Equivocal evaluation of progressive disease in patients treated with immune checkpoint inhibitors: a challenge for clinical trials and biomarker research

2020 ◽  
pp. 1-4
Author(s):  
Anastasios Kyriazoglou ◽  
Benoit Beuselinck
Keyword(s):  
Clinical Trials ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Progressive Disease ◽  
Checkpoint Inhibitors ◽  
Biomarker Research

Cardiotoxicity of immune checkpoint inhibitors: A systematic review and meta-analysis of randomised clinical trials

2021 ◽  
Vol 148 ◽  
pp. 76-91
Author(s):  
Elisa Agostinetto ◽  
Daniel Eiger ◽  
Matteo Lambertini ◽  
Marcello Ceppi ◽  
Marco Bruzzone ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Randomised Clinical Trials

scholarly journals New drug developments in metastatic gastric cancer

2018 ◽  
Vol 11 ◽  
pp. 175628481880807 ◽  
Author(s):  
Aaron C. Tan ◽  
David L. Chan ◽  
Wasek Faisal ◽  
Nick Pavlakis
Keyword(s):  
Gastric Cancer ◽  
Clinical Trials ◽  
Targeted Therapies ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Treatment Options ◽  
Predictive Biomarkers ◽  
Metastatic Gastric Cancer ◽  
New Era

Metastatic gastric cancer is associated with a poor prognosis and novel treatment options are desperately needed. The development of targeted therapies heralded a new era for the management of metastatic gastric cancer, however results from clinical trials of numerous targeted agents have been mixed. The advent of immune checkpoint inhibitors has yielded similar promise and results from early trials are encouraging. This review provides an overview of the systemic treatment options evaluated in metastatic gastric cancer, with a focus on recent evidence from clinical trials for targeted therapies and immune checkpoint inhibitors. The failure to identify appropriate predictive biomarkers has hampered the success of many targeted therapies in gastric cancer, and a deeper understanding of specific molecular subtypes and genomic alterations may allow for more precision in the application of novel therapies. Identifying appropriate biomarkers for patient selection is essential for future clinical trials, for the most effective use of novel agents and in combination approaches to account for growing complexity of treatment options.

scholarly journals Combinatorial benefit without synergy in recent clinical trials of immune checkpoint inhibitors

2020 ◽  
Author(s):  
Adam C. Palmer ◽  
Benjamin Izar ◽  
Peter K. Sorger
Keyword(s):  
Clinical Trials ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Single Agent ◽  
Combination Therapies ◽  
Anti Tumor Activity

ABSTRACTHundreds of clinical trials are testing whether combination therapies can increase the anti-tumor activity of Immune Checkpoint Inhibitors (ICIs). We find that the benefits of recently reported and approved combinations involving ICIs are fully accounted for by increasing the chance of a single-agent response (drug independence), with no requirement for additive or synergistic efficacy. Thus, the degree of success of combinations involving ICIs with other therapies is largely predictable.

scholarly journals Immune Checkpoint Inhibitors as Monotherapy or Within a Combinatorial Strategy in Advanced Hepatocellular Carcinoma

2020 ◽  
Vol 21 (17) ◽  
pp. 6302
Author(s):  
Michela Guardascione ◽  
Giuseppe Toffoli
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Trials ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Kinase Inhibitors ◽  
Checkpoint Inhibitors ◽  
Target Therapy ◽  
Antiangiogenic Agents ◽  
Advanced Hepatocellular Carcinoma ◽  
Advanced Hcc

In advanced-stage hepatocellular carcinoma (HCC), systemic treatment represents the standard therapy. Target therapy has marked a new era based on a greater knowledge of molecular disease signaling. Nonetheless, survival outcomes and long-term response remain unsatisfactory, mostly because of the onset of primary or acquired resistance. More recently, results from clinical trials with immune targeting agents, such as the immune checkpoint inhibitors (ICIs), have shown a promising role for these drugs in the treatment of advanced HCC. In the context of an intrinsic tolerogenic liver environment, since HCC-induced immune tolerance, it is supported by multiple immunosuppressive mechanisms and several clinical trials are now underway to evaluate ICI-based combinations, including their associations with antiangiogenic agents or multikinase kinase inhibitors and multiple ICIs combinations. In this review, we will first discuss the basic principles of hepatic immunogenic tolerance and the evasive mechanism of antitumor immunity in HCC; furthermore we will elucidate the consistent biological rationale for immunotherapy in HCC even in the presence of an intrinsic tolerogenic environment. Subsequently, we will critically report and discuss current literature on ICIs in the treatment of advanced HCC, including a focus on the currently explored combinatorial strategies and their rationales. Finally, we will consider both challenges and future directions in this field.

Large scale adverse event data mining for targeted therapies development.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2538-2538
Author(s):  
Mayur Sarangdhar ◽  
Bruce Aronow ◽  
Anil Goud Jegga ◽  
Brian Turpin ◽  
Erin Haag Breese ◽  
...  
Keyword(s):  
Data Mining ◽  
Clinical Trials ◽  
Adverse Event ◽  
Big Data ◽  
Real World ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Large Scale ◽  
Checkpoint Inhibitors ◽  
Anaplastic Lymphoma

2538 Background: Targeted anti-cancer small molecule drugs & immune therapies have had a dramatic impact in improving outcomes & the approach to clinical trials. Increasingly, regulatory approvals are expedited with small studies designed to identify strong efficacy signals. However, this may limit the extent of safety profiling. The use of large scale/big data meta-analyses can identify novel safety & efficacy signals in "real-world" medical settings. Methods: We used AERSMine, an open-source data mining platform to identify drug toxicity signatures in the FDA’s Adverse Event Reporting System of 8.6 million patients. We identified patients (n = 732,198) who received either traditional and targeted cancer therapy & identified therapy-specific toxicity patterns. Patients were classified based on exposures: anthracyclines (n = 83,179), platinum (117,993), antimetabolites (93,062), alkylators (81,507), antimicrotubule agents (97,726), HER2 inhibitors (40,040), VEGFis (79,144), VEGF-TKis (90,734), multi TKis (34,457), anaplastic lymphoma Kis (7,635), PI3K-AKT-mTOR inhibitors (33,864), Bruton TKis (9,247), MEKis (4,018), immunomodulatory agents (174,810), proteasome inhibitors (44,681), immune checkpoint inhibitors (20,287). Pharmacovigilance metrics [Relative Risks & safety signals] were used to establish statistical correlation & toxicity signatures were differentiated using the Kolmogorov–Smirnov test. Results: To validate the use of the AERSMine to detect AEs, we focused on cardiotoxicity. It identified classic drug associated AEs (e.g. ventricular dysfunction with anthracyclines, HER2is & VEGFis; VEGFi hypertension & vascular toxicity; multi TKIs vascular events). AERSMine also identified recently reported uncommon toxicities of myositis/myocarditis with immune checkpoint inhibitors. It indicated a higher frequency of myositis/myocarditis with combination immune checkpoint therapy, paralleling industry corporate safety databases. These toxicities were reported at higher frequencies in patients > 65 yrs. Conclusions: AERSMine “big data” analyses provide a sensitive tool to detect potential new patterns of AEs simultaneously across multiple clinical trials & in the real-world setting.

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