Clinical Research Directory

Regorafenib After Failure of Lenvatinib in Patients With Unresectable HCC: The RELEVANT-HCC Trial

The purpose of this clinical trial is to evaluate the efficacy and safety of regorafenib as a subsequent therapy for patients with hepatocellular carcinoma (HCC) who have failed prior lenvatinib treatment. This investigational study aims to assess the therapeutic benefits and safety profile of regorafenib in patients whose disease has progressed following the use of lenvatinib, a targeted therapy for hepatocellular carcinoma

Regorafenib After Treatment Failure of First Line Immune Checkpoint Inhibitor Treatment in Advanced Hepatocellular Carcinoma Patients

Immune checkpoint inhibitor (ICI)-based regimens (atezolizumab+bevacizumab, durvalumab+tremelimumab, nivolumab+ipilimumab) are now a first-line standard for advanced hepatocellular carcinoma (HCC). For Child-Pugh (CP) A patients, regorafenib, cabozantinib, and ramucirumab are approved second-line agents, but there is no approved second-line systemic therapy for CP-B. In CP-B historical controls treated with best supportive care, median progression free survival (PFS) was \~1.4 months in a REACH trial subgroup analysis and \~1.9 months in a CELESTIAL trial subgroup analysis. Regorafenib demonstrated benefit as a post-sorafenib second-line therapy in CP-A patients in the RESORCE trial, but prospective evidence in CP-B is lacking. A multicenter retrospective study of CP-B patients receiving second-line regorafenib after sorafenib reported a median PFS of 1.8 months, and prospective data after ICI-based first-line therapy are not available. This study will evaluate the efficacy and safety of regorafenib as second-line therapy in CP-B patients with disease progression after first-line ICI-based treatment. The primary objective is to demonstrate superiority over historical controls, with PFS as the primary endpoint. After written informed consent, all participants will receive regorafenib. Regorafenib will be administered at 120 mg orally once daily at the same time each day, after a meal with water, for 3 consecutive weeks followed by 1 week off (4-week cycle). Treatment must start within 3 days after screening and will continue until disease progression, unacceptable toxicity, withdrawal of consent, or study termination, whichever occurs first. After treatment discontinuation, patients will be followed every 12 week (+/-7 days) for survival status and subsequent anticancer therapies, and survival follow-up will continue for at least 12 months after enrollment of the last participant.

Genomic and Methylation Markers in SCLC and LCNEC for Chemo-Immunotherapy Resistance Prediction (STRATUS)

The goal of this observational study is to understand how genomic and epigenetic factors contribute to resistance against chemo-immunotherapy in adults diagnosed with extensive-stage small cell lung cancer (ES-SCLC) or metastatic large cell neuroendocrine carcinoma (LCNEC). Both ES-SCLC and LCNEC are aggressive forms of lung cancer with limited treatment options and poor prognosis. While initial responses to chemo-immunotherapy are often promising, most patients develop resistance within a few months, resulting in disease progression and limited survival. This study seeks to explore the molecular and cellular changes that drive resistance, providing insights that could guide more personalized and effective treatment strategies in the future. The study focuses on identifying genomic and methylation signatures, as well as analyzing circulating tumor cells (CTCs) and tumor DNA (ctDNA), to better understand the mechanisms of resistance. By collecting and analyzing these biomarkers over time, researchers aim to identify patterns that distinguish patients who benefit long-term from therapy from those who experience early resistance. These findings may pave the way for new diagnostic tools and therapies to predict and overcome resistance to chemo-immunotherapy. The main questions this study seeks to answer are: Are there specific genomic or methylation patterns that predict resistance to chemo-immunotherapy in ES-SCLC and LCNEC? How are circulating tumor cells (CTCs) and tumor DNA (ctDNA) associated with disease progression, treatment response, and survival? What molecular differences exist between patients who respond long-term and those who develop resistance early in their treatment? Participants will: Provide blood and tumor tissue samples before treatment to establish baseline molecular profiles. Undergo follow-up visits every 9 weeks during treatment, where additional blood samples and imaging tests will be collected to monitor disease progression and treatment response. Optionally provide tissue samples through re-biopsy if the disease progresses, enabling researchers to compare changes in tumor biology over time. All blood and tissue samples will be de-identified and securely stored for genomic and epigenetic analyses. Blood samples will be examined for circulating tumor cells and tumor DNA, while tumor tissue samples will undergo in-depth genomic and methylation profiling. Researchers will use advanced molecular and bioinformatics techniques to uncover specific patterns associated with resistance, aiming to improve current treatment strategies and develop more precise therapies. The study will analyze data from patients over three years, encompassing various stages of treatment and disease progression. By examining longitudinal samples, the study aims to capture the dynamic changes that occur in the tumor microenvironment and how these relate to treatment outcomes. This research is particularly important because current treatment options for ES-SCLC and LCNEC are limited, and there are no established methods to predict which patients will respond to chemo-immunotherapy. Identifying biomarkers of resistance could transform clinical care, allowing oncologists to tailor treatments to individual patients' molecular profiles and improve survival outcomes. Ultimately, the findings from this study could lead to the development of new biomarkers for resistance, improve early detection of treatment failure, and provide the foundation for novel therapies targeting resistant cancer cells. By addressing a critical gap in the understanding of resistance mechanisms, the STRATUS trial has the potential to significantly advance the field of personalized oncology.

Pre-operative Characteristics for Prediction of Supraglottic Airway Failure Using Machine Learning (ERICA)

Supraglottic airway devices (SGA) are a safe and well-established technique for airway management. Nowadays, up to 60% of general anaesthetics performed in European countries use SGA. In 0.2-4.7% SGA fail and require conversion to tracheal tubes. The ERICA study will use artificial intelligence methods to develop a model that can predict the risk of an unplanned SGA conversion based on pre-operative characteristics available during the premedication visit.