Treatment options beyond immunotherapy in patients with wild-type lung adenocarcinoma: a Delphi consensus

Purpose: Immunotherapy-based approaches are standard first-line treatments for advanced/metastatic lung cancer or for chemoradiotherapy consolidation in locally advanced disease. Uncertainty on how to treat patients at disease progression prompted us to develop a consensus document on post-immunotherapy options in Spain for patients with advanced wild-type lung adenocarcinoma. Methods: After extensive literature review, a 5-member scientific committee generated 33 statements in 4 domains: general aspects (n = 4); post-durvalumab in locally advanced disease (n = 6); post-first-line immunotherapy ± chemotherapy in advanced/metastatic disease (n = 11); and post-first-line platinum-based chemotherapy in advanced/metastatic disease (n = 12). A panel of 26 lung cancer experts completed 2 Delphi iterations through an online platform rating their degree of agreement/disagreement (first-round scale 1–5 and second-round scale 1–4, 1 = strongly disagree, 4/5 = strongly agree) for each statement. Second-round consensus: ≥ 70% of responses were in categories 1/2 (disagreement) or 3/4 (agreement). Results: Consensus was reached for 2/33 statements in the first Delphi round and in 29/31 statements in the second round. Important variables informing treatment at disease progression with an immunotherapy-based treatment include: disease aggressiveness, previous treatment, accumulated toxicity, progression-free interval, PD-L1 expression, and tumour mutational burden. A platinum-based chemotherapy should follow a first-line immunotherapy treatment without chemotherapy. Treatment with docetaxel + nintedanib may be appropriate post-durvalumab in refractory patients or following progression to first-line chemotherapy + immunotherapy, or second-line chemotherapy after first-line immunotherapy, or first-line chemotherapy in some patients with low/negative PD-L1 expression, or second-line immunotherapy after first-line chemotherapy. Conclusions: To support decision making following progression to immunotherapy-based treatment in patients with advanced wild-type lung adenocarcinoma, a consensus document has been developed.The project was funded by Boehringer Ingelheim

Pd-(L)1 inhibitors as monotherapy for the first-line treatment of non-small-cell lung cancer patients with high pd-l1 expression : A network meta-analysis

Altres ajuts: RocheProgrammed cell death-ligand 1 (PD-L1) has emerged as a potential biomarker for selec-tion of patients more likely to respond to immunotherapy and as a prognostic factor in non-small cell lung cancer (NSCLC). In this network meta-analysis, we aimed to evaluate the efficacy of first-line anti-PD-(L)1 monotherapy in advanced NSCLC patients with high PD-L1 expression (≥50%) compared to platinum-based chemotherapy. We also evaluated efficacy outcomes according to tumor mutational burden (TMB). To that end, we conducted a systematic review. Six clinical trials with 2111 patients were included. In head-to-head comparisons, immunotherapy showed a significant improvement in progression-free survival (PFS: HRpooled = 0.69, 95% CI: 0.52-0.90, p = 0.007), overall survival (OS: HRpooled = 0.69, 95% CI: 0.61-0.78; p < 0.001) and overall response rate (ORR) (Risk ratio (RR)pooled = 1.354, 95% CI: 1.04-1.762, p = 0.024). In the assessment of relative efficacy for PFS through indirect comparisons, pembrolizumab (results from KEYNOTE-024) ranked highest followed by cemiplimab and atezolizumab, with statistical significance determined for some of the drugs. In terms of OS, cemiplimab ranked highest followed by atezolizumab and pembrolizumab, although non-significant OS was determined for these drugs. In conclusion, PD-(L)1 inhibitor mon-otherapy improves efficacy outcomes in the first line setting of advanced NSCLC patients with high PD-L1 expression. Evaluations with longer follow up are still needed to determine the superiority of any specific drug

Automatic speech analysis to early detect functional cognitive decline in elderly population

This study aimed at evaluating whether people with a normal cognitive function can be discriminated from subjects with a mild impairment of cognitive function based on a set of acoustic features derived from spontaneous speech. Voice recordings from 90 Italian subjects (age &gt;65 years; group 1: 47 subjects with MMSE&gt;26; group 2: 43 subjects with 20≤ MMSE ≤26) were collected. Voice samples were processed using a MATLAB-based custom software to derive a broad set of known acoustic features. Linear mixed model analyses were performed to select the features able to significantly distinguish between groups. The selected features (% of unvoiced segments, duration of unvoiced segments, % of voice breaks, speech rate, and duration of syllables), alone or in addition to age and years of education, were used to build a learning-based classifier. The leave-one-out cross validation was used for testing and the classifier accuracy was computed. When the voice features were used alone, an overall classification accuracy of 0.73 was achieved. When age and years of education were additionally used, the overall accuracy increased up to 0.80. These performances were lower than the accuracy of 0.86 found in a recent study. However, in that study the classification was based on several tasks, including more cognitive demanding tasks. Our results are encouraging because acoustic features, derived for the first time only from an ecologic continuous speech task, were able to discriminate people with a normal cognitive function from people with a mild cognitive decline. This study poses the basis for the development of a mobile application performing automatic voice analysis on-the-fly during phone calls, which might potentially support the detection of early signs of functional cognitive decline

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases

Limiting motorboat noise on coral reefs boosts fish reproductive success

Anthropogenic noise impacts are pervasive across taxa, ecosystems and the world. Here, we experimentally test the hypothesis that protecting vulnerable habitats from noise pollution can improve animal reproductive success. Using a season-long field manipulation with an established model system on the Great Barrier Reef, we demonstrate that limiting motorboat activity on reefs leads to the survival of more fish offspring compared to reefs experiencing busy motorboat traffic. A complementary laboratory experiment isolated the importance of noise and, in combination with the field study, showed that the enhanced reproductive success on protected reefs is likely due to improvements in parental care and offspring length. Our results suggest noise mitigation could have benefits that carry through to the population-level by increasing adult reproductive output and offspring growth, thus helping to protect coral reefs from human impacts and presenting a valuable opportunity for enhancing ecosystem resilience

Changes of energy fluxes in marine animal forests of the anthropocene: Factors shaping the future seascape

Climate change is already transforming the seascapes of our oceans by changing the energy availability and the metabolic rates of the organisms. Among the ecosystem-engineering species that structure the seascape, marine animal forests (MAFs) are the most widespread. These habitats, mainly composed of suspension feeding organisms, provide structural complexity to the sea floor, analogous to terrestrial forests. Because primary and secondary productivity is responding to different impacts, in particular to the rapid ongoing environmental changes driven by climate change, this paper presents some directions about what could happen to different MAFs depending on these fast changes. Climate change could modify the resistance or resilience of MAFs, potentially making them more sensitive to impacts from anthropic activities (i.e. fisheries and coastal management), and vice versa, direct impacts may amplify climate change constraints in MAFs. Such changes will have knock-on effects on the energy budgets of active and passive suspension feeding organisms, as well as on their phenology, larval nutritional condition, and population viability. How the future seascape will be shaped by the new energy fluxes is a crucial question that has to be urgently addressed to mitigate and adapt to the diverse impacts on natural systems

Long-term effect of 2 intensive statin regimens on treatment and incidence of cardiovascular events in familial hypercholesterolemia : The SAFEHEART study

Funding: This study was supported by Fundación Hipercolesterolemia Familiar; Grant G03/181 Grant 08-2008 Centro Nacional de Investigaci?n Cardiovascular (CNIC).Background: Maximal doses of potent statins are the basement of treatment of familial hypercholesterolemia (FH). Little is known about the use of different statin regimens in FH. Objectives: The objectives of the study were to describe the treatment changes and low-density lipoprotein cholesterol (LDL-C) goal achievement with atorvastatin (ATV) and rosuvastatin (RV) in the SAFEHEART cohort, as well as to analyze the incidence of atherosclerotic cardiovascular events (ACVEs) and changes in the cardiovascular risk. Methods: SAFEHEART is a prospective follow-up nationwide cohort study in a molecularly defined FH population. The patients were contacted on a yearly basis to obtain relevant changes in life habits, medication, and ACVEs. Results: A total of 1939 patients were analyzed. Median follow-up was 6.6 years (5-10). The estimated 10-year risk according the SAFEHEART risk equation was 1.61 (0.67-3.39) and 1.22 (0.54-2.93) at enrollment for ATV and RV, respectively (P <.001). There were no significant differences at the follow-up: 1.29 (0.54-2.82) and 1.22 (0.54-2.76) in the ATV and RV groups, respectively (P =.51). Sixteen percent of patients in primary prevention with ATV and 18% with RV achieved an LDL-C <100 mg/dL and 4% in secondary prevention with ATV and 5% with RV achieved an LDL-C <70 mg/dL. The use of ezetimibe was marginally greater in the RV group. One hundred sixty ACVEs occurred during follow-up, being its incidence rate 1.1 events/100 patient-years in the ATV group and 1.2 in the RV group (P =.58). Conclusion: ATV and RV are 2 high-potency statins widely used in FH. Although the reduction in LDL-C levels was greater with RV than with ATV, the superiority of RV for reducing ACVEs was not demonstrated

LungBEAM: A prospective multicenter study to monitor stage IV NSCLC patients with EGFR mutations using BEAMing technology

Objectives: The aim of LungBEAM was to determine the value of a novel epidermal growth factor receptor (EGFR) mutation test in blood based on BEAMing technology to predict disease progression in advanced non-small cell lung cancer (NSCLC) patients treated with first- or second-generation EGFR-tyrosine kinase inhibitors (EGFR-TKIs). Another goal was to monitor the dynamics of EGFR mutations, as well as to track EGFR exon 20 p.T790M (p.T790M) resistance during treatment, as critical indicators of therapeutic efficacy and patient survival. Methods: Stage IV NSCLC patients with locally confirmed EGFR-TKI sensitizing mutations (ex19del and/or L858R) in biopsy tissue who were candidates to receive first- or second-generation EGFR-TKI as first-line therapy were included. Plasma samples were obtained at baseline and every 4 weeks during treatment until a progression-free survival (PFS) event or until study completion (72-week follow-up). The mutant allele fraction (MAF) was determined for each identified mutation using BEAMing. Results: A total of 68 of the 110 (61.8%) patients experienced a PFS event. Twenty-six patients (23.6%) presented with an emergent p.T790M mutation in plasma at some point during follow-up, preceding radiologic progression with a median of 76 (interquartile ratio: 54–111) days. Disease progression correlated with the appearance of p.T790M in plasma with a hazard ratio (HR) of 1.94 (95% confidence interval [CI], 1.48–2.54; p < 0.001). The HR for progression in patients showing increasing plasma sensitizing mutation levels (positive MAF slope) versus patients showing either decreasing or unchanged plasma mutation levels (negative or null MAF slopes) was 3.85 (95% CI, 2.01–7.36; p < 0.001). Conclusion: Detection and quantification of EGFR mutations in circulating tumor DNA using the highly sensitive BEAMing method should greatly assist in optimizing treatment decisions for advanced NSCLC patients. © 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd