Integrating patients' views into health technology assessment: Analytic hierarchy process (AHP) as a method to elicit patient preferences

Background: Patient involvement is widely acknowledged to be a valuable component in health technology assessment (HTA) and healthcare decision making. However, quantitative approaches to ascertain patients' preferences for treatment endpoints are not yet established. The objective of this study is to introduce the analytic hierarchy process (AHP) as a preference elicitation method in HTA. Based on a systematic literature review on the use of AHP in health care in 2009, the German Institute for Quality and Efficiency in Health Care (IQWiG) initiated an AHP study related to its HTA work in 2010. - \ud Methods: The AHP study included two AHP workshops, one with twelve patients and one with seven healthcare professionals. In these workshops, both patients and professionals rated their preferences with respect to the importance of different endpoints of antidepressant treatment by a pairwise comparison of individual endpoints. These comparisons were performed and evaluated by the AHP method and relative weights were generated for each endpoint. - \ud Results: The AHP study indicates that AHP is a well-structured technique whose cognitive demands were well handled by patients and professionals. The two groups rated some of the included endpoints of antidepressant treatment differently. For both groups, however, the same six of the eleven endpoints analyzed accounted for more than 80 percent of the total weight. - \ud Conclusions: AHP can be used in HTA to give a quantitative dimension to patients' preferences for treatment endpoints. Preference elicitation could provide important information at various stages of HTA and challenge opinions on the importance of endpoints

A scattered landscape: assessment of the evidence base for 71 patient decision aids developed in a hospital setting

Background Recent publications reveal shortcomings in evidence review and summarization methods for patient decision aids. In the large-scale "Share to Care (S2C)" Shared Decision Making (SDM) project at the University Hospital Kiel, Germany, one of 4 SDM interventions was to develop up to 80 decision aids for patients. Best available evidence on the treatments' impact on patient-relevant outcomes was systematically appraised to feed this information into the decision aids. Aims of this paper were to (1) describe how PtDAs are developed and how S2C evidence reviews for each PtDA are conducted, (2) appraise the quality of the best available evidence identified and (3) identify challenges associated with identified evidence. Methods The quality of the identified evidence was assessed based on GRADE quality criteria and categorized into high-, moderate-, low-, very low-quality evidence. Evidence appraisal was conducted across all outcomes assessed in an evidence review and for specific groups of outcomes, namely mortality, morbidity, quality of life, and treatment harms. Challenges in evidence interpretation and summarization resulting from the characteristics of decision aids and the type and quality of evidence are identified and discussed. Conclusions Evidence reviews in this project were carefully conducted and summarized. However, the evidence identified for our decision aids was indeed a "scattered landscape" and often poor quality. Facing a high prevalence of low-quality, non-directly comparative evidence for treatment alternatives doesn't mean it is not necessary to choose an evidence-based approach to inform patients. While there is an urgent need for high quality comparative trials, best available evidence nevertheless has to be appraised and transparently communicated to patients

Making shared decision-making (SDM) a reality: protocol of a large-scale long-term SDM implementation programme at a Northern German University Hospital

Introduction: Shared decision-making (SDM) is not yet widely used when making decisions in German hospitals. Making SDM a reality is a complex task. It involves training healthcare professionals in SDM communication and enabling patients to actively participate in communication, in addition to providing sound, easy to understand information on treatment alternatives in the form of evidence-based patient decision aids (EbPDAs). This project funded by the German Innovation Fund aims at designing, implementing and evaluating a multicomponent, large-scale and integrative SDM programme-called SHARE TO CARE (S2C)-at all clinical departments of a University Hospital Campus in Northern Germany within a 4-year time period. Methods and analysis S2C tackles the aforementioned components of SDM: (1) training physicians in SDM communication, (2) activating and empowering patients, (3) developing EbPDAs in the most common/relevant diseases and (4) training other healthcare professionals in SDM coaching. S2C is designed together with patients and providers. The physicians' training programme entails an online and an in situ training module. The decision coach training is based on a similar but less comprehensive approach. The development of online EbPDAs follows the International Patient Decision Aid Standards and includes written, graphical and video-based information. Validated outcomes of SDM implementation are measured in a preintervention and postintervention evaluation design. Process evaluation accompanies programme implementation. Health economic impact of the intervention is investigated using a propensity-score-matched approach based on potentially preference-sensitive hospital decisions. Ethics and dissemination Ethics committee review approval has been obtained from Medical Ethics Committee of the Medical Faculty of the Christian-Albrechts-University Kiel. Project information and results will be disseminated at conferences, on project-hosted websites at University Hospital Medical Center Schleswig Holstein and by S2C as well as in peer-reviewed and professional journals

Estimation of input costs for a Markov model in a German health economic evaluation of newer antidepressants

Background: Estimating input costs for Markov models in health economic evaluations requires health state-specific costing. This is a challenge in mental illnesses such as depression, as interventions are not clearly related to health states. We present a hybrid approach to health state-specific cost estimation for a German health economic evaluation of antidepressants. Methods: Costs were determined from the perspective of the community of persons insured by statutory health insurance (“SHI insuree perspective”) and included costs for outpatient care, inpatient care, drugs, and psychotherapy. In an additional step, costs for rehabilitation and productivity losses were calculated from the societal perspective. We collected resource use data in a stepwise hierarchical approach using SHI claims data, where available, followed by data from clinical guidelines and expert surveys. Bottom-up and top-down costing approaches were combined. Results: Depending on the drug strategy and health state, the average input costs varied per patient per 8-week Markov cycle. The highest costs occurred for agomelatine in the health state first-line treatment (FT) (“FT relapse”) with €506 from the SHI insuree perspective and €724 from the societal perspective. From both perspectives, the lowest costs (excluding placebo) were €55 for selective serotonin reuptake inhibitors in the health state “FT remission.” Conclusion: To estimate costs in health economic evaluations of treatments for depression, it can be necessary to link different data sources and costing approaches systematically to meet the requirements of the decision-analytic model. As this can increase complexity, the corresponding calculations should be presented transparently. The approach presented could provide useful input for future models

Common Genetic Variation And Age at Onset Of Anorexia Nervosa

Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe

A genome-wide association study of anorexia nervosa

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10−7) in SOX2OT and rs17030795 (P=5.84×10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10−6) between CUL3 and FAM124B and rs1886797 (P=8.05×10−6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4×10−6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

Shared genetic risk between eating disorder- and substance-use-related phenotypes:Evidence from genome-wide association studies

First published: 16 February 202