Advanced neuroendocrine tumors (NETs) are rare cancers, characterized by prolonged survival (median\>5 years). If five medical options are now approved and 4 others are only recommended, the best sequence is still unknown. No single study on long-term cumulative toxicity of consecutive treatment interventions has been published so far. Taking into account real-world context is required for sound decision- making that cannot be answered by randomized trials. Project objectives and brief description of the methods, which will be used to achieve them: Study team will construct a longitudinal prospective cohort of consecutive non resectable or metastatic NET patients using the GTE-RENATEN network to evaluate the real world cumulative and limiting toxicities. They will expect, as primary endpoint, a difference in survival without limiting (\>grade 1 adverse event according to nci.ctc V5) persistent (\>6 months) toxicity between therapeutics classes or therapeutics sequences in the real life conditions all along the treatments lines, since metastasis diagnosis. All NET primary patients will be enrolled. Patients will be followed until the primary endpoint is reached, death or until 5 years. Based on our pilot study, we plan to enroll 1100 patients to detect 150 events and adjust for 15 cofounders and 10% of lost to follow-up. Cox model adapted to time-related dependency will be used to analyze the data and machine learning will be utilized to take into account the number of confounding factors, interactions and nonlinear relationship. The best model of prediction will be validated in a subgroup of the cohort population. Expected results: Study team will create a tool to help therapeutic decision in order to identify in a given patient the best therapeutic class or sequence with the lowest risk of persistent limiting toxicity.
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Survival without persistent limiting toxicity
Timeframe: "From enrollment to the end of follow up at 5 years"