scholarly journals A Study of Patient Preferences for the Treatment of Non–small Cell Lung Cancer in Western China: A Discrete-Choice Experiment

2021 ◽  
Vol 9 ◽  
Author(s):  
Fei Liu ◽  
Haiyao Hu ◽  
Jing Wang ◽  
Yingyao Chen ◽  
Sun Hui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Disease Control ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Progression Free Survival ◽  
Disease Control Rate ◽  
Free Survival ◽  
Nsclc Patients

Background: Non–small cell lung cancer (NSCLC) is the most common histologic type of lung cancer, accounting for 70–85% of all lung cancers. It has brought a heavy burden of disease and financial cost to families, society, and the nation of China. Patients have differing preferences for treatment because of their varying physical conditions and socioeconomic backgrounds, which ultimately affects the choice of treatment as well as treatment outcomes. For better and sustained health outcomes, it is vital to understand patients' preferences. We can then provide medical services to match these preferences and needs rather than basing treatment on our clinical viewpoints alone.Objectives: The aim of this study was to elicit patient preferences for treatment using a discrete-choice experiment and to explore the value/importance that patients place on the different attributes of treatment in order to provide a basis for clinical decision making and patient health management.Methods: The study was conducted with NSCLC patients from three typical hospitals in southwestern China. After identifying patient-relevant treatment attributes via literature review and qualitative semi structured interviews, a discrete-choice experiment (DCE) including seven patient-relevant attributes was conducted using a fractional factorial SAS design. The empiric data analyses of patients were performed using mixed logit models.Results: NSCLC patients (N = 202) completed a survey via a face-to-face interview. Among the seven attributes, the following were considered important: progression-free survival, disease control rate, cost, weakness/fatigue, and nausea/vomiting; mode of administration and rash were considered less important. A clear preference for an increase in progression-free survival and disease control rate was demonstrated. Compared with 5 months of progression-free survival, respondents were willing to pay more (19,860 RMB) for 11 months of progression-free survival (coef.: 0.687). Compared with a 60% rate of disease control, respondents were willing to pay more (19,940 RMB) for a 90% rate of disease control (coef.: 0.690).Conclusions: This study demonstrates the value of DCEs in determining patient preferences for the treatment of NSCLC. The results indicate that not only efficacy factors (such as progression-free survival and disease control rate) were considered but also other factors (such as side effects and treatment costs) and trade-offs between attributes were held to be important. These results are in accord with expectations and can provide evidence for more effective and efficient treatment results. Furthermore, the current results can increase benefits if the presented therapies can be designed, assessed, and chosen based on patient-oriented findings.

scholarly journals Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer

2020 ◽  
pp. LMT44
Author(s):  
James Newman ◽  
Isabel Preeshagul ◽  
Nina Kohn ◽  
Craig Devoe ◽  
Nagashree Seetharamu
Keyword(s):  
Lung Cancer ◽  
Disease Control ◽  
Predictive Value ◽  
Checkpoint Inhibitor ◽  
Progression Free Survival ◽  
Disease Control Rate ◽  
Smoking History ◽  
Free Survival ◽  
Smoking Intensity ◽  
Nsclc Patients

Background: Noninvasive biomarkers predicting immune checkpoint inhibitor (ICI) response are urgently needed. We evaluated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR), smoking history, smoking intensity, BMI and programmed death ligand 1 (PD-L1) expression in non-small-cell lung cancer (NSCLC) patients treated with ICIs. Materials & methods: Single-center retrospective study included 137 patients from July 2015 to February 2018. Outcomes included 3-month disease control rate, progression-free survival, and overall survival. Predictive value of biomarkers was assessed independently and in a multivariable model. Results: NLR was associated with all outcomes. Smoking history was predictive of progression-free survival and smoking intensity was predictive of disease control rate. BMI and PD-L1 were not associated with any outcome. High BMI was associated with low NLR. Conclusion: Simple clinical biomarkers can predict response to ICIs. A score incorporating both clinical factors and established tissue/serum biomarkers may be useful in identifying NSCLC patients who would benefit from ICIs.

scholarly journals Line of therapy and patient preferences regarding lung cancer treatment: a discrete-choice experiment

2021 ◽  
Vol 37 (4) ◽  
pp. 643-653
Author(s):  
Sarah Janse ◽  
Ellen Janssen ◽  
Tanya Huwig ◽  
Upal Basu Roy ◽  
Andrea Ferris ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Treatment ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Lung Cancer Treatment ◽  
Line Of Therapy

scholarly journals Patient Preferences for Attributes of Chemotherapy for Lung Cancer: Discrete Choice Experiment Study in Japan

2021 ◽  
Vol 12 ◽  
Author(s):  
Yasuo Sugitani ◽  
Kyoko Ito ◽  
Shunsuke Ono
Keyword(s):  
Lung Cancer ◽  
Adverse Events ◽  
Cancer Patients ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Logit Model ◽  
Choice Experiment ◽  
Relative Importance ◽  
Lung Cancer Patients

Our study objective was to determine lung cancer chemotherapy attributes that are important to patients in Japan. A discrete choice experiment survey in an anonymous web-based questionnaire format with a reward was completed by 200 lung cancer patients in Japan from November 25, 2019, to November 27, 2019. The relative importance of patient preferences for each attribute was estimated using a conditional logit model. A hierarchical Bayesian logit model was also used to estimate the impact of each demographic characteristic on the relative importance of each attribute. Of the 200 respondents, 191 with consistent responses were included in the analysis. In their preference, overall survival was the most important, followed by diarrhea, nausea, rash, bone marrow suppression (BMS), progression-free survival, fatigue, interstitial lung disease, frequency of administration, and duration of administration. The preferences were influenced by demographic characteristics (e.g., gender and age) and disease background (e.g., cancer type and stage). Interestingly, the experience of cancer drug therapies and adverse events had a substantial impact on the hypothetical drug preferences. For the Japanese lung cancer patients, improved survival was the most important attribute that influenced their preference for chemotherapy, followed by adverse events, including diarrhea, nausea, rash, and BMS. The preferences varied depending on the patient’s demographic and experience. As drug attributes can affect patient preferences, pharmaceutical companies should be aware of the patient preferences and develop drugs that respond to segmented market needs.

scholarly journals Patient Preferences for Lung Cancer Treatments: A Study Protocol for a Preference Survey Using Discrete Choice Experiment and Swing Weighting

2021 ◽  
Vol 8 ◽  
Author(s):  
Dario Monzani ◽  
Serena Petrocchi ◽  
Serena Oliveri ◽  
Jorien Veldwijk ◽  
Rosanne Janssens ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Lung Cancer ◽  
Decision Making ◽  
Health Literacy ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Preference Elicitation ◽  
Nsclc Patients

Background: Advanced treatment options for non-small cell lung cancer (NSCLC) consist of immunotherapy, chemotherapy, or a combination of both. Decisions surrounding NSCLC can be considered as preference-sensitive because multiple treatments exist that vary in terms of mode of administration, treatment schedules, and benefit–risk profiles. As part of the IMI PREFER project, we developed a protocol for an online preference survey for NSCLC patients exploring differences in preferences according to patient characteristics (preference heterogeneity). Moreover, this study will evaluate and compare the use of two different preference elicitation methods, the discrete choice experiment (DCE) and the swing weighting (SW) task. Finally, the study explores how demographic (i.e., age, gender, and educational level) and clinical (i.e., cancer stage and line of treatment) information, health literacy, health locus of control, and quality of life may influence or explain patient preferences and the usefulness of a digital interactive tool in providing information on preference elicitation tasks according to patients.Methods: An online survey will be implemented with the aim to recruit 510 NSCLC patients in Belgium and Italy. Participants will be randomized 50:50 to first receive either the DCE or the SW. The survey will also collect information on participants' disease-related status, health locus of control, health literacy, quality of life, and perception of the educational tool.Discussion: This protocol outlines methodological and practical steps to quantitatively elicit and study patient preferences for NSCLC treatment alternatives. Results from this study will increase the understanding of which treatment aspects are most valued by NSCLC patients to inform decision-making in drug development, regulatory approval, and reimbursement. Methodologically, the comparison between the DCE and the SW task will be valuable to gain information on how these preference methods perform against each other in eliciting patient preferences. Overall, this protocol may assist researchers, drug developers, and decision-makers in designing quantitative patient preferences into decision-making along the medical product life cycle.

Patient preferences for specialist outpatient video consultations: A discrete choice experiment

2021 ◽  
pp. 1357633X2110228
Author(s):  
Centaine L Snoswell ◽  
Anthony C Smith ◽  
Matthew Page ◽  
Liam J Caffery
Keyword(s):  
General Practitioner ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Healthcare Delivery ◽  
General Practitioner Practice ◽  
Specialist Care ◽  
Time Away ◽  
Out Of Pocket Costs

Introduction Telehealth has been shown to improve access to care, reduce personal expenses and reduce the need for travel. Despite these benefits, patients may be less inclined to seek a telehealth service, if they consider it inferior to an in-person encounter. The aims of this study were to identify patient preferences for attributes of a healthcare service and to quantify the value of these attributes. Methods We surveyed patients who had taken an outpatient telehealth consult in the previous year using a survey that included a discrete choice experiment. We investigated patient preferences for attributes of healthcare delivery and their willingness to pay for out-of-pocket costs. Results Patients ( n = 62) preferred to have a consultation, regardless of type, than no consultation at all. Patients preferred healthcare services with lower out-of-pocket costs, higher levels of perceived benefit and less time away from usual activities ( p < 0.008). Most patients preferred specialist care over in-person general practitioner care. Their order of preference to obtain specialist care was a videoconsultation into the patient’s local general practitioner practice or hospital ( p < 0.003), a videoconsultation into the home, and finally travelling for in-person appointment. Patients were willing to pay out-of-pocket costs for attributes they valued: to be seen by a specialist over videoconference ($129) and to reduce time away from usual activities ($160). Conclusion Patients value specialist care, lower out-of-pocket costs and less time away from usual activities. Telehealth is more likely than in-person care to cater to these preferences in many instances.

scholarly journals Patient preferences for use of virtual consultations in an orthopaedic rehabilitation setting: Results from a discrete choice experiment

2021 ◽  
pp. 135581962110354
Author(s):  
Anthony W Gilbert ◽  
Emmanouil Mentzakis ◽  
Carl R May ◽  
Maria Stokes ◽  
Jeremy Jones
Keyword(s):  
Conceptual Model ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Patient Preferences ◽  
Choice Experiment ◽  
Best Practice ◽  
Time Of Day ◽  
Problem Area ◽  
Fractional Factorial ◽  
The Impact

Objective Virtual Consultations may reduce the need for face-to-face outpatient appointments, thereby potentially reducing the cost and time involved in delivering health care. This study reports a discrete choice experiment (DCE) that identifies factors that influence patient preferences for virtual consultations in an orthopaedic rehabilitation setting. Methods Previous research from the CONNECT (Care in Orthopaedics, burdeN of treatmeNt and the Effect of Communication Technology) Project and best practice guidance informed the development of our DCE. An efficient fractional factorial design with 16 choice scenarios was created that identified all main effects and partial two-way interactions. The design was divided into two blocks of eight scenarios each, to reduce the impact of cognitive fatigue. Data analysis were conducted using binary logit regression models. Results Sixty-one paired response sets (122 subjects) were available for analysis. DCE factors (whether the therapist is known to the patient, duration of appointment, time of day) and demographic factors (patient qualifications, access to equipment, difficulty with activities, multiple health issues, travel costs) were significant predictors of preference. We estimate that a patient is less than 1% likely to prefer a virtual consultation if the patient has a degree, is without access to the equipment and software to undertake a virtual consultation, does not have difficulties with day-to-day activities, is undergoing rehabilitation for one problem area, has to pay less than £5 to travel, is having a consultation with a therapist not known to them, in 1 weeks’ time, lasting 60 minutes, at 2 pm. We have developed a simple conceptual model to explain how these factors interact to inform preference, including patients’ access to resources, context for the consultation and the requirements of the consultation. Conclusions This conceptual model provides the framework to focus attention towards factors that might influence patient preference for virtual consultations. Our model can inform the development of future technologies, trials, and qualitative work to further explore the mechanisms that influence preference.

Sign in / Sign up

Export Citation Format

Share Document