Refine
Year of publication
- 2021 (74) (remove)
Language
- English (74)
Has Fulltext
- yes (74)
Is part of the Bibliography
- no (74)
Keywords
- BESIII (6)
- Branching fraction (3)
- e+-e− Experiments (3)
- Initial state radiation (2)
- Lepton colliders (2)
- Particle decays (2)
- Absolute branching fraction (1)
- Born cross section (1)
- Charm physics (1)
- Charmed baryon (1)
Background. Angiosarcomas are rare and heterogeneous tumors with poor prognosis. The clinical subtypes are classified depending on the primary site and etiology. Methods. We conducted a retrospective, monocentric study of 136 patients with localized AS between May 1985 and November 2018. Overall survival (OS), local recurrence-free survival (LRFS), and metastasis-free survival (MFS) were estimated using the Kaplan–Meier method. To identify prognostic factors, univariate and multivariate analyses were performed based on Cox regressions. Results. The median age was 67 years (19–72.8 years). Primary sites were cutaneous (27.2%), breast (38.2%), and deep soft tissue (34.6%). The majority was primary angiosarcomas (55.9%) followed by postradiation (40.4%) and chronic lymphedema angiosarcomas (2.9%). Prognosis significantly differed depending on the primary site and etiology. Shortest median OS and MFS were observed in deep soft tissue angiosarcomas, whereas cutaneous angiosarcomas, angiosarcomas of the breast, and radiation-associated angiosarcomas displayed worse median LRFS. Univariate analyses showed better OS for tumor size <10 cm (p = 0.009), negative surgical margins ( = 0.021), and negative lymph node status (p = 0.007). LRFS and MFS were longer for tumor size <10 cm (p = 0.012 and p = 0.013). In multivariate analyses, age <70 years was the only independent positive prognostic factor for OS in all subgroups. For LRFS, secondary AS of the breast was a negative prognostic factor (HR: 2.35; p = 0.035). Conclusions. Different behaviors and prognoses depending on the primary site and etiology should be considered for the treatment of this heterogeneous disease. In cutaneous angiosarcomas of the head/neck and postradiation angiosarcomas of the breast, local recurrence seems to have a crucial impact on OS. Therefore, improved local therapies and local tumor staging may have to be implemented. However, in deep soft tissue angiosarcomas, distant recurrence seems to have a major influence on prognosis, which indicates a benefit of additional perioperative chemotherapy.
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.
Lenalidomide (LEN) maintenance (MT) post autologous stem cell transplantation (ASCT) is standard of care in newly diagnosed multiple myeloma (MM) but has not been compared to other agents in clinical trials. We retrospectively compared bortezomib (BTZ; n = 138) or LEN (n = 183) MT from two subsequent GMMG phase III trials. All patients received three cycles of BTZ-based triplet induction and post-ASCT MT. BTZ MT (1.3 mg/m2 i.v.) was administered every 2 weeks for 2 years. LEN MT included two consolidation cycles (25 mg p.o., days 1–21 of 28 day cycles) followed by 10–15 mg/day for 2 years. The BTZ cohort more frequently received tandem ASCT (91% vs. 33%) due to different tandem ASCT strategies. In the LEN and BTZ cohort, 43% and 46% of patients completed 2 years of MT as intended (p = 0.57). Progression-free survival (PFS; HR = 0.83, p = 0.18) and overall survival (OS; HR = 0.70, p = 0.15) did not differ significantly with LEN vs. BTZ MT. Patients with <nCR after first ASCT were assigned tandem ASCT in both trials. In patients with <nCR and tandem ASCT (LEN: n = 54 vs. BTZ: n = 84), LEN MT significantly improved PFS (HR = 0.61, p = 0.04) but not OS (HR = 0.46, p = 0.09). In conclusion, the significant PFS benefit after eliminating the impact of different tandem ASCT rates supports the current standard of LEN MT after ASCT.
Objective To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.
Study design and setting Using individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).
Results Prior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.
Conclusions Predictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.
Trial registration number PROSPERO id: CRD42018088129.
Background: Cumulative anticholinergic exposure, also known as anticholinergic burden, is associated with a variety of adverse outcomes. However, studies show that anticholinergic effects tend to be underestimated by prescribers, and anticholinergics are the most frequently prescribed potentially inappropriate medication in older patients. The grading systems and drugs included in existing scales to quantify anticholinergic burden differ considerably and do not adequately account for patients’ susceptibility to medications. Furthermore, their ability to link anticholinergic burden with adverse outcomes such as falls is unclear. This study aims to develop a prognostic model that predicts falls in older general practice patients, to assess the performance of several anticholinergic burden scales, and to quantify the added predictive value of anticholinergic symptoms in this context.
Methods: Data from two cluster-randomized controlled trials investigating medication optimization in older general practice patients in Germany will be used. One trial (RIME, n = 1,197) will be used for the model development and the other trial (PRIMUM, n = 502) will be used to externally validate the model. A priori, candidate predictors will be selected based on a literature search, predictor availability, and clinical reasoning. Candidate predictors will include socio-demographics (e.g. age, sex), morbidity (e.g. single conditions), medication (e.g. polypharmacy, anticholinergic burden as defined by scales), and well-being (e.g. quality of life, physical function). A prognostic model including sociodemographic and lifestyle-related factors, as well as variables on morbidity, medication, health status, and well-being, will be developed, whereby the prognostic value of extending the model to include additional patient-reported symptoms will be also assessed. Logistic regression will be used for the binary outcome, which will be defined as “no falls” vs. “≥1 fall” within six months of baseline, as reported in patient interviews. Discussion: As the ability of different anticholinergic burden scales to predict falls in older patients is unclear, this study may provide insights into their relative importance as well as into the overall contribution of anticholinergic symptoms and other patient characteristics. The results may support general practitioners in their clinical decision-making and in prescribing fewer medications with anticholinergic properties.
This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, |GE | and |GM|, using the ¯pp → μ+μ− reaction at PANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at PANDA, using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is ¯pp → π+π−,due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distribuations of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented.
We report a measurement of the observed cross sections of e+ e− → J/ψX based on 3.21 fb − 1 of data accumulated at energies from 3.645 to 3.891 GeV with the BESIII detector operated at the BEPCII collider. In analysis of the cross sections, we measured the decay branching fractions of B(ψ(3686) → J/ψX) = (64.4 ± 0.6 ± 1.6)% and B(ψ(3770) → J/ψX) = (0.5 ± 0.2 ± 0.1)% for the first time. The energy-dependent line shape of these cross sections cannot be well described by two Breit-Wigner (BW) amplitudes of the expected decays ψ (3686) → J/ψX and ψ(3770) → J/ψX. Instead, it can be better described with one more BW amplitude of the decay R(3760)→ J/ψX. Under this assumption, we extracted the R (3760) mass M R (3760 ) = 3766.2 ± 3.8 ± 0.4 MeV/c2, total width Γ tot R ( 3760 ) = 22.2 ± 5.9 ± 1.4 MeV, and product of leptonic width and decay branching fraction
ΓeeR(3760) B[R(3760) → J/ψX] = (79.4 ± 85.5 ± 11.7) eV. The significance of the R(3760) is 5.3σ. The first uncertainties of these measured quantities are from fits to the cross sections and second systematic.
We measure the inclusive semielectronic decay branching fraction of the D+s meson. A double-tag technique is applied to e+e− annihilation data collected by the BESIII experiment at the BEPCII collider, operating in the center-of-mass energy range 4.178–4.230 GeV. We select positrons fromD+s→Xe+νe with momenta greater than 200 MeV/c and determine the laboratory momentum spectrum, accounting for the effects of detector efficiency and resolution. The total positron yield and semielectronic branching fraction are determined by extrapolating this spectrum below the momentum cutoff. We measure the D+s semielectronic branching fraction to be(6.30±0.13(stat.)±0.09(syst.)±0.04(ext.))%, showing no evidence for unobserved exclusive semielectronic modes. We combine this result with external data taken from literature to determine the ratio of the D+s and D0 semielectronic widths, Γ(D+s→Xe+νe)Γ(D0→Xe+νe)=0.790±0.016(stat.)±0.011(syst.)±0.016(ext.). Our results are consistent with and more precise than previous measurements.
The electromagnetic process is studied with the initial-state-radiation technique using 7.5 fb−1 of data collected by the BESIII experiment at seven energy points from 3.773 to 4.600 GeV. The Born cross section and the effective form factor of the proton are measured from the production threshold to 3.0 GeV/ using the invariant-mass spectrum. The ratio of electric and magnetic form factors of the proton is determined from the analysis of the proton-helicity angular distribution.
Using data samples collected with the BESIII detector operating at the BEPCII storage ring at center-of-mass energies from 4.178 to 4.600 GeV, we study the process eþe− → π0Xð3872Þγ and search for Zcð4020Þ0 → Xð3872Þγ. We find no significant signal and set upper limits on σðeþe− → π0Xð3872ÞγÞ · BðXð3872Þ → πþπ−J=ψÞ and σðeþe− → π0Zcð4020Þ0Þ · BðZcð4020Þ0 → Xð3872ÞγÞ · BðXð3872Þ → πþπ−J=ψÞ for each energy point at 90% confidence level, which is of the order of several tenths pb.