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Panattoni L, Kearney M, Land N, Flottemesch T, Sullivan P, Kirker M, Bharmal M, Hauber B. Understanding Clinician Preferences for Treatment Attributes in Oncology: A Discrete Choice Experiment of Oncologists' and Urologists' Preferences for First-Line Treatment of Locally Advanced/Unresectable Metastatic Urothelial Carcinoma in Five European Countries. PHARMACOECONOMICS 2024; 42:895-909. [PMID: 38472738 DOI: 10.1007/s40273-024-01359-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/21/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION Prior discrete choice experiments (DCE) in oncology found that, on average, clinicians rank survival as the most important treatment attribute. We investigate heterogeneity in clinician preferences within the context of first-line treatment for advanced urothelial carcinoma in Spain, France, Italy, Germany, and the UK. METHODS The online DCE included 12 treatment choice tasks, each comparing two hypothetical therapy profiles defined by treatment attributes: grade 3/4 treatment-related adverse events (TRAEs), induction and maintenance administration schedules, progression-free survival, and overall survival (OS). We used a random parameters logit model to estimate attribute relative importance (RI) (0-100%) and generate preference shares for four treatment profiles. Results were stratified by country. Preference heterogeneity was evaluated by latent class analysis. RESULTS In August and September 2022, 498 clinicians (343 oncologists and 155 urologists) completed the DCE. OS had the strongest influence on clinicians' preferences [RI = 62%; range, 51.6% (Germany) to 63.7% (Spain)] followed by frequency of grade 3/4 TRAEs (RI = 27%). Among treatment profiles, the chemotherapy plus immune checkpoint inhibitor maintenance therapy profile had the largest preference share [51%; range, 38% (Italy) to 56% (UK)]. Four latent classes of clinicians were identified (N = 469), with different treatment profile preferences: survival class (30.1%), trade-off class (22.4%), no strong preference class (40.9%), and aggressive treatment class (6.6%). OS was not the most important attribute for 30.0% of clinicians. CONCLUSION While average sample results were consistent with those of prior DCEs, this study found heterogeneity in clinician preferences within and across countries, highlighting the diversity in clinician decision making in oncology.
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Affiliation(s)
| | | | | | | | | | | | - Murtuza Bharmal
- EMD Serono, Research & Development Institute, Inc., Billerica, MA, USA
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Bullen A, Ryan M, Ennis H, Gray E, Loría-Rebolledo LE, McIntyre M, Hall P. Trade-offs between overall survival and side effects in the treatment of metastatic breast cancer: eliciting preferences of patients with primary and metastatic breast cancer using a discrete choice experiment. BMJ Open 2024; 14:e076798. [PMID: 38684245 PMCID: PMC11057309 DOI: 10.1136/bmjopen-2023-076798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 03/01/2024] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES There has been a recent proliferation in treatment options for patients with metastatic breast cancer. Such treatments often involve trade-offs between overall survival and side effects. Our study aims to estimate the trade-offs that could be used to inform decision-making at the individual and policy level. DESIGN We designed a discrete choice experiment (DCE) to look at preferences for avoiding severity levels of side effects when choosing treatment for metastatic breast cancer. Treatment attributes were: fatigue, nausea, diarrhoea, other side effects (peripheral neuropathy, hand-foot syndrome and mucositis) and urgent hospital admission and overall survival. Responses were analysed using an error component logit model. We estimated the relative importance of attributes and minimum acceptable survival for improvements in side effects. SETTING The DCE was completed online by UK residents with self-reported diagnoses of breast cancer. PARTICIPANTS 105 respondents participated, of which 72 patients had metastatic breast cancer and 33 patients had primary breast cancer. RESULTS Overall survival had the largest relative importance, followed by other side effects, diarrhoea, nausea and fatigue. The risk of urgent hospital admission was not significant. While overall survival was the most important attribute, respondents were willing to forgo some absolute probability of overall survival for reductions in all Grade 2 side effects (12.02% for hand-foot syndrome, 11.01% for mucositis, 10.42% for peripheral neuropathy, 6.33% for diarrhoea and 3.62% for nausea). Grade 1 side effects were not significant, suggesting respondents have a general tolerance for them. CONCLUSIONS Patients are willing to forgo overall survival to avoid particular severity levels of side effects. Our results have implications for data collected in research studies and can help inform person-centred care and shared decision-making.
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Affiliation(s)
- Alistair Bullen
- Edinburgh Clinical Trials Unit, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - Mandy Ryan
- Health Economics Research Unit, University of Aberdeen, Aberdeen, UK
| | | | - Ewan Gray
- The University of Edinburgh, Edinburgh, UK
| | | | | | - Peter Hall
- The University of Edinburgh, Edinburgh, UK
- Western General Hospital, Edinburgh, UK
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Zhang M, He X, Wu J, Xie F. Differences between physician and patient preferences for cancer treatments: a systematic review. BMC Cancer 2023; 23:1126. [PMID: 37980466 PMCID: PMC10657542 DOI: 10.1186/s12885-023-11598-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/01/2023] [Indexed: 11/20/2023] Open
Abstract
BACKGROUND Shared decision-making is useful to facilitate cancer treatment decisions. However, it is difficult to make treatment decisions when physician and patient preferences are different. This review aimed to summarize and compare the preferences for cancer treatments between physicians and patients. METHODS A systematic literature search was conducted on PubMed, Embase, PsycINFO, CINAHL and Scopus. Studies elicited and compared preferences for cancer treatments between physicians and patients were included. Information about the study design and preference measuring attributes or questions were extracted. The available relative rank of every attribute in discrete choice experiment (DCE) studies and answers to preference measuring questions in non-DCE studies were summarized followed by a narrative synthesis to reflect the preference differences. RESULTS Of 12,959 studies identified, 8290 were included in the title and abstract screening and 48 were included in the full text screening. Included 37 studies measured the preferences from six treatment-related aspects: health benefit, adverse effects, treatment process, cost, impact on quality of life, and provider qualification. The trade-off between health benefit and adverse effects was the main focus of the included studies. DCE studies showed patients gave a higher rank on health benefit and treatment process, while physicians gave a higher rank on adverse effects. Non-DCE studies suggested that patients were willing to take a higher risk of adverse effects or lower health benefit than physicians when accepting a treatment. CONCLUSIONS Physicians and patients had important preference differences for cancer treatment. More sufficient communication is needed in cancer treatment decision-making.
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Affiliation(s)
- Mengqian Zhang
- School of Pharmaceutical Science and Technology, Tianjin University, No 92 Weijin Road, Nankai District, Tianjin, CO, 300072, China
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China
| | - Xiaoning He
- School of Pharmaceutical Science and Technology, Tianjin University, No 92 Weijin Road, Nankai District, Tianjin, CO, 300072, China.
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China.
| | - Jing Wu
- School of Pharmaceutical Science and Technology, Tianjin University, No 92 Weijin Road, Nankai District, Tianjin, CO, 300072, China.
- Center for Social Science Survey and Data, Tianjin University, Tianjin, China.
| | - Feng Xie
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
- Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, ON, Canada
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Feng Z, Meng J, Sun Y, Xie T, Lu W, Wang G, Geng J. Assessment of patients' preferences for new anticancer drugs in China: a best-worst discrete choice experiment on three common cancer types. BMJ Open 2023; 13:e072469. [PMID: 37270199 DOI: 10.1136/bmjopen-2023-072469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/05/2023] Open
Abstract
OBJECTIVES Despite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM. DESIGN We identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best-worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity. SETTING The BWDCE was conducted in Jiangsu province and Hebei province in China. PARTICIPANTS Patients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited. RESULTS Data from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p<0.001). The low incidence of severe to life-threatening side effects, prolonged progression-free survival and the low incidence of mild to moderate side effects were also positive predictors of patients' preferences (p<0.001). Out-of-pocket cost was a negative predictor of their preferences (p<0.001). According to subgroup analysis by type of cancer, the improvement in HRQoL remained the most valuable attribute. However, the relative importance of other attributes varied by type of cancer. Whether patients were newly diagnosed or previously diagnosed cancer cases played a dominant role in the preference heterogeneity within each subgroup. CONCLUSIONS Our study can assist in the implementation of SDM by providing evidence on patients' preferences for new anticancer drugs. Patients should be informed of the multiattribute values of new drugs and encouraged to make decisions reflecting their values.
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Affiliation(s)
- Zhe Feng
- Department of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China
| | - Jingyi Meng
- Department of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China
| | - Yanjun Sun
- Department of Radiotherapy, Tinghu District People's Hospital, Yancheng, Jiangsu, China
| | - Tongling Xie
- Department of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China
- Department of Medical Informatics, The People's Hospital of Rugao, Nantong, Jiangsu, China
| | - Wenzhang Lu
- Department of Respiratory, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China
| | - Guohua Wang
- Institute of Special Environmental Medicine, Nantong University, Nantong, Jiangsu, China
| | - Jinsong Geng
- Department of Medical Informatics, Nantong University Medical School, Nantong, Jiangsu, China
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Collacott H, Soekhai V, Thomas C, Brooks A, Brookes E, Lo R, Mulnick S, Heidenreich S. A Systematic Review of Discrete Choice Experiments in Oncology Treatments. THE PATIENT 2021; 14:775-790. [PMID: 33950476 DOI: 10.1007/s40271-021-00520-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/17/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND As the number and type of cancer treatments available rises and patients live with the consequences of their disease and treatments for longer, understanding preferences for cancer care can help inform decisions about optimal treatment development, access, and care provision. Discrete choice experiments (DCEs) are commonly used as a tool to elicit stakeholder preferences; however, their implementation in oncology may be challenging if burdensome trade-offs (e.g. length of life versus quality of life) are involved and/or target populations are small. OBJECTIVES The aim of this review was to characterise DCEs relating to cancer treatments that were conducted between 1990 and March 2020. DATA SOURCES EMBASE, MEDLINE, and the Cochrane Database of Systematic Reviews were searched for relevant studies. STUDY ELIGIBILITY CRITERIA Studies were included if they implemented a DCE and reported outcomes of interest (i.e. quantitative outputs on participants' preferences for cancer treatments), but were excluded if they were not focused on pharmacological, radiological or surgical treatments (e.g. cancer screening or counselling services), were non-English, or were a secondary analysis of an included study. ANALYSIS METHODS Analysis followed a narrative synthesis, and quantitative data were summarised using descriptive statistics, including rankings of attribute importance. RESULT Seventy-nine studies were included in the review. The number of published DCEs relating to oncology grew over the review period. Studies were conducted in a range of indications (n = 19), most commonly breast (n =10, 13%) and prostate (n = 9, 11%) cancer, and most studies elicited preferences of patients (n = 59, 75%). Across reviewed studies, survival attributes were commonly ranked as most important, with overall survival (OS) and progression-free survival (PFS) ranked most important in 58% and 28% of models, respectively. Preferences varied between stakeholder groups, with patients and clinicians placing greater importance on survival outcomes, and general population samples valuing health-related quality of life (HRQoL). Despite the emphasis of guidelines on the importance of using qualitative research to inform attribute selection and DCE designs, reporting on instrument development was mixed. LIMITATIONS No formal assessment of bias was conducted, with the scope of the paper instead providing a descriptive characterisation. The review only included DCEs relating to cancer treatments, and no insight is provided into other health technologies such as cancer screening. Only DCEs were included. CONCLUSIONS AND IMPLICATIONS Although there was variation in attribute importance between responder types, survival attributes were consistently ranked as important by both patients and clinicians. Observed challenges included the risk of attribute dominance for survival outcomes, limited sample sizes in some indications, and a lack of reporting about instrument development processes. PROTOCOL REGISTRATION PROSPERO 2020 CRD42020184232.
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Affiliation(s)
- Hannah Collacott
- Evidera, The Ark, 2nd Floor, 201 Talgarth Road, London, W6 8BJ, UK.
| | - Vikas Soekhai
- Erasmus University, Rotterdam, The Netherlands
- Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Caitlin Thomas
- Evidera, The Ark, 2nd Floor, 201 Talgarth Road, London, W6 8BJ, UK
| | - Anne Brooks
- Evidera, 7101 Wisconsin Avenue, Suite 1400, Bethesda, MD, 20814, USA
| | - Ella Brookes
- Evidera, The Ark, 2nd Floor, 201 Talgarth Road, London, W6 8BJ, UK
| | - Rachel Lo
- Evidera, The Ark, 2nd Floor, 201 Talgarth Road, London, W6 8BJ, UK
| | - Sarah Mulnick
- Evidera, 7101 Wisconsin Avenue, Suite 1400, Bethesda, MD, 20814, USA
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Pearce A, Harrison M, Watson V, Street DJ, Howard K, Bansback N, Bryan S. Respondent Understanding in Discrete Choice Experiments: A Scoping Review. THE PATIENT 2021; 14:17-53. [PMID: 33141359 PMCID: PMC7794102 DOI: 10.1007/s40271-020-00467-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 09/30/2020] [Indexed: 11/27/2022]
Abstract
INTRODUCTION Despite the recognised importance of participant understanding for valid and reliable discrete choice experiment (DCE) results, there has been limited assessment of whether, and how, people understand DCEs, and how 'understanding' is conceptualised in DCEs applied to a health context. OBJECTIVES Our aim was to identify how participant understanding is conceptualised in the DCE literature in a health context. Our research questions addressed how participant understanding is defined, measured, and used. METHODS Searches were conducted (June 2019) in the MEDLINE, EMBASE, PsychINFO and Econlit databases, as well as hand searching. Search terms were based on previous DCE systematic reviews, with additional understanding keywords used in a proximity-based search strategy. Eligible studies were peer-reviewed journal articles in the field of health, related to DCE or best-worst scaling type 3 (BWS3) studies, and reporting some consideration or assessment of participant understanding. A descriptive analytical approach was used to chart relevant data from each study, including publication year, country, clinical area, subject group, sample size, study design, numbers of attributes, levels and choice sets, definition of understanding, how understanding was tested, results of the understanding tests, and how the information about understanding was used. Each study was categorised based on how understanding was conceptualised and used within the study. RESULTS Of 306 potentially eligible articles identified, 31 were excluded based on titles and abstracts, and 200 were excluded on full-text review, resulting in 75 included studies. Three categories of study were identified: applied DCEs (n = 52), pretesting studies (n = 7) and studies of understanding (n = 16). Typically, understanding was defined in relation to either the choice context, such as attribute terminology, or the concept of choosing. Very few studies considered respondents' engagement as a component of understanding. Understanding was measured primarily through qualitative pretesting, rationality or validity tests included in the survey, and participant self-report, however reporting and use of the results of these methods was inconsistent. CONCLUSIONS Those conducting or using health DCEs should carefully select, justify, and report the measurement and potential impact of participant understanding in their specific choice context. There remains scope for research into the different components of participant understanding, particularly related to engagement, the impact of participant understanding on DCE validity and reliability, the best measures of understanding, and methods to maximise participant understanding.
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Affiliation(s)
- Alison Pearce
- Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia.
| | - Mark Harrison
- Centre for Health Evaluation and Outcome Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Verity Watson
- Health Economics Research Unit, University of Aberdeen, Aberdeen, Scotland
| | - Deborah J Street
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW, Australia
| | - Kirsten Howard
- Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
| | - Nick Bansback
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Stirling Bryan
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
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