Pandemia e Infodemia. Informazione, conoscenza, automazione

This article aims to explore the connection between the conflicts in information policies occurring during the present pandemic situation and the potential abuse of automation technologies in the processing of information. From a historical point of view, the connection between an effective elaboration of information and the development of automation technologies has been devised by authors such as Norbert Wiener, Claude Shannon and Alan Turing, at the very beginning of the modern theory of information. This seemed to be justified by historical circumstances that are still quoted in order to discipline and “militarise” the spreading of information during the pandemic. By taking reference to authors such as Gilbert Simondon and Bernard Stiegler, on the contrary, it may be shown that automation cannot by itself guarantee the most appropriate diffusion and sharing of information during a global crisis, whereas, according to these authors, a certain margin of indetermination – freedom and concreteness – must be implemented in any automatic process to let a machine, even the most algorythmic one, work properly and rightly serve the cause of its users

Modelling of tribo-electrostatic separation for industrial by-products recycling

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Lenalidomide Maintenance with or without Prednisone in Newly Diagnosed Myeloma Patients: A Pooled Analysis

We conducted a pooled analysis of two phase III trials, RV-MM-EMN-441 and EMN01, to compare maintenance with lenalidomide-prednisone vs. lenalidomide in newly diagnosed transplant-eligible and -ineligible myeloma patients. Primary endpoints were progression-free survival, progression-free survival 2 and overall survival with both regimens. A secondary aim was to evaluate the impact of duration of maintenance on overall survival and on outcome after relapse. A total of 625 patients (lenalidomide-prednisone arm, n = 315; lenalidomide arm, n = 310) were analyzed. The median follow-up was 58 months. Median progression-free survival (25 vs. 19 months; p = 0.08), progression-free survival 2 (56 vs. 49 months; p = 0.9) and overall survival (73 months vs. NR; p = 0.08) were not significantly different between the two arms. Toxicity profiles of lenalidomide-prednisone and lenalidomide were similar, with the exception of neutropenia that was higher in the lenalidomide arm (grade ≥ 3: 9% vs. 19%, p < 0.001), without an increase in the rate of infections. Overall survival (median NR vs. 49 months, p < 0.001), progression-free survival from relapse (median 35 vs. 24 months, p = 0.004) and overall survival from relapse (median not reached vs. 41 months, p = 0.002) were significantly longer in patients continuing maintenance for ≥2 years. We showed that the addition of prednisone at 25 or 50 mg every other day (eod) to lenalidomide maintenance did not induce any significant advantage

Survival Risk Scores for Real-Life Relapsed/Refractory Multiple Myeloma Patients Receiving Elotuzumab or Carfilzomib In Combination With Lenalidomide and Dexamethasone as Salvage Therapy: Analysis of 919 Cases Outside Clinical Trials

The present study aimed to develop two survival risk scores (RS) for overall survival (OS, SRSKRd/EloRd) and progression-free survival (PFS, PRSKRd/EloRd) in 919 relapsed/refractory multiple myeloma (RRMM) patients who received carfilzomib, lenalidomide, and dexamethasone (KRd)/elotuzumab, lenalidomide, and dexamethasone (EloRd). The median OS was 35.4 months, with no significant difference between the KRd arm versus the EloRd arm. In the multivariate analysis, advanced ISS (HR = 1.31; P = 0.025), interval diagnosis–therapy (HR = 1.46; P = 0.001), number of previous lines of therapies (HR = 1.96; P &lt; 0.0001), older age (HR = 1.72; P &lt; 0.0001), and prior lenalidomide exposure (HR = 1.30; P = 0.026) remained independently associated with death. The median PFS was 20.3 months, with no difference between the two strategies. The multivariate model identified a significant progression/death risk increase for ISS III (HR = 1.37; P = 0.002), &gt;3 previous lines of therapies (HR = 1.67; P &lt; 0.0001), older age (HR = 1.64; P &lt; 0.0001), and prior lenalidomide exposure (HR = 1.35; P = 0.003). Three risk SRSKRd/EloRd categories were generated: low-risk (134 cases, 16.5%), intermediate-risk (467 cases, 57.3%), and high-risk categories (213 cases, 26.2%). The 1- and 2-year OS probability rates were 92.3% and 83.8% for the low-risk (HR = 1, reference category), 81.1% and 60.6% (HR = 2.73; P &lt; 0.0001) for the intermediate-risk, and 65.5% and 42.5% (HR = 4.91; P &lt; 0.0001) for the high-risk groups, respectively. Notably, unlike the low-risk group, which did not cross the median timeline, the OS median values were 36.6 and 18.6 months for the intermediate- and high-risk cases, respectively. Similarly, three PRSKRd/EloRd risk categories were engendered. Based on such grouping, 338 (41.5%) cases were allocated in the low-, 248 (30.5%) in the intermediate-, and 228 (28.0%) in the high-risk groups. The 1- and 2-year PFS probability rates were 71.4% and 54.5% for the low-risk (HR = 1, reference category), 68.9% and 43.7% (HR = 1.95; P &lt; 0.0001) for the intermediate-risk, and 48.0% and 27.1% (HR = 3.73; P &lt; 0.0001) for the high-risk groups, respectively. The PFS median values were 29.0, 21.0, and 11.7 months for the low-, intermediate-, and high-risk cases. This analysis showed 2.7- and 4.9-fold increased risk of death for the intermediate- and high-risk cases treated with KRd/EloRd as salvage therapy. The combined progression/death risks of the two categories were increased 1.3- and 2.2-fold compared to the low-risk group. In conclusion, SRSKRd/EloRd and PRSKRd/EloRd may represent accessible and globally applicable models in daily clinical practice and ultimately represent a prognostic tool for RRMM patients who received KRd or EloRd