Characteristics, management, and healthcare resources of patients with advanced non-small-cell lung cancer surviving 5 years after nivolumab treatment initiation: A national database analysis.

BACKGROUND: Data on long-term survivors with advanced non-small-cell lung cancer (NSCLC) treated with nivolumab are available from randomized trials. Characteristics, management, and healthcare resources of those patients need to be confirmed with real-world data. METHODS: The UNIVOC retrospective observational study included all patients with advanced NSCLC recorded in the French national hospital database starting nivolumab in 2015 and followed them until December 2020. The Kaplan-Meier method estimated the overall survival (OS). A machine learning approach identified patients with similar treatment sequences. RESULTS: Within the 3,050 patients who had nivolumab initiation,5-year OS rate was 14.6 % (95 %CI 13.3 %-16.2 %). In total, data covering at least 5 years of follow-up were retrieved for 231 surviving patients. Survivors were younger, often female and had fewer comorbidities than non-survivors. Three clusters of patients with different nivolumab treatment durations were identified: 1/ Continuous nivolumab treatment; 2/ Long period of nivolumab treatment followed by chemotherapy or no treatment; 3/ Short period of nivolumab treatment then chemotherapy or no treatment. At 5 years, 61.0 % of survivors were no longer receiving systemic therapy, 26.4 % were treated with nivolumab, 8.7 % chemotherapy, and 3.9 % other immunotherapies. Among 5-y survivor patients, the average number of hospitalisations per patient decreased from 23.4 to 12.8 between the 1st and the 5th year. In the 5th year, 46 % of patients had no more hospitalization for lung cancer. CONCLUSIONS: This large nationwide study confirms the long-term benefit of nivolumab treatment for advanced NSCLC patients in the real-world setting, with a 5-year survival rate similar to that reported in clinical trials.

Machine Learning-Based Analysis of Treatment Sequences Typology in Advanced Non-Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab.

PURPOSE: Immune checkpoint inhibitors substantially changed advanced non-small-cell lung cancer (aNSCLC) management and can lead to long-term survival. The aims of this study were (1) to use a machine learning method to establish a typology of treatment sequences on patients with aNSCLC who were alive 2 years after initiating a treatment with anti-programmed death-ligand 1 monoclonal antibody nivolumab and (2) to describe the patients' characteristics according to the typology of treatment sequences. MATERIALS AND METHODS: This retrospective observational study was based on data from the comprehensive French hospital discharge database for all patients with lung cancer with at least one line of platinum-based chemotherapy, starting nivolumab between January 1, 2015, and December 31, 2016, and alive 2 years after nivolumab treatment initiation. Patients were followed until December 31, 2018. A typology of most common treatment sequences was established using hierarchical clustering with time sequence analysis. RESULTS: Two thousand two hundred twelve study patients were, on average, 63.0 years old, 69.9% of them were men, and 61.9% had a nonsquamous cell carcinoma. During the 2 years after nivolumab treatment initiation, clusters of patients with four basic types of treatment sequences were identified: (1) almost continuous nivolumab treatment (44% of patients); (2) nivolumab most of the time followed by a treatment-free interval or a chemotherapy (15% of patients); and a short or medium nivolumab treatment, followed by (3) a long systemic treatment-free interval (17% of patients) or (4) a long chemotherapy (23% of patients). CONCLUSION: This machine learning approach enabled the identification of a typology of four representative treatment sequences observed in long-term survival. It was noted that most long-term survivors were treated with nivolumab for well over 1 year.