Search

Background Adherence to ADHD medication is a complex phenomenon as the decision to adhere is influenced by a range of factors. To design tailored interventions to promote adherence, it is important to understand the factors that influence adherence in the context of its three phases: initiation, implementation and discontinuation. Objective The objective of this study was to explore the phase‐specific factors that influence adherence to medication in adults who have a diagnosis of ADHD. Methods Three focus groups (FGs) were conducted with twenty adults with ADHD in different metropolitan areas of Sydney, Australia. FGs were transcribed verbatim and thematically analysed. Results Participants’ decision to initiate medication (the initiation phase) was influenced by their perceived needs (desire to improve academic and social functioning) and concerns (fear of side‐effects) about medication following a similar process as defined by the Necessity‐Concerns Framework (NCF). The balance between benefits of medication (needs) and side‐effects (concerns) continued to determine participants’ daily medication‐taking (the implementation phase) and persistence (or discontinuation) with their medication. Forgetfulness and stigma were reported as concerns negatively impacting the implementation phase, while medication cost and dependence influenced the discontinuation phase of adherence. Conclusions Adults’ decision to initiate, continue or discontinue medication is influenced by a range of factors; some are unique to each phase while some are common across the phases. Participants balanced the needs for the medication against their concerns in determining whether to adhere to medication at each phase. It appears that the NCF has applicability when decision making about medication is explored at the three phases of adherence.

This paper explores the methodological aspects of a user‐led study investigating mental health service user experiences of targeted violence and abuse (often called 'hate crime'). 'Keeping Control' was a 16‐month qualitative study, undertaken in the context of adult safeguarding reforms in England. By collecting data on service user concepts and experiences, the research sought to address a gap in research and practice knowledge relating to targeted violence, abuse and hostility against people with mental health problems. In this paper, we discuss the significance of the design and methodology used for this study, with a particular focus on the interviews with service users. The research was both user‐led and carried out in collaboration with practitioners and academics, a form of research co‐production. Our aim is to inform researchers, practitioners and policymakers about the value of user leadership in co‐productive research with practitioners, particularly for a highly sensitive and potentially distressing topic.

BackgroundHistorically, safety mental health research has tended to focus on risks of homicide, suicide and deaths. Although wider safety issues are now recognized in regards to mental health services, the safety of mental health transitions, a key research and policy priority according to World Health Organisation, has not been explored.ObjectiveThe purpose of this study was to investigate perceptions of safety in mental health transitions (hospital to community) amongst five stakeholder groups.Design and settingAn online, international cross‐sectional, open‐ended questionnaire.ParticipantsThere were five stakeholder participant groups: service users; families/carers; mental health‐care professionals; researchers; and end users of research.ResultsNinety‐three participants from 12 different countries responded. Three overarching themes emerged: ‘individual/clinical’, ‘systems/services’ and ‘human, behavioural and social’ elements of safe mental health transitions. Whilst there was a great focus on clinical elements from researchers and healthcare professionals, service users and carers considered safety in terms of human, behavioural and social elements of transitional safety (ie loneliness, emotional readiness for discharge) and systems/services (ie inter‐professional communication).DiscussionSafety in mental health‐care transitions is perceived differently by service users and families compared to healthcare professionals and researchers. Traditional safety indicators for care transitions such as suicide, self‐harm and risk of adverse drug events are raised as important. However, service users and families in particular have a much wider perception of transitions safety.ConclusionFuture quality and safety research and policy should consider including a service user voice and consider integration of psychosocial elements in discharge interventions.

Background Individual patient data meta-analyses (IPD-MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD-MA have been published in recent years, but there is much variation in how these IPD-MA were performed. A number of existing methods were found, but there is no consensus as to which methods are preferred as the standard methods for statistical analysis in DTA IPD-MA. Objectives To create a web-based tool which integrates recommended statistical analyses for DTA IPD-MA, and allows researchers to analyse the data and visualize the results with interactive plots. Methods A systematic methodological review was performed to identify statistical analyses and data visualization methods used in DTA IPD-MA. Methods were evaluated by the authors and recommended analyses were integrated into the IPDmada tool which is freely available online with the user interface developed with R Shiny package. Results IPDmada allows users to upload their own data, perform the meta-analysis with both continuous and dichotomized tests, and incorporate individual level covariate-adjusted analysis. All tables and figures can be exported as .csv or .pdf files. A hypothetical dataset was used to illustrate the application of IPDmada. Conclusions IPDmada will be very helpful to researchers doing DTA IPD-MA, since it not only facilitates the statistical analysis but also provides a standard framework. The introduction of IPDmada will harmonize the methods used in DTA IPD-MA and ensure the quality of such analyses. Highlights IPDmada is a newly developed web-based tool for performing statistical analysis of individual patient data meta-analysis of diagnostic accuracy and visualizing the results. The tool is freely available to all the researchers, and requiring no installation of statistical software/packages. The tool has an user-friendly interface, and allows meta-analysis on both dichotomized and continuous test results. Researchers can easily use this tool to investigate the threshold effect and covariate effect on the summary accuracy. The introduction and implementation of IPDmada will serve as a useful tool for DTA IPD-MA and increase the quality of such studies.

Background Psychiatric rehospitalization is a complex phenomenon in need of more person-centred approaches. The current paper aimed to explore how community-based actions and daily life influence mental health and rehospitalization. Design, setting and participants The qualitative study included focus group data from six European countries including 59 participants. Data were thematically analysed following an inductive approach deriving themes and subthemes in relation to facilitators and barriers to mental health. Results Barriers consisted of subthemes (financial difficulty, challenging family circumstances and stigma), and facilitators consisted of three subthemes (complementing services, signposting and recovery). The recovery subtheme consisted of a further five categories (family and friends, work and recreation, hope, using mental health experience and meaning). Discussion Barriers to mental health largely related to social determinants of mental health, which may also have implications for psychiatric rehospitalization. Facilitators included community-based actions and aspects of daily life with ties to personal recovery. By articulating the value of these facilitators, we highlight benefits of a person-centred and recovery-focused approach also within the context of psychiatric rehospitalization. Conclusions This paper portrays how person-centred approaches and day-to-day community actions may impact psychiatric rehospitalization via barriers and facilitators, acknowledging the social determinants of mental health and personal recovery. Patient or public contribution The current study included participants with experience of psychiatric rehospitalization from six different European countries. Furthermore, transcripts were read by several of the focus group participants, and a service user representative participated in the entire research process in the original study.

Evidence-based decision-making is predicated on the ability of users to find and comprehend results from systematic review. Evidence producers have an obligation to support evidence users in this process. The Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) program-a producer of rigorous and comprehensive systematic reviews for two decades-has set a gold standard for reliability in health evidence reviews in the United States. It has recently begun a program of active support for evidence dissemination and uptake beyond mere publication of lengthy reports. This Brief Methods Note critiques the current paper-based format for systematic reviews and describes the development of a next generation (NxGen) AHRQ EPC Effective Health Care website. This redesigned platform will allow end-users of all types to find and share the evidence they need through data visualizations and other interactive displays. Several design principles guided the development of NxGen to make systematic review findings more accessible, customizable, adaptable, interactive, and shareable. NxGen will include visualizations for report results that are expressed as meta-analyses as well as those with narrative syntheses, through forest or bubble plots, respectively. Visual and interactive evidence heat maps are also planned. The NxGen version of the Effective Health Care website is planned to go live in the latter half of 2020 or early 2021.

Introduction Interrupted Time Series (ITS) studies may be used to assess the impact of an interruption, such as an intervention or exposure. The data from such studies are particularly amenable to visual display and, when clearly depicted, can readily show the short‐ and long‐term impact of an interruption. Further, well‐constructed graphs allow data to be extracted using digitizing software, which can facilitate their inclusion in systematic reviews and meta‐analyses. Aim We provide recommendations for graphing ITS data, examine the properties of plots presented in ITS studies, and provide examples employing our recommendations. Methods and results Graphing recommendations from seminal data visualization resources were adapted for use with ITS studies. The adapted recommendations cover plotting of data points, trend lines, interruptions, additional lines and general graph components. We assessed whether 217 graphs from recently published (2013‐2017) ITS studies met our recommendations and found that 130 graphs (60%) had clearly distinct data points, 100 (46%) had trend lines, and 161 (74%) had a clearly defined interruption. Accurate data extraction (requiring distinct points that align with axis tick marks and labels that allow the points to be interpreted) was possible in only 72 (33%) graphs. Conclusion We found that many ITS graphs did not meet our recommendations and could be improved with simple changes. Our proposed recommendations aim to achieve greater standardization and improvement in the display of ITS data, and facilitate re‐use of the data in systematic reviews and meta‐analyses., Highlights Application of data visualization recommendations can improve quality of interrupted time series graphs.Well‐designed graphs accurately depict time series data, any impact of the interruption, and the results of the analysis.Well‐designed graphs facilitate data extraction for use in systematic reviews and reproducibility.An assessment of graphs included in interrupted time series studies (published between 2013 and 2017) found that graphs often do not meet core graphing recommendations.

Objectives To describe and reflect on the methods and influence of involvement of young people with lived experience within a complex evidence synthesis. Study design and setting Linked syntheses of quantitative and qualitative systematic reviews of evidence about interventions to improve the mental health of children and young people (CYP) with long‐term physical conditions (LTCs). Methods Involvement was led by an experienced patient and public involvement in research lead. Young people with long‐term physical conditions and mental health issues were invited to join a study‐specific Children and Young People's Advisory Group (CYPAG). The CYPAG met face to face on four occasions during the project with individuals continuing to contribute to dissemination following report submission. Results Eight young people joined the CYPAG. Their views and experiences informed (a) a systematic review evaluating the effectiveness of interventions intended to improve the mental health of CYP with LTCs, (b) a systematic review exploring the experiences of interventions intended to improve the mental well‐being of CYP with LTCs and (c) an overarching synthesis. The CYPAG greatly contributed to the team's understanding and appreciation of the wider context of the research. The young people found the experience of involvement empowering and felt they would use the knowledge they had gained about the research process in the future. Conclusion Creating an environment that enabled meaningful engagement between the research team and the CYPAG had a beneficial influence on the young people themselves, as well as on the review process and the interpretation, presentation and dissemination of findings.

Background Deeply divided ideological positions challenge collaboration when engaging youth with mental disorders, caregivers and providers in mental health research. The integrative dynamics (ID) approach can restructure relationships and overcome ‘us vs them’ thinking. Objective To assess the extent to which an experience‐based co‐design (EBCD) approach to patient and family engagement in mental health research aligned with ID processes. Methods A retrospective case study of EBCD data in which transitional‐aged youth (n = 12), caregivers (n = 8) and providers (n = 10) co‐designed prototypes to improve transitions from child to adult services. Transcripts from focus groups and a co‐design event, co‐designed prototypes, the resulting model, evaluation interviews and author reflections were coded deductively based on core ID concepts, while allowing for emergent themes. Analysis was based on pattern matching. Triangulation across data sources, research team, and youth and caregiver reflections enhanced rigour. Findings The EBCD focus group discussions of touchpoints in experiences aligned with ID processes of acknowledging the past, by revealing the perceived identity mythos of each group, and allowing expression of and working through emotional pain. These ID processes were briefly revisited in the co‐design event, where the focus was on the remaining ID processes: building cross‐cutting connections and reconfiguring relationships. The staged EBCD approach may facilitate ID, by working within one's own perspective prior to all perspectives working together in co‐design. Conclusion Researchers can augment patient engagement approaches by applying ID principles with staged integration of groups to improve relations in mental health systems, and EBCD shows promise to operationalize this.

Background: There is limited evidence of genuine equal partnership where power is shared with young people with mental health difficulties throughout all research stages, particularly in data collection and analysis.\ud Objective: To describe how our qualitative study, exploring young peoples’ perceptions on the feasibility of using technology to detect mental health deterioration, was co- produced using principles of co-production, whilst reflecting on impact, challenges and recommendations.\ud Methods: Young people with experience of mental health difficulties were appointed and then worked with researchers throughout all research stages. The study was evaluated against the five principles of co-production. Reflections from researchers and young people were collected throughout.\ud Results: Seven young people formed an initial Young People's Advisory Group (YPAG); three became co-researchers. Reflection was key throughout the process. Sharing power became easier and more evident as trust, confidence and mutual re- spect grew over time, particularly after a safe space was established. The safe space was crucial for open discussions, and our WhatsApp group enabled continual com- munication, support and shared decision-making. The resulting co-produced topic guide, coding framework, thematic map, papers and presentations demonstrated significant impact.\ud Conclusions: To our knowledge, this is the first qualitative mental health study to be co-produced using the principles of co-production. Our rigorous assessment can be utilized as an informative document to help others to produce meaningful co- produced future research. Although co-production takes time, it makes significant impact to the research, researchers and co-researchers. Flexible funding for spon- taneous suggestions from co-researchers and more time for interview training is recommended.

Background Patient and public involvement (PPI) is increasingly required in mental health services research. To empower patients to actively address depression, the GET.FEEDBACK.GP study evaluates a patient-targeted feedback intervention after depression screening using the Patient Health Questionnaire (PHQ-9). Objective To refine the patient-targeted feedback from a previous study within a participatory research team (PRT) by conducting workshops to investigate patients' needs and preferences for feedback. To evaluate the process and outcome of PPI. Design Patient and public involvement was carried out on the levels of collaboration and consultation. A PRT of patient partners and researchers planned and conducted three workshops with patients. Patients' needs were investigated using a focus group. Participants prioritized needs, discussed feedback drafts and evaluated two drafts using cognitive debriefings. Researchers of the PRT communicated the results at project level. PPI was evaluated using the Public and Patient Engagement Evaluation Tools (PPEET). Setting and participants A purposeful sampling of N = 12 patients with experiences of depression participated in at least one workshop. Results Relevant content-related needs about feedback (eg no distinction between severe and moderate symptoms), recommendations for action and patient-relevant information were considered. Needs for comprehensible, valuing, nonstigmatizing language and design elements (eg dimensional bar) were implemented. Workshops and PRT were positively evaluated. Discussion and conclusions Patient and public involvement influenced the content, wording and design of the feedback. Strengths include two levels of PPI, methodical diversity and purposeful sampling. Limitations include the lack of inclusion of patients who are unaware of their depression. The evaluated PPI concept can be useful for future studies.

Aim The aim of the study was to assess the influence of the number of hours of daily nursing care for NHPPD in medical departments on missed care and the correlation between NHPPD and in-hospital mortality. Background Patient mortality can be a consequence of missed care as it correlates with the nurse-patient ratio. One of the methods to measure missed care is the Nursing Hours per Patient Day rating. Methods The study sample included 44,809 patients including 971 deaths in 8 wards. The influence of nursing hours, nursing education, and the percentage of patients' classification on in-hospital mortality were evaluated with backward stepwise linear regression. Results One hour added to the average NHPPD in medical departments was related to a decrease in mortality rate by 6.8 per 1,000 patient days and a lower chance for the emergence of unplanned death by 36%. Conclusions The number of NHPPD and the percentage of professional nurses are factors influencing missed care and in-hospital mortality. Implications for nursing management The severe consequences of missed care, that is mortality, and the correlation between in-hospital mortality, nursing education and nursing-patient ratio, which are indicators of care quality, are arguments for maintaining adequate staffing levels to avoid missed care.

Latinos in the United States represent a disproportionate burden of illness and disease and face barriers to accessing health care and related resources. Culturally tailored, evidence‐based interventions hold promise in addressing many of these challenges. Yet, ensuring patient voice is vital in the successful development and implementation of such interventions. Thus, this paper examines the application of analytic hierarchy process (AHP) to inform the augmentation and implementation of an evidence‐based chronic disease self‐management programme for underserved Latinos living with both minor depression and chronic illness. The process of AHP allows for direct input from the individuals that would utilize such a programme, including afflicted individuals, their family members and the health educators/promotores that would be responsible for implementation. Specifically, 45 participants, including 15 individuals with chronic disease, 15 family members/caregivers and 15 promotores, partook in the Stakeholder Values Questionnaire, which elicited preferences and values regarding major goals, processes and content for the intervention. AHP was employed to analyse pairwise comparison ratings and to determine differences and similarities across stakeholder groups. This analytical technique allowed for the adaptation of the EBI to stakeholders' specific priorities and preferences and facilitated complex decision‐making. Findings not only shed light on similarities and differences between stakeholder groups, but also the magnitude of these priorities and preferences and allowed the intervention to be driven by the participants, themselves. Applying AHP was a unique opportunity to optimize the decision‐making process to inform cultural adaptation of an EBI while considering multiple viewpoints systematically.

Background A new diagnosis of complex post-traumatic stress disorder, CPTSD, has been agreed by the World Health Organization, WHO, and evidence is needed for what psychological treatment might be effective, particularly from those with experience of the disorder. We used a novel participatory approach to explore patient views and simultaneously studied the impact on the patient researchers of the research process itself. In this paper, we report on the latter section of the study how the involvement in research of patients with CPTSD affected their mental health. Symptoms of CPTSD may include emotional dysregulation, feelings of self-worthlessness and difficulties in relationships. Objective The aim of this study section was to explore whether patients' mental health could be promoted through empowering them to participate in research on CPTSD. Design The study had a qualitative, participatory design. The clinician who led the research (first author) held group meetings with patient researchers to explore the impact of the research process. The clinician also kept notes on the process in a reflective log. Setting and participants Six patient researchers participated in research with other patients with lived experience of CPTSD in an NHS outpatient unit in a London hospital. Intervention studied The research process itself was analysed in group meetings with researchers which the clinician recorded and transcribed. Findings Participation in research may promote increased self-confidence and social inclusion for those with CPTSD. Conclusion Involvement in research may be seen as an empowering intervention because patients felt it contributed to recovery.

Fragmentation of processes and interventions plague the psychotherapies (Gilbert & Kirby, 2019). Part of the problem is that we have not agreed on a framework that could be the basis for integrating knowledge and the scientific enquiry of processes and interventions. This paper outlines an approach that brings together a variety of different disciplines in the service of consilience (Wilson, 1998, Consilience: The unity of knowledge, Vintage, New York, NY; Siegel, 2019). It presents the importance of an evolutionary framework for understanding the proclivities and dispositions for mental suffering and antisocial behaviour, and how they are choreographed in different sociodevelopmental contexts. Building on earlier models (Gilbert, 1989, Human nature and suffering, Routledge, London, UK; Gilbert, 1995, Clin. Psychol. Psychother., 2, 135; Gilbert, 1998, Br. J. Med. Psychol., 71, 353; Gilbert, 2016, Case formulation in cognitive behaviour therapy: The treatment of challenging cases, Wiley, Chichester, UK, pp. 50–89) the call is for an integrative, evolutionary, contextual, biopsychosocial approach to psychology and psychotherapy. Practitioner points Evolutionary functional analysis is part of an evolutionary, contextual, biopsychosocial approach to mental health that can serve as a scientific platform for the future developments of psychotherapy.Therapist skills and training will increasing need to focus on the multidimensional textures of mental states especially the context‐social‐body linkages.Therapies of the future will also focus more on the moral aspects of therapy and address the need to promote prosocial and ethical behaviour to self and others.

Network meta-analysis (NMA) can be used to compare multiple competing treatments for the same disease. In practice, usually a range of outcomes is of interest. As the number of outcomes increases, summarizing results from multiple NMAs becomes a nontrivial task, especially for larger networks. Moreover, NMAs provide results in terms of relative effect measures that can be difficult to interpret and apply in every-day clinical practice, such as the odds ratios. In this article, we aim to facilitate the clinical decision-making process by proposing a new graphical tool, the Kilim plot, for presenting results from NMA on multiple outcomes. Our plot compactly summarizes results on all treatments and all outcomes; it provides information regarding the strength of the statistical evidence of treatment effects, while it illustrates absolute, rather than relative, effects of interventions. Moreover, it can be easily modified to include considerations regarding clinically important effects. To showcase our method, we use data from a network of studies in antidepressants. All analyses are performed in R and we provide the source code needed to produce the Kilim plot, as well as an interactive web application.

It is often challenging to present the available evidence in a timely and comprehensible manner. We aimed to visualize the evolution of evidence about antidepressants for depression by conducting cumulative network meta-analyses (NMAs) and to examine whether it could have helped the selection of optimal drugs. We built a Shiny web application that performs and presents cumulative NMAs based on R netmeta. We used a comprehensive dataset of double-blind randomized controlled trials of 21 antidepressants in the acute treatment of major depression. The primary outcomes were efficacy (treatment response) and acceptability (all-cause discontinuation), and treatment effects were summarized via odds ratios. We evaluated the confidence in evidence using the CINeMA (Confidence in Network Meta-Analysis) framework for a series of consecutive NMAs. Users can change several conditions for the analysis, such as the period of synthesis, among the others. We present the league tables and two-dimensional plots that combine efficacy, acceptability and level of confidence in the evidence together, for NMAs conducted in 1990, 1995, 2000, 2005, 2010, and 2016. They reveal that through the past four decades, newly approved drugs often showed initially exaggerated results, which tended to diminish and stabilize after approximately a decade. Over the years, the drugs with relative superiority changed dramatically; but as the evidence network grew larger and better connected, the overall confidence improved. The Shiny app visualizes how evidence evolved over years, emphasizing the need for a careful interpretation of relative effects between drugs, especially for the potentially amplified performance of newly approved drugs. HIGHLIGHTS: Network meta-analysis is considered to be a proper way of demonstrating the available evidence, since it allows comparisons between multiple interventions, and has been proved to be statistically powerful. It is challenging to present the voluminous results of NMA in an efficient and comprehendible manner. Evidence evolution based on the relatively new method NMA has not been investigated yet. The results of NMA should not only include the effects but also the confidence in the evidence, which can help interpret the findings appropriately. Effective use of rapidly developing statistical analysis and presentation tools such as Shiny package in R, may facilitate and simplify the visualization of NMA output. We should stay conservative towards new drugs, as their performance was often shown to be exaggerated initially, and it took time to become stable.

Purpose: The implementation of photon-counting detectors is widely expected to be the next breakthrough in X-ray computed tomography (CT) instrumentation. A small number of prototype scanners equipped with direct-conversion detectors based on room-temperature semiconductors, such as CdTe and CdZnTe (CZT), are currently installed at medical centers. Here, we investigate the feasibility of using silicon photomultiplier (SiPM)-based scintillation detectors in photon-counting computed tomography (PCCT) scanners, as a potential alternative to CdTe and CZT detectors. Methods: We introduce a model that allows us to compute the expected energy resolution as well as the expected pulse shape and associated rate capability of SiPM-based PCCT detectors. The model takes into account SiPM saturation and optical crosstalk, because these phenomena may substantially affect the performance of SiPM-based PCCT detectors with sub-mm pixels. We present model validation experiments using a single-pixel detector consisting of a 0.9 × 0.9 × 1.0 mm3 LuAP:Ce scintillation crystal coupled to a 1 × 1 mm2 SiPM. We subsequently use the validated model to compute the expected performance of the fast scintillators LYSO:Ce, LuAP:Ce, and LaBr3:Ce, coupled to currently available SiPMs, as well as to a more advanced SiPM prototype with improved dynamic range, for sub-mm pixel sizes. Results: The model was found to be in good agreement with the validation experiments, both with respect to energy resolution and pulse shape. It shows how saturation progressively degrades the energy resolution of detectors equipped with currently available SiPMs as the pixel size decreases. Moreover, the expected pulse duration is relatively long (~200 ns) with these SiPMs. However, when LuAP:Ce and LaBr3:Ce are coupled to the more advanced SiPM prototype, the pulse duration improves to less than 60 ns, which is in the same order of magnitude as pulses from CdTe and CZT detectors. It follows that sufficient rate capability can be achieved with pixel sizes of 400 μm or smaller. Moreover, LaBr3:Ce detectors can provide an energy resolution of 11.5%-13.5% at 60 keV, comparable to CdTe and CZT detectors. Conclusions: This work provides first evidence that it may be feasible to develop SiPM-based scintillation detectors for PCCT that can compete with CdTe and CZT detectors in terms of energy resolution and rate capability.

Effect direction (evidence to indicate improvement, deterioration, or no change in an outcome) can be used as a standardized metric which enables the synthesis of diverse effect measures in systematic reviews. The effect direction (ED) plot was developed to support the synthesis and visualization of effect direction data. Methods for the ED plot require updating in light of new Cochrane guidance on alternative synthesis methods. To update the ED plot, statistical significance was removed from the algorithm for within-study synthesis and use of a sign test was considered to examine whether patterns of ED across studies could be due to chance alone. The revised methods were applied to an existing Cochrane review of the health impacts of housing improvements. The revised ED plot provides a method of data visualization in synthesis without meta-analysis that incorporates information about study characteristics and study quality, using ED as a common metric, without relying on statistical significance to combine outcomes of single studies. The results of sign tests, when appropriate, suggest caution in over-interpreting apparent patterns in effect direction, especially when the number of included studies is small. The revised ED plot meets the need for alternative methods of synthesis and data visualization when meta-analysis is not possible, enabling a transparent link between the data and conclusions of a systematic review. ED plots may be particularly useful in reviews that incorporate nonrandomized studies, complex systems approaches, and diverse sources of evidence, due to the variety of study designs and outcomes in such reviews.

Most studies aiming to construct reference or standard charts use a cross‐sectional design, collecting one measurement per participant. Reference or standard charts can also be constructed using a longitudinal design, collecting multiple measurements per participant. The choice of appropriate statistical methodology is important as inaccurate centiles resulting from inferior methods can lead to incorrect judgements about fetal or newborn size, resulting in suboptimal clinical care. Reference or standard centiles should ideally provide the best fit to the data, change smoothly with age (eg, gestational age), use as simple a statistical model as possible without compromising model fit, and allow the computation of Z‐scores from centiles to simplify assessment of individuals and enable comparison with different populations. Significance testing and goodness‐of‐fit statistics are usually used to discriminate between models. However, these methods tend not to be useful when examining large data sets as very small differences are statistically significant even if the models are indistinguishable on actual centile plots. Choosing the best model from amongst many is therefore not trivial. Model choice should not be based on statistical considerations (or tests) alone as sometimes the best model may not necessarily offer the best fit to the raw data across gestational age. In this paper, we describe the most commonly applied methodologies available for the construction of age‐specific reference or standard centiles for cross‐sectional and longitudinal data: Fractional polynomial regression, LMS, LMST, LMSP, and multilevel regression methods. For illustration, we used data from the INTERGROWTH‐21st Project, ie, newborn weight (cross‐sectional) and fetal head circumference (longitudinal) data as examples.

This paper discusses the features of study design and methodological considerations for constructing reference centile charts for attained size, growth, and velocity charts with a focus on human growth charts used during pregnancy. Recent systematic reviews of pregnancy dating, fetal size, and newborn size charts showed that many studies aimed at constructing charts are still conducted poorly. Important design features such as inclusion and exclusion criteria, ultrasound quality control measures, sample size determination, anthropometric evaluation, gestational age estimation, assessment of outliers, and chart presentation are seldom well addressed, considered, or reported. Many of these charts are in clinical use today and directly affect the identification of at‐risk newborns that require treatment and nutritional strategies. This paper therefore reiterates some of the concepts previously identified as important for growth studies, focusing on considerations and concepts related to study design, sample size, and methodological considerations with an aim of obtaining valid reference or standard centile charts. We discuss some of the key issues and provide more details and practical examples based on our experiences from the INTERGROWTH‐21st Project. We discuss the statistical methodology and analyses for cross‐sectional studies and longitudinal studies in a separate article in this issue.

Background The prevalence of neuropsychiatric symptoms (NPS) diminishes the quality of life and increases the care burden in patients with dementia. Despite the clinical importance of dementia-associated NPS, no protocols for treating NPS are already well established. Attention has turned to the effectiveness of nonpharmacological treatments for NPS since their potential safe alternative to pharmacotherapy. Objective This study is aimed to compare the effects in older individuals with dementia living in a residential care, of two intervention programs, the gesture-verbal treatment (GVT), a treatment implemented by us on a previous method for word retrieval in individuals with aphasia, and the better-known doll therapy (DT). The GVT would act on both receptive and expressive language skills, the DT on attachment and emotional connections. Methods We evaluated NPS by the neuropsychiatric inventory in a total of 30 patients divided into 3 groups, the GVT, the DT, and control groups, using a pre-post design. The treatment groups completed 12-week nonpharmacological interventions in addition to standard rehabilitative therapies, while the control group participated only in standard rehabilitative therapies. Results The DT group showed significant improvements in agitation, irritability, apathy, depression, and delusions relative to controls. The GVT group showed significant improvements in apathy and depression with respect to controls. The DT intervention ameliorated symptoms of agitation compared to the GVT intervention whereas the GVT intervention improved apathy compared to the DT intervention. Conclusion Improved understanding of the potential therapeutic benefits of different treatments for neuropsychiatric symptoms is crucial for establishing nonpharmacological interventions in dementia.

A common challenge for the development of drugs in rare diseases and special populations, eg, paediatrics, is the small numbers of patients that can be recruited into clinical trials. Extrapolation can be used to support development and licensing in paediatrics through the structured integration of available data in adults and prospectively generated data in paediatrics to derive conclusions that support licensing decisions in the target paediatric population. In this context, Bayesian analyses have been proposed to obtain formal proof of efficacy of a new drug or therapeutic principle by using additional information (data, opinion, or expectation), expressed through a prior distribution. However, little is said about the impact of the prior assumptions on the evaluation of outcome and prespecified strategies for decision-making as required in the regulatory context. On the basis of examples, we explore the use of data-based Bayesian meta-analytic-predictive methods and compare these approaches with common frequentist and Bayesian meta-analysis models. Noninformative efficacy prior distributions usually do not change the conclusions irrespective of the chosen analysis method. However, if heterogeneity is considered, conclusions are highly dependent on the heterogeneity prior. When using informative efficacy priors based on previous study data in combination with heterogeneity priors, these may completely determine conclusions irrespective of the data generated in the target population. Thus, it is important to understand the impact of the prior assumptions and ensure that prospective trial data in the target population have an appropriate chance, to change prior belief to avoid trivial and potentially erroneous conclusions.

Aim To compare the patient acuity, nurse staffing and workforce, missed nursing care and patient outcomes among hospital unit-clusters. Background Relationships among acuity, nurse staffing and workforce, missed nursing care and patient outcomes are not completely understood. Method Descriptive design with data from four unit-clusters: medical, surgical, combined and step-down units. Descriptive statistics were used to compare acuity, nurse staffing coverage, education and expertise, missed nursing care and selected nurse-sensitive outcomes. Results Patient acuity in general (medical, surgical and combined) floors is similar to step-down units, with an average of 5.6 required RN hours per patient day. In general wards, available RN hours per patient day reach only 50% of required RN hours to meet patient needs. Workforce measures are comparable among unit-clusters, and average missed nursing care is 21%. Patient outcomes vary among unit-clusters. Conclusion Patient acuity is similar among unit-clusters, while nurse staffing coverage is halved in general wards. While RN education, expertise and missed care are comparable among unit-clusters, mortality, skin injuries and risk of family compassion fatigue rates are higher in general wards. Implications for nursing management Nurse managers play a pivotal role in hustling policymakers to address structural understaffing in general wards, to maximize patient safety outcomes.

Background: Patient and public involvement (PPI) is becoming more commonplace in mental health research. There are strong moral and ethical arguments for good quality PPI. Few studies have documented and evaluated PPI in self-harm and suicide research. Inconsistent reporting of PPI makes it difficult to discern practices that deliver quality, effective and meaningful involvement. It is important to understand and address emotional support needs of PPI members contributing to sensitive topics such as suicide and self-harm. Therefore, this study will examine the effect of PPI on self-harm and suicide research and explore patients', carers' and researchers' experiences and views in relation to the quality of PPI practice and provision of appropriate support for PPI members. Methods: This protocol outlines the longitudinal, mixed methodological approach that will be taken. Qualitative and quantitative data will be collected via baseline and repeated questionnaires, document review and semi-structured interviews. Both PPI members and researchers will be invited to participate in this study. The two-year data collection period will enable evaluation of PPI throughout the entire research cycle. An integrated approach will be taken to data analysis, using inductive thematic analysis and descriptive and repeated measures analyses, to address specified study aims. Dissemination: Findings from this study will inform practical guidance to support self-harm and suicide researchers in effectively involving people with experiential knowledge in their research. Analyses will offer insight into the effect of PPI throughout the research process and assess changes in PPI members' and researchers' experiences of involvement across a two-year period.

Objective In contrast to research agendas being predominantly set by scientists or funders, a collaborative approach was used to spot future goals for research on obsessive‐compulsive disorder. Methods First, we conducted a meta‐review and then compared the results of two online surveys with OCD professionals and patients on research priorities. The literature search was performed in three comprehensive databases, and ten research goals were extracted. Sixty‐four patients and eight professionals responded to open questions on their five most important goals. Then, they ranked the ten aims extracted from the literature on a 6‐point Likert scale. Results For patients and professionals, research on treatment gains that persist long‐term was most important. Concerning the top five goals listed in an open format, for patients, development and maintenance of the disease was as important as psychotherapy and its efficacy. In contrast, for professionals, the efficacy and the optimization of psychotherapy were the far most important research goals. Conclusions We proposed one possibility to involve patients in OCD research, and the multitude of answers presents a wealth of research ideas. Practice Implications Since consistent research involvement may contribute to its clinical impact, researchers are now invited to translate our findings into empirical studies.

Background Mental health carers contribute a unique set of perspectives and lived experiences to research; however, national research ethics guidelines do not specifically address the issues that affect informal carers as participants. Objective This study sought to explore Australian mental health consumer and carer views on the ethical conduct of research involving mental health carers. Design A public forum (n = 14; consumer = 5, carer = 9) and a subsequent series of interviews (n = 10; consumer = 5, carer = 4, both = 1) were conducted to investigate consumer and carer views on mental health research ethics. Data collection and analysis drew strongly on methodological features of grounded theory. Results Conducting research involving carers and consumer‐carer relationships raises potential concerns related to story ownership. Lived experience stories have shared and separate elements; thus, it is important to consider potential risks to the privacy of non‐participants and of social harm to participants' relationships when conducting research in this space. These risks could be minimized and managed through communication between researchers and participants, and within relationships. Conclusions When conducting research involving carers and consumer‐carer relationships, researchers may need to facilitate the negotiation of information‐sharing boundaries within relationships and the safe and confidential telling of shared stories.

Background: Great advancements have been made in patient and public involvement (PPI), including the development of guidance on how to conduct, report and evaluate PPI. Despite these efforts, the evidence base remains relatively weak. A substantive methodological development is required. This is particularly important for vulnerable groups within society, for whom PPI can be challenging but has the potential to play a transformative role in shaping research. Objectives: To describe the group dynamic characteristics and immediate impact of PPI from the user representatives’ perspective in a case study of refugee involvement in the development of mental health intervention research. To pilot and methodologically appraise the Active Involvement of Users in Research Observation Schedule and Questionnaire. Design: The Active Involvement of Users in Research Observation Schedule and Questionnaire were administered together with a focus group discussion. Setting: ‘Refugee Advisors’ were involved in the development of a randomized con‐ trolled trial protocol evaluating a brief group intervention for refugee children expe‐ riencing symptoms of post‐traumatic stress in Sweden. Results: The multi‐method approach demonstrated good feasibility. There were clear examples of how the advisors influenced research development. The advisors described a perceived impact on the research, equality and acceptance, and knowledge gain. A sense of appreciation and empowerment was also interpreted. However, potential issues relating to the relevance of contributions and use of an interpreter were identified. Discussion and conclusion: The methodological approach piloted in this study offers a promising, rigorous way to evaluate PPI. The research tools require further refinement and validation.

The analysis of adverse events plays an important role in the benefit assessment of drugs. Consequently, results on adverse events are an integral part of reimbursement dossiers submitted by pharmaceutical companies to health policy decision-makers. Methods applied in the analysis of adverse events commonly include simple standard methods for contingency tables. However, the results produced may be misleading if observations are censored at the time of discontinuation due to treatment switching or noncompliance, resulting in unequal follow-up periods. In this paper, we present examples to show that the application of inadequate methods for the analysis of adverse events in the reimbursement dossier can lead to a downgrading of the evidence on a drug's benefit in the subsequent assessment, as greater harm from the drug cannot be excluded with sufficient certainty. Legal regulations on the benefit assessment of drugs in Germany are presented, in particular, with regard to the analysis of adverse events. Differences in safety considerations between the drug approval process and the benefit assessment are discussed. We show that the naive application of simple proportions in reimbursement dossiers frequently leads to uninterpretable results if observations are censored and the average follow-up periods differ between treatment groups. Likewise, the application of incidence rates may be misleading in the case of recurrent events and unequal follow-up periods. To allow for an appropriate benefit assessment of drugs, adequate survival time methods accounting for time dependencies and duration of follow-up are required, not only for time-to-event efficacy endpoints but also for adverse events. © 2016 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd.

Marine pollution is ubiquitous, and is one of the key factors influencing contemporary marine biodiversity worldwide. To protect marine biodiversity, how do we surveil, document and predict the short- and long-term impacts of pollutants on at-risk species? Modern genomics tools offer high-throughput, information-rich and increasingly cost-effective approaches for characterizing biological responses to environmental stress, and are important tools within an increasing sophisticated kit for surveiling and assessing impacts of pollutants on marine species. Through the lens of recent research in marine killifish, we illustrate how genomics tools may be useful for screening chemicals and pollutants for biological activity and to reveal specific mechanisms of action. The high dimensionality of transcriptomic responses enables their usage as highly specific fingerprints of exposure, and these fingerprints can be used to diagnose environmental problems. We also emphasize that molecular pathways recruited to respond at physiological timescales are the same pathways that may be targets for natural selection during chronic exposure to pollutants. Gene complement and sequence variation in those pathways can be related to variation in sensitivity to environmental pollutants within and among species. Furthermore, allelic variation associated with evolved tolerance in those pathways could be tracked to estimate the pace of environmental health decline and recovery. We finish by integrating these paradigms into a vision of how genomics approaches could anchor a modernized framework for advancing the predictive capacity of environmental and ecotoxicological science.

A now common goal in medical research is to investigate the inter‐relationships between a repeatedly measured biomarker, measured with error, and the time to an event of interest. This form of question can be tackled with a joint longitudinal‐survival model, with the most common approach combining a longitudinal mixed effects model with a proportional hazards survival model, where the models are linked through shared random effects. In this article, we look at incorporating delayed entry (left truncation), which has received relatively little attention. The extension to delayed entry requires a second set of numerical integration, beyond that required in a standard joint model. We therefore implement two sets of fully adaptive Gauss–Hermite quadrature with nested Gauss–Kronrod quadrature (to allow time‐dependent association structures), conducted simultaneously, to evaluate the likelihood. We evaluate fully adaptive quadrature compared with previously proposed non‐adaptive quadrature through a simulation study, showing substantial improvements, both in terms of minimising bias and reducing computation time. We further investigate, through simulation, the consequences of misspecifying the longitudinal trajectory and its impact on estimates of association. Our scenarios showed the current value association structure to be very robust, compared with the rate of change that we found to be highly sensitive showing that assuming a simpler trend when the truth is more complex can lead to substantial bias. With emphasis on flexible parametric approaches, we generalise previous models by proposing the use of polynomials or splines to capture the longitudinal trend and restricted cubic splines to model the baseline log hazard function. The methods are illustrated on a dataset of breast cancer patients, modelling mammographic density jointly with survival, where we show how to incorporate density measurements prior to the at‐risk period, to make use of all the available information. User‐friendly Stata software is provided. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Risk prediction models are used to predict a clinical outcome for patients using a set of predictors. We focus on predicting low‐dimensional binary outcomes typically arising in epidemiology, health services and public health research where logistic regression is commonly used. When the number of events is small compared with the number of regression coefficients, model overfitting can be a serious problem. An overfitted model tends to demonstrate poor predictive accuracy when applied to new data. We review frequentist and Bayesian shrinkage methods that may alleviate overfitting by shrinking the regression coefficients towards zero (some methods can also provide more parsimonious models by omitting some predictors). We evaluated their predictive performance in comparison with maximum likelihood estimation using real and simulated data. The simulation study showed that maximum likelihood estimation tends to produce overfitted models with poor predictive performance in scenarios with few events, and penalised methods can offer improvement. Ridge regression performed well, except in scenarios with many noise predictors. Lasso performed better than ridge in scenarios with many noise predictors and worse in the presence of correlated predictors. Elastic net, a hybrid of the two, performed well in all scenarios. Adaptive lasso and smoothly clipped absolute deviation performed best in scenarios with many noise predictors; in other scenarios, their performance was inferior to that of ridge and lasso. Bayesian approaches performed well when the hyperparameters for the priors were chosen carefully. Their use may aid variable selection, and they can be easily extended to clustered‐data settings and to incorporate external information. © 2015 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd.

Various sources of variation in observed response in clinical trials and clinical practice are considered, and ways in which the corresponding components of variation might be estimated are discussed. Although the issues have been generally well‐covered in the statistical literature, they seem to be poorly understood in the medical literature and even the statistical literature occasionally shows some confusion. To increase understanding and communication, some simple graphical approaches to illustrating issues are proposed. It is also suggested that reducing variation in medical practice might make as big a contribution to improving health outcome as personalising its delivery according to the patient. It is concluded that the common belief that there is a strong personal element in response to treatment is not based on sound statistical evidence. © 2015 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Objective: To evaluate and validate the time of completion and results of a new method of searching for systematic reviews, the exhaustive search method (ESM), using a pragmatic comparison. Methods: Single-line search strategies were prepared in a text document. Term completeness was ensured with a novel optimization technique. Macros in MS Word converted the syntaxes between databases and interfaces almost automatically. We compared search characteristics, such as number of search terms and databases, and outcomes, such as number of included and retrieved references and precision, from ESM searches and other Dutch academic hospitals identified by searching PubMed for systematic reviews published between 2014 and 2016. We compared time to perform the ESM with a secondary comparator of recorded search times from published literature and contact with authors to acquire unpublished data. Results: We identified 73 published Erasmus MC systematic reviews and 258 published by other Dutch academic hospitals meeting our criteria. We pooled search time data from 204 other systematic reviews. The ESM searches differed by using 2 times more databases, retrieving 44% more references, including 20% more studies in the final systematic review, but the time needed for the search was 8% of that of the control group. Similarities between methods include precision and the number of search terms. Conclusions: The evaluated similarities and differences suggest that the ESM is a highly efficient way to locate more references meeting the specified selection criteria in systematic reviews than traditional search methods. Further prospective research is required.

Clustered data are common in medical research. Typically, one is interested in a regression model for the association between an outcome and covariates. Two complications that can arise when analysing clustered data are informative cluster size (ICS) and confounding by cluster (CBC). ICS and CBC mean that the outcome of a member given its covariates is associated with, respectively, the number of members in the cluster and the covariate values of other members in the cluster. Standard generalised linear mixed models for cluster-specific inference and standard generalised estimating equations for population-average inference assume, in general, the absence of ICS and CBC. Modifications of these approaches have been proposed to account for CBC or ICS. This article is a review of these methods. We express their assumptions in a common format, thus providing greater clarity about the assumptions that methods proposed for handling CBC make about ICS and vice versa, and about when different methods can be used in practice. We report relative efficiencies of methods where available, describe how methods are related, identify a previously unreported equivalence between two key methods, and propose some simple additional methods. Unnecessarily using a method that allows for ICS/CBC has an efficiency cost when ICS and CBC are absent. We review tools for identifying ICS/CBC. A strategy for analysis when CBC and ICS are suspected is demonstrated by examining the association between socio-economic deprivation and preterm neonatal death in Scotland.

This article is about the recognition of personhood when death occurs in early life. Drawing from anthropological perspectives on personhood at the beginnings and ends of life, it examines the implications of competing religious and customary definitions of personhood for a small sample of young British Pakistani Muslim women who experienced miscarriage and stillbirth. It suggests that these women's concerns about the lack of recognition given to the personhood of their fetus or baby constitute a challenge to customary practices surrounding burial as a Muslim. The article suggests that these women's concerns cannot be adequately glossed as a clash of Islamic belief versus Western medicine. Rather, they represent a renegotiation of Islamic opinion and customary practices within the broader context of changes in the medical and social norms surrounding pregnancy loss and infant death in multi-ethnic British society.

Jürgen Habermas is regarded as a central bioconservative commentator in the debate on the ethics of human prenatal genetic manipulations. While his main work on this topic, The Future of Human Nature, has been widely examined in regard to his position on prenatal genetic enhancement, his arguments regarding prenatal genetic therapeutic interventions have for the most part been overlooked. In this work I do two things. First, I present the three necessary conditions that Habermas establishes for a prenatal genetic manipulation to be regarded as morally permissible. Second, I examine if mitochondrial replacement techniques meet these necessary conditions. I investigate, specifically, the moral permissibility of employing pronuclear transfer and maternal spindle transfer. I conclude that, according to a Habermasian perspective on prenatal genetic manipulation, maternal spindle transfer (without using a preselected sperm and egg) and pronuclear transfer are morally impermissible. Maternal spindle transfer is, in principle, morally permissible, but only when we have beforehand preselected a sperm and an egg for our reproductive purpose. These findings are relevant for bioconservatives, both for those who hold a Habermasian stance and for those who hold something akin to a Habermasian stance, because they answer the question: what should bioconservatives do regarding mitochondrial replacement techniques? In fact, the answer to this question does not only normatively prescribe what bioconservatives should do in terms of their personal morality, but it also points towards what kind of legislation regulating mitochondrial replacement techniques they should aim at.

A number of meta‐analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta‐analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta‐analytic framework, the between‐study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between‐study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between‐study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual‐level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030–3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level. Copyright © 2012 John Wiley & Sons, Ltd.

Occasionally, things go so wrong in a clinical trial that a change must be made. For example, the originally planned primary outcome may be measured completely unreliably. Is there any recourse? One may still be able to salvage the trial using a permutation test if a change is made before breaking the treatment blind. The solution is not a panacea; we discuss the limitations and legitimate grounds for criticism. Still, when it is needed, the procedure is preferable to rigid adherence to a design that makes no sense. Published 2012. This article is a US Government work and is in the public domain in the USA.

Network meta-analysis (multiple treatments meta-analysis, mixed treatment comparisons) attempts to make the best use of a set of studies comparing more than two treatments. However, it is important to assess whether a body of evidence is consistent or inconsistent. Previous work on models for network meta-analysis that allow for heterogeneity between studies has either been restricted to two-arm trials or followed a Bayesian framework. We propose two new frequentist ways to estimate consistency and inconsistency models by expressing them as multivariate random-effects meta-regressions, which can be implemented in some standard software packages. We illustrate the approach using the mvmeta package in Stata. Copyright © 2012 John Wiley & Sons, Ltd.

This article reviews recent advances in ‘microbiome studies’: molecular, statistical and graphical techniques to explore and quantify how microbial organisms affect our environments and ourselves given recent increases in sequencing technology. Microbiome studies are moving beyond mere inventories of specific ecosystems to quantifications of community diversity and descriptions of their ecological function. We review the last 24 months of progress in this sort of research, and anticipate where the next 2 years will take us. We hope that bioinformaticians will find this a helpful springboard for new collaborations with microbiologists.

One of the main motivations to study amphioxus is its potential for understanding the last common ancestor of chordates, which notably gave rise to the vertebrates. An important feature in this respect is the slow evolutionary rate that seems to have characterized the cephalochordate lineage, making amphioxus an interesting proxy for the chordate ancestor, as well as a key lineage to include in comparative studies. Whereas slow evolution was first noticed at the phenotypic level, it has also been described at the genomic level. Here, we examine whether the amphioxus genome is indeed a good proxy for the genome of the chordate ancestor, with a focus on protein-coding genes. We investigate genome features, such as synteny, gene duplication and gene loss, and contrast the amphioxus genome with those of other deuterostomes that are used in comparative studies, such as Ciona, Oikopleura and urchin.

Life expectancy has dramatically increased in industrialized nations over the last 200 hundred years. The aging of populations carries over to clinical research and leads to an increasing representation of elderly and multimorbid individuals in study populations. Clinical research in these populations is complicated by the fact that individuals are likely to experience several potential disease endpoints that prevent some disease-specific endpoint of interest from occurrence. Large developments in competing risks methodology have been achieved over the last decades, but we assume that recognition of competing risks in the clinical community is still marginal. It is the aim of this article to address translational aspects of competing risks to the clinical community. We describe clinical populations where competing risks issues may arise. We then discuss the importance of agreement between the competing risks methodology and the study aim, in particular the distinction between etiologic and prognostic research questions. In a review of 50 clinical studies performed in individuals susceptible to competing risks published in high-impact clinical journals, we found competing risks issues in 70% of all articles. Better recognition of issues related to competing risks and of statistical methods that deal with competing risks in accordance with the aim of the study is needed. Copyright (C) 2011 John Wiley & Sons, Ltd.

Ortholog identification is used in gene functional annotation, species phylogeny estimation, phylogenetic profile construction and many other analyses. Bioinformatics methods for ortholog identification are commonly based on pairwise protein sequence comparisons between whole genomes. Phylogenetic methods of ortholog identification have also been developed; these methods can be applied to protein data sets sharing a common domain architecture or which share a single functional domain but differ outside this region of homology. While promiscuous domains represent a challenge to all orthology prediction methods, overall structural similarity is highly correlated with proximity in a phylogenetic tree, conferring a degree of robustness to phylogenetic methods. In this article, we review the issues involved in orthology prediction when data sets include sequences with structurally heterogeneous domain architectures, with particular attention to automated methods designed for high-throughput application, and present a case study to illustrate the challenges in this area.

Orthology is a powerful refinement of homology that allows us to describe more precisely the evolution of genomes and understand the function of the genes they contain. However, because orthology is not concerned with genomic position, it is limited in its ability to describe genes that are likely to have equivalent roles in different genomes. Because of this limitation, the concept of ‘positional orthology’ has emerged, which describes the relation between orthologous genes that retain their ancestral genomic positions. In this review, we formally define this concept, for which we introduce the shorter term ‘toporthology’, with respect to the evolutionary events experienced by a gene’s ancestors. Through a discussion of recent studies on the role of genomic context in gene evolution, we show that the distinction between orthology and toporthology is biologically significant. We then review a number of orthology prediction methods that take genomic context into account and thus that may be used to infer the important relation of toporthology.

Despite the common assumption that orthologs usually share the same function, there have been various reports of divergence between orthologs, even among species as close as mammals. The comparison of mouse and human is of special interest, because mouse is often used as a model organism to understand human biology. We review the literature on evidence for divergence between human and mouse orthologous genes, and discuss it in the context of biomedical research.

Eukaryotic chromatin can be highly dynamic and can continuously exchange between an open transcriptionally active conformation and a compacted silenced one. Post-translational modifications of histones have a pivotal role in regulating chromatin states, thus influencing all chromatin dependent processes. Methylation is currently one of the best characterized histone modification and occurs on arginine and lysine residues. Histone methylation can regulate other modifications (e.g. acetylation, phosphorylation and ubiquitination) in order to define a precise functional chromatin environment. In this review we focus on histone methylation and demethylation, as well as on the enzymes responsible for setting these marks. In particular we are describing novel concepts on the interdependence of histone modifications marks and discussing the molecular mechanisms governing this cross-talks.

In standard survival analysis, it is generally assumed that every individual will experience someday the event of interest. However, this is not always the case, as some individuals may not be susceptible to this event. Also, in medical studies, it is frequent that patients come to scheduled interviews and that the time to the event is only known to occur between two visits. That is, the data are interval‐censored with a cure fraction. Variable selection in such a setting is of outstanding interest. Covariates impacting the survival are not necessarily the same as those impacting the probability to experience the event. The objective of this paper is to develop a parametric but flexible statistical model to analyze data that are interval‐censored and include a fraction of cured individuals when the number of potential covariates may be large. We use the parametric mixture cure model with an accelerated failure time regression model for the survival, along with the extended generalized gamma for the error term. To overcome the issue of non‐stable and non‐continuous variable selection procedures, we extend the adaptive LASSO to our model. By means of simulation studies, we show good performance of our method and discuss the behavior of estimates with varying cure and censoring proportion. Lastly, our proposed method is illustrated with a real dataset studying the time until conversion to mild cognitive impairment, a possible precursor of Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The goal of the Gene Ontology (GO) project is to provide a uniform way to describe the functions of gene products from organisms across all kingdoms of life and thereby enable analysis of genomic data. Protein annotations are either based on experiments or predicted from protein sequences. Since most sequences have not been experimentally characterized, most available annotations need to be based on predictions. To make as accurate inferences as possible, the GO Consortium's Reference Genome Project is using an explicit evolutionary framework to infer annotations of proteins from a broad set of genomes from experimental annotations in a semi-automated manner. Most components in the pipeline, such as selection of sequences, building multiple sequence alignments and phylogenetic trees, retrieving experimental annotations and depositing inferred annotations, are fully automated. However, the most crucial step in our pipeline relies on software-assisted curation by an expert biologist. This curation tool, Phylogenetic Annotation and INference Tool (PAINT) helps curators to infer annotations among members of a protein family. PAINT allows curators to make precise assertions as to when functions were gained and lost during evolution and record the evidence (e.g. experimentally supported GO annotations and phylogenetic information including orthology) for those assertions. In this article, we describe how we use PAINT to infer protein function in a phylogenetic context with emphasis on its strengths, limitations and guidelines. We also discuss specific examples showing how PAINT annotations compare with those generated by other highly used homology-based methods.