Predictors of long-term response to abiraterone in patients with metastastic castration-resistant prostate cancer: a retrospective cohort study

We aimed to identify clinical predictors of long-term response to abiraterone (defined as >12 months drug exposure) in a retrospective cohort of metastatic castration-resistant prostate cancer patients treated in post-docetaxel setting at 24 Italian centers. The Cox proportional hazards model was used to analyze the association between clinical features and the duration of drug exposure. Results were expressed as hazard ratios (HR) with associated 95% confidence intervals (CI). A total of 143 patients met the inclusion criteria. Their median age was 73 years, median Gleason score 8 and median abiraterone exposure 20 months. At the univariate analysis, a significant correlation with the duration of abiraterone exposure was found for Gleason score (HR 0.82, 95% CI 0.71-0.96; p=0.012), PSA (HR 1.10, 95% CI 1.03-1.18; p=0.08) and lactic dehydrogenase levels (HR 1.22, 95% CI 1.02-1.46; p=0.027), while the association between lower alkaline phosphatase levels and treatment duration was marginally significant (HR 1.07, 95% CI 0.99-1.16; p=0.074). Only PSA and Gleason score were predictive of long-term treatment duration in the multivariate analysis. No other clinical factors resulted to be predictive of sustained response to abiraterone, including metastatic disease at diagnosis and visceral disease, suggesting that all subgroups of patients may derive a substantial clinical benefit from abiraterone treatment. These findings need to be validated in prospective, larger studies

Stiffness in total knee arthroplasty

Stiffness is a relatively uncommon complication after total knee arthroplasty. It has been defined as a painful limitation in the range of movement (ROM). Its pathogenesis is still unclear even if some risk factors have been identified. Patient-related conditions may be difficult to treat. Preoperative ROM is the most important risk factor, but an association with diabetes, reflex sympathetic dystrophy, and general pathologies such as juvenile rheumatoid arthritis and ankylosing spondylitis has been demonstrated. Moreover, previous surgery may be an additional cause of an ROM limitation. Postoperative factors include infections, arthrofibrosis, heterotrophic ossifications, and incorrect rehabilitation protocol. Infections represent a challenging problem for the orthopaedic surgeon, and treatment may require long periods of antibiotics administration. However, it is widely accepted that an aggressive rehabilitation protocol is mandatory for a proper ROM recovery and to avoid the onset of arthrofibrosis and heterotrophic ossifications. Finally, surgery-related factors represent the most common cause of stiffness; they include errors in soft-tissue balancing, component malpositioning, and incorrect component sizing. Although closed manipulation, arthroscopic and open arthrolysis have been proposed, they may lead to unpredictable results and incomplete ROM recovery. Revision surgery must be proposed in the case of well-documented surgical errors. These operations are technically demanding and may be associated with high risk of complications; therefore they should be accurately planned and properly performed

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project

Potential Role of Tumor-Derived Exosomes in Non-Small-Cell Lung Cancer in the Era of Immunotherapy

Lung cancer, of which non-small-cell lung cancer (NSCLC) represents about 80% of all cases, is the second most common cancer diagnosed in the general population and one of the major causes of cancer-related deaths worldwide. Overall, the outcomes of patients with advanced NSCLC are still disappointing despite advances in diagnosis and treatment. In recent years immune-checkpoint inhibitors (ICIs), administered alone or in combination with chemotherapy, have revolutionized the treatment landscape of patients with advanced non-small-cell lung cancer. However, until now, tissue expression of PD-L1 and tumor mutation burden represent the only available biomarkers for NSCLC patients treated with ICIs. A growing body of evidence showed that tumor-derived exosomes (TDEs) have the PD-L1 protein on their surface and that they are involved in angiogenesis, tumor growth, invasion, metastasis and immune escape. This review focused on the potential clinical applications of TDEs in NSCLC, including their possible role as a biomarker for prognosis and disease monitoring in patients undergoing immunotherapy

Clinical approaches to treat patients with non-small cell lung cancer and epidermal growth factor receptor tyrosine kinase inhibitor acquired resistance

The discovery of epidermal growth factor receptor activating mutations (EGFR Mut+) has determined a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). In several phase III studies, patients with NSCLC EGFR Mut+ achieved a significantly better progression-free survival when treated with a first- (gefitinib, erlotinib) or second-generation (afatinib) EGFR tyrosine kinase inhibitor (TKI) compared with standard chemotherapy. However, despite these impressive results, most patients with NSCLC EGFR Mut+ develop acquired resistance to TKIs. This review will discuss both the mechanisms of resistance to TKIs and the therapeutic strategies to overcome resistance, including emerging data on third-generation TKIs