In the last few years, several agents targeting molecules that sustain the survival and the proliferation of chronic lymphocytic leukemia (CLL) cells have become clinically available. Most of these ...drugs target surface proteins, such as CD19 or CD20, via monoclonal or bispecific monoclonal antibodies (BsAbs), CAR T cells, intracellular proteins like BTK by using covalent or non-covalent inhibitors or BCL2 with first or second generation BH3-mimetics. Since the management of CLL is evolving quickly, in this review we highlighted the most important innovative treatments including novel double and triple combination therapies, CAR T cells and BsAbs for CLL. Recently, a large number of studies on novel combinations and newer strategic options for CLL therapy have been published or presented at international conferences, which were summarized and linked together. Although the management of treatment with a single continuous agent is easier, the emergence of protein mutations, long-term toxicities and costs are important concerns that favor the use of a fixed duration therapy. In the future, a measurable residual disease (MRD)-guided treatment cessation and MRD-based re-initiation of targeted therapy seems to be a more feasible approach, allowing identification of the patients who might benefit from continuous therapy or who might need a consolidation with BsAbs or CAR T cells to clear the neoplastic clone.
Traders and investors are interested in accurately predicting cryptocurrency prices to increase returns and minimize risk. However, due to their uncertainty, volatility, and dynamism, forecasting ...crypto prices is a challenging time series analysis task. Researchers have proposed predictors based on statistical, machine learning (ML), and deep learning (DL) approaches, but the literature is limited. Indeed, it is narrow because it focuses on predicting only the prices of the few most famous cryptos. In addition, it is scattered because it compares different models on different cryptos inconsistently, and it lacks generality because solutions are overly complex and hard to reproduce in practice. The main goal of this paper is to provide a comparison framework that overcomes these limitations. We use this framework to run extensive experiments where we compare the performances of widely used statistical, ML, and DL approaches in the literature for predicting the price of five popular cryptocurrencies, i.e., XRP, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), and Monero (XMR). To the best of our knowledge, we are also the first to propose using the temporal fusion transformer (TFT) on this task. Moreover, we extend our investigation to hybrid models and ensembles to assess whether combining single models boosts prediction accuracy. Our evaluation shows that DL approaches are the best predictors, particularly the LSTM, and this is consistently true across all the cryptos examined. LSTM reaches an average RMSE of 0.0222 and MAE of 0.0173, respectively, 2.7% and 1.7% better than the second-best model. To ensure reproducibility and stimulate future research contribution, we share the dataset and the code of the experiments.
Complex karyotype (CK) at chronic lymphocytic leukemia (CLL) diagnosis is a negative biomarker of adverse outcome. Since the impact of CK and its subtypes, namely type-2 CK (CK with major structural ...abnormalities) or high-CK (CK with ≥5 chromosome abnormalities), on the risk of developing Richter syndrome (RS) is unknown, we carried out a multicenter real-life retrospective study to test its prognostic impact. Among 540 CLL patients, 107 harbored a CK at CLL diagnosis, 78 were classified as CK2 and 52 as high-CK. Twenty-eight patients developed RS during a median follow-up of 6.7 years. At the time of CLL diagnosis, CK2 and high-CK were more common and predicted the highest risk of RS transformation, together with advanced Binet stage, unmutated (U)-IGHV, 11q-, and TP53 abnormalities. We integrated these variables into a hierarchical model: high-CK and/or CK2 patients showed a 10-year time to RS (TTRS) of 31%; U-IGHV/11q- /TP53 abnormalities/Binet stage B-C patients had a 10-year TTRS of 12%; mutated (M)-IGHV without CK and TP53 disruption a 10-year TTRS of 3% (P<0.0001). We herein demonstrate that CK landscape at CLL diagnosis allows the risk of RS transformation to be refined and we recapitulated clinico-biological variables into a prognostic model.
Short-term electricity markets are becoming more relevant due to less-predictable renewable energy sources, attracting considerable attention from the industry. The balancing market is the closest to ...real-time and the most volatile among them. Its price forecasting literature is limited, inconsistent and outdated, with few deep learning attempts and no public dataset. This work applies to the Irish balancing market a variety of price prediction techniques proven successful in the widely studied day-ahead market. We compare statistical, machine learning, and deep learning models using a framework that investigates the impact of different training sizes. The framework defines hyperparameters and calibration settings; the dataset and models are made public to ensure reproducibility and to be used as benchmarks for future works. An extensive numerical study shows that well-performing models in the day-ahead market do not perform well in the balancing one, highlighting that these markets are fundamentally different constructs. The best model is LEAR, a statistical approach based on LASSO, achieving a mean absolute error of 32.82 €/MWh, surpassing more complex and computationally demanding approaches with errors ranging from 33.71 €/MWh to 44.55 €/MWh.
•We compared a variety of predictive models on the Irish balancing market.•The balancing market is more volatile than the day ahead market.•Statistical and machine learning approaches outperform deep learning ones.•We made the dataset and code available to encourage research in the field.
Secondary antibody deficiencies (SAD) may require immunoglobulin replacement therapy (IgRT). While the intravenous route (IVIG) is broadly considered effective in SAD, the use of subcutaneous ...immunoglobulins (SCIG) is mainly adopted from the experience in primary antibody deficiencies (PAD), where SCIG have been shown to perform as effective as IVIG. However, evidence-based data on SCIG administration in SAD patients are still insufficient. Herein we retrospectively evaluated the efficacy and safety profile of SCIG treatment in 131 SAD patients as compared to a group of 102 PAD patients. We found SCIG being equally effective in reducing annual infectious rate both in SAD and PAD patients. However, SAD patients required lower SCIG dosage and lower IgG through level to achieve similar biological effect in terms of infection burden, at the steady state. SAD patients also showed better correlation between SCIG dose and serum IgG achieved value. Furthermore, within SAD, SCIG were found to work irrespective of the underlying disease. Especially in Non-Hodgkin Lymphoma patients, whose indication to IgRT is still not included in all guidelines and for whom evidence-based data are still lacking, SCIG were as effective as in Chronic Lymphocytic Leukemia or Multiple Myeloma patients, and SCIG discontinuation, without evidence of B cell recovery, led to IgG decline and relapsed infections. Finally, treatment tolerance in SAD patients was comparable to the PAD cohort. Globally, our data suggest that SCIG, as already appreciated in PAD, represent a valuable option in SAD patients, independent on the disease leading to antibody deficiency.
Various neurological complications, affecting both the central and peripheral nervous system, can frequently be experienced by cancer survivors after exposure to conventional chemotherapy, but also ...to modern immunotherapy. In this review, we provide an overview of the most well-known adverse events related to chemotherapy, with a focus on chemotherapy induced peripheral neurotoxicity, but we also address some emerging novel clinical entities related to cancer treatment, including chemotherapy-related cognitive impairment and immune-mediated adverse events. Unfortunately, efficacious curative or preventive treatment for all these neurological complications is still lacking. We provide a description of the possible mechanisms involved to drive future drug discovery in this field, both for symptomatic treatment and neuroprotection.
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