Efficacy and tolerability of bendamustine, bortezomib and dexamethasone in patients with relapsed-refractory multiple myeloma: a phase II study.

Bendamustine demonstrated synergistic efficacy with bortezomib against multiple myeloma (MM) cells in vitro and seems an effective treatment for relapsed-refractory MM (rrMM). This phase II study evaluated bendamustine plus bortezomib and dexamethasone (BVD) administered over six 28-day cycles and then every 56 days for six further cycles in patients with rrMM treated with 4 prior therapies and not refractory to bortezomib. The primary study end point was the overall response rate after four cycles. In total, 75 patients were enrolled, of median age 68 years. All patients had received targeted agents, 83% had 1-2 prior therapies and 33% were refractory to the last treatment. The response ratepartial response (PR) was 71.5% (16% complete response, 18.5% very good PR, 37% partial remission). At 12 months of follow-up, median time-to-progression (TTP) was 16.5 months and 1-year overall survival was 78%. According to Cox regression analysis, only prior therapy with bortezomib plus lenalidomide significantly reduced TTP (9 vs 17 months; hazard ratio=4.5; P=0.005). The main severe side effects were thrombocytopenia (30.5%), neutropenia (18.5%), infections (12%), neuropathy (8%) and gastrointestinal and cardiovascular events (both 6.5%). The BVD regimen is feasible, effective and well-tolerated in difficult-to-treat patients with rrMM.

Modeling the first stages of Cu precipitation in α-Fe using a hybrid atomistic kinetic Monte Carlo approach.

We simulate the coherent stage of Cu precipitation in α-Fe with an atomistic kinetic Monte Carlo (AKMC) model. The vacancy migration energy as a function of the local chemical environment is provided on-the-fly by a neural network, trained with high precision on values calculated with the nudged elastic band method, using a suitable interatomic potential. To speed up the simulation, however, we modify the standard AKMC algorithm by treating large Cu clusters as objects, similarly to object kinetic Monte Carlo approaches. Seamless matching between the fully atomistic and the coarse-grained approach is achieved again by using a neural network, that provides all stability and mobility parameters for large Cu clusters, after training on atomistically informed results. The resulting hybrid algorithm allows long thermal annealing experiments to be simulated, within a reasonable CPU time. The results obtained are in very good agreement with several series of experimental data available from the literature, spanning over different conditions of temperature and alloy composition. We deduce from these results and relevant parametric studies that the mobility of Cu clusters containing one vacancy plays a central role in the precipitation mechanism.

The effect of prolonged irradiation on defect production and ordering in Fe-Cr and Fe-Ni alloys.

The understanding of the primary radiation damage in Fe-based alloys is of interest for the use of advanced steels in future fusion and fission reactors. In this work Fe-Cr alloys (with 5, 6.25, 10 and 15% Cr content) and Fe-Ni alloys (with 10, 40, 50 and 75% Ni content) were used as model materials for studying the features of steels from a radiation damage perspective. The effect of prolonged irradiation (neglecting diffusion), i.e. the overlapping of single 5 keV displacement cascade events, was studied by molecular dynamics simulation. Up to 200 single cascades were simulated, randomly induced in sequence in one simulation cell, to study the difference between fcc and bcc lattices, as well as initially ordered and random crystals. With increasing numbers of cascades we observed a saturation of Frenkel pairs in the bcc alloys. In fcc Fe-Ni, in contrast, we saw a continuous accumulation of defects: the growth of stacking-fault tetrahedra and a larger number of self-interstitial atom clusters were seen in contrast to bcc alloys. For all simulations the defect clusters and the short range order parameter were analysed in detail depending on the number of cascades in the crystal. We also report the modification of the repulsive part of the Fe-Ni interaction potential, which was needed to study the non-equilibrium processes.

Calculation of proper energy barriers for atomistic kinetic Monte Carlo simulations on rigid lattice with chemical and strain field long-range effects using artificial neural networks.

In this paper we take a few steps further in the development of an approach based on the use of an artificial neural network (ANN) to introduce long-range chemical effects and zero temperature relaxation (elastic strain) effects in a rigid lattice atomistic kinetic Monte Carlo (AKMC) model. The ANN is trained to predict the vacancy migration energies as calculated given an interatomic potential with the nudged elastic band method, as functions of the local atomic environment. The kinetics of a single-vacancy migration is thus predicted as accurately as possible, within the limits of the given interatomic potential. The detailed procedure to apply this method is described and analyzed in detail. A novel ANN training algorithm is proposed to deal with the necessarily large number of input variables to be taken into account in the mathematical regression of the migration energies. The application of the ANN-based AKMC method to the simulation of a thermal annealing experiment in Fe-20%Cr alloy is reported. The results obtained are found to be in better agreement with experiments, as compared to already published simulations, where no atomic relaxation was taken into account and chemical effects were only heuristically allowed for.

Self-trapped interstitial-type defects in iron.

Small interstitial-type defects in iron with complex structures and very low mobilities are revealed by molecular dynamics simulations. The stability of these defect clusters formed by nonparallel {110} dumbbells is confirmed by density functional theory calculations, and it is shown to increase with increasing temperature due to large vibrational formation entropies. This new family of defects provides an explanation for the low mobility of clusters needed to account for experimental observations of microstructure evolution under irradiation at variance with the fast migration obtained from previous atomistic simulations for conventional self-interstitial clusters.

Infectious complications in adult acute lymphoblastic leukemia (ALL): experience at one single center.

Literature provides no specific data concerning the type and the risk factors for infection in adult patients with acute lymphoblastic leukemia (ALL). We retrospectively analyzed 97 adult ALL patients who underwent conventional chemotherapy during a 14-year period with the aim to assess the incidence and the factors affecting onset and outcome of infections. We found that during induction therapy 50% of patients developed infection, mainly caused by gram-negative bacteria and with a mortality rate of 11%. In multivariate analysis age > 60 years was significantly associated with more infections (P = 0.04) and higher related mortality (P = 0.03). Moreover, in 22% of patients infectious complications occurred during consolidation or maintenance therapy. Mortality rate of these infections, mostly due to opportunistic pathogens, was 16%. Factors affecting mortality was the cumulative dose of methylprednisolone given during induction therapy ( < or = 2600 mg = 31% vs. > 2600 mg = 69%; P = 0.03). Among neutropenic patients, adults with ALL represent a peculiar population since they frequently develop gram negative infections during induction and opportunistic infections during post-remission treatments. Advanced age and high-dose methylprednisolone result the major risk factors for infection related mortality in the former therapeutic phase and in the latter one, respectively.

Gemcitabine alone or combined with cisplatin in relapsed or refractory multiple myeloma.

Gemcitabine is a pyrimidine nucleoside analog with antitumor activity against solid tumor malignancies and leukemia. We evaluated its activity as a single agent and combining it with cisplatin in relapsed-refractory multiple myeloma (MM). Sixteen patients with advanced MM received intravenous gemcitabine 1250 mg/mq (days 1, 8 and 15) as a single agent for a total of 3 monthly courses. The responders received another three courses, and the non-responders received three courses of gemcitabine 1000 mg/mq (days 1, 8 and 15) plus cisplatin 80 mg/mq (day 1). No grade 4 hematological toxicity was seen after gemcitabine treatment, whereas > or = 3 grade neutropenia and thrombocytopenia were seen in 21 and 13% of the gemcitabine-cisplatin infusions, respectively. Non-hematological toxicity was negligible for both the regimens. After three courses of gemcitabine as a single agent, th e response rate was 31% (1 complete response, 1 partial response and 3 minimal response). Eight patients (50%) achieved stable disease and 3 (19%) had disease progression. Ten patients received gemcitabine-cisplatin and were evaluable for the response. Two patients progressed, four maintained stable disease whereas four patients, unresponsive to gemcitabine, obtained a response (3 partial response and 1 minimal response). With a median follow-up of 13 months (range 8-17.5), 7 patients (44%) died, 5 (31%) had disease progression, 1 (6%) relapsed, 1 was still in partial response (+11 months) and 2 (13%) had a stable disease. Median time to treatment failure (TTF) was 8 months (CI95%: 7.6-8.4) and median overall survival (OS) was 16 months (CI95%: 10-22). These results showed that gemcitabine and gemcitabine-cisplatin were feasible regimens and well tolerated in advanced relapsed-refractory MM. The response rates, the TTF and OS were similar to other salvage chemotherapy regimens; nevertheless, the quality of response was modest particularly after gemcitabine alone. Better results might be obtained combining gemcitabine with other chemotherapy compounds or with biologically based therapies.