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Background: Tumor boards constitute the main consensus and clinical decision-making body of multidisciplinary teams (MDTs) in cancer care. With the increasing clinical complexity of treatment options (eg, targeted therapies, multimodal treatments) and the progressive incorporation of new areas of intervention (eg, survivorship care), tumor boards are now required to play a central role in all cancer processes. However, although frameworks are in place to evaluate MDT quality, only few web-based tools are available for this purpose; indeed, no web-based MDT evaluation tools have been developed for or adapted to the Spanish National Health System. Objective: The first aim of this study was to develop a web-based self-assessment model (Autoevaluacion de Equipos Multidisciplinares de Atencion al Cancer [AEMAC]) for evaluating multidisciplinary cancer teams in Spain and the second aim was to validate this tool by testing its metric properties, acceptability, and usability. Methods: We designed and validated the AEMAC program in 3 stages. In the first stage (research), we reviewed the available scientific evidence and performed a qualitative case study of good practice in multidisciplinary care within the Spanish National Health System (n=4 centers and 28 health care professionals). The results were used to define the thematic areas and quality criteria for the self-evaluation model, which were then discussed and validated by a group of experts. The second stage (development) involved the technological development of a web app that would be accessible from any mobile device. In the third stage (piloting and validation), we conducted 4 pilot tests (n=15 tumor boards, 243 professionals) and used the results to analyze the acceptability and usefulness of the tool. Results: We designed a self-assessment model based on 5 thematic areas encompassing a total of 25 quality components, which users rated on a 3-option development scale. The evaluation process, which was managed entirely from the web app, consisted of individual self-assessment, group prioritization, and creation of an improvement plan. Cronbach alpha (.86), McDonald's omega (0.88), and various fit indices (comparative fit index between 0.95 and 1 and goodness-of-fit index between 0.97 and 0.99 for all 5 aspects) confirmed internal consistency. The mean rating for overall satisfaction with the tool and for consistency between the content of the tool and the reality of tumor boards was 7.6 out of 10. Conclusions: The results obtained during the period of research and piloting of the AEMAC program showed that it has an appropriate structure and metric properties and could therefore be implemented in a real context and generalized to other hospitals. As a virtual tool, it helps to measure the key aspects of MDT quality, such as effectiveness of collaboration and communication, leadership, and the organizational environment.

As there is now a growing interest in mHealth apps for cancer patients, we here present and test the Lalaby App to monitor lung cancer patients' Quality of life (QoL) through mobile sensors and integrated questionnaires. The app was used in a 2-week study to register two lung cancer patients' activity without problems or interruptions. The patients frequently reported activities, symptoms, and questionnaires, indicating their engagement with the app. They registered their experience through the UEQ-S integrated into the app. Patient 1 mainly reported a neutral experience, while Patient 2 found it highly positive. They considered the app leading-edge and helpful and would recommend it to others, while both patients valued it positively (3.72 and 4.64 on a scale of 1-5). The app's aesthetics and its notifications helped their engagement. We found correlations between sensors' data and patients' QoL. We also detected QoL and functional status variations after treatment for both patients. After a "Tasks Test," two oncologists assessed the app's dashboard usability as excellent (SUS scores 85 and 87.5 on a 0-100 scale), easy-to-use and helpful. Their experience was positive (UEQ-S overall scale 2.81 (mean), -3 to +3 scale). The app allows monitoring the QoL of lung cancer patients remotely and in real-time while controlling patients' experience to stop the use if necessary, avoiding overwhelm.

[EN] Finding angiogenic prognostic markers in advanced non-small-cell lung cancer is still an unmet medical need. We explored a set of genetic variants in the VEGF-pathway as potential biomarkers to predict clinical outcomes of patients with non-small-cell lung cancer treated with chemotherapy plus bevacizumab. We prospectively analyzed the relationship between VEGF-pathway components with both pathological and prognostic variables in response to chemotherapy plus bevacizumab in 168 patients with non-squamous non-small-cell lung cancer. Circulating levels of VEGF and VEGFR2 and expression of specific endothelial surface markers and single-nucleotide polymorphisms in VEGF-pathway genes were analyzed. The primary clinical endpoint was progression-free survival. Secondary endpoints included overall survival and objective tumor response. VEGFR-1 rs9582036 variants AA/AC were associated with increased progression-free survival (p = 0.012 and p = 0.035, respectively), and with improved overall survival (p = 0.019) with respect to CC allele. Patients with VEGF-A rs3025039 harboring allele TT had also reduced mortality risk (p = 0.049) compared with the CC allele. The VEGF-A rs833061 variant was found to be related with response to treatment, with 61.1% of patients harboring the CC allele achieving partial treatment response. High pre-treatment circulating levels of VEGF-A were associated with shorter progression-free survival (p = 0.036). In conclusion, in this prospective study, genetic variants in VEGFR-1 and VEGF-A and plasma levels of VEGF-A were associated with clinical benefit, progression-free survival, or overall survival in a cohort of advanced non-squamous non-small-cell lung cancer patients receiving chemotherapy plus antiangiogenic therapy., The authors thank Drs. Blanca Piedrafita and Vanessa Marfil at Medical Statistics Consulting for medial writing services. RR also wish to acknowledge the support by the Asociacion Espanola Contra el Cancer (AECC).