Journal and News Scan

This article reviews recent efforts to evaluate the use of osimertinib, a third-generation EGFR tyrosine kinase inhibitor (TKI), in the neoadjuvant setting for patients with resectable EGFR-mutant non-small cell lung cancer (NSCLC). While adjuvant osimertinib has shown benefits in delaying recurrence, as shown in the ADAURA trial, its effectiveness as a neoadjuvant monotherapy remains under evaluation. The NORA trial, along with the NEOS trial and a U.S.-based study, showed good tolerability and universal R0 resection rates; however, the objective response rates (ORRs) and low pathologic response were modest, especially in patients with nodal disease. 
 
This editorial discusses how these findings suggest that neoadjuvant osimertinib may be insufficient as monotherapy, particularly when compared to immunotherapy-based combinations used in EGFR-wildtype disease. It calls for future trials to refine patient selection, explore combination strategies (e.g., with chemotherapy), and validate surrogate endpoints such as ctDNA clearance or residual viable tumor. 
 
These insights are highly relevant to the CTSNet community, as it informs surgical planning and the integration of targeted therapies in the evolving landscape of personalized lung cancer treatment. 

This article studied the use of both surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR) in patients with low-flow, low-gradient aortic stenosis, including both classical and paradoxical variants of the condition. A total of 131 patients (52 percent) underwent SAVR, while 117 patients (47 percent) underwent TAVR. The outcomes showed comparable results in terms of 20-day mortality, stroke, and the need for pacemaker, suggesting similarities between the two techniques. 

The question of whether minimal invasive extracorporeal circulation (MiECC) represents the optimal perfusion strategy in cardiac surgery remains unanswered. The authors aimed to systematically review the entire literature and thoroughly address the impact of MiECC vs conventional cardiopulmonary bypass (cCPB) on adverse clinical outcomes after cardiac surgery. Major databases, including PubMed, Scopus, and Cochrane, were searched for relevant articles as well as conference proceedings from major congresses up to August 31, 2024. All randomized controlled trials (RCTs) that fulfilled universally accepted MiECC criteria were included in the analysis. The primary outcome was mortality, while morbidity and transfusion requirements were secondary outcomes. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool. All studies that met the outcomes of interest of this systematic review were eligible for synthesis. Of the 738 records identified, 36 RCTs were included in the meta-analysis, with a total of 4,849 patients. MiECC was associated with significantly reduced mortality (OR 0.66; 95 percent CI: 0.53-0.81; p=0.0002; I2=0 percent) as well as risk of postoperative myocardial infarction (OR 0.42; 95 percent CI: 0.26-0.68; p=0.002; I2=0 percent) and cerebrovascular events (OR 0.55; 95 percent CI: 0.37-0.80; p=0.007; I2=0 percent). Additionally, MiECC reduced RBC transfusion requirements, blood loss, and the rate of reexploration for bleeding, along with the incidence of atrial fibrillation. This resulted in significantly reduced durations of mechanical ventilation, ICU, and hospital stay. 

This is the largest meta-analysis published to date, providing robust evidence for the beneficial effect of MiECC in reducing postoperative morbidity and mortality after cardiac surgery and prompts for a wider adoption of this technology. 

This research developed a deep learning algorithm to predict pathological pleural invasion (pPL) from thoracoscopic imagery in patients with cT1 tumors receiving sublobar resections. The study included 80 patients, with the learning model trained on 64 cases and validated on 16. The algorithm's predictive performance was evaluated against surgeons' intraoperative judgments using McNemar's test. The tumor recognition component achieved 78 percent image-level accuracy, while the pPL prediction model demonstrated 69 percent patient-level accuracy compared to the surgeons' 75 percent (P=0.32). While the researchers acknowledge that clinical implementation would require at least 90 percent accuracy, these findings suggest the AI approach shows promise, achieving performance similar to that of surgeons despite the modest dataset size.