Publications by authors named "C Sagan"
Article Synopsis
- Advanced non-small cell lung cancer (NSCLC) patients with high PD-L1 expression (≥ 50%) who are treated with osimertinib showed significantly shorter progression-free survival (PFS) and overall survival (OS) compared to those with lower expression levels, indicating PD-L1 as a negative prognostic factor.
- The study analyzed the effects of PD-L1 expression on survival outcomes in 96 newly diagnosed patients with EGFR mutations receiving osimertinib, with a focus on data collected from May 2018 to November 2022.
- Key findings reveal that higher PD-L1 expression, along with poor performance status and uncommon EGFR mutations, were associated with worse survival outcomes, highlighting the need for careful
Importance: Numerous Black individuals experience racism persistently throughout their lives, with repercussions extending into health care settings. The perspectives of Black individuals regarding emergency department (ED) care, racism, and patient-centered approaches for dismantling structural racism remain less explored.
Objective: To qualitatively explore the perspectives and experiences of Black patients related to race, racism, and health care following a recent ED visit.
Background: Although brain metastases (BM) at diagnosis are common in non-squamous NSCLC patients (ns-NSCLC), they have been mostly excluded from randomized trials. The aim of this retrospective study was to evaluate real-word outcomes of frontline immune checkpoint inhibitor (ICI) in these patients.
Methods: Our study assess the intracranial and overall efficacy of first-line ICI-based therapy compared to chemotherapy (CT) in ns-NSCLC patients diagnosed with BM, showing no targetable alterations.
Article Synopsis
- BRCA1 and BRCA2 genes are essential for repairing DNA damage, and their mutations can predict how sensitive high-grade ovarian cancer (HGOC) is to certain treatments, but current testing methods are expensive and slow.
- This study introduces a deep learning classifier that predicts BRCA mutations using whole slide images of HGOC, developed from a substantial patient cohort, and shows promise in increasing efficiency and accuracy in testing.
- The classifier achieved high performance metrics, suggesting that it can effectively detect phenotypic changes linked to BRCA mutations, making it a potential prescreening tool for future use.