We would like to sincerely thank everyone whose health data is contributing to this research. Without your participation, this study would not be possible. Every contribution helps researchers better understand lung cancer and improve care for patients today and in the future.
Study Name: PREDICT-EGFR
Study type: Retrospective study (i.e., based on medical information already collected in the past, without any changes to your care).
Main objective: To identify criteria that can predict the duration of response to osimertinib treatment in patients with lung cancer harboring an EGFR gene mutation, in order to help physicians better select the most appropriate treatment for each patient.
Number of patients involved: Approximately 300 people.
Country: France (11 hospitals and cancer treatment centers).
Study period: Patients treated through January 1, 2024, are included. The analysis is expected to be completed in the first quarter of 2026.
Impact on your care: None. This study has no direct impact on your care. No treatments will be changed, and no additional tests will be performed.
Responsible institution: Saint-Joseph Hospital Foundation, on behalf of Paris Saint-Joseph and Marie Lannelongue Hospitals
Principal Investigator: Dr. Nadia Guezour
Contact: nguezour@ghpsj.fr — Tel.: 01 44 12 85 10
Technical subcontractor: Lifen (data structuring and pseudonymization as part of the LUCC project)
Framework project: LUCC "Lung Cancer" project, led by the Gustave Roussy Cancer Center
"Non-small cell" lung cancer is the most common type of lung cancer. In some patients (about 10 to 15 out of 100), the tumor has a specific change (called a mutation) in a gene called EGFR (for “Epidermal Growth Factor Receptor”). This mutation is even more common in people who have never smoked (more than 50 out of 100).
In recent years, a drug called osimertinib (a tablet taken orally once daily) has significantly improved the prognosis for people whose tumors carry this mutation. This treatment helps keep the disease under control for a long period of time.
Despite its effectiveness, osimertinib eventually loses its ability to control the disease (this is referred to as tumor progression ).
Recent studies have shown that combining osimertinib with chemotherapy (treatment administered as an infusion in a hospital) can delay this progression. However, this combination also causes:
Currently, doctors lack a reliable tool to determine which patients would truly benefit from adding chemotherapy and which patients could continue with osimertinib alone while maintaining a good quality of life.
That is precisely the goal of this study: to develop a tool (a scoring system) to help doctors choose the best treatment for each patient.
Identify the factors (patient and tumor characteristics) that can predict how long treatment with osimertinib alone will control the disease (known as “progression-free survival”).
The goal is to develop a risk score that can be used to classify patients into two groups:
The study includes adults (18 years of age and older) who meet all of the following criteria:
This does not include individuals under the age of 18, those with another concurrent cancer, or those who have objected to the reuse of their data.
This study is retrospective and multicenter (conducted at multiple hospitals). This means that:
The data comes from the LUCC project (a major lung cancer research initiative). Lifen helps transform the information contained in medical records (radiology, laboratory results, consultations, etc.) into structured data that can be used for research, using supervised, non-generative artificial intelligence tools (meaning they do not create new information: they only extract what is already written in the documents). The results produced by these tools are verified by humans.
All data is pseudonymized: your name and contact information are replaced with a code, so researchers cannot directly identify you.
Some of your medical and administrative data is collected when you are treated in a healthcare facility. This data is useful for the advancement of research.
This research, conducted in the public interest, aims to develop knowledge in order to develop new treatments or improve the overall management of patients suffering from the same disease as you. If you agree to your data being used for this study, you will not have to make any additional visits or undergo any additional examinations.
Only information already in your medical file will be collected. No directly identifying data (surname, first name or contact details) will be included in the cohorts.
Eleven centers in France are participating in this study as part of the LUCC project:
Protecting your personal data is our top priority. Here are the measures we have in place:
No. This study has no direct impact on your care:
If the results of this study make it possible to develop a reliable risk score, future studies could be conducted to:
EGFR — A gene that, when altered (mutated), can promote the growth of lung cancer cells.
Mutation — A change in a gene that can alter how cells behave.
Osimertinib — An oral medication (tablet) that specifically targets cancer cells carrying a mutation in the EGFR gene.
Chemotherapy — A drug treatment (often administered by infusion) that destroys cancer cells, but can also affect normal cells and cause side effects.
Metastasis — The spread of cancer from its original site to other parts of the body.
Progression-free survival — The length of time during which the disease is under control and does not worsen while the patient is receiving treatment.
Pseudonymization — Replacing names and identifying information with a code to protect patients' identities.
Retrospective study — A study that analyzes medical data collected in the past, without any new intervention.
Risk score — A tool used to assess the likelihood of an event occurring (in this case, disease progression), to help doctors make treatment decisions.
