basis of one of our follow-up studies. Certainly, willingness to provide a blood draw (generally for genetic testing) was higher than a second biopsy specimen. Finally, our patient population was derived from a single tertiary cancer center within a universal healthcare system, and was therefore potentially select, which may impact on the generalizability of our results. Conclusion
Despite significant advances in pharmacogenomics in recent years, the diffusion of pharmacogenomic testing into patient care has been variable [38–41]. Although the reasons underlying this are multifactorial and include a relative lack of large-scale prospective trials validating the impact of genomic variability on drug response, several authors have expressed concern that the cost of testing
may be prohibitive and/or that patients may be resistant to adopting this technology [42,43]. In this study, we found the opposite. While acknowledging the limitations of our study, we have shown that among cancer patients accepting chemotherapy, the vast majority were accepting of pharmacogenomic testing and were willing to accept considerable out-of-pocket costs and delays in treatment to avail of testing. However, in line with previous studies, we observed a self-perceived lack of clarity of understanding of pharmacogenomics in a substantial minority of our cancer patients that could potentially impact on the actual utilization of pharmacogenomic testing in clinical practice. Although the majority of cancer patients want to participate in decision-making on pharmacogenomic testing, a considerable proportion lacked the necessary knowledge to make fully informed choices. Significant efforts to improve patient education are therefore warranted.
Acknowledgements This work was supported by the Princess Margaret Hospital Foundation and the Posluns Family Foundation. Amalia M. Issa’s work is partially funded by In Health, the Institute for Health Technology Studies. Previous presentations: (a) Poster presentation ‘Cancer Patients’ and Physicians’ Preferences for DecisionMaking Regarding Pharmacogenomic Testing (PGT)’, American Society of Clinical Oncology Quality Care Symposium, San Diego, 2012 (Conquer Cancer Foundation of ASCO Merit Award recipient). (b) Oral presentation ‘Cancer Patient Acceptance, Understanding, and Willingness to Pay for Pharmacogenetic Testing (PGT)’, American Society of Clinical Oncology Annual Meeting, Chicago, 2012. (c) Poster presentation ‘Patient Attitudes toward Receiving Chemotherapy and Pharmacogenetic Testing in Curative and Palliative Cancer Patients’, 27th International Conference on Pharmacoepidemiology & Therapeutic Risk Management, Chicago, 2011. Conflicts of interest
Geoffrey Liu holds the Alan B. Brown Chair in Molecular Genomics and the Cancer Care Ontario Chair in Experimental Therapeutics and Population Studies and is a member of the Canadian Pharmacogenetic Network for Drug Safety. For the remaining authors there are no conflicts of interest.
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