Early peripheral clearance of leukemia-associated immunophenotypes in AML: centralized analysis of a randomized trial

Although genetics is a relevant risk factor in acute myeloid leukemia (AML), it can be minimally informative and/or not readily available for the early identification of patients at risk for treatment failure. In a randomized trial comparing standard vs high-dose induction (ClinicalTrials.gov 64NCT00495287), we studied early peripheral blast cell clearance (PBC) as a rapid predictive assay of chemotherapy response to determine whether it correlates with the achievement of complete remission (CR), as well as postremission outcome, according to induction intensity. Individual leukemia-associated immunophenotypes (LAIPs) identified pretherapy by flow cytometry were validated and quantified centrally after 3 days of treatment, expressing PBC on a logarithmic scale as the ratio of absolute LAIP1 cells on day 1 and day 4. Of 178 patients, 151 (84.8%) were evaluable. Patients in CR exhibited significantly higher median PBC (2.3 log) compared with chemoresistant patients (1.0 log; P<.0001). PBC<1.0 predicted the worst outcome (CR, 28%). With 1.5 log established as the most accurate cutoff predicting CR, 87.5% of patients with PBC .1.5 (PBChigh, n = 96) and 43.6% of patients with PBC 641.5 (PBClow, n = 55) achieved CR after single-course induction (P<.0001). CR and PBChigh rates were increased in patients randomized to the high-dose induction arm (P 5 .04) and correlated strongly with genetic/cytogenetic risk. In multivariate analysis, PBC retained significant predictive power for CR, relapse risk, and survival. Thus, PBC analysis can provide a very early prediction of outcome, correlates with treatment intensity and disease subset, and may support studies of customized AML therapy

Shedding light on typical species : implications for habitat monitoring

Habitat monitoring in Europe is regulated by Article 17 of the Habitats Directive, which suggests the use of typical species to assess habitat conservation status. Yet, the Directive uses the term “typical” species but does not provide a definition, either for its use in reporting or for its use in impact assessments. To address the issue, an online workshop was organized by the Italian Society for Vegetation Science (SISV) to shed light on the diversity of perspectives regarding the different concepts of typical species, and to discuss the possible implications for habitat monitoring. To this aim, we inquired 73 people with a very different degree of expertise in the field of vegetation science by means of a tailored survey composed of six questions. We analysed the data using Pearson's Chi-squared test to verify that the answers diverged from a random distribution and checked the effect of the degree of experience of the surveyees on the results. We found that most of the surveyees agreed on the use of the phytosociological method for habitat monitoring and of the diagnostic and characteristic species to evaluate the structural and functional conservation status of habitats. With this contribution, we shed light on the meaning of “typical” species in the context of habitat monitoring

A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease

Background: Mechanisms of myocardial ischemia in obstructive and non-obstructive coronary artery disease (CAD), and the interplay between clinical, functional, biological and psycho-social features, are still far to be fully elucidated. Objectives: To develop a machine-learning (ML) model for the supervised prediction of obstructive versus non-obstructive CAD. Methods: From the EVA study, we analysed adults hospitalized for IHD undergoing conventional coronary angiography (CCA). Non-obstructive CAD was defined by a stenosis < 50% in one or more vessels. Baseline clinical and psycho-socio-cultural characteristics were used for computing a Rockwood and Mitnitski frailty index, and a gender score according to GENESIS-PRAXY methodology. Serum concentration of inflammatory cytokines was measured with a multiplex flow cytometry assay. Through an XGBoost classifier combined with an explainable artificial intelligence tool (SHAP), we identified the most influential features in discriminating obstructive versus non-obstructive CAD. Results: Among the overall EVA cohort (n = 509), 311 individuals (mean age 67 ± 11 years, 38% females; 67% obstructive CAD) with complete data were analysed. The ML-based model (83% accuracy and 87% precision) showed that while obstructive CAD was associated with higher frailty index, older age and a cytokine signature characterized by IL-1β, IL-12p70 and IL-33, non-obstructive CAD was associated with a higher gender score (i.e., social characteristics traditionally ascribed to women) and with a cytokine signature characterized by IL-18, IL-8, IL-23. Conclusions: Integrating clinical, biological, and psycho-social features, we have optimized a sex- and gender-unbiased model that discriminates obstructive and non-obstructive CAD. Further mechanistic studies will shed light on the biological plausibility of these associations. Clinical trial registration: NCT02737982

Cost of implementing CAR-T activity and managing CAR-T patients: an exploratory study

BackgroundChimeric antigen receptor T cells (CAR-T) represent an innovation but raise issues for healthcare payers because of the uncertainty on impact at market launch, high cost and important organisational impact. The literature has focused on their assessment, appraisal and market access solutions. No evidence on the costs sustained to implement CAR-T is available and a few studies reported the cost of the CAR-T clinical pathway, including the activities that are remunerated through inpatient or outpatient fee-for-service/episode. This paper aims at filling the information gap, assessing the cost of implementing CAR-T activity and the full cost of managing the CAR-T clinical pathway.MethodsCost analysis relied on the Activity Based Costing approach, which was applied to two Italian healthcare organisations, both CAR-T Centres authorized by the regional governments with a minimum of 20 patients treated with the first two CAR-T therapies launched on the market.ResultsThe cost of implementing CAR-T was estimated at euro1.31 million (calculated for one of the organizations with complete data). Most of these costs (77%) were generated by quality assurance activity. The mean cost per patient entering the CAR-T pathway (59 and 27) and surviving at follow-up (21 and 5) ranges from euro48K to euro57K and from euro96K to euro106K, respectively. Fees for hospitalization and infusion of gene therapy accounts for more than 70% of these costs. The actual hospitalisation cost varies greatly across patients and is in general lower than the fee-for-episode paid by the region to the hospital.ConclusionsDespite its limitations (exploratory nature; the time spent by staff on activities which are not remunerated through fees was estimated through interviews with the CAR-T coordinators; cost items are not fully comparable), this research highlighted the relevant organisational and economic impact of CAR-T and provided important insights for policy makers and healthcare managers: the necessity to invest resources in CAR-T implementation; the need for assessing activities which are not remunerated through fees for service / episode; the opportunity to shift from fee-for-episode / service to bundled payments for CAR-T clinical pathway