A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

SIMPLE SUMMARY: The interest in using Machine-Learning (ML) techniques in clinical research is growing. We applied ML to build up a novel prognostic model from patients affected with Mantle Cell Lymphoma (MCL) enrolled in a phase III open-labeled, randomized clinical trial from the Fondazione Italiana Linfomi (FIL)—MCL0208. This is the first application of ML in a prospective clinical trial on MCL lymphoma. We applied a novel ML pipeline to a large cohort of patients for which several clinical variables have been collected at baseline, and assessed their prognostic value based on overall survival. We validated it on two independent data series provided by European MCL Network. Due to its flexibility, we believe that ML would be of tremendous help in the development of a novel MCL prognostic score aimed at re-defining risk stratification. ABSTRACT: Background: Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). Methods: We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0–9.6; High→Int, HR: 2.3, 95% CI: 1.5–4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

N^N^C platinum(II) and palladium(II) cyclometallates of 6,6′-diphenyl-2,2′-bipyridine, L: crystal and molecular structure of [Pd(L–H)Cl]

Reaction of K2[PtCl4] or Na2[PdCl4] with 6,6′-diphenyl-2,2′-bipyridine, L, gives the cyclometallated species [Pt(L–H)Cl], 1, and [Pd(L–H)Cl], 2, respectively, where L–H is a terdentate N^N^C anionic ligand originated by direct activation of a C(sp2)–H bond. The crystal structure of 2 has been solved by X-ray diffraction and compared to that of the analogous complex [Pd(L′–H)Cl] L′ = 6-phenyl-2,2′-bipyridine. The second phenyl ring in 2 entails a considerable distortion of the coordination around the metal. A similar distortion is also to be expected in the analogous compound 1, due to the almost equal covalent radii of palladium(II) and platinum(II). From the complexes 1 and 2 the chloride can be displaced with AgBF4 and substituted by CO or PPh3 to give the corresponding cationic species. By reaction of 1 with Na[BH4] substitution of H− for Cl− can be achieved: the rare hydrido complex [Pt(L–H)H], stabilized only by nitrogen ligands, was isolated in the solid state and fully characterized in solution. It is noteworthy that in the case of the 6-phenyl-2,2′-bipyridine the analogous terminal hydride [Pd(L′–H)H] is unstable. In platinum chemistry the reaction of 6-substituted 2,2′-bipyridines is known to give either N^N^C or N′^C(3) rollover cyclometallation, depending on the nature of the metal precursor. In the case of 6,6′-Ph2-2,2′-bipy cyclometallation was also shown to undergo multiple C–H activation giving the C^N^C pincer complex [Pt(L-2H)(DMSO)]. The latter species can be related to complex 1: indeed its reaction with HCl produces complex 1 and [Pt(L–H)(DMSO)Cl], a rollover species with a pendant phenyl substituent

Comprehensive Geriatric Assessment is an essential tool to support treatment decisions in elderly patients with Diffuse Large B Cell Lymphoma: A prospective multicenter evaluation on 173 patients by the Lymphoma Italian Foundation (FIL)

We performed a multicenter study to validate the concept that a simple comprehensive geriatric assessment (CGA) can identify elderly, non-fi t patients with diff use large B-cell lymphoma (DLBCL) in whom curative treatment is not better then palliation, and to analyze potential benefi ts of treatment modulation after further subdividing the non-fi t category by CGA criteria. One hundred and seventy-three patients aged 69 treated with curative or palliative intent by clinical judgement only were grouped according to CGA into fi t (46%), unfi t (16%) and frail (38%) categories. Two-year overall survival (OS) was signifi cantly better in fi t than in non-fi t patients (84% vs. 47%; p 0.0001). Survival in unfi t and frail patients was not signifi cantly diff erent. Curative treatment slightly improved 2-year OS in unfi t (75% vs. 45%) but not in frail patients (44% vs. 39%). CGA was confi rmed as very effi cient in identifying elderly patients with DLBCL who can benefi t from a curative approach. Further eff orts are needed to better tailor therapies in non-fi t patients

Khorana score and histotype predicts incidence of early venous thromboembolism in Non-Hodgkin lymphomas: A Pooled-Data analysis of 12 clinical trials of fondazione italiana linfomi (FIL)

Current data suggests that the risk of venous thromboembolism (VTE) in patients with non-Hodgkin lymphoma (NHL) is comparable to that observed in patients with solid tumours, although more robust confirmatory analyses are required. With that in mind, we investigated the occurrence of VTE in a pooled analysis of 12 \ue2\u80\u9cFondazione Italiana Linfomi\ue2\u80\u9d (FIL) prospective clinical studies. Specifically, we wished to assess the cumulative incidence of VTE in NHL patients, evaluate the predictive value of the Khorana Score (KS), and identify other potential risk factors for VTEs. Data for VTE occurrence were retrieved from study databases and pharmacovigilance reports. Our analysis includes 1717 patients from 12 prospective phase II and III trials, including newly diagnosed NHL. We observed 53 VTEs (any grade) in 46 patients, with 20 severe VTEs in 17 patients. The cumulative incidences for \ue2\u80\u9eall-grade\ue2\u80\u9c or grade \ue2\u89\ua53 VTEs were 2.9 % (95 % CI: 2.1-3.8) and 1.1 % (95 % CI: 0.6-1.6), respectively. KS categories were positively associated with the risk of VTE of any grade, and with severe events (i. e. grade \ue2\u89\ua53; Gray\ue2\u80\u99s test p-values = 0.048 and 0.012, respectively). Among NHL patients, those with diffuse large B-cell lymphoma (DLBCL) showed a greater risk of (any grade) VTE (HR: 3.42, 95 % CI: 1.32-8.84, p-value = 0.011). Our study indicates that 1) VTE is a relevant complication for NHL patients, 2) KS is predictive of VTE events and 3) DLBCL histotype is an independent risk factor for VTE incidence, for which preventative interventions could be considered

Rituximab plus bendamustine as front-line treatment in frail elderly ( extgreater70 years) patients with diffuse large b-cell non-hodgkin lymphoma: A phase ii multicenter study of the fondazione italiana linfomi

We conducted a phase II study to assess activity and safety profile of bendamustine and rituximab in elderly patients with untreated diffuse large B-cell lymphoma (DLBCL) who were prospectively defined as frail using a simplified version of the Comprehensive Geriatric Assessment (CGA). Patients had to be over 70 years of age, with histologically confirmed DLBCL. Frail patients were those younger than 80 years with a frail profile at CGA or older than 80 years with an unfit profile. Treatment consisted of 4-6 courses of bendamustine [90 mg/m 2 days (d)1-2] and rituximab (375 mg/m 2 d1) administered every 28 days. Other main study end points were complete remission rate and the rate of extra-hematologic adverse events. Forty-nine patients were enrolled of whom 45 were confirmed eligible. Overall, 24 patients achieved a complete remission (53%; 95%CI: 38-68%) and the overall response rate was 62% (95%CI: 47-76%). The most frequent grade 3-4 adverse event was neutropenia (37.8%). Grade 3-4 extra-hematologic adverse events were observed in 7 patients (15.6%; 95%CI: 6.5-29.5%); the most frequent was grade 3 infection in 2 patients. With a median follow up of 33 months (range 1-52), the median progression-free survival was ten months (95%CI: 7-25). The study shows promising activity and manageable toxicity profile of BR combination as first-line therapy for patients with DLBCL who are prospectively defined as frail according to a simplified CGA, as adopted in this trial (clinicaltrials.gov identifier: 01990144)