Abstract
Objective Lung cancer is a major cause of cancer-related deaths and thus represents a global health problem. According to World Health Organization (WHO) estimates, approximately 1.37 million people die each year from lung cancer. Different therapeutic approaches as well as several treatment options exist. To date decisions on which therapies to use have largely been made by clinical experts. Comparative preference studies show that underlying weighting of treatment goals by experts is not necessarily congruent with the preferences of affected patients.Aim and methodsThe aim of this empirical study was to ascertain patient preferences in relation to treatment of non-small-cell lung cancer (NSCLC). After identification of patient-relevant treatment attributes via literature review and qualitative interviews(ten) a discrete-choice experiment including seven patient-relevant attributes was conducted using a fractional factorial NGene-design. Statistical data analysis was performed using latent class models.ResultsThe qualitative part of this study identified outcome measures related to efficacy, side effects and mode of administration. A total of 211 NSCLC patients (N = 211) participated in the computer-assisted personal interview. A clear preference for an increase in “progression-free survival” (coef.: 1.087) and a reduction of “tumor-associated symptoms”(cough, shortness of breath and pain); coef.: 1.090) was demonstrated, followed by the reduction of side effects: “nausea and vomiting” (coef.: 0.605); “rash” (coef.: 0.432); “diarrhea” (coef.: 0.427); and, “tiredness and fatigue” (coef.: 0.423). The “mode of administration” was less important for participants (coef.: 0.141).ConclusionPreference measurement showed “progression-free survival” and “tumor-associated symptoms” had a significant influence on the treatment decision. Subgroup analysis revealed that the importance of “progression-free survival” increases with increased therapy experience. Based on the presented results therapies can be designed, assessed and chosen on the basis of patient-oriented findings. As such, more effective and efficient care of patients can be achieved and benefits increased.
Highlights
The qualitative part of this study identified outcome measures related to efficacy, side effects and mode of administration
In N = 10, qualitative semi-structured interviews with nonsmall-cell lung cancer (NSCLC) patients (N = 6), care givers (N = 3), and other cancer patients (N = 1) were conducted and the treatment characteristics extracted from the literature were tested
The model estimates in terms of structural parameters within the latent class model were subsequently calculated, which reflects the strength of influence of the individual structure parameters in each class. ‘‘Likelihood ratio tests’’, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to check the accuracy of the model, to determine the most appropriate model and to test for parameters that might improve the model fit
Summary
Decision model: Attributes and levels At the beginning literature research on the indication of NSCLC was conducted (PubMed, Medline, and Cochrane Library) to document the available state-of-the-art treatment options. The method of concentric circles was used to complement the relevant literature [40]. The aim of the search was to identify potential properties and characteristics of NSCLC treatments in general and from the patients’ perspective. In N = 10, qualitative semi-structured interviews with NSCLC patients (N = 6), care givers (N = 3), and other cancer patients (N = 1) were conducted and the treatment characteristics extracted from the literature were tested. Identified therapeutic features were confirmed and their relevance to the patients was assessed. Patients could name additional as yet unidentified treatment attributes that would be patient-
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