A Predictive Model for Personalized Therapeutic Interventions in Non-small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) constitutes the most common type of lung cancer and is frequently diagnosed at advanced stages. Clinical studies have shown that molecular targeted therapies increase survival and improve quality of life in patients. Nevertheless, the realization of personalized therapies for NSCLC faces a number of challenges including the integration of clinical and genetic data and a lack of clinical decision support tools to assist physicians with patient selection. To address this problem, we used frequent pattern mining to establish the relationships of patient characteristics and tumor response in advanced NSCLC. Univariate analysis determined that smoking status, histology, epidermal growth factor receptor (EGFR) mutation, and targeted drug were significantly associated with response to targeted therapy. We applied four classifiers to predict treatment outcome from EGFR tyrosine kinase inhibitors. Overall, the highest classification accuracy was 76.56% and the area under the curve was 0.76. The decision tree used a combination of EGFR mutations, histology, and smoking status to predict tumor response and the output was both easily understandable and in keeping with current knowledge. Our findings suggest that support vector machines and decision trees are a promising approach for clinical decision support in the patient selection for targeted therapy in advanced NSCLC.

Maintenance therapy in NSCLC: why? To whom? Which agent?

Maintenance therapy is emerging as a treatment strategy in the management of advanced non small cell lung cancer (NSCLC). Initial trials addressing the question of duration of combination chemotherapy failed to show any overall survival benefit for the prolonged administration over a fixed number of cycles with an increased risk for cumulative toxicity. Nowadays several agents with different ways of administration and a different pattern of toxicity have been formally investigated in the maintenance setting. Maintenance strategies include continuing with an agent already present in the induction regimen or switching to a different one. Taking into consideration that no comparative trials of maintenance with different chemotherapy drugs or targeted agents have been conducted, the choice and the duration of maintenance agents is largely empirical. Furthermore, it is still unknown and it remains an open question if this approach needs to be proposed to every patient in the case of partial/complete response or stable disease after the induction therapy. Here, we critically review available data on maintenance treatment, discussing the possibility to tailor the right treatment to the right patient, in an attempt to optimize costs and benefits of an ever-growing panel of different treatment options.

Maintenance therapy in advanced non-small cell lung cancer: evolution, tolerability and outcomes

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death in the industrialized world. Despite significant progress in early stage disease, survival rates for advanced disease remain low. Maintenance therapy is a treatment strategy that has been investigated extensively in NSCLC and has been the subject of considerable recent debate. Options for maintenance include continuing the initial combination chemotherapy regimen, continuing only single agent chemotherapy ('continuation maintenance') or introducing a new agent ('switch' maintenance therapy). Therapies that have been studied in this setting in randomized trials to date include chemotherapy, molecularly targeted agents and immunotherapy approaches. Following the development of multiple new agents that show activity in NSCLC, and have a tolerable side-effect profile, there has been increasing interest in utilizing them to maintain response to initial therapy after treatment with platinum-based doublets. Despite considerable controversy, it has become an acceptable treatment paradigm. Here, we briefly outline the evolution of this treatment paradigm and examine which subgroups of patients are most likely to benefit.