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Background: The aim of this meta-analysis was to evaluate efficacy and safety of first-line chemotherapy with or without a monoclonal antibody in elderly patients ( ≥ 70 years) with metastatic colorectal cancer (mCRC), since they are frequently underrepresented in clinical trials.
Results: Individual data from 10 studies were included. From a total of 3271 patients, 604 patients (18%) were ≥ 70 years (median 73 years, range 70–88). Of these, 335 patients were treated with a bevacizumab-based first-line regimen and 265 were treated with chemotherapy only. The median PFS was 8.2 vs. 6.5 months and the median OS was 16.7 vs. 13.0 months in patients treated with and without bevacizumab, respectively. The safety profile of bevacizumab in combination with first-line chemotherapy did not differ from published clinical trials.
Materials and Methods: PubMed and Cochrane Library searches were performed on 29 April 2013 and studies published to this date were included. Authors were contacted to request progression-free survival (PFS), overall survival (OS) data, patient data on treatment regimens, age, sex and potential signs of toxicity in patients ≥ 70 years of age.
Conclusions: This meta-analysis suggests that the addition of bevacizumab to standard first-line chemotherapy improves clinical outcome in elderly patients with mCRC and is well tolerated.
Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs.
Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel.
Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1–25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0–88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%—subcutaneous; 29%—intravenous; 1%—unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy.
Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.
Background: Patients with liver cirrhosis have a highly elevated risk of developing bacterial infections that significantly decrease survival rates. One of the most relevant infections is spontaneous bacterial peritonitis (SBP). Recently, NOD2 germline variants were found to be potential predictors of the development of infectious complications and mortality in patients with cirrhosis. The aim of the INCA (Impact of NOD2 genotype-guided antibiotic prevention on survival in patients with liver Cirrhosis and Ascites) trial is to investigate whether survival of this genetically defined high-risk group of patients with cirrhosis defined by the presence of NOD2 variants is improved by primary antibiotic prophylaxis of SBP.
Methods/Design: The INCA trial is a double-blind, placebo-controlled clinical trial with two parallel treatment arms (arm 1: norfloxacin 400 mg once daily; arm 2: placebo once daily; 12-month treatment and observational period). Balanced randomization of 186 eligible patients with stratification for the protein content of the ascites (<15 versus ≥15 g/L) and the study site is planned. In this multicenter national study, patients are recruited in at least 13 centers throughout Germany. The key inclusion criterion is the presence of a NOD2 risk variant in patients with decompensated liver cirrhosis. The most important exclusion criteria are current SBP or previous history of SBP and any long-term antibiotic prophylaxis. The primary endpoint is overall survival after 12 months of treatment. Secondary objectives are to evaluate whether the frequencies of SBP and other clinically relevant infections necessitating antibiotic treatment, as well as the total duration of unplanned hospitalization due to cirrhosis, differ in both study arms. Recruitment started in February 2014.
Discussion: Preventive strategies are required to avoid life-threatening infections in patients with liver cirrhosis, but unselected use of antibiotics can trigger resistant bacteria and worsen outcome. Thus, individualized approaches that direct intervention only to patients with the highest risk are urgently needed. This trial meets this need by suggesting stratified prevention based on genetic risk assessment. To our knowledge, the INCA trial is first in the field of hepatology aimed at rapidly transferring and validating information on individual genetic risk into clinical decision algorithms.
Trial registrations: German Clinical Trials Register DRKS00005616. Registered 22 January 2014. EU Clinical Trials Register EudraCT 2013-001626-26. Registered 26 January 2015.
Seroconversion rates following influenza vaccination in patients with hematologic malignancies after hematopoietic stem cell transplantation (HSCT) are known to be lower compared to healthy adults. The aim of our diagnostic study was to determine the rate of seroconversion after 1 or 2 doses of a novel split virion, inactivated, AS03-adjuvanted pandemic H1N1 influenza vaccine (A/California/7/2009) in HSCT recipients (ClinicalTrials.gov Identifier: NCT01017172). Blood samples were taken before and 21 days after a first dose and 21 days after a second dose of the vaccine. Antibody (AB) titers were determined by hemagglutination inhibition assay. Seroconversion was defined by either an AB titer of ≤1:10 before and ≥1:40 after or ≥1:10 before and ≥4-fold increase in AB titer 21 days after vaccination. Seventeen patients (14 allogeneic, 3 autologous HSCT) received 1 dose and 11 of these patients 2 doses of the vaccine. The rate of seroconversion was 41.2% (95% confidence interval [CI] 18.4-67.1) after the first and 81.8% (95% CI 48.2-97.7) after the second dose. Patients who failed to seroconvert after 1 dose of the vaccine were more likely to receive any immunosuppressive agent (P = .003), but time elapsed after or type of HSCT, age, sex, or chronic graft-versus-host disease was not different when compared to patients with seroconversion. In patients with hematologic malignancies after HSCT the rate of seroconversion after a first dose of an adjuvanted H1N1 influenza A vaccine was poor, but increased after a second dose.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
Ultrasonic guided waves have been used successfully in structural health monitoring systems to detect damage in isotropic and composite materials with simple and complex geometry. A limitation of current research is given by a lack of freely available benchmark measurements to comparatively evaluate existing methods. This article introduces the extendable online platform Open Guided Waves (http://www.open-guided-waves.de) where high-quality and well-documented datasets for guided wave-based inspections are provided. In this article, we describe quasi-isotropic carbon-fiber-reinforced polymer plates with embedded piezoelectric transducers as a first benchmark structure. Intentionally, this is a structure of medium complexity to enable many researchers to apply their methods. In a first step, ultrasound and X-ray measurements were acquired to verify pristine conditions. Next, mechanical testing was done to determine the stiffness tensor and sample density based on standard test procedures. Guided wave measurements were divided into two parts: first, acoustic wave fields were acquired for a broad range of frequencies by three-dimensional scanning laser Doppler vibrometry. Second, structural health monitoring measurements in the carbon-fiber-reinforced polymer plate were collected at constant temperature using a distributed transducer network and a surface-mounted reversible defect model. Initial results serving as validation are presented and discussed.