ABSTRACT
Introduction: Lung cancer is one of the most diagnosed malignancies with increasing incidence worldwide. Immunotherapy is the main oncological treatment for advanced non-small cell lung cancer (NSCLC), for which the discovery of new efficient biomarkers is crucial. Scientific evidence points to the importance of the Lung Immune Prognostic Index (LIPI), but its predictive significance is unclear. Aim: The aim of this study was to investigate the clinical significance and predictive role of LIPI in patients with advanced NSCLC and PD-L1 mutation who are eligible for immunotherapy in combination with chemotherapy. In addition, to our knowledge, this is the first time that the association between COVID-19 infection and the course and outcome of oncologic treatment of NSCLC has been investigated. Patients and Methods: Patients were divided into four study groups according to strictly defined clinical parameters, therapeutic approach, and COVID-19 infection. LIPI was determined and its predictive power was evaluated in all studied groups, as well as overall survival (OS), progression-free survival (PFS), and disease control rate (DCR). Results: This study confirmed the understudied and uncertain predictive power and clinical relevance of LIPI as a biomarker in patients with advanced NSCLC. Patients infected with COVID-19 had a higher survival rate than uninfected patients despite the therapeutic approach, which may be attributed to their hospitalization and intensive medical management during the pandemic. Conclusions: Findings obtained in this study may help to determine treatment options according to the clinical condition of the patient by using LIPI values as a non-invasive, readily available and economically acceptable predictive biomarker in lung oncology.
ABSTRACT
Attitudes towards open peer review, open data and use of preprints influence scientists' engagement with those practices. Yet there is a lack of validated questionnaires that measure these attitudes. The goal of our study was to construct and validate such a questionnaire and use it to assess attitudes of Croatian scientists. We first developed a 21-item questionnaire called Attitudes towards Open data sharing, preprinting, and peer-review (ATOPP), which had a reliable four-factor structure, and measured attitudes towards open data, preprint servers, open peer-review and open peer-review in small scientific communities. We then used the ATOPP to explore attitudes of Croatian scientists (n = 541) towards these topics, and to assess the association of their attitudes with their open science practices and demographic information. Overall, Croatian scientists' attitudes towards these topics were generally neutral, with a median (Md) score of 3.3 out of max 5 on the scale score. We also found no gender (P = 0.995) or field differences (P = 0.523) in their attitudes. However, attitudes of scientist who previously engaged in open peer-review or preprinting were higher than of scientists that did not (Md 3.5 vs. 3.3, P<0.001, and Md 3.6 vs 3.3, P<0.001, respectively). Further research is needed to determine optimal ways of increasing scientists' attitudes and their open science practices.