Significant increase of patient information and satisfaction with longer initial consultation duration in breast cancer - first results of the WAVES study

Aim of the study: The "WAVES" study (Widening Aims and giving patients a Voice for Expanded Structures in breast cancer care developed jointly by patients and physicians) aims to illuminate current breast cancer care structures with special focus on physician-patient-communication. Methods: The study is conducted within and funded by the BZKF (Bavarian Center for Cancer Research). Here, we present the results of the first preplanned analysis of the survey designed together with patients and patient advocates with the aim of adequately reflecting patients concerns. It is based on the evaluation of the first 1.000 patients who participated between 05/2022 and 08/2023, focusing on the duration of the first diagnosis consultation. Results: The participants were between 23 and 89 years old (mean: 59.18 years). There was a significant association between longer initial consultation duration and higher patient satisfaction (p < 0.001). When the first consultation lasted 30 minutes or more, patients stated more frequently that they felt better informed (p < 0.001) and had fully or substantially understood the content (p < 0.001). Conclusion: These results demonstrate a significantly higher satisfaction and better preparation of patients with initial breast cancer diagnosis if physicians’ communication lasted 30 minutes or more. Therefore the WAVES study clearly demonstrates the need for improved communication structures in terms of an appropriate time frame for breast cancer patients, which is not reflected in the current reimbursement structures

A roadmap to improve the quality of atrial fibrillation management:proceedings from the fifth Atrial Fibrillation Network/European Heart Rhythm Association consensus conference

At least 30 million people worldwide carry a diagnosis of atrial fibrillation (AF), and many more suffer from undiagnosed, subclinical, or 'silent' AF. Atrial fibrillation-related cardiovascular mortality and morbidity, including cardiovascular deaths, heart failure, stroke, and hospitalizations, remain unacceptably high, even when evidence-based therapies such as anticoagulation and rate control are used. Furthermore, it is still necessary to define how best to prevent AF, largely due to a lack of clinical measures that would allow identification of treatable causes of AF in any given patient. Hence, there are important unmet clinical and research needs in the evaluation and management of AF patients. The ensuing needs and opportunities for improving the quality of AF care were discussed during the fifth Atrial Fibrillation Network/European Heart Rhythm Association consensus conference in Nice, France, on 22 and 23 January 2015. Here, we report the outcome of this conference, with a focus on (i) learning from our 'neighbours' to improve AF care, (ii) patient-centred approaches to AF management, (iii) structured care of AF patients, (iv) improving the quality of AF treatment, and (v) personalization of AF management. This report ends with a list of priorities for research in AF patients

A large-scale genome-wide association study meta-analysis of cannabis use disorder

Summary Background Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07–1·15, p=1·84 × 10−9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86–0·93, p=6·46 × 10−9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10−21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. Funding National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.Peer reviewe

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case–control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10–13) and African ancestries (rs2066702; P = 2.2 × 10–9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit–hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.</p

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

First published: 16 February 202

Cancer data quality and harmonization in Europe: the experience of the BENCHISTA Project – international benchmarking of childhood cancer survival by stage

IntroductionVariation in stage at diagnosis of childhood cancers (CC) may explain differences in survival rates observed across geographical regions. The BENCHISTA project aims to understand these differences and to encourage the application of the Toronto Staging Guidelines (TG) by Population-Based Cancer Registries (PBCRs) to the most common solid paediatric cancers.MethodsPBCRs within and outside Europe were invited to participate and identify all cases of Neuroblastoma, Wilms Tumour, Medulloblastoma, Ewing Sarcoma, Rhabdomyosarcoma and Osteosarcoma diagnosed in a consecutive three-year period (2014-2017) and apply TG at diagnosis. Other non-stage prognostic factors, treatment, progression/recurrence, and cause of death information were collected as optional variables. A minimum of three-year follow-up was required. To standardise TG application by PBCRs, on-line workshops led by six tumour-specific clinical experts were held. To understand the role of data availability and quality, a survey focused on data collection/sharing processes and a quality assurance exercise were generated. To support data harmonization and query resolution a dedicated email and a question-and-answers bank were created.Results67 PBCRs from 28 countries participated and provided a maximally de-personalized, patient-level dataset. For 26 PBCRs, data format and ethical approval obtained by the two sponsoring institutions (UCL and INT) was sufficient for data sharing. 41 participating PBCRs required a Data Transfer Agreement (DTA) to comply with data protection regulations. Due to heterogeneity found in legal aspects, 18 months were spent on finalizing the DTA. The data collection survey was answered by 68 respondents from 63 PBCRs; 44% of them confirmed the ability to re-consult a clinician in cases where stage ascertainment was difficult/uncertain. Of the total participating PBCRs, 75% completed the staging quality assurance exercise, with a median correct answer proportion of 92% [range: 70% (rhabdomyosarcoma) to 100% (Wilms tumour)].ConclusionDifferences in interpretation and processes required to harmonize general data protection regulations across countries were encountered causing delays in data transfer. Despite challenges, the BENCHISTA Project has established a large collaboration between PBCRs and clinicians to collect detailed and standardised TG at a population-level enhancing the understanding of the reasons for variation in overall survival rates for CC, stimulate research and improve national/regional child health plans

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10) and African ancestries (rs2066702; P = 2.2 × 10). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.AMSUNY DownstatePsychiatry and Behavioral SciencesInstitute for Genomics in HealthN/

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

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.AMSUNY DownstatePsychiatry and Behavioral SciencesInstitute for Genomics in HealthN/

Impact of the early phase of the COVID pandemic on cancer treatment delivery and the quality of cancer care: a scoping review and conceptual model

AbstractBackgroundThe disruption of health services due to coronavirus disease (COVID) is expected to dramatically alter cancer care; however, the implications for care quality and outcomes remain poorly understood.ObjectiveWe undertook a scoping review to evaluate what is known in the literature about how cancer treatment has been modified as a result of the COVID pandemic in patients receiving treatment for solid tumours, and what domains of quality of care are most impacted.MethodsCitations were retrieved from MEDLINE and EMBASE (from 1 January 2019 to 28 October 2020), utilizing search terms grouped by the key concept (oncology, treatment, treatment modifications and COVID). Articles were excluded if they dealt exclusively with management of COVID-positive patients, modifications to cancer screening, diagnosis or supportive care or were not in English. Articles reporting on guidelines, consensus statements, recommendations, literature reviews, simulations or predictive models, or opinions in the absence of accompanying information on experience with treatment modifications in practice were excluded. Treatment modifications derived from the literature were stratified by modality (surgery, systemic therapy (ST) and radiotherapy) and thematically grouped. To understand what areas of quality were most impacted, modifications were mapped against the Institute of Medicine’s quality domains. Where reported, barriers and facilitators were abstracted and thematically grouped to understand drivers of treatment modifications. Findings were synthesized into a logic model to conceptualize the inter-relationships between different modifications, as well as their downstream impacts on outcomes.ResultsIn the 87 retained articles, reductions in outpatients visits (26.4%) and delays/deferrals were commonly reported across all treatment modalities (surgery: 50%; ST: 55.8% and radiotherapy: 56.7%), as were reductions in surgical capacity (57.1%), alternate systemic regimens with longer treatment intervals or use of oral agents (19.2%) and the use of hypofractionated radiotherapy regimens (40.0%). Delivery of effective, timely and equitable care was the quality domains found to be the most impacted. The most commonly reported facilitator of maintaining cancer care delivery levels was the shift to virtual models of care (62.1%), while patient-initiated deferrals and cancellations (34.8%), often due to fear of contracting COVID (60.9%), was a commonly reported barrier.ConclusionsAs it will take a considerable amount of time for the cancer system to resume capacity and adjust models of care in response to the pandemic, these treatment delays and modifications will likely be prolonged and will negatively impact the quality of care and patient outcomes.</jats:sec

Recovery of a quality improvement project during the COVID pandemic.

246 Background: Prior to COVID we undertook a QI project with the aim improving the documentation of a best possible medication history (BPMH) or medication reconciliation (MedRec) for patients initiating systemic therapy (ST) in ambulatory oncology, where care spans multiple providers and patients may be at increased risk of adverse drug events. While initial improvements were realized (16.7% and 3.9% increases for BPMH and MedRec, respectively), completion rates returned to baseline following the start of the COVID pandemic. Methods: Guided by the four-phase Quality Implementation Framework we sought to recover implementation of MedRec. We initially undertook a purposeful re-examination of the MedRec process (Phase 1) to identify barriers to conducting MedRec during COVID. This guided the tailored selection of Expert Recommendations for Implementing Change (ERIC) implementation strategies utilized during the successive phase of the project. During each phase the proportion of patients with documented BPMH or MedRec within 30 days of initiating ST out of those eligible was calculated. Results: Major barriers to conducting MedRec during COVID included reduced resources (time, human resources and physical resources), loss of dedicated staff, and change in workflow/ clinical models brought on by the introduction of virtual care. This informed our strategy to improve capacity to conduct MedRec (Phase 2) through the development and distribution of educational materials, revisions of professional roles, and creation of a new dedicated clinical team consisting of existing modified duty nurses to conduct MedRec. To support ongoing implementation (Phase 3), additional implementation strategies included the staged implementation scale-up, conduct of educational meetings/ outreach visits, facilitation, and provision of clinical supervision. The impact of each phase of implementation on BPMH and MedRec completion rates is summarized in Table. Conclusions: Recovery of a quality improvement intervention during COVID was realized through the utilization of a structured, implementation process model approach to identify and address barriers to implementation. Future work will focus on improvement of MedRec completion rates by clinicians, and on embedding processes into practice (Phase 4) to support sustainability of the intervention.[Table: see text] </jats:p