Analysis of the cost effectiveness of different strategies for the antenatal diagnosis of chromosomal aberrations in cases of ultrasound-identified fetal abnormalities

OBJECTIVE

Principal objective of this work was to analyse the cost effectiveness of different sequences of cytogenetic techniques from the hospital's point of view, after prenatal ultrasound has identified fetal malformations.

METHODS

Cytogenetic tests were performed for each case in 3 strategies, and their results are reported and compared to one reference strategy. Two new simulated strategies were considered: chromosomal microarrays alone and a direct test + CMA.

MAIN OUTCOMES MEASURES

cost-effectiveness ratio.

RESULTS

A single test result was positive in 234 of the 835 pregnancies studied (28%). CMA alone would have identified 239 abnormalities. In the simulated direct test + CMA sequence, the direct test alone would have been positive for 66.1% of the abnormalities identified. When testing was indicated for NT, reference strategy (Direct + karyotyping) costs 1 084.8 euros by positive test results. Strategies Direct + CMA and CMA alone cost respectively 992.7 and 550.0 euros by positive test results. For OUM indications, reference strategy costs 2 937.8 euros by positive test results. Strategies Direct + CMA and CMA alone cost respectively, 2 118.4 and 1 304.7 euros by positive test results.

CONCLUSIONS

CMA appears to be the most effective test for prenatal cytogenetic diagnosis of fetal abnormalities identified by ultrasound.

Current Strategies and Future Directions to Achieve Deep Molecular Response and Treatment-Free Remission in Chronic Myeloid Leukemia

The treatment of chronic myeloid leukemia (CML) has been radically changed by the approval of tyrosine kinase inhibitors (TKIs), which target BCR-ABL1 kinase activity. CML is now managed as a chronic disease requiring long-term treatment and close molecular monitoring. It has been shown that in a substantial number of patients who have achieved a stable deep molecular response (DMR), TKI treatment can be safely discontinued without loss of response. Therefore, treatment-free remission (TFR), through the achievement of a DMR, is increasingly regarded as a feasible treatment goal in many CML patients. However, only nilotinib has approval in this setting and a number of controversial aspects remain regarding treatment choices and timings, predictive factors, patient communication, and optimal strategies to achieve successful TFR. This narrative review aims to provide a comprehensive overview on how to optimize the path to DMR and TFR in patients with CML, and discusses recent data and future directions.

Trophic interactions drive the emergence of diel vertical migration patterns: a game-theoretic model of copepod communities

Diel vertical migration (DVM), the daily movement of organisms through oceanic water columns, is mainly driven by spatio-temporal variations in the light affecting the intensity of predator-prey interactions. Migration patterns of an organism are intrinsically linked to the distribution of its conspecifics, its prey and its predators, each with their own fitness-seeking imperatives. We present a mechanistic, trait-based model of DVM for the different components of a pelagic community. Specifically, we consider size, sensory mode and feeding mode as key traits, representing a community of copepods that prey on each other and are, in turn, preyed upon by fish. Using game-theoretic principles, we explore the optimal distribution of the main groups of a planktonic pelagic food web simultaneously. Within one single framework, our model reproduces a whole suite of observed patterns, such as size-dependent DVM patterns of copepods and reverse migrations. These patterns can only be reproduced when different trophic levels are considered at the same time. This study facilitates a quantitative understanding of the drivers of DVM, and is an important step towards mechanistically underpinned predictions of DVM patterns and biologically mediated carbon export.

Modeling Epidemics Spreading on Social Contact Networks

Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.