MLT may benefit cancer patients who are also receiving chemotherapy, radiotherapy, supportive therapy, or palliative therapy by improving survival and ameliorating the side effects of chemotherapy.

Objectives Breast cancer (BrC) and its treatments impair health-related quality of life (HRQoL). Utility is a measure of HRQoL that includes preferences for health outcomes, used in treatment decision-making. Generic preference-based instruments lack BrC-specific concerns, indicating the need for a BrC-specific preference-based instrument. Our objective was to determine dimensions of the European Organisation for Research and Treatment of Cancer (EORTC) general cancer (QLQ-C30) and breast module (BR45) instruments, the first step in our development of the novel Breast Utility Instrument (BUI). Methods Patients (n = 408) attending outpatient BrC clinics at an urban cancer centre, and representing a spectrum of BrC health states, completed the QLQ-C30 and BR45. We performed confirmatory factor analysis of the combined QLQ-C30 and BR45 using mean-and variance-adjusted unweighted least squares estimation. The hypothesized factor model was based on clinical relevance, item distributions, missing data, item-importance, and internal reliability of dimensions. Models were evaluated based on global and item fit, local areas of strain, and likelihood ratio tests of nested models. Results Our final model had 10 dimensions: physical and role functioning, emotional functioning, social functioning, body image, pain, fatigue, systemic therapy side effects, sexual functioning and enjoyment, arm and breast symptoms, and endocrine therapy symptoms. Good overall model fit was achieved: χ2/df: 1.45, Tucker-Lewis index: 0.946, comparative fit index: 0.951, standardized root-mean-square residual: 0.069, root-mean-square error of approximation: 0.033 (0.030–0.037). All items had salient factor loadings (λ>0.4, p<0.001). Conclusions We identified important BrC HRQoL dimensions to develop the BUI, a BrC-specific preference-based instrument.

BackgroundOver 30% of individuals use natural health products (NHPs) for osteoarthritis-related pain. The Deficit Model for the Public Understanding of Science suggests that if individuals are given more information (especially about scientific evidence) they will make better health-related decisions. In contrast, the Contextual Model argues that scientific evidence is one of many factors that explain how consumers make health-related decisions. The primary objective was to investigate how the level of scientific evidence supporting the efficacy of NHPs impacts consumer decision-making in the self-selection of NHPs by individuals with osteoarthritis.MethodsThe means-end chain approach to product evaluation was used to compare laddering interviews with two groups of community-dwelling Canadian seniors who had used NHPs to treat their osteoarthritis. Group 1 (n=13) had used only NHPs (glucosamine and/or chondroitin) with “high” scientific evidence of efficacy. Group 2 (n=12) had used NHPs (methylsulfonylmethane (MSM) and/or bromelain) with little or no scientific evidence supporting efficacy. Content analysis and generation of hierarchical value maps facilitated the identification of similarities and differences between the two groups.ResultsThe dominant decision-making chains for participants in the two scientific evidence categories were similar. Scientific evidence was an important decision-making factor but not as important as the advice from health care providers, friends and family. Most participants learned about scientific evidence via indirect sources from health care providers and the media.ConclusionsThe Contextual Model of the public understanding of science helps to explain why our participants believed scientific evidence is not the most important factor in their decision to use NHPs to help manage their osteoarthritis.

Introduction. Generic preference-based instruments inadequately measure breast cancer (BrC) health-related quality-of-life preferences given advances in therapy. Our overall purpose is to develop the Breast Utility Instrument (BUI), a BrC-specific preference-based instrument. This study describes the selection of the BUI items. Methods. A total of 408 patients from diverse BrC health states completed the EORTC QLQ-C30 and BR45 (breast module). For each of 10 dimensions previously assessed with confirmatory factor analysis, we evaluated data fit to the Rasch model based on global model and item fit, including threshold ordering, item residuals, infit and outfit, differential item functioning (age), and unidimensionality. Misfitting items were removed iteratively, and the model fit was reassessed. From items fitting the Rasch model, we selected 1 item per dimension based on high patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance. Results. Global model fit was good in 7 and borderline in 3 dimensions. Separation index was acceptable in 4 dimensions. Item selection criteria were maximized for the following items: 1) physical functioning (trouble taking a long walk), 2) emotional functioning (worry), 3) social functioning (interfering with social activities), 4) pain (having pain), 5) fatigue (tired), 6) body image (dissatisfied with your body), 7) systemic therapy side effects (hair loss), 8) sexual functioning (interest in sex), 9) breast symptoms (oversensitive breast), and 10) endocrine therapy symptoms (problems with your joints). Conclusions. We propose 10 items for the BUI. Our next steps include assessing the measurement properties prior to eliciting preference weights of the BUI. Highlights A previous confirmatory factor analysis established 10 dimensions of the European Organisation for Research and Treatment of Cancer (EORTC) core quality of life questionnaire (QLQ-C30) and its breast module (BR45). In this study, we selected 1 item per dimension based on fit to the Rasch model, patient- and clinician-rated item importance, breadth of item thresholds, and clinical relevance. These items form the core of the future Breast Utility Instrument (BUI). The future BUI will be a novel breast cancer–specific preference-based instrument that potentially will better reflect women’s preferences in clinical decision making and cost utility analyses.