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Mutations of the isocitrate dehydrogenase-1 (IDH1) and IDH2 genes are among the most frequent alterations in acute myeloid leukemia (AML) and can be found in ∼20% of patients at diagnosis. Among 4930 patients (median age, 56 years; interquartile range, 45-66) with newly diagnosed, intensively treated AML, we identified IDH1 mutations in 423 (8.6%) and IDH2 mutations in 575 (11.7%). Overall, there were no differences in response rates or survival for patients with mutations in IDH1 or IDH2 compared with patients without mutated IDH1/2. However, distinct clinical and comutational phenotypes of the most common subtypes of IDH1/2 mutations could be associated with differences in outcome. IDH1-R132C was associated with increased age, lower white blood cell (WBC) count, less frequent comutation of NPM1 and FLT3 internal tandem mutation (ITD) as well as with lower rate of complete remission and a trend toward reduced overall survival (OS) compared with other IDH1 mutation variants and wild-type (WT) IDH1/2. In our analysis, IDH2-R172K was associated with significantly lower WBC count, more karyotype abnormalities, and less frequent comutations of NPM1 and/or FLT3-ITD. Among patients within the European LeukemiaNet 2017 intermediate- and adverse-risk groups, relapse-free survival and OS were significantly better for those with IDH2-R172K compared with WT IDH, providing evidence that AML with IDH2-R172K could be a distinct entity with a specific comutation pattern and favorable outcome. In summary, the presented data from a large cohort of patients with IDH1/2 mutated AML indicate novel and clinically relevant findings for the most common IDH mutation subtypes.
(1) Background: Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who are biologically at high risk for the development of loco–regional recurrences after postoperative radiotherapy (PORT) but at intermediate risk according to clinical risk factors may benefit from additional concurrent chemotherapy. In this matched-pair study, we aimed to identify a corresponding predictive gene signature. (2) Methods: Gene expression analysis was performed on a multicenter retrospective cohort of 221 patients that were treated with postoperative radiochemotherapy (PORT-C) and 283 patients who were treated with PORT alone. Propensity score analysis was used to identify matched patient pairs from both cohorts. From differential gene expression analysis and Cox regression, a predictive gene signature was identified. (3) Results: 108 matched patient pairs were selected. We identified a 2-metagene signature that stratified patients into risk groups in both cohorts. The comparison of the high-risk patients between the two types of treatment showed higher loco–regional control (LRC) after treatment with PORT-C (p < 0.001), which was confirmed by a significant interaction term in Cox regression (p = 0.027), i.e., the 2-metagene signature was indicative for the type of treatment. (4) Conclusion: We have identified a novel gene signature that may be helpful to identify patients with high-risk HNSCC amongst those at intermediate clinical risk treated with PORT, who may benefit from additional concurrent chemotherapy.
Innovation is considered essential for today's organizations to survive and thrive. Researchers have also stressed the importance of leadership as a driver of followers' innovative work behavior (FIB). Yet, despite a large amount of research, three areas remain understudied: (a) The relative importance of different forms of leadership for FIB; (b) the mechanisms through which leadership impacts FIB; and (c) the degree to which relationships between leadership and FIB are generalizable across cultures. To address these lacunae, we propose an integrated model connecting four types of positive leadership behaviors, two types of identification (as mediating variables), and FIB. We tested our model in a global data set comprising responses of N = 7,225 participants from 23 countries, grouped into nine cultural clusters. Our results indicate that perceived LMX quality was the strongest relative predictor of FIB. Furthermore, the relationships between both perceived LMX quality and identity leadership with FIB were mediated by social identification. The indirect effect of LMX on FIB via social identification was stable across clusters, whereas the indirect effects of the other forms of leadership on FIB via social identification were stronger in countries high versus low on collectivism. Power distance did not influence the relations.
The optimal follow-up care for relapse detection in acute myeloid leukemia (AML) patients in first remission after consolidation therapy with intensive chemotherapy is not established. In this retrospective study, we evaluate the diagnostic value of an intensive relapse surveillance strategy by regular bone marrow aspirations (BMA) in these patients. We identified 86 patients with newly diagnosed non-promyelocytic AML who had reached complete remission (CR) after intensive induction and consolidation chemotherapy between 2007 and 2019. Annual relapse rates were 40%, 17%, and 2% in years 1–3, respectively. Patients in CR were surveilled by BMA scheduled every 3 months for 2 years, followed by BMA every 6 months. This surveillance regimen detected 29 of 55 relapses (53%), 11 of which were molecular relapses (20%). The remaining 26 of 55 relapses (47%) were diagnosed by non-surveillance BMA prompted by specific suspicion of relapse. Most patients showed concurrent morphological abnormalities in peripheral blood (PB) at time of relapse. Seven percent of all morphological relapses occurred without simultaneous PB abnormalities and would have been delayed without surveillance BMA. Intensified monthly PB assessment paired with BMA every 3 months during the first 2 years may be a highly sensitive relapse surveillance strategy.
In the original paper, the sign used to determine the global polarization PH was opposite to the convention used in previous papers, particularly, published by the STAR Collaboration to which the results are compared to in Fig. 5. The correct version of Eq. (3) in the paper for PH is...
Purpose: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization.
Methods: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16).
Results: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface.
Conclusion: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.
The inclusive production of the J/ψ and ψ(2S) charmonium states is studied as a function of centrality in p-Pb collisions at a centre-of-mass energy per nucleon pair sNN−−−√ = 8.16 TeV at the LHC. The measurement is performed in the dimuon decay channel with the ALICE apparatus in the centre-of-mass rapidity intervals −4.46 < ycms < −2.96 (Pb-going direction) and 2.03 < ycms < 3.53 (p-going direction), down to zero transverse momentum (pT). The J/ψ and ψ(2S) production cross sections are evaluated as a function of the collision centrality, estimated through the energy deposited in the zero degree calorimeter located in the Pb-going direction. The pT-differential J/ψ production cross section is measured at backward and forward rapidity for several centrality classes, together with the corresponding average 〈pT〉 and ⟨p2T⟩ values. The nuclear effects affecting the production of both charmonium states are studied using the nuclear modification factor. In the p-going direction, a suppression of the production of both charmonium states is observed, which seems to increase from peripheral to central collisions. In the Pb-going direction, however, the centrality dependence is different for the two states: the nuclear modification factor of the J/ψ increases from below unity in peripheral collisions to above unity in central collisions, while for the ψ(2S) it stays below or consistent with unity for all centralities with no significant centrality dependence. The results are compared with measurements in p-Pb collisions at sNN−−−√ = 5.02 TeV and no significant dependence on the energy of the collision is observed. Finally, the results are compared with theoretical models implementing various nuclear matter effects.
Themultiplicity dependence of the pseudorapidity density of charged particles in proton–proton (pp) collisions at centre-of-mass energies √s = 5.02, 7 and 13 TeV measured by ALICE is reported. The analysis relies on track segments measured in the midrapidity range (|η| < 1.5). Results are presented for inelastic events having at least one charged particle produced in the pseudorapidity interval |η| < 1. The multiplicity dependence of the pseudorapidity density of charged particles is measured with mid- and forward rapidity multiplicity estimators, the latter being less affected by autocorrelations.Adetailed comparison with predictions from the PYTHIA 8 and EPOS LHC event generators is also presented. The results can be used to constrain models for particle production as a function of multiplicity in pp collisions.
Measurements of the production of muons from heavy-flavour hadron decays in Pb–Pb collisions at √sNN = 5.02 and 2.76 TeV using the ALICE detector at the LHC are reported. The nuclear modification factor RAA at √sNN = 5.02 TeV is measured at forward rapidity (2.5 < y < 4) as a function of transverse momentum pT in central, semi-central, and peripheral collisions over a wide pT interval, 3 < pT < 20 GeV/c, in which muons from beauty-hadron decays are expected to take over from charm as the dominant source at high pT (pT > 7 GeV/c). The RAA shows an increase of the suppression of the yields of muons from heavy-flavour hadron decays with increasing centrality. A suppression by a factor of about three is observed in the 10% most central collisions. The RAA at √sNN = 5.02 TeV is similar to that at √sNN = 2.76 TeV. The precise RAA measurements have the potential to distinguish between model predictions implementing different mechanisms of parton energy loss in the high-density medium formed in heavy-ion collisions. They place important constraints for the understanding of the heavy-quark interaction with the hot and dense QCD medium.
Bloodstream infections (BSI) are a frequent complication in patients with hematological and oncological diseases. However, the impact of different bacterial species causing BSI and of multiple BSI remains incompletely understood. We performed a retrospective study profiling 637 bacterial BSI episodes in hematological and oncological patients. Based on the 30-day (30d) overall survival (OS), we analyzed different types of multiple BSI and grouped BSI-associated bacteria into clusters followed by further assessment of clinical and infection-related characteristics. We discovered that polymicrobial BSI (different organisms on the first day of a BSI episode) and sequential BSI (another BSI before the respective BSI episode) were associated with a worse 30d OS. Different bacterial groups could be classified into three BSI outcome clusters based on 30d OS: favorable (FAV) including mainly common skin contaminants, Escherichia spp. and Streptococcus spp.; intermediate (INT) including mainly Enterococcus spp., vancomycin-resistant Enterococcus spp., and multidrug-resistant gram-negative bacteria (MDRGN); and adverse (ADV) including MDRGN with an additional carbapenem-resistance (MDRGN+CR). A polymicrobial or sequential BSI especially influenced the outcome in the combination of two INT cluster BSI. The presence of a polymicrobial BSI and the assignment into the BSI outcome clusters were identified as independent risk factors for 30d mortality in a Cox multivariate regression analysis. The assignment to a BSI outcome cluster and the differentiated perspective of multiple BSI open new insights into the prognosis of patients with BSI and should be further validated in other patient cohorts.