3,026 research outputs found

    Reducing combinatorial uncertainties: A new technique based on MT2 variables

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    We propose a new method to resolve combinatorial ambiguities in hadron collider events involving two invisible particles in the final state. This method is based on the kinematic variable MT2 and on the MT2-assisted-on-shell reconstruction of invisible momenta, that are reformulated as `test' variables Ti of the correct combination against the incorrect ones. We show how the efficiency of the single Ti in providing the correct answer can be systematically improved by combining the different Ti and/or by introducing cuts on suitable, combination-insensitive kinematic variables. We illustrate our whole approach in the specific example of top anti-top production, followed by a leptonic decay of the W on both sides. However, by construction, our method is also directly applicable to many topologies of interest for new physics, in particular events producing a pair of undetected particles, that are potential dark-matter candidates. We finally emphasize that our method is apt to several generalizations, that we outline in the last sections of the paper.Comment: 1+23 pages, 8 figures. Main changes in v3: (1) discussion at the end of sec. 2 improved; (2) added sec. 4.2 about the method's dependence on mass information. Matches journal versio

    ACCORD (ACcurate COnsensus Reporting Document): A reporting guideline for consensus methods in biomedicine developed via a modified Delphi

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    \ua9 2024 Gattrell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background In biomedical research, it is often desirable to seek consensus among individuals who have differing perspectives and experience. This is important when evidence is emerging, inconsistent, limited, or absent. Even when research evidence is abundant, clinical recommendations, policy decisions, and priority-setting may still require agreement from multiple, sometimes ideologically opposed parties. Despite their prominence and influence on key decisions, consensus methods are often poorly reported. Our aim was to develop the first reporting guideline dedicated to and applicable to all consensus methods used in biomedical research regardless of the objective of the consensus process, called ACCORD (ACcurate COnsensus Reporting Document). Methods and findings We followed methodology recommended by the EQUATOR Network for the development of reporting guidelines: a systematic review was followed by a Delphi process and meetings to finalize the ACCORD checklist. The preliminary checklist was drawn from the systematic review of existing literature on the quality of reporting of consensus methods and suggestions from the Steering Committee. A Delphi panel (n = 72) was recruited with representation from 6 continents and a broad range of experience, including clinical, research, policy, and patient perspectives. The 3 rounds of the Delphi process were completed by 58, 54, and 51 panelists. The preliminary checklist of 56 items was refined to a final checklist of 35 items relating to the article title (n = 1), introduction (n = 3), methods (n = 21), results (n = 5), discussion (n = 2), and other information (n = 3). Conclusions The ACCORD checklist is the first reporting guideline applicable to all consensus-based studies. It will support authors in writing accurate, detailed manuscripts, thereby improving the completeness and transparency of reporting and providing readers with clarity regarding the methods used to reach agreement. Furthermore, the checklist will make the rigor of the consensus methods used to guide the recommendations clear for readers. Reporting consensus studies with greater clarity and transparency may enhance trust in the recommendations made by consensus panels

    Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

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    BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables - nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER+ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%. CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence. British Journal of Cancer (2010) 102, 1503 - 1510. doi:10.1038/sj.bjc.6605627 www.bjcancer.co

    Advancing the field of health systems research synthesis.

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    Those planning, managing and working in health systems worldwide routinely need to make decisions regarding strategies to improve health care and promote equity. Systematic reviews of different kinds can be of great help to these decision-makers, providing actionable evidence at every step in the decision-making process. Although there is growing recognition of the importance of systematic reviews to inform both policy decisions and produce guidance for health systems, a number of important methodological and evidence uptake challenges remain and better coordination of existing initiatives is needed. The Alliance for Health Policy and Systems Research, housed within the World Health Organization, convened an Advisory Group on Health Systems Research (HSR) Synthesis to bring together different stakeholders interested in HSR synthesis and its use in decision-making processes. We describe the rationale of the Advisory Group and the six areas of its work and reflects on its role in advancing the field of HSR synthesis. We argue in favour of greater cross-institutional collaborations, as well as capacity strengthening in low- and middle-income countries, to advance the science and practice of health systems research synthesis. We advocate for the integration of quasi-experimental study designs in reviews of effectiveness of health systems intervention and reforms. The Advisory Group also recommends adopting priority-setting approaches for HSR synthesis and increasing the use of findings from systematic reviews in health policy and decision-making

    PTK (protein tyrosine kinase)-6 and HER2 and 4, but not HER1 and 3 predict long-term survival in breast carcinomas

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    The HER receptors are of therapeutic and prognostic significance in breast cancer, and their function is modulated by cytoplasmic tyrosine kinases like PTK6 (brk). We performed a retrospective study on archival breast cancer samples from patients with long follow-up and compared the protein expression between individual HERs and between HERs and the PTK6. Univariate and multivariate analyses were used to study the prognostic value of parameters. Metastases-free survival of patients for longer than 240 months was inversely associated (P⩽0.05) with nodal status, tumour size, and oestrogen receptor status, but was also directly associated with high protein expression levels of HER4 and PTK6 in Kaplan–Meier analysis. In multivariate analysis for metastases-free survival of >240 months, the stepwise selected parameters were tumour size (relative risk 3.1), PTK6 expression (0.4), and number of positive lymph nodes (1.2). Furthermore, we demonstrated a timedependence of the prognostic value attributed to the parameters. The HER receptors (HER2,4), but not PTK6, were independent prognostic markers for metastases-free survival at 60 months, whereas at 240 months PTK6 is the strongest prognostic marker. We demonstrate that PTK6 is a prognostic marker of metastases-free survival in breast cancer, and is independent of the classical morphological and molecular markers of lymph node involvement, tumour size, and HER2 status

    Trends in referrals to liaison psychiatry teams from UK emergency departments for patients over 65

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    INTRODUCTION: The number of people over the age of 65 attending Emergency Departments (ED) in the United Kingdom (UK) is increasing. Those who attend with a mental health related problem may be referred to liaison psychiatry for assessment. Improving responsiveness and integration of liaison psychiatry in general hospital settings is a national priority. To do this psychiatry teams must be adequately resourced and organised. However, it is unknown how trends in the number and type referrals of older people to liaison psychiatry teams by EDs are changing, making this difficult. METHODS: We performed a national multi-centre retrospective service evaluation, analysing existing psychiatry referral data from EDs of people over 65. We described trends in the number, rate, age, mental health presentation, and time taken to assessment over a 7 years period. RESULTS: Referral data from 28 EDs across England and Scotland were analysed (n = 18,828 referrals). There was a general trend towards increasing numbers of people referred to liaison psychiatry year on year. Variability in referral numbers between different departments, ranged from 0.1 to 24.3 per 1000 ED attendances. The most common reasons for referral were mood disorders, self-harm and suicidal ideas. The majority of referrals were assessed within 60 min, however there is variability between departments, some recording waits over 11 h. DISCUSSION: The data suggests great inter-departmental variability in referral numbers. Is not possible to establish the cause of variability. However, the data highlights the importance of asking further questions about why the differences exist, and the impact that has on patient care

    A study of backward going pp and π\pi^{-} in νμCC\nu_{\mu}CC interactions with the NOMAD detector

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    Backward proton and π\pi^- production has been studied in νμCC\nu_{\mu}CC interactions with carbon nuclei. Detailed analyses of the momentum distributions, of the production rates, and of the general features of events with a backward going particle, have been carried out in order to understand the mechanism producing these particles. The backward proton data have been compared with the predictions of the reinteraction and the short range correlation models.Comment: 29 pages, 14 figures, submitted to Nucl. Phys.
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