Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk.

Objectives: Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) to analyze differences between patients with LC based on family history of cancer (FHC).
Materials and Methods: From August 2016 to June 2020 clinical information was obtained from Thoracic Tumors Registry (TTR), a nationwide database sponsored by the Spanish Lung Cancer Group. In addition to descriptive statistical analysis, an AI-assisted analysis was performed. The German Technical Information Library supported the merging of data from the electronic medical records and database of the TTR. The results of the AI-assisted analysis were reported using Knowledge Graph, Unified Schema and descriptive and predictive analyses.
Results: Analyses were performed in two phases: first, conventional statistical analysis including 11,684 patients of those 5,806 had FHC. Median overall survival (OS) for the global population was 23 months (CI 95 %: 21.39-24.61) in patients with FHC versus 21 months (CI 95 %: 19.53-22.48) in patients without FHC (NFHC), p < 0.001. The second AI-assisted analysis included 5,788 patients of those 939 had FHC. 58.48 % of women with FHC had LC. 9.53 % of patients had an EGFR or HER2 mutation or ALK translocation and at least one relative with cancer. A family history of LC was associated with an increased risk of smoking-related LC. Non-smokers with a family history of LC were more likely to have an EGFR mutation in NSCLC. In Bayesian network analysis, 55 % of patients with a family history of LC and never-smokers had an EGFR mutation.
Conclusion: In our population, the incidence of LC in patients with a FHC is higher in women and younger patients. FHC is a risk factor and predictor of LC development, especially in people ≤ 50 years. These results were confirmed by conventional statistics and AI-assisted analysis.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Calvo reported receiving personal fees from Roche, Bristol Myers Squibb, Merck Sharp & Dohme, AstraZeneca, Takeda, Pfizer, Sanofi and AMGEN outside the submitted work; being a consultant or advisor and speakerś bureau for Roche, Bristol Myers Squibb/Celgene, Merck Sharp & Dohme, AstraZeneca, Takeda Sanofi and AMGEN and receiving travel, accommodations, and expenses from Takeda, Roche, Bristol Myers Squibb and Merck Sharp & Dohme. Dr. Carcereny reported receiving consulting fees from AstraZeneca, Novartis, Boehringer Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme; payment or honoraria from AstraZeneca, Roche, Boehringer Ingelheim, Bristol Myers Squibb, Pfizer and receiving travel, accommodations, and expenses from Roche, Merck Sharp & Dohme, Takeda, Bristol Myers Squibb and Pfizer. Dr. Cobo reported receiving consulting fees from Novartis, AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Takeda, Pfizer, Kyowa, Sanofi, Jansen; payment or honoraria from Novartis, AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Takeda, Kyowa, Pierre-Fabre, Novocure, Sanofi, Jansen and receiving travel, accommodations, and expenses from AstraZeneca, Boehringer-Ingelheim, Roche, Bristol Myers Squibb, Merck Sharp & Dohme, Lilly, Pierre-Fabre and being advisor for Gilead. Dr. López-Castro reported receiving consulting fees from Takeda, Roche, Pfizer, Novartis, Pierre-Fabre, Bristol Myers Squibb; payment or honoraria from Pfizer, Pierre-Fabre, Takeda, Roche, Novartis Jansen and receiving travel, accommodations, and expenses from Roche, Takeda, Novartis and Merck Sharp & Dohme. Dr. Bernabé reported receiving grant from Roche; payment or honoraria from Roche, Merck Sharp & Dohme, Pfizer, AMGEN, Takeda, Astrazeneca and receiving travel, accommodations, and expenses from Roche, Bristol Myers Squibb and being advisor for Takeda, Roche, Bristol Myers Squibb and Astrazeneca. Dr. Garcia-Campelo reported receiving consulting fees from AMGEN, AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Roche, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Sanofi, Takeda, Pfizer; payment or honoraria from AMGEN, AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Roche, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Sanofi, Takeda and receiving travel, accommodations, and expenses from AstraZeneca, Roche, Pfizer and being advisor for AstraZeneca. Dr. del Barco reported receiving travel, accommodations and expenses from Merck Sharp & Dohme. Dr. Bosch-Barrera reported receiving grants from Pfizer and Roche outside the submitted work; payment or honoraria from Astrazeneca, Pfizer, Merck Sharp & Dohme, Bristol Myers Squibb, Roche, Sanofi and receiving travel, accommodations, and expenses from Merck Sharp & Dohme, Roche and Takeda. Dr. Provencio reported receiving grants from Bristol Myers Squibb, Takeda, Roche, Pfizer, and Merck Sharp & Dohme outside the submitted work; being a consultant or advisor for Bristol Myers Squibb, Roche, Merck Sharp & Dohme, AstraZeneca, and Takeda; being on the speakers’ bureau for Bristol Myers Squibb, Roche, AstraZeneca, and Merck Sharp & Dohme; receiving research funds from Pierre Fabre, Roche, Boehringer Ingelheim, and Bristol Myers Squibb; and receiving travel, accommodations, and expenses from Roche, Bristol Myers Squibb, and AstraZeneca. The remaining authors declare no conflict of interest.
(Copyright © 2024. Published by Elsevier B.V.)