Treatment decision-making in chronic lymphocytic leukaemia: Key factors for healthcare professionals. PRELIC study

Boqué, Concepción; Abad, M.R.; Agustín, María José; García-Goñi, Manuel; Moreno, Carolina; Gabás‐Rivera, Clara; Granados, Enrique; Castro-Gómez, Antonio; Pardo, Carlos; Lizán, Luís

doi:10.1016/j.jgo.2019.03.010

Cited by 6 publications

(11 citation statements)

References 40 publications

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“…Most studies reported coefficients (n = 72, 91%; e.g. [37,51,60,80,98]), with 17% (n = 12) of those reporting no other output measure. Behavioural outputs included marginal rates of substitution (n = 36, 46%; e.g.…”

Section: Resultsmentioning

confidence: 99%

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A Systematic Review of Discrete Choice Experiments in Oncology Treatments

Collacott

Soekhai

Thomas

et al. 2021

Patient

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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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Section: Resultsmentioning

confidence: 99%

“…[54,63,77,90,113]) or mixed or random parameter logit (n = 29, 37%; e.g. [37,47,60,76,88]), as well as latent class logit (n = 6, 8%; e.g. [40,50,53,57,100]), hierarchical bayes (n = 7, 9%; e.g.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review of Discrete Choice Experiments in Oncology Treatments

Collacott

Soekhai

Thomas

et al. 2021

Patient

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“…Also, efficacy was characterized by a very high RI, although second to cost, in a DCE experiment evaluating hematologists’ and pharmacists’ preferences for treatment selection for CLL, showing a consistent evaluation of this attribute from a clinical and service organization perspective. 10 The relative weight of the risk of serious infections was identical in the 2 groups of our DCE. Le et al 11 also found that the risk of infections was important, yet not more than that of atrial fibrillation or treatment discontinuation due to adverse events.…”

Section: Discussionmentioning

confidence: 73%

“…In addition, the conjoint analysis may help to compare preferences of the different actors involved in CLL management, finding commonalities and inconsistencies, which may be valued in organizational perspectives. 10 , 11 , 14 …”

Section: Discussionmentioning

confidence: 99%

What Are the Attributes Prioritized in the Choice of Therapy in Chronic Lymphocytic Leukemia? A Patient-physician Cross-matching Analysis of a Discrete Choice Experiment

et al. 2022

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Several treatment options are available for chronic lymphocytic leukemia (CLL) and, for this reason, treatment choice can result challenging after introducing oral targeted agents. This study aims at comparing patients’ and hematologists’ preferences for attributes of CLL treatments. An online cross-sectional survey has been delivered to clinicians and patients affected by CLL in Italy. A discrete choice experiment has been conducted so to estimate each attribute’s relative importance (RI) and assess the preference weight for each level of each attribute. An expert panel agreed on investigating the following attributes: progression-free survival (PFS) and measurable residual disease, route of administration/therapy duration and follow-up frequency, incidence of diarrhea (episodes/day), serious infections (grade 3 or 4), and atrial fibrillation. Overall, 746 patients and 109 clinicians accessed the survey, and 215 and 69, respectively, filled it in. The most important attributes were PFS (RI 30%) for hematologists and the risk of severe infections (RI 24%) for patients. Clinicians rated preference for maximum efficacy and lowest risk of severe infection very high (30%). Both patients and clinicians preferred oral administration while considering duration of therapy less relevant. The frequency of hospital appointments was negligible for patients, while clinicians preferred a quarterly frequency. Considering all attributes, diarrhea was weighted more by clinicians than by patients. Atrial fibrillation was not relevant for clinicians, while it was not negligible for patients. In conclusion, clinicians and patients favor an oral therapy, including continuous treatment, if associated with prolonged PFS, albeit with particular attention to the risk of serious infections.

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“…In addition, given the high costs of these new treatments, physicians need to assess which drugs or combinations provide the best value for patients and the healthcare system and are thus worth pursuing (1). In publicly-funded National Healthcare Systems, prescribing physicians can be considered as serving a dual role, acting as patients' advocates but also as society's gatekeepers of the use of resources (58). We found that, despite cost (for the healthcare system) being the attribute with lower RI, it has an influence on oncologists' (although not for patients) preferences.…”

Section: Discussionmentioning

confidence: 84%

Preferences for Renal Cell Carcinoma Pharmacological Treatment: A Discrete Choice Experiment in Patients and Oncologists

et al. 2022

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IntroductionThe purpose of this investigation was to explore patients’ and oncologists’ preferences for the characteristics of a pharmacological regimen for patients with advanced renal cell carcinoma (aRCC).Material and MethodsCross-sectional observational study based on a discrete choice experiment (DCE) conducted in Spain. A literature review, a focus group with oncologists and interviews with patients informed the DCE design. Five attributes were included: progression survival gain, risk of serious adverse events (SAEs), health-related quality of life (HRQoL), administration mode, and treatment cost. Preferences were analyzed using a mixed-logit model to estimate relative importance (RI) of attributes (importance of an attribute in relation to all others), which was compared between aRCC patients and oncologists treating aRCC. Willingness to pay (WTP, payer: health system) for a benefit in survival or in risk reduction and maximum acceptable risk (MAR) in SAEs for improving survival were estimated from the DCE. Subgroup analyses were performed to identify factors that influence preference.ResultsA total of 105 patients with aRCC (77.1% male, mean age 65.9 years [SD: 10.4], mean time since RCC diagnosis 6.3 years [SD: 6.1]) and 67 oncologists (52.2% male, mean age 41.9 years [SD: 8.4], mean duration of experience in RCC 10.2 years [SD: 7.5]) participated in the study. The most important attribute for patients and oncologists was survival gain (RI: 43.6% vs. 54.7% respectively, p<0.05), followed by HRQoL (RI: 35.5% vs. 18.0%, respectively, p<0.05). MAR for SAEs was higher among oncologists than patients, while WTP (for the health system) was higher for patients. Differences in preferences were found according to time since diagnosis and education level (patients) or length of professional experience (oncologists).ConclusionPatients’ and oncologists’ preferences for aRCC treatment are determined mainly by the efficacy (survival gain) but also by the HRQoL provided. The results of the study can help to inform decision-making in the selection of appropriate aRCC treatment.

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Treatment decision-making in chronic lymphocytic leukaemia: Key factors for healthcare professionals. PRELIC study

Cited by 6 publications

References 40 publications

A Systematic Review of Discrete Choice Experiments in Oncology Treatments

A Systematic Review of Discrete Choice Experiments in Oncology Treatments

What Are the Attributes Prioritized in the Choice of Therapy in Chronic Lymphocytic Leukemia? A Patient-physician Cross-matching Analysis of a Discrete Choice Experiment

Preferences for Renal Cell Carcinoma Pharmacological Treatment: A Discrete Choice Experiment in Patients and Oncologists

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