84 research outputs found

    Not your average biker; Criminal careers of members of Dutch outlaw motorcycle gangs

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    Based on criminal career data of a sample of 601 police-identified outlaw motorcycle gang members and an age-matched comparison group of 300 non-gang affiliated motorcycle owners, the current analysis examines various dimensions of the criminal careers of outlaw bikers, including participation, onset, frequency, and crime mix. Results show that Dutch outlaw bikers are more often convicted than the average Dutch motorcyclist, and that these convictions not only pertain to minor offenses but also to serious and violent crimes. We find that outlaw bikers’ criminal careers differ from that of the average Dutch motorcyclist already during the juvenile and early adult years, but also – and more so – during the adult years. These results fit the enhancement hypothesis of gang membership and suggest that both selection of crime prone individuals in outlaw motorcycle gangs and facilitation of criminal behavior whilst in the gang are taking place.Criminal Justice: Legitimacy, accountability, and effectivit

    TAO: Techniques for algorithm-level obfuscation during high-level synthesis

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    Intellectual Property (IP) theft costs semiconductor design companies billions of dollars every year. Unauthorized IP copies start from reverse engineering the given chip. Existing techniques to protect against IP theft aim to hide the IC's functionality, but focus on manipulating the HDL descriptions. We propose TAO as a comprehensive solution based on high-level synthesis to raise the abstraction level and apply algorithmic obfuscation automatically. TAO includes several transformations that make the component hard to reverse engineer during chip fabrication, while a key is later inserted to unlock the functionality. Finally, this is a promising approach to obfuscate large-scale designs despite the hardware overhead needed to implement the obfuscation

    Erratum to: Circulating tumor DNA as a biomarker for monitoring early treatment responses of patients with advanced lung adenocarcinoma receiving immune checkpoint inhibitors.

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    The following error appeared in Section 3.5 in Ref. [1]. Instead of ‘Progressive disease-L1 expression data were available for 87 patients’, the text should read ‘PD-L1 expression data were available for 87 patients’. We apologize for this error.</p

    External validation of NTCP-models for radiation pneumonitis in lung cancer patients treated with chemoradiotherapy

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    PURPOSE: Normal tissue complication probability (NTCP) models can be used to estimate the risk of radiation pneumonitis (RP). The aim of this study was to externally validate the most frequently used prediction models for RP, i.e., the QUANTEC and APPELT models, in a large cohort of lung cancer patients treated with IMRT or VMAT. [1-2] METHODS AND MATERIALS: This prospective cohort study, included lung cancer patients treated between 2013 and 2018. A closed testing procedure was performed to test the need for model updating. To improve model performance, modification or removal of variables was considered. Performance measures included tests for goodness of fit, discrimination, and calibration.RESULTS: In this cohort of 612 patients, the incidence of RP ≥ grade 2 was 14.5%. For the QUANTEC-model, recalibration was recommended which resulted in a revised intercept and adjusted regression coefficient (from 0.126 to 0.224) of the mean lung dose (MLD),. The APPELT-model needed revision including model updating with modification and elimination of variables. After revision, the New RP-model included the following predictors (and regression coefficients): MLD (B = 0.250), age (B = 0.049, and smoking status (B = 0.902). The discrimination of the updated APPELT-model was higher compared to the recalibrated QUANTEC-model (AUC: 0.79 vs. 0.73).CONCLUSIONS: This study demonstrated that both the QUANTEC- and APPELT-model needed revision. Next to changes of the intercept and regression coefficients, the APPELT model improved further by model updating and performed better than the recalibrated QUANTEC model. This New RP-model is widely applicable containing non-tumour site specific variables, which can easily be collected.</p

    A Systematic Evaluation of Cost-Saving Dosing Regimens for Therapeutic Antibodies and Antibody-Drug Conjugates for the Treatment of Lung Cancer

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    Background: Expensive novel anticancer drugs put a serious strain on healthcare budgets, and the associated drug expenses limit access to life-saving treatments worldwide. Objective: We aimed to develop alternative dosing regimens to reduce drug expenses. Methods: We developed alternative dosing regimens for the following monoclonal antibodies used for the treatment of lung cancer: amivantamab, atezolizumab, bevacizumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and ramucirumab; and for the antibody-drug conjugate trastuzumab deruxtecan. The alternative dosing regimens were developed by means of modeling and simulation based on the population pharmacokinetic models developed by the license holders. They were based on weight bands and the administration of complete vials to limit drug wastage. The resulting dosing regimens were developed to comply with criteria used by regulatory authorities for in silico dose development. Results: We found that alternative dosing regimens could result in cost savings that range from 11 to 28%, and lead to equivalent pharmacokinetic exposure with no relevant increases in variability in exposure. Conclusions: Dosing regimens based on weight bands and the use of complete vials to reduce drug wastage result in less expenses while maintaining equivalent exposure. The level of evidence of our proposal is the same as accepted by regulatory authorities for the approval of alternative dosing regimens of other monoclonal antibodies in oncology. The proposed alternative dosing regimens can, therefore, be directly implemented in clinical practice.</p

    Dynamic Changes of Circulating Tumor DNA Predict Clinical Outcome in Patients With Advanced Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors

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    PURPOSE Immune checkpoint inhibitors (ICIs) are increasingly being used in non-small-cell lung cancer (NSCLC), yet biomarkers predicting their benefit are lacking. We evaluated if on-treatment changes of circulating tumor DNA (ctDNA) from ICI start (t0) to after two cycles (t1) assessed with a commercial panel could identify patients with NSCLC who would benefit from ICI. PATIENTS AND METHODS The molecular ctDNA response was evaluated as a predictor of radiographic tumor response and long-term survival benefit of ICI. To maximize the yield of ctDNA detection, de novo mutation calling was performed. Furthermore, the impact of clonal hematopoiesis (CH)-related variants as a source of biologic noise was investigated. RESULTS After correction for CH-related variants, which were detected in 75 patients (44.9%), ctDNA was detected in 152 of 167 (91.0%) patients. We observed only a fair agreement of the molecular and radiographic response, which was even more impaired by the inclusion of CH-related variants. After exclusion of those, a ≥ 50% molecular response improved progression-free survival (10 v 2 months; hazard ratio [HR], 0.55; 95% CI, 0.39 to 0.77; P =.0011) and overall survival (18.4 v 5.9 months; HR, 0.44; 95% CI, 0.31 to 0.62; P,.0001) compared with patients not achieving this end point. After adjusting for clinical variables, ctDNA response and STK11/KEAP1 mutations (HR, 2.08; 95% CI, 1.4 to 3.0; P,.001) remained independent predictors for overall survival, irrespective of programmed death ligand-1 expression. A landmark survival analysis at 2 months (n = 129) provided similar results. CONCLUSION On-treatment changes of ctDNA in plasma reveal predictive information for long-term clinical benefit in ICI-treated patients with NSCLC. A broader NSCLC patient coverage through de novo mutation calling and the use of a variant call set excluding CH-related variants improved the classification of molecular responders, but had no significant impact on survival

    Efficacy of serology driven “test and treat strategy” for eradication of H. pylori in patients with rheumatic disease in the Netherlands

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    The treatment of choice of H. pylori infections is a 7-day triple-therapy with a proton pump inhibitor (PPI) plus amoxicillin and either clarithromycin or metronidazole, depending on local antibiotic resistance rates. The data on efficacy of eradication therapy in a group of rheumatology patients on long-term NSAID therapy are reported here. This study was part of a nationwide, multicenter RCT that took place in 2000–2002 in the Netherlands. Patients who tested positive for H. pylori IgG antibodies were included and randomly assigned to either eradication PPI-triple therapy or placebo. After completion, follow-up at 3 months was done by endoscopy and biopsies were sent for culture and histology. In the eradication group 13% (20/152, 95% CI 9–20%) and in the placebo group 79% (123/155, 95% CI 72–85%) of the patients were H. pylori positive by histology or culture. H. pylori was successfully eradicated in 91% of the patients who were fully compliant to therapy, compared to 50% of those who were not (difference of 41%; 95% CI 18–63%). Resistance percentages found in isolates of the placebo group were: 4% to clarithromycin, 19% to metronidazole, 1% to amoxicillin and 2% to tetracycline

    Life-prolonging treatment restrictions and outcomes in patients with cancer and COVID-19:an update from the Dutch Oncology COVID-19 Consortium

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    AIM OF THE STUDY: The coronavirus disease 2019 (COVID-19) pandemic significantly impacted cancer care. In this study, clinical patient characteristics related to COVID-19 outcomes and advanced care planning, in terms of non-oncological treatment restrictions (e.g. do-not-resuscitate codes), were studied in patients with cancer and COVID-19. METHODS: The Dutch Oncology COVID-19 Consortium registry was launched in March 2020 in 45 hospitals in the Netherlands, primarily to identify risk factors of a severe COVID-19 outcome in patients with cancer. Here, an updated analysis of the registry was performed, and treatment restrictions (e.g. do-not-intubate codes) were studied in relation to COVID-19 outcomes in patients with cancer. Oncological treatment restrictions were not taken into account. RESULTS: Between 27th March 2020 and 4th February 2021, 1360 patients with cancer and COVID-19 were registered. Follow-up data of 830 patients could be validated for this analysis. Overall, 230 of 830 (27.7%) patients died of COVID-19, and 60% of the remaining 600 patients with resolved COVID-19 were admitted to the hospital. Patients with haematological malignancies or lung cancer had a higher risk of a fatal outcome than other solid tumours. No correlation between anticancer therapies and the risk of a fatal COVID-19 outcome was found. In terms of end-of-life communication, 50% of all patients had restrictions regarding life-prolonging treatment (e.g. do-not-intubate codes). Most identified patients with treatment restrictions had risk factors associated with fatal COVID-19 outcome. CONCLUSION: There was no evidence of a negative impact of anticancer therapies on COVID-19 outcomes. Timely end-of-life communication as part of advanced care planning could save patients from prolonged suffering and decrease burden in intensive care units. Early discussion of treatment restrictions should therefore be part of routine oncological care, especially during the COVID-19 pandemic
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