Understanding Lung Cancer Related Risk Factors and Their Impact
Understanding Lung Cancer Related Risk Factors and Their Impact
LUCIA aims to develop prediction models for the early diagnosis of lung cancer based on the identification of risk factors and deeper cellular knowledge, by recording real-world data; with risk assessment tools, non-invasive devices and omics analysis. These models will enable new clinical pathways and diagnostic workflow to be implemented to ensure early diagnosis and confirmation, including classification of lung cancer subtype.
Lung cancer is the leading cause of cancer death worldwide, causing more deaths than breast and prostate cancer combined.
The current five-year survival rate after diagnosis of all types of lung cancer in Europe is 13% (11.2% for men and 13.9% for women). The five-year survival rate for some types of lung cancer ranges from 6% to 7% (small cell LC) and 23% to 28% for non-small cell lung cancer (NSCLC).
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. According to principles established in 1968, a screening program should be based on pathology that can be improved through the use of population screening.
The evidence suggests two important gaps in early detection. On the one hand, the identification of risk factors beyond smoking and age. And on the other hand, the only tool for early detection that has been shown to reduce morbidity and mortality in lung cancer is chest CT, a test that may not be sustainable in the long term for many healthcare systems. In parallel, lung cancer diagnoses among never smokers and reduced smokers are increasing rapidly, suggesting that if lung cancer screening research continues focusing only on the heaviest smokers, a gap will persist between the population that performs the test and the population that suffers from the disease.
Evidence also suggests that people undergoing screening are not being optimally referred for follow-up or kept engaged in long-term screening.
Currently there are important deficiencies when it comes to achieving an adequate lung cancer screening program. The incidence in individuals without a history of smoking is increasingly higher. Therefore, an observational, longitudinal, multicenter cohort analytical study will be conducted to determine eligibility for screening based on individualized risk (based on age, a more detailed smoking history, occupational exposure, and other risk factors such as ethnicity and family history of lung cancer) and the development and validation of lung cancer risk predictive models that can improve screening efficiency and reduce lung cancer morbidity and mortality.
These models will allow new clinical pathways and diagnostic workflow to be implemented to ensure rapid diagnosis and confirmation, including lung cancer subtype classification.
The study consists of collecting data from participants in 4 visits over two years. During each visit, the clinical evaluation will be carried out, which will consist of the collection of sociodemographic data and clinical history, physical examination, concomitant medication, collection of exposure data and guide symptoms, Quality of Life questionnaires and geolocation. In addition, the following tests will be performed: low-dose computed tomography (LDCT), blood tests, genomic analysis and tests with new non-invasive devices (spectrometry on card (SPOC), breath analyzer (BAN) and broad-spectrum biomarker sensor patch (WBSP)). With all this, the aim is to develop and validate new tests based on new non-invasive and easy-to-use technologies that allow for the implementation of more efficient, acceptable and equitable population screening programs in the near future.
The completion of this project will allow to provide data that can be used to better understand and discover new risk factors for suffering from lung cancer and therefore improve the management of the disease.
Furthermore, this study will favor the reduction of long-term morbidity and mortality from lung cancer and will allow the future implementation of a lung cancer program.
Inclusion Criteria (for the 3 phases):
Inclusion criteria for Phase 2: Precision Screening:
Inclusion criteria for Phase 3: Diagnosis:
- Patients diagnosed with indeterminate pulmonary nodules or Lung Cancer from the screening phases.
Exclusion Criteria:
eunate.aranaarri@osakidetza.eus+34 944881593 ext. 841593
joneneko.idoyagauribarrena@bio-bizkaia.eus+34 944881593 ext. 841593
Liège, Wallonia 4000, Belgium
j.guiot@chuliege.be+32.4.284.49.01
benoit.ernst@uliege.be
Alvils.Krams@aslimnica.lv
ilmars.stonans@lu.lv+ 371 28655158
eunate.aranaarri@osakidetza.eus+34 944881593 ext. 841593
joneneko.idoyagauribarrena@bio-bizkaia.eus+34 944881593 ext. 841593
david.vicente.sspa@juntadeandalucia.es
cristinasimarro5@gmail.com650307416
luqueluis2@gmail.com