Frailty multi-state models for the analysis of survival data from multicenter clinical trials

Proportional hazards models are among the most popular regression models in survival analysis. Multi-state models generalise them in the sense of jointly considering different types of events along with their interrelations, whereas frailty models introduce random effects to account for unobserved risk factors, possibly shared by groups of subjects. The integration of frailty and multi-state methodology is interesting to control for unobserved heterogeneity in presence of complex event history structures, particularly appealing in multicenter clinical trials applications. In the present thesis we propose the incorporation of nested frailties in the transition-specific hazard function; then, we develop and evaluate both parametric and semi-parametric inference. Simulation studies, performed thanks to an innovative method for generating dependent multi-state survival data, show that parametric inference is correct but extremely imprecise, whilst semiparametric methods are very competitive to evaluate the effect of covariates. Two case studies are presented, relative to cancer multicenter clinical trials. The multi-state nature of the models allows to study the treatment effect taking into account intermediate events, while the presence of frailties reduces the attenuation effect due to clustering. Finally, we present two new software tools, one to fit parametric frailty models with up to twenty possible combinations of baseline and frailty distributions, and one implementing semiparametric inference for multilevel frailty models, essential to fit the new nested frailty multi-state models

Taking AI risks seriously: a new assessment model for the AI Act

The EU Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, we propose applying the risk categories to specific AI scenarios, rather than solely to fields of application, using a risk assessment model that integrates the AIA with the risk approach arising from the Intergovernmental Panel on Climate Change (IPCC) and related literature. This integrated model enables the estimation of AI risk magnitude by considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We illustrate this model using large language models (LLMs) as an example

How to evaluate the risks of Artificial Intelligence: a proportionality-based, risk model for the AI Act

The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI systems (AIs), the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. Our suggestion is to apply the four categories to the risk scenarios of each AIs, rather than solely to its field of application. We address this model flaw by integrating the AIA with the framework arising from the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This makes possible addressing AI risk considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. Then we integrate the proposed model with a proportionality-based balance among values considered by the AIA’s risk analysis. The resulting semi-quantitative approach identifies a more efficient way to implement the AIA and addresses the regulatory issue of general-purpose AI (GPAI)

Lenalidomide normalizes tumor vessels in colorectal cancer improving chemotherapy activity

BACKGROUND: Angiogenesis inhibition is a promising approach for treating metastatic colorectal cancer (mCRC). Recent evidences support the seemingly counterintuitive ability of certain antiangiogenic drugs to promote normalization of residual tumor vessels with important clinical implications. Lenalidomide is an oral drug with immune-modulatory and anti-angiogenic activity against selected hematologic malignancies but as yet little is known regarding its effectiveness for solid tumors. The aim of this study was to determine whether lenalidomide can normalize colorectal cancer neo-vessels in vivo, thus reducing tumor hypoxia and improving the benefit of chemotherapy. METHODS: We set up a tumorgraft model with NOD/SCID mice implanted with a patient-derived colorectal cancer liver metastasis. The mice were treated with oral lenalidomide (50 mg/Kg/day for 28 days), intraperitoneal 5-fluorouracil (5FU) (20 mg/Kg twice weekly for 3 weeks), combination (combo) of lenalidomide and 5FU or irrelevant vehicle. We assessed tumor vessel density (CD146), pericyte coverage (NG2; alphaSMA), in vivo perfusion capability of residual vessels (lectin distribution essay), hypoxic areas (HP2-100 Hypoxyprobe) and antitumor activity in vivo and in vitro. RESULTS: Treatment with lenalidomide reduced tumor vessel density (p = 0.0001) and enhanced mature pericyte coverage of residual vessels (p = 0.002). Perfusion capability of tumor vessels was enhanced in mice treated with lenalidomide compared to controls (p = 0.004). Accordingly, lenalidomide reduced hypoxic tumor areas (p = 0.002) and enhanced the antitumor activity of 5FU in vivo. The combo treatment delayed tumor growth (p = 0.01) and significantly reduced the Ki67 index (p = 0.0002). Lenalidomide alone did not demonstrate antitumor activity compared to untreated controls in vivo or against 4 different mCRC cell lines in vitro. CONCLUSIONS: We provide the first evidence of tumor vessel normalization and hypoxia reduction induced by lenalidomide in mCRC in vivo. This effect, seemingly counterintuitive for an antiangiogenic compound, translates into indirect antitumor activity thus enhancing the therapeutic index of chemotherapy. Our findings suggest that further research should be carried out on synergism between lenalidomide and conventional therapies for treating solid tumors that might benefit from tumor vasculature normalization

Moxetumomab pasudotox in heavily pre-treated patients with relapsed/refractory hairy cell leukemia (HCL): long-term follow-up from the pivotal trial

Background Moxetumomab pasudotox is a recombinant CD22-targeting immunotoxin. Here, we present the long-term follow-up analysis of the pivotal, multicenter, open-label trial (NCT01829711) of moxetumomab pasudotox in patients with relapsed/refractory (R/R) hairy cell leukemia (HCL). Methods Eligible patients had received ≥ 2 prior systemic therapies, including ≥ 2 purine nucleoside analogs (PNAs), or ≥ 1 PNA followed by rituximab or a BRAF inhibitor. Patients received 40 µg/kg moxetumomab pasudotox intravenously on Days 1, 3, and 5 of each 28-day cycle for up to six cycles. Disease response and minimal residual disease (MRD) status were determined by blinded independent central review. The primary endpoint was durable complete response (CR), defined as achieving CR with hematologic remission (HR, blood counts for CR) lasting > 180 days. Results Eighty adult patients were treated with moxetumomab pasudotox and 63% completed six cycles. Patients had received a median of three lines of prior systemic therapy; 49% were PNA-refractory, and 38% were unfit for PNA retreatment. At a median follow-up of 24.6 months, the durable CR rate (CR with HR > 180 days) was 36% (29 patients; 95% confidence interval: 26–48%); CR with HR ≥ 360 days was 33%, and overall CR was 41%. Twenty-seven complete responders (82%) were MRD-negative (34% of all patients). CR lasting ≥ 60 months was 61%, and the median progression-free survival without the loss of HR was 71.7 months. Hemolytic uremic and capillary leak syndromes were each reported in ≤ 10% of patients, and ≤ 5% had grade 3–4 events; these events were generally reversible. No treatment-related deaths were reported. Conclusions Moxetumomab pasudotox resulted in a high rate of durable responses and MRD negativity in heavily pre-treated patients with HCL, with a manageable safety profile. Thus, it represents a new and viable treatment option for patients with R/R HCL, who currently lack adequate therapy.publishedVersio

The italian quaternary volcanism

The peninsular and insular Italy are punctuated by Quaternary volcanoes and their rocks constitute an important aliquot of the Italian Quaternary sedimentary successions. Also away from volcanoes themselves, volcanic ash layers are a common and frequent feature of the Quaternary records, which provide us with potential relevant stratigraphic and chronological markers at service of a wide array of the Quaternary science issues. In this paper, a broad representation of the Italian volcano logical community has joined to provide an updated comprehensive state of art of the Italian Quaternary volcanism. The eruptive history, style and dynamics and, in some cases, the hazard assessment of about thirty Quaternary volcanoes, from the north ernmost Mt. Amiata, in Tuscany, to the southernmost Pantelleria and Linosa, in Sicily Channel, are here reviewed in the light of the substantial improving of the methodological approaches and the overall knowledge achieved in the last decades in the vol canological field study. We hope that the present review can represent a useful and agile document summarising the knowledege on the Italian volcanism at the service of the Quaternary community operating in central Mediterranean area