Sacituzumab govitecan: breakthrough targeted therapy for triple-negative breast cancer

Introduction: Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype associated with an increased risk of recurrence and cancer-related death. Unlike hormone receptor-positive or HER2-positive breast cancers, there are limited targeted therapies available to treat TNBC and cytotoxic chemotherapy remains the mainstay of treatment. Sacituzumab govitecan (IMMU-132) is an antibody-drug conjugate targeting Trop-2 expressing cells and selectively delivering SN-38, an active metabolite of irinotecan.

Areas covered: This review covers the mechanism of action, safety and efficacy of sacituzumab govitecan in patients with previously treated, metastatic TNBC. Additionally, efficacy data in other epithelial malignancies is included based on a PubMed search for ‘sacituzumab govitecan’ and ‘clinical trial’.

Expert opinion: Sacituzumab govitecan has promising anti-cancer activity in patients with metastatic TNBC previously treated with at least two prior lines of systemic therapy based on a single arm Phase I/II clinical trial. A confirmatory Phase III randomized clinical trial is ongoing. Sacituzumab govitecan has a manageable side effect profile, with the most common adverse events being nausea, neutropenia, and diarrhea. The activity of sacituzumab govitecan likely extends beyond TNBC with promising early efficacy data in many other epithelial cancers, including hormone receptor-positive breast cancer.     

Explicit Finite Element Models Accurately Predict Subject-Specific and Velocity-Dependent Kinetics of Sideways Fall Impact

The majority of hip fractures in the elderly are the result of a fall from standing or from a lower height. Current injury models focus mostly on femur strength while neglecting subject-specific loading. This article presents an injury modeling strategy for hip fractures related to sideways falls that takes subject-specific impact loading into account. Finite element models (FEMs) of the human body were used to predict the experienced load and the femoral strength in a single model. We validated these models for their predicted peak force, effective pelvic stiffness, and fracture status against matching ex vivo sideways fall impacts (n = 11) with a trochanter velocity of 3.1 m/s. Furthermore, they were compared to sideways impacts of volunteers with lower impact velocities that were previously conducted by other groups. Good agreement was found between the ex vivo experiments and the FEMs with respect to peak force (root mean square error [RMSE] = 10.7%, R² = 0.85) and effective pelvic stiffness (R² = 0.92, RMSE = 12.9%). The FEMs were predictive of the fracture status for 10 out of 11 specimens. Compared to the volunteer experiments from low height, the FEMs overestimated the peak force by 25% for low BMI subjects and 8% for high BMI subjects. The effective pelvic stiffness values that were derived from the FEMs were comparable to those derived from impacts with volunteers. The force attenuation from the impact surface to the femur ranged between 27% and 54% and was highly dependent on soft tissue thickness (R² = 0.86). The energy balance in the FEMS showed that at the time of peak force 79% to 93% of the total energy is either kinetic or was transformed to soft tissue deformation. The presented FEMs allow for direct discrimination between fracture and nonfracture outcome for sideways falls and bridge the gap between impact testing with volunteers and impact conditions representative of real life falls. © 2019 American Society for Bone and Mineral Research.     

Is routine extubation overnight safe in cardiac surgery patients?

Objectives

Expedient extubation after cardiac surgery has been associated with improved outcomes, leading to postoperative extubation frequently during overnight hours. However, recent evidence in a mixed medical-surgical intensive care unit population demonstrated worse outcomes with overnight extubation. This study investigated the impact of overnight extubation in a statewide, multicenter Society of Thoracic Surgeons database.

Attentional selectivity,automaticity, and self-efficacy predict simulator-acquired skill transfer to the clinical environment

Introduction

Several studies demonstrated that simulator-acquired skill transfer to the operating room is incomplete. Our objective was to identify trainee characteristics that predict the transfer of simulator-acquired skill to the operating room.