Glioblastoma in the oldest old: Clinical characteristics, therapy, and outcome in patients aged 80 years and older

Background: Incidence rates of glioblastoma in very old patients are rising. The standard of care for this cohort is only partially defined and survival remains poor. The aims of this study were to reveal current practice of tumor-specific therapy and supportive care, and to identify predictors for survival in this cohort. Methods: Patients aged 80 years or older at the time of glioblastoma diagnosis were retrospectively identified in 6 clinical centers in Switzerland and France. Demographics, clinical parameters, and survival outcomes were annotated from patient charts. Cox proportional hazards modeling was performed to identify parameters associated with survival. Results: Of 107 patients, 45 were diagnosed by biopsy, 30 underwent subtotal resection, and 25 had gross total resection. In 7 patients, the extent of resection was not specified. Postoperatively, 34 patients did not receive further tumor-specific treatment. Twelve patients received radiotherapy with concomitant temozolomide, but only 2 patients had maintenance temozolomide therapy. Fourteen patients received temozolomide alone, 35 patients received radiotherapy alone, 1 patient received bevacizumab, and 1 took part in a clinical trial. Median progression-free survival (PFS) was 3.3 months and median overall survival (OS) was 4.2 months. Among patients who received any postoperative treatment, median PFS was 3.9 months and median OS was 7.2 months. Karnofsky performance status (KPS) ≥70%, gross total resection, and combination therapy were associated with better outcomes. The median time spent hospitalized was 30 days, accounting for 23% of the median OS. End-of-life care was mostly provided by nursing homes (n = 20; 32%) and palliative care wards (n = 16; 26%). Conclusions: In this cohort of very old patients diagnosed with glioblastoma, a large proportion was treated with best supportive care. Treatment beyond surgery and, in particular, combined modality treatment were associated with longer OS and may be considered for selected patients even at higher ages

A new model to determine the dispersion of fatigue damage evaluations

Reliable predictions of remaining lives of civil or mechanical structures subjected to fatigue damage are very difficult to be made. In general, fatigue damage is extremely sensitive to the random variations of material mechanical properties, environment and loading. These variations may induce large dispersions when the structural fatigue life has to be predicted. Wirsching (1970) mentions dispersions of the order of 30 to 70 % of the mean calculated life. The presented paper introduces a model to estimate the fatigue damage dispersion based on known statistical distributions of the fatigue parameters (material properties and loading). The model is developed by expanding into Taylor series the set of equations that describe fatigue damage for crack initiation

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction

Efflux in Fungi: La Pièce de Résistance

Pathogens must be able to overcome both host defenses and antimicrobial treatment in order to successfully infect and maintain colonization of the host. One way fungi accomplish this feat and overcome intercellular toxin accumulation is efflux pumps, in particular ATP-binding cassette transporters and transporters of the major facilitator superfamily. Members of these two superfamilies remove many toxic compounds by coupling transport with ATP hydrolysis or a proton gradient, respectively. Fungal genomes encode a plethora of members of these families of transporters compared to other organisms. In this review we discuss the role these two fungal superfamilies of transporters play in virulence and resistance to antifungal agents. These efflux transporters are responsible not only for export of compounds involved in pathogenesis such as secondary metabolites, but also export of host-derived antimicrobial compounds. In addition, we examine the current knowledge of these transporters in resistance of pathogens to clinically relevant antifungal agents

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease