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      Patient Preference and Adherence (submit here)

      This international, peer-reviewed Open Access journal by Dove Medical Press focuses on the growing importance of patient preference and adherence throughout the therapeutic process. Sign up for email alerts here.

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      Therapy preferences of patients with lung and colon cancer: a discrete choice experiment

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          Abstract

          Objectives

          There is increasing interest in studies that examine patient preferences to measure health-related outcomes. Understanding patients’ preferences can improve the treatment process and is particularly relevant for oncology. In this study, we aimed to identify the subgroup-specific treatment preferences of German patients with lung cancer (LC) or colorectal cancer (CRC).

          Methods

          Six discrete choice experiment (DCE) attributes were established on the basis of a systematic literature review and qualitative interviews. The DCE analyses comprised generalized linear mixed-effects model and latent class mixed logit model.

          Results

          The study cohort comprised 310 patients (194 with LC, 108 with CRC, 8 with both types of cancer) with a median age of 63 (SD =10.66) years. The generalized linear mixed-effects model showed a significant ( P<0.05) degree of association for all of the tested attributes. “Strongly increased life expectancy” was the attribute given the greatest weight by all patient groups. Using latent class mixed logit model analysis, we identified three classes of patients. Patients who were better informed tended to prefer a more balanced relationship between length and health-related quality of life (HRQoL) than those who were less informed. Class 2 (LC patients with low HRQoL who had undergone surgery) gave a very strong weighting to increased length of life. We deduced from Class 3 patients that those with a relatively good life expectancy (CRC compared with LC) gave a greater weight to moderate effects on HRQoL than to a longer life.

          Conclusion

          Overall survival was the most important attribute of therapy for patients with LC or CRC. Differences in treatment preferences between subgroups should be considered in regard to treatment and development of guidelines. Patients’ preferences were not affected by sex or age, but were affected by the cancer type, HRQoL, surgery status, and the main source of information on the disease.

          Most cited references32

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          Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

          Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice data, it does not address the issue of minimum sample size requirements in terms of the statistical power of hypothesis tests on the estimated coefficients. The purpose of this paper is threefold: (1) to provide insight into whether and how researchers have dealt with sample size calculations for healthcare-related DCE studies; (2) to introduce and explain the required sample size for parameter estimates in DCEs; and (3) to provide a step-by-step guide for the calculation of the minimum sample size requirements for DCEs in health care. Electronic supplementary material The online version of this article (doi:10.1007/s40271-015-0118-z) contains supplementary material, which is available to authorized users.
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            Quality of life of patients with lung cancer

            Lung cancer is the major cause of oncologic-related death worldwide. Due to delayed diagnosis, 5-year survival rate accounts for only 15%. Treatment includes surgery, adjuvant chemotherapy, and radiation therapy; however, it is burdened by many side effects. Progress of the disease, severity of its symptoms, and side effects decrease significantly the quality of life (QoL) in those patients. The level of self-assessed QoL helps in predicting survival, which is especially important among patients receiving palliative care. Patients assess their functioning in five dimensions (physical, psychological, cognitive, social, and life roles), severity of symptoms, financial problems, and overall QoL. The QoL in lung cancer patients is lower than in healthy population and patients suffering from other malignancies. It is affected by the severity and the number of symptoms such as fatigue, loss of appetite, dyspnea, cough, pain, and blood in sputum, which are specific for lung tumors. Fatigue and respiratory problems reduce psychological dimension of QoL, while sleep problems reduce cognitive functioning. Physical dimension (related to growing disability) decreases in most of the patients. Also, most of them are unable to play their family and social roles. The disease is a frequent reason of irritation, distress, and depression. Management of the disease symptoms may improve QoL. Controlling the level of fatigue, pulmonary rehabilitation, and social and spiritual support are recommended. Early introduction of tailored palliative treatment is a strategy of choice for improvement of QoL in lung cancer patients.
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              Choice Experiments to Quantify Preferences for Health and Healthcare: State of the Practice.

              Stated-preference methods increasingly are used to quantify preferences in health economics, health technology assessment, benefit-risk analysis and health services research. The objective of stated-preference studies is to acquire information about trade-off preferences among treatment outcomes, prioritization of clinical decision criteria, likely uptake or adherence to healthcare products and acceptability of healthcare services or policies. A widely accepted approach to eliciting preferences is discrete-choice experiments. Patient, physician, insurant or general-public respondents choose among constructed, experimentally controlled alternatives described by decision-relevant features or attributes. Attributes can represent complete health states, sets of treatment outcomes or characteristics of a healthcare system. The observed pattern of choice reveals how different respondents or groups of respondents implicitly weigh, value and assess different characteristics of treatments, products or services. An important advantage of choice experiments is their foundation in microeconomic utility theory. This conceptual framework provides tests of internal validity, guidance for statistical analysis of latent preference structures, and testable behavioural hypotheses. Choice experiments require expertise in survey-research methods, random-utility theory, experimental design and advanced statistical analysis. This paper should be understood as an introduction to setting up a basic experiment rather than an exhaustive critique of the latest findings and procedures. Where appropriate, we have identified topics of active research where a broad consensus has not yet been established.
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                Author and article information

                Journal
                Patient Prefer Adherence
                Patient Prefer Adherence
                Patient Preference and Adherence
                Patient preference and adherence
                Dove Medical Press
                1177-889X
                2017
                26 September 2017
                : 11
                : 1647-1656
                Affiliations
                [1 ]Leibniz University of Hannover, Center for Health Economics Research (CHERH), Hannover, Germany
                [2 ]Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
                [3 ]Department of Pneumology, Hannover Medical School, Hannover, Germany
                [4 ]Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany
                Author notes
                Correspondence: Katharina Schmidt, Leibniz Universität Hannover, Center for Health Economics Research Hannover (CHERH), Otto-Brenner-Str 1, 30159 Hannover, Germany, Tel +49 511 762 17346, Fax +49 511 762 5081, Email ks@ 123456cherh.de
                Article
                ppa-11-1647
                10.2147/PPA.S138863
                5630067
                29033552
                06ab4896-e88b-4969-a7ab-bd0615d904f5
                © 2017 Schmidt et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

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                Categories
                Original Research

                Medicine
                patient preferences,lung cancer,colorectal cancer,germany,latent class model,multi-criteria decision making

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