Multi-Criteria Decision Making for Medical Device Development

International audienceThe development of a new product is a complicated multi-stakeholder process with a significant risk of failure. This is particularly true in the medical device sector, where there are strict therapeutic, psychological, and normative constraints. This article presents a multi-criteria decision making process called “Define, Prioritize, Measure, and Aggregate” (DPMA). DPMA is designed to help engineering managers in decision making during the development process of new medical devices. The model is based on two sets of criteria linked to business and customer satisfaction. These criteria are weighted using the analytic hierarchy process (AHP) and group decision making (GDM) process. The performance of a medical device is measured according to each criterion. Furthermore, the final score of GO/NO GO alternatives are calculated with the simple additive weighting (SAW) method. A case study for the development of a new kind of femoral implant is presented to demonstrate the implementation of the DPMA process. This study shows that the application of the DPMA process during the design of a 3D printed femoral prosthesis provided engineering managers the key elements and green light to go ahead with the development of this medical device

A Generalized Mechano-Pharmaco-Biological Model For Bone Remodeling Including Cortisol Variation

The process of bone remodeling requires a strict coordination of bone resorption and formation in time and space in order to maintain consistent bone quality and quantity. Bone-resorbing osteoclasts and bone-forming osteoblasts are the two major players in the remodeling process. Their coordination is achieved by generating the appropriate number of osteoblasts since osteoblastic-lineage cells govern the bone mass variation and regulate a corresponding number of osteoclasts. Furthermore, diverse hormones, cytokines and growth factors that strongly link osteoblasts to osteoclasts coordinated these two cell populations. The understanding of this complex remodeling process and predicting its evolution is crucial to manage bone strength under physiologic and pathologic conditions. Several mathematical models have been suggested to clarify this remodeling process, from the earliest purely phenomenological to the latest biomechanical and mechanobiological models. In this current article, a general mathematical model is proposed to fill the gaps identified in former bone remodeling models. The proposed model is the result of combining existing bone remodeling models to present an updated model, which also incorporates several important parameters affecting bone remodeling under various physiologic and pathologic conditions. Furthermore, the proposed model can be extended to include additional parameters in the future. These parameters are divided into four groups according to their origin, whether endogenous or exogenous, and the cell population they affect, whether osteoclasts or osteoblasts. The model also enables easy coupling of biological models to pharmacological and/or mechanical models in the future. (c) 2021 by the authors. Licensee MDPI, Basel, Switzerland

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Bioluminescence-Based Tumor Quantification Method for Monitoring Tumor Progression and Treatment Effects in Mouse Lymphoma Models

International audienceAlthough bioluminescence imaging (BLI) shows promise for monitoring tumor burden in animal models of cancer, these analyses remain mostly qualitative. Here we describe a method for bioluminescence imaging to obtain a semi-quantitative analysis of tumor burden and treatment response. This method is based on the calculation of a luminoscore, a value that allows comparisons of two animals from the same or different experiments. Current BLI instruments enable the calculation of this luminoscore, which relies mainly on the acquisition conditions (back and front acquisitions) and the drawing of the region of interest (manual markup around the mouse). Using two previously described mouse lymphoma models based on cell engraftment, we show that the luminoscore method can serve as a noninvasive way to verify successful tumor cell inoculation, monitor tumor burden, and evaluate the effects of in situ cancer treatment (CpG-DNA). Finally, we show that this method suits different experimental designs. We suggest that this method be used for early estimates of treatment response in preclinical small-animal studies

Mouse models of primary central nervous system lymphomas: tools for basing funding and therapeutic strategies

International audiencePrimary central nervous system lymphomas (PCNSL) include ocular and cerebral lymphomas and are rare aggressive malignancies with poor prognoses. Compared with other lymphomas, they are a challenge for clinicians and scientists, for diagnosis and therapeutic progress and their prognosis remains unsatisfactory, because of the lack of molecular and biological knowledge. Indeed, several limitations of human sample present a major obstacle to the identification of the particular microenvironment of the sanctuary sites where these tumor cells grow. In addition, the generally poor overall condition and performance status of patients with PCNSL limit their participation in prospective trials. Therefore, animal models of PCNSL are essential for tumor microenvironment characterization and for antitumor response studying. In this review, we have compiled the B-and T-cell PCNSL mouse models that are used to improve our understanding of the lymphoma microenvironment, tropism and migration and to investigate novel therapeutic strategies

Preclinical study of Ublituximab, a Glycoengineered anti-human CD20 antibody, in murine models of primary cerebral and intraocular B-cell lymphomas

International audiencePURPOSE: Primary cerebral lymphoma (PCL) and primary intraocular lymphoma (PIOL) belong to the systemic diffuse large B-cell lymphoma family and are characterized by the presence of CD20(+) lymphoma B cells in the brain or the eye. These highly aggressive malignancies have a poor prognosis and no specific therapy. The presence of effector immune cells in the damaged brain and vitreous suggests that treatment with anti-human CD20 (hCD20) monoclonal antibodies might be effective. We developed murine models of PCL and PIOL to assess the intracerebral and intraocular antitumor effect of ublituximab, a promising glycoengineered anti-hCD20 mAb with a high affinity for FcgammaRIIIa (CD16) receptors. METHODS: The murine lymphoma B-cell line A20.IIA-GFP-hCD20 (H-2(d)) was injected into the right cerebral striatum or the vitreous of immunocompetent adult BALB/c mice (H-2(d)). Four to 7 days later, ublituximab was injected intracerebrally or intravitreously into the tumor site. Rituximab was the reference compound. Survival was monitored for injected mice; histopathological and flow cytometric analyses were performed to study tumor growth and T-cell infiltration. RESULTS: Single doses of ublituximab, injected intracerebrally or intravitreously, had a marked antitumor effect, more pronounced than that obtained with the same dose of rituximab in these conditions. The reduction in tumor cells was correlated with an increased proportion of CD8(+) T cells. This efficacy was observed only against lymphoma B cells expressing hCD20. CONCLUSIONS: These in vivo results confirm the potential of the glycoengineered anti-hCD20 mAb ublituximab as an innovative therapeutic approach to treat primary central nervous system lymphoma and other B-cell lymphomas