Conectar
Cardiac surgery remains a high-risk procedure for bleeding despite advances in patient blood management. Conventional centrifugation-based autotransfusion devices primarily recover red blood cells, losing platelets and coagulation factors. The SAME autotransfusion device (i-SEP, Nantes, France) introduces an innovative filtration-based approach, recovering erythrocytes, leucocytes and platelets to enhance perioperative haemostasis. The main objective is to determine whether the filtration-based SAME device reduces significant perioperative bleeding compared with the centrifugation-based system in high-risk cardiac surgery patients.
The Centrifugation-based vs filtration-based intraOperative cell saLvage on qualiTy of peRioperAtive haemostasis iN cardiac surgEry (COLTRANE) trial is a multicentre, parallel-group, single-blinded, superiority-randomised clinical trial. Conducted over 19 months in 10 French hospitals, the study will target patients at high risk of bleeding undergoing on-pump cardiac surgery via sternotomy. A total of 570 patients (285 per group) are required to achieve 80% statistical power for detecting clinically significant differences. Eligible patients will be randomised to either a centrifugation-based or filtration-based autotransfusion group. Both groups will follow standardised perioperative and cardiopulmonary bypass management, with the devices used only intraoperatively. The primary outcome is the proportion of patients with clinically significant perioperative bleeding defined as classes 2 to 4 of the Universal Definition of Perioperative Bleeding. The secondary outcomes include device efficiency and safety, perioperative haemostasis, lengths of intensive care unit and hospital stays, early postoperative morbidity and 30-day all-cause mortality. Ancillary studies will be performed to evaluate cell recovery and washing performance, the viscoelastic properties of retransfused blood (Quantra Qplus; Stago, Asnières-sur-Seine, France), and the effect of salvaged leucocytes on postoperative inflammation and immune function.
This trial has received a favourable opinion from the Committee for the Protection of Persons and authorisation from the French authorities (Comité de protection des personnes Nord Ouest, IDRCB: 2023-A02566-39). Protocol V.1.1 was approved on 22 January 2024. The trial is registered on ClinicalTrials.gov (NCT06425614). The findings will be disseminated through oral communications at national and international scientific meetings and peer-reviewed journal publications. Individual participant data will be made available on reasonable request to qualified researchers, following review and approval by the study sponsor and ethics committee.
ClinicalTrials.gov, NCT06425614.
by Julius Thomas, Lucas Malla, Benard Shibwabo
BackgroundBreast cancer (BC) continues to pose a substantial global health concern, necessitating continuous advancements in therapeutic approaches. Neoadjuvant chemotherapy (NAC) has gained prominence as a key therapeutic strategy, and there is growing interest in the predictive utility of Background Parenchymal Enhancement (BPE) in evaluating the response of breast tumors to NAC. However, the analysis of BPE as a predictive biomarker, along with the techniques used to model BPE changes for accurate and timely predictions of treatment response presents several obstacles. This systematic review aims to thoroughly investigate recent advancements in the analytical methodologies for BPE analysis, and to evaluate their reliability and effectiveness in predicting breast tumor response to NAC, ultimately contributing to the development of personalized and effective therapeutic strategies.
MethodsA comprehensive and structured literature search was conducted across key electronic databases, including Cochrane Database of Systematic Reviews, Google Scholar, PubMed, and IEEE Xplore covering articles published up to May 10, 2024. The inclusion criteria targeted studies focusing on breast cancer cohorts treated with NAC, involving both pre-treatment and at least one post-treatment breast dynamic contrast-enhanced Magnetic Resonance Imaging (DCE-MRI) scan, and analyzing BPE utility in predicting breast tumor response to NAC. Methodological quality assessment and data extraction were performed to synthesize findings and identify commonalities and differences among various BPE analytical approaches.
ResultsThe search yielded a total of 882 records. After meticulous screening, 78 eligible records were identified, with 13 studies ultimately meeting the inclusion criteria for the systematic review. Analysis of the literature revealed a significant evolution in BPE analysis, from early studies focusing on single time-point BPE analysis to more recent studies adopting longitudinal BPE analysis. The review uncovered several gaps that compromise the accuracy and timeliness of existing longitudinal BPE analysis methods, such as missing data across multiple imaging time points, manual segmentation of the whole-breast region of interest, and over reliance on traditional statistical methods like logistic regression for modeling BPE and pathological complete response (pCR).
ConclusionThis review provides a thorough examination of current advancements in analytical approaches for BPE analysis in predicting breast tumor response to NAC. The shift towards longitudinal BPE analysis has highlighted significant gaps, suggesting the need for alternative analytical techniques, particularly in the realm of artificial intelligence (AI). Future longitudinal BPE research work should focus on standardization in longitudinal BPE measurement and analysis, through integration of deep learning-based approaches for automated tumor segmentation, and implementation of advanced AI technique that can better accommodate varied breast tumor responses, non-linear relationships and complex temporal dynamics in BPE datasets, while also handling missing data more effectively. Such integration could lead to more precise and timely predictions of breast tumor responses to NAC, thereby enhancing personalized and effective breast cancer treatment strategies.
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