Risk communication in a patient decision aid for radiotherapy in breast cancer: How to deal with uncertainty?

Background and aimPatient decision aids for oncological treatment options, provide information on the effect on recurrence rates and/or survival benefit, and on side-effects and/or burden of different treatment options. However, often uncertainty exists around the probability estimates for recurrence/survival and side-effects which is too relevant to be ignored. Evidence is lacking on the best way to communicate these uncertainties. The aim of this study is to develop a method to incorporate uncertainties in a patient decision aid for breast cancer patients to support their decision on radiotherapy.MethodsFirstly, qualitative interviews were held with patients and health care professionals. Secondly, in the development phase, thinking aloud sessions were organized with four patients and 12 health care professionals, individual and group-wise.ResultsConsensus was reached on a pictograph illustrating the whole range of uncertainty for local recurrence risks, in combination with textual explanation that a more exact personalized risk would be given by their own physician. The pictograph consisted of 100 female icons in a 10 x 10 array. Icons with a stepwise gradient color indicated the uncertainty margin. The prevalence and severity of possible side-effects were explained using verbal labels.ConclusionsWe developed a novel way of visualizing uncertainties in recurrence rates in a patient decision aid. The effect of this way of communicating risk uncertainty is currently being tested in the BRASA study (NCT03375801).     

Shared decision making in consultations for hypertension: Qualitative study in general practice

BackgroundHypertension is mainly managed in primary care. Shared decision making is widely recommended as an approach to treatment decision making. However, no studies have investigated; in detail, what happens during primary care consultations for hypertension.AimTo understand patients’ and clinicians’ experience of shared decision making for hypertension in primary care, in order to propose how it might be better supported.DesignLongitudinal qualitative study.SettingFive general practices in south‐west England.MethodInterviews with a purposive sample of patients with hypertension, and with the health‐care practitioners they consulted, along with observations of clinical consultations, for up to 6 appointments. Interviews and consultations were audio‐recorded and observational field notes taken. Data were analysed thematically.ResultsForty‐six interviews and 18 consultations were observed, with 11 patients and nine health‐care practitioners (five GPs, one pharmacist and three nurses). Little shared decision making was described by participants or observed. Often patients’ understanding of their hypertension was limited, and they were not aware there were treatment choices. Consultations provided few opportunities for patients and clinicians to reach a shared understanding of their treatment choices. Opportunities for patients to engage in choices were limited by structured consultations and the distribution of decisions across consultations.ConclusionFor shared decision making to be better supported, consultations need to provide opportunities for patients to learn about their condition, to understand that there are treatment choices, and to discuss these choices with clinicians.Patient or Public ContributionA patient group contributed to the design of this study.     

Can Machine Learning Methods Produce Accurate and Easy-to-Use Preoperative Prediction Models of One-Year Improvements in Pain and Functioning After Knee Arthroplasty?

BackgroundApproximately 15%-20% of total knee arthroplasty (TKA) patients do not experience clinically meaningful improvements. We sought to compare the accuracy and parsimony of several machine learning strategies for developing predictive models of failing to experience minimal clinically important differences in patient-reported outcome measures (PROMs) 1 year after TKA.MethodsPatients (N = 587) in 3 large Veteran Health Administration facilities completed PROMs before and 1 year after TKA (92% follow-up). Preoperative PROMs and electronic health record data were used to develop and validate models to predict failing to experience at least a minimal clinically important difference in Knee Injury and Osteoarthritis Outcome Score (KOOS) Total, KOOS JR, and KOOS subscales (Pain, Symptoms, Activities of Daily Living, Quality of Life, and recreation). Several machine learning strategies were used for model development. Ten-fold cross-validation and bootstrapping were used to produce measures of overall accuracy (C-statistic, Brier Score). The sensitivity and specificity of various predicted probability cut-points were examined.ResultsThe most accurate models produced were for the Activities of Daily Living, Pain, Symptoms, and Quality of Life subscales of the KOOS (C-statistics 0.76, 0.72, 0.72, and 0.71, respectively). Strategies varied substantially in terms of the numbers of inputs required to achieve similar accuracy, with none being superior for all outcomes.ConclusionModels produced in this project provide estimates of patient-specific improvements in major outcomes 1 year after TKA. Integrating these models into clinical decision support, informed consent and shared decision making could improve patient selection, education, and satisfaction.Level of EvidenceLevel III, diagnostic study.     

护理人员参与共享决策实践认知和体验质性研究的Meta整合

目的 整合护理人员参与共享决策实践认知和体验的质性研究,为护理人员参与和实施决策共享提供参考和依据。方法 检索中国生物医学数据库、中国知网、万方、PubMed、Web of Science、CINAHL、Embase、Cochrane Library数据库中有关护理人员参与共享决策实践的认知和体验的质性研究,检索时限为建库至2022年10月。使用澳大利亚JBI循证卫生保健中心质性研究质量评价工具评价,汇集性整合方法进行整合。结果 共纳入13篇文献,提取36个主题,归纳为11个类别和6个整合结果：护士混淆共享决策的概念;对实行共享决策持批判性态度;肯定和认同共享决策;在共享决策中经历负面体验;共享决策赋予了护士新的角色;护士参与共享决策需要增强自身素质和外部条件的支持。结论 护士在共享决策中扮演了重要的角色,管理者要重视护士角色培养,根据护士需求提供培训和指导,发挥护士在共享决策中的角色价值。     

Generalizing Bayesian phylogenetics to infer shared evolutionary events

Many processes of biological diversification can simultaneously affect multiple evolutionary lineages. Examples include multiple members of a gene family diverging when a region of a chromosome is duplicated, multiple viral strains diverging at a “super-spreading” event, and a geological event fragmenting whole communities of species. It is difficult to test for patterns of shared divergences predicted by such processes because all phylogenetic methods assume that lineages diverge independently. We introduce a Bayesian phylogenetic approach to relax the assumption of independent, bifurcating divergences by expanding the space of topologies to include trees with shared and multifurcating divergences. This allows us to jointly infer phylogenetic relationships, divergence times, and patterns of divergences predicted by processes of diversification that affect multiple evolutionary lineages simultaneously or lead to more than two descendant lineages. Using simulations, we find that the method accurately infers shared and multifurcating divergence events when they occur and performs as well as current phylogenetic methods when divergences are independent and bifurcating. We apply our approach to genomic data from two genera of geckos from across the Philippines to test if past changes to the islands’ landscape caused bursts of speciation. Unlike previous analyses restricted to only pairs of gecko populations, we find evidence for patterns of shared divergences. By generalizing the space of phylogenetic trees in a way that is independent from the likelihood model, our approach opens many avenues for future research into processes of diversification across the life sciences.

There are many processes of biological diversification that affect multiple evolutionary lineages, generating patterns of temporally clustered divergences across the tree of life. Understanding such processes of diversification has important implications across many fields and scales of biology. At the scale of genome evolution, the duplication of a chromosome segment harboring multiple members of a gene family causes multiple, simultaneous (or “shared”) divergences across the phylogenetic history of the gene family (1–4). In epidemiology, when a pathogen is spread by multiple infected individuals at a social gathering, this will create shared divergences across the pathogen’s “transmission tree” (5–7). If one of these individuals infects two or more others, this will create a multifurcation (a lineage diverging into three or more descendants) in the transmission tree. At regional or global scales, when biogeographic processes fragment communities, this can cause shared divergences across multiple affected species (8–13). If the landscape is fragmented into three or more regions, this can also cause multifurcations (14). For example, the repeated fragmentation of the Philippines by interglacial rises in sea level since the late Pliocene (15–19) has been an important model to help explain remarkably high levels of microendemism and biodiversity across the archipelago (20–30). This model predicts that recently diverged taxa across the islands should have (potentially multifurcating) divergence times clustered around the beginning of interglacial periods. We are limited in our ability to infer patterns of divergences predicted by such processes because phylogenetic methods assume that lineages diverge independently.To formalize this assumption of independent divergences and develop ways to relax it, it is instructive to view phylogenetic inference as an exercise of statistical model selection, where each topology is a separate model (31–33). Current methods for estimating rooted phylogenies with N tips only consider tree models with N−1 bifurcating divergences and assume that these divergences are independent, conditional on the topology (see ref. 34 for multifurcations in unrooted trees). If, in the history leading to the tips we are studying, diversification processes affected multiple lineages simultaneously or caused them to diverge into more than two descendants, the true tree could have shared or multifurcating divergences. This would make current phylogenetic models with N−1 independent divergence times overparameterized, introducing unnecessary error (Fig. 1). Even worse, with current methods, we lack an obvious way of using our data to test for patterns of shared or multifurcating divergences predicted by such processes.Open in a separate windowFig. 1.A hypothetical evolutionary history with shared divergences (Left) and the benefits of the generalizing tree space under such conditions (Right). Current methods are restricted to one class of tree models, where the tree is fully bifurcating and independent divergence-time parameters are estimated for all internal nodes (Center). Figure was made by using Gram [v4.0.0 (35)] and the P4 phylogenetic toolkit [v1.4 5742542 (36)]. Image credit for top and bottom lizard silhouettes: Phylopic/Steven Traver. Image credit for middle lizard silhouettes: Pixabay/No-longer-here.We relax the assumption of independent, bifurcating divergences by introducing a Bayesian approach to generalizing the space of tree models to allow for shared and multifurcating divergences. In our approach, we view trees with N−1 bifurcating divergences as only one class of tree models in a greater space of trees with anywhere from 1 to N−1 potentially shared and/or multifurcating divergences (SI Appendix, Fig. S1). We introduce reversible-jump Markov chain Monte Carlo (MCMC) algorithms (37–39) to sample this generalized space of trees, allowing us to jointly infer evolutionary relationships, shared and multifurcating divergences, and divergence times. We couple these algorithms with a likelihood model for directly calculating the probability of biallelic characters, given a population (or species) phylogeny, while analytically integrating over all possible gene trees under a coalescent model and all possible mutational histories under a finite-sites model of character evolution (40, 41). Using simulations, we find that the generalized tree model accurately infers shared and multifurcating divergences, while maintaining a low rate of falsely inferring such divergences. To test for patterns of shared and multifurcating divergences predicted by repeated fragmentation of the Philippines by interglacial rises in sea level (42–44), we apply the generalized tree model to genomic data from two genera of geckos codistributed across the islands.     

A tumor metastasis‐associated molecule TWIST1 is a favorable target for cancer immunotherapy due to its immunogenicity

Although neoantigens are one of the most favorable targets in cancer immunotherapy, it is less versatile and costly to apply neoantigen‐derived cancer vaccines to patients due to individual variation. It is, therefore, important to find highly immunogenic antigens between tumor‐specific or associated antigens that are shared among patients. Considering the cancer immunoediting theory, immunogenic tumor cells cannot survive in the early phase of tumor progression including two processes: elimination and equilibrium. We hypothesized that highly immunogenic molecules are allowed to be expressed in tumor cells after an immune suppressive tumor microenvironment was established, if these molecules contribute to tumor survival. In the current study, we focused on TWIST1 as a candidate for highly immunogenic antigens because it is upregulated in tumor cells under hypoxia and promotes tumor metastasis, which is observed in the late phase of tumor progression. We demonstrated that TWIST1 had an immunogenic peptide sequence TWIST1_140–162, which effectively activated TWIST1‐specific CD4⁺ T‐cells. In a short‐term culture system, we detected more TWIST1‐specific responses in breast cancer patients compared with in healthy donors. Vaccination with the TWIST1 peptide also showed efficient expansion of TWIST1‐reactive HTLs in humanized mice. These findings indicate that TWIST1 is a highly immunogenic shared antigen and a favorable target for cancer immunotherapy.     

A Call to Wellness – Whitiwhitia i te ora: Exploring Māori and Occupational Therapy Perspectives on Health

The World Health Organization records that indigenous peoples throughout the world experience poor health. The concept of health was explored from a Māori world view and compared with occupational therapy perspectives. The aim was to understand and value indigenous knowledge and promote culturally safe responsive practice. Māori methodologies were employed to protect the Māori knowledge shared in the study. This involved applying seven principles, including respect for people, be cautious, and look, listen, and speak. Perspectives on health and wellbeing were collected in 2008–2009 from indigenous occupational therapists, other occupational therapists and indigenous health practitioners using interviews and a questionnaire. The findings are presented as a conceptual framework, depicting a whare, a Māori meeting house to show relationships between culture and health. Key concepts held by occupational therapists and Māori were spirituality, holistic views, client responsive practice, and environmental contexts. Areas of difference were the focus on occupations, the interdependence of indigenous relationships, and the place of the extended family in supporting wellness. A strength was the respect for Māori methodologies and limitations were the number of participants (N = 23) and the small proportion of Māori therapists in Aotearoa/New Zealand. Recommendations: Attention to culture is vital for appropriate, safe, and responsive practice. The conceptual framework provides a tool to inform, guide, and evaluate practice understandings. It acknowledges the importance of the individual within their extended family, their natural environment, and the historical, social, and political realities of living as Māori. Further research should explore the use of the framework and interaction between occupational therapy practice and specific indigenous cultures. Copyright © 2014 John Wiley & Sons, Ltd.     

Including the voice of paediatric patients: Cocreation of an engagement game

BackgroundEngaging patients in health care, research and policy is essential to improving patient‐important health outcomes and the quality of care. Although the importance of patient engagement is increasingly acknowledged, clinicians and researchers still find it difficult to engage patients, especially paediatric patients. To facilitate the engagement of children and adolescents in health care, the aim of this project is to develop an engagement game.MethodsA user‐centred design was used to develop a patient engagement game in three steps: (1) identification of important themes for adolescents regarding their illness, treatment and hospital care, (2) evaluation of the draft version of the game and (3) testing usability in clinical practice. Adolescents (12–18 years) were engaged in all steps of the development process through focus groups, interviews or a workshop. These were audio‐recorded, transcribed verbatim and analysed in MAXQDA.Results(1) The important themes for adolescents (N = 15) were included: visiting the hospital, participating, disease and treatment, social environment, feelings, dealing with staff, acceptation, autonomy, disclosure and chronically ill peers. (2) Then, based on these themes, the engagement game was developed and the draft version was evaluated by 13 adolescents. Based on their feedback, changes were made to the game (e.g., adjusting the images and changing the game rules). (3) Regarding usability, the pilot version was evaluated positively. The game helped adolescents to give their opinion. Based on the feedback of adolescents, some last adjustments (e.g., changing colours and adding a game board) were made, which led to the final version of the game, All Voices Count.ConclusionsWorking together with adolescents, All Voices Count, a patient engagement game was developed. This game provides clinicians with a tool that supports shared decision‐making to address adolescents'' wishes and needs.Patient or Public ContributionPaediatric patients, clinicians, researchers, youth panel of Fonds NutsOhra and patient associations (Patient Alliance for Rare and Genetic Diseases, Dutch Childhood Cancer Organization) were involved in all phases of the development of the patient engagement game—from writing the project plan to the final version of the game.     

Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision‐making

BackgroundLung cancer treatment decisions are typically made among clinical experts in a multidisciplinary tumour board (MTB) based on clinical data and guidelines. The rise of artificial intelligence and cultural shifts towards patient autonomy are changing the nature of clinical decision‐making towards personalized treatments. This can be supported by clinical decision support systems (CDSSs) that generate personalized treatment information as a basis for shared decision‐making (SDM). Little is known about lung cancer patients'' treatment decisions and the potential for SDM supported by CDSSs. The aim of this study is to understand to what extent SDM is done in current practice and what clinicians need to improve it.ObjectiveTo explore (1) the extent to which patient preferences are taken into consideration in non‐small‐cell lung cancer (NSCLC) treatment decisions; (2) clinician perspectives on using CDSSs to support SDM.DesignMixed methods study consisting of a retrospective cohort study on patient deviation from MTB advice and reasons for deviation, qualitative interviews with lung cancer specialists and observations of MTB discussions and patient consultations.Setting and ParticipantsNSCLC patients (N = 257) treated at a single radiotherapy clinic and nine lung cancer specialists from six Dutch clinics.ResultsWe found a 10.9% (n = 28) deviation rate from MTB advice; 50% (n = 14) were due to patient preference, of which 85.7% (n = 12) chose a less intensive treatment than MTB advice. Current MTB recommendations are based on clinician experience, guidelines and patients'' performance status. Most specialists (n = 7) were receptive towards CDSSs but cited barriers, such as lack of trust, lack of validation studies and time. CDSSs were considered valuable during MTB discussions rather than in consultations.ConclusionLung cancer decisions are heavily influenced by clinical guidelines and experience, yet many patients prefer less intensive treatments. CDSSs can support SDM by presenting the harms and benefits of different treatment options rather than giving single treatment advice. External validation of CDSSs should be prioritized.Patient or Public ContributionThis study did not involve patients or the public explicitly; however, the study design was informed by prior interviews with volunteers of a cancer patient advocacy group. The study objectives and data collection were supported by Dutch health care insurer CZ for a project titled ‘My Best Treatment’ that improves patient‐centeredness and the lung cancer patient pathway in the Netherlands.