• Giulia Pasello, Alberto Pavan, Ilaria Attili, Alberto Bortolami, Laura Bonanno, Jessica Menis, PierFranco Conte, and Valentina Guarneri.
• Oncology 2, Istituto Oncologico Veneto IRCCS, Padova, Italy. Electronic address: giulia.pasello@iov.veneto.it.
• Cancer Treat. Rev. 2020 Jul 1; 87: 102031.

AbstractImmune checkpoint inhibitors (ICIs) targeting programmed death 1 (PD-1) and PD-ligand 1 (PD-L1) quickly subverted the standard of treatment in Non-Small Cell Lung Cancer (NSCLC), where they were first introduced in all comers previously treated advanced/metastatic NSCLC patients and subsequently in the first line of PD-L1 selected cases of metastatic and locally advanced disease. Treatment algorithm is an evolving landscape, where the introduction of front-line ICIs, with or without chemotherapy, unavoidably influences the following treatment lines. In this context, medical oncologists are currently facing many unclear issues, which have been not clarified so far by available data. Effectiveness and safety in special populations underrepresented in clinical trials - such as elderly, poor PS, hepatitis or human immunodeficiency virus-affected patients - are only a part of the unexplored side of ICIs in the real world. Indeed, pivotal randomized clinical trials (RCTs) often lack of external validity because eligibility criteria exclude some patient subgroups commonly treated in real-world clinical practice. Similarly, cost-effectiveness and sustainability of these innovative agents are important issues to be considered in the real-world. Though affected by several limitations, real-world evidence (RWE) studies allow to collect data regarding overall treated patients in clinical practice according to local authority regulations, overcoming the intrinsic limits of RCTs. The present review focuses on RWE about ICIs in lung cancer treatment, with particular reference to special patient populations, and discusses potential application of real-world data in a potential innovative drug development model.Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

26 keywords...

hide…