Validation of the ALFA prognostic score in first line ALK translocated non-small cell lung cancer (NSCLC) treated with second generation ALK inhibitors

Lung cancer is one of the most common and serious cancers worldwide. A type called non-small cell lung cancer (NSCLC) accounts for about 85% of all cases. Within NSCLC, a small group of patients—around 3% to 5%—have a change in their cancer cells called an anaplastic lymphoma kinase (ALK) rearrangement. This change makes the cancer grow differently and affects how it responds to certain treatments. People with this type of lung cancer are often younger and may have never smoked.

Over the years, new treatments called ALK inhibitors have helped these patients live longer and better lives. These drugs work by blocking the proteins that allow these tumors to grow. There have been multiple generations of the ALK inhibitors with each new generation improving progression free survival (PFS), the length of time a patient lives without the disease worsening. Newer drugs like brigatinib and alectinib work even better and usually have fewer side effects. A newer option, lorlatinib, also shows strong results. But doctors don’t yet know which drug works best for which patients, because they haven’t been directly compared.

In an earlier project, we looked at patients treated with brigatinib and created a prognostic score—a tool to estimate how long patients live without their cancer getting worse.

We found that this score could help predict outcomes. For example, some patients had an average PFS of over 35 months, while others had much shorter outcomes.

In this new project, we will test that score in a different group of patients who received alectinib instead of brigatinib, using data from the ALEX clinical trial. We will look at how well the score predicts both general PFS and intracranial PFS (how well the cancer is controlled in the brain).

By doing this, we aim to help doctors choose the best treatment for each individual patient based on their specific characteristics, improving care and personalizing treatment plans.