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Introduction: End-of-life care is an essential task performed by most healthcare providers and often involves decision-making about how and where patients want to receive care. To provide decision support to healthcare professionals and patients in this difficult situation, we will systematically review a knowledge cluster of the end-of-life care preferences of older patients with multimorbidity that we previously identified using an evidence map., Methods and Analysis: We will systematically search for studies reporting end-of-life care preferences of older patients (mean age ≥60) with multimorbidity (≥2 chronic conditions) in MEDLINE, CINAHL, PsycINFO, Social Sciences Citation Index, Social Sciences Citation Index Expanded, PSYNDEX and The Cochrane Library from inception to September 2019. We will include all primary studies that use quantitative, qualitative and mixed methodologies, irrespective of publication date and language.Two independent reviewers will assess eligibility, extract data and describe evidence in terms of study/population characteristics, preference assessment method and end-of-life care elements that matter to patients (eg, life-sustaining treatments). Risk of bias/applicability of results will be independently assessed by two reviewers using the Mixed-Methods Appraisal Tool. Using a convergent integrated approach on qualitative/quantitative studies, we will synthesise information narratively and, wherever possible, quantitatively., Ethics and Dissemination: Due to the nature of the proposed systematic review, ethics approval is not required. Results from our research will be disseminated at relevant (inter-)national conferences and via publication in peer-reviewed journals. Synthesising evidence on end-of-life care preferences of older patients with multimorbidity will improve shared decision-making and satisfaction in this final period of life., Prospero Registration Number: CRD42020151862., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Unwanted anticholinergic effects are both underestimated and frequently overlooked. Failure to identify adverse drug reactions (ADRs) can lead to prescribing cascades and the unnecessary use of over-the-counter products. The objective of this systematic review and meta-analysis is to explore and quantify the frequency and severity of ADRs associated with amitriptyline vs. placebo in randomized controlled trials (RCTs) involving adults with any indication, as well as healthy individuals., Methods: A systematic search in six electronic databases, forward/backward searches, manual searches, and searches for Food and Drug Administration (FDA) and European Medicines Agency (EMA) approval studies, will be performed. Placebo-controlled RCTs evaluating amitriptyline in any dosage, regardless of indication and without restrictions on the time and language of publication, will be included, as will healthy individuals. Studies of topical amitriptyline, combination therapies, or including < 100 participants, will be excluded. Two investigators will screen the studies independently, assess methodological quality, and extract data on design, population, intervention, and outcomes ((non-)anticholinergic ADRs, e.g., symptoms, test results, and adverse drug events (ADEs) such as falls). The primary outcome will be the frequency of anticholinergic ADRs as a binary outcome (absolute number of patients with/without anticholinergic ADRs) in amitriptyline vs. placebo groups. Anticholinergic ADRs will be defined by an experienced clinical pharmacologist, based on literature and data from Martindale: The Complete Drug Reference. Secondary outcomes will be frequency and severity of (non-)anticholinergic ADRs and ADEs. The information will be synthesized in meta-analyses and narratives. We intend to assess heterogeneity using meta-regression (for indication, outcome, and time points) and I 2 statistics. Binary outcomes will be expressed as odds ratios, and continuous outcomes as standardized mean differences. Effect measures will be provided using 95% confidence intervals. We plan sensitivity analyses to assess methodological quality, outcome reporting etc., and subgroup analyses on age, dosage, and duration of treatment., Discussion: We will quantify the frequency of anticholinergic and other ADRs/ADEs in adults taking amitriptyline for any indication by comparing rates for amitriptyline vs. placebo, hence, preventing bias from disease symptoms and nocebo effects. As no standardized instrument exists to measure it, our overall estimate of anticholinergic ADRs may have limitations., Systematic Review Registration: Submitted to PROSPERO; assignment is in progress.

Background: Male breast cancer (MBC) is rare, and most previous studies limited their focus on clinical aspects of the disease. Psychosocial implications and care needs of MBC patients are poorly understood., Objectives: The aim of this study is to explore the experiences of men living with breast cancer and to identify supportive care needs., Methods: Eighteen men were interviewed using qualitative, semi-structured telephone interviews. Qualitative content analysis was used to analyze the data., Results: The majority of men did not have negative feelings about having a "women's disease," although some felt that stigmatization threatened their masculinity. Male sex was perceived as hindering access to adequate care. Patients identified key barriers including (1) a lack of awareness and experience of treating males among health professionals; (2) treatment and available information were based on evidence for females; and (3) lacking support services., Conclusion: To improve MBC care, it is important to raise awareness of the disease and to adapt treatment strategies, patient information, and support services to meet the needs of men., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2019 by S. Karger AG, Basel.)

Objectives: To systematically identify knowledge clusters and research gaps in the health-related preferences of older patients with multimorbidity by mapping current evidence., Design: Evidence map (systematic review variant)., Data Sources: MEDLINE, EMBASE, PsycINFO, PSYNDEX, CINAHL and Science Citation Index/Social Science Citation Index/-Expanded from inception to April 2018., Study Selection: Studies reporting primary research on health-related preferences of older patients (mean age ≥60 years) with multimorbidity (≥2 chronic/acute conditions)., Data Extraction: Two independent reviewers assessed studies for eligibility, extracted data and clustered the studies using MAXQDA-18 content analysis software., Results: The 152 included studies (62% from North America, 28% from Europe) comprised 57 093 patients overall (range 9-9105). All used an observational design except for one interventional study: 63 (41%) were qualitative (59 cross-sectional, 4 longitudinal), 85 (57%) quantitative (63 cross-sectional, 22 longitudinal) and 3 (2%) used mixed methods. The setting was specialised care in 85 (56%) and primary care in 54 (36%) studies. We identified seven clusters of studies on preferences: end-of-life care (n=51, 34%), self-management (n=34, 22%), treatment (n=32, 21%), involvement in shared decision making (n=25, 17%), health outcome prioritisation/goal setting (n=19, 13%), healthcare service (n=12, 8%) and screening/diagnostic testing (n=1, 1%). Terminology (eg, preferences, views and perspectives) and concepts (eg, trade-offs, decision regret, goal setting) used to describe health-related preferences varied substantially between studies., Conclusion: Our study provides the first evidence map on the preferences of older patients with multimorbidity. Included studies were mostly conducted in developed countries and covered a broad range of issues. Evidence on patient preferences concerning decision-making on screening and diagnostic testing was scarce. Differences in employed terminology, decision-making components and concepts, as well as the sparsity of intervention studies, are challenges for future research into evidence-based decision support seeking to elicit the preferences of older patients with multimorbidity and help them construct preferences., Trial Registration Number: Open Science Framework (OSF): DOI 10.17605/OSF.IO/MCRWQ., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Interaction of conditions and treatments, complicated care needs and substantial treatment burden make patient-physician encounters involving multimorbid older patients highly complex. To optimally integrate patients' preferences, define and prioritise realistic treatment goals and individualise care, a patient-centred approach is recommended. However, the preferences of older patients, who are especially vulnerable and frequently multimorbid, have not been systematically investigated with regard to their health status. The purpose of this evidence map is to explore current research addressing health-related preferences of older patients with multimorbidity, and to identify the knowledge clusters and research gaps., Methods and Analysis: To identify relevant research, we will conduct searches in the electronic databases MEDLINE, EMBASE, PsycINFO, PSYNDEX, CINAHL, Social Science Citation Index, Social Science Citation Index Expanded and the Cochrane library from their inception. We will check reference lists of relevant articles and carry out cited reference research (forward citation tracking). Two independent reviewers will screen titles and abstracts, check full texts for eligibility and extract the data. Any disagreement will be resolved and consensus reached with the help of a third reviewer. We will include both qualitative and quantitative studies, and address preferences from the patients' perspectives in a multimorbid population of 60 years or older. There will be no restrictions on the publication language. Data extraction tables will present study and patient characteristics, aim of study, methods used to identify preferences and outcomes (ie, type of preferences). We will summarise the data using tables and figures (ie, bubble plot) to present the research landscape and to describe clusters and gaps., Ethics and Dissemination: Due to the nature of the proposed evidence map, ethics approval will not be required. Results from our research will be disseminated by means of specifically prepared materials for patients, at relevant (inter)national conferences and via publication in peer-reviewed journals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Multimorbidity is prevalent and related to adverse outcomes. The effect on mortality is disputed, possibly because studies show differences in the diseases which operationalize multimorbidity. The aim of this study is to analyze the effects of three multimorbidity patterns (representing subgroups of diseases) on mortality., Methods: We conducted a longitudinal observational study based on insurance claims data of ambulatory care from 2005 to 2009. Analyses are based on 46 chronic conditions with a prevalence ≥1%. We included 52,217 females and 71,007 males aged 65+ and insured by the Gmünder ErsatzKasse throughout 2004. Our outcome was 5-year overall mortality documented as exact time of death. We calculated hazard ratios by Cox regression analyses with time-dependent covariates. Three statistical models were analyzed: (a) the individual diseases, (b) the number of diseases in multimorbidity patterns, and (c) a count of all diseases, all calculated separately for genders and adjusted for age., Results: During the study period, 12,473 males (17.6%) and 7,457 females (14.3%) died. The general effect of multimorbidity on mortality was small (females: 1.02, 1.01-1.02; males: 1.04, 1.03-1.04). The number of neuropsychiatric disorders was related to higher mortality (1.33, 1.30-1.36; 1.46, 1.43-1.50). Cardiovascular and metabolic disorders had inconsistent effects (0.99, 0.97-1.01; 1.08, 1.07-1.09). Psychiatric, psychosomatic, and pain-related disorders were related to higher life expectancy (0.87, 0.86-0.89; 0.88, 0.87-0.90)., Conclusions: Chronic diseases have heterogeneous effects on mortality and generalized measures of multimorbidity reflect and even out the effects of the single diseases. In multimorbidity studies, a careful selection of diseases is therefore important., Competing Interests: Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.