Mathematical models for the prediction of resistances and treatment optimization in pediatric lymphoblastic leukemias (LLAMAT).
Acute lymphoblastic leukemias (ALL) are the most frequent type of cancer in children. Current treatments have improved survival to 80% of diagnosed patients but there are still many children dying of this disease. LLAMAT’s study intends to gather more quantitative data on the disease, both at diagnosis and during follow-up, to better monitor its evolution, predict potential relapses and optimize the therapeutic combinations used.
Where is it being implemented?
The protocol has been approved and is running at Hospital de Jerez (Cádiz), Hospital Virgen de la Arrixaca (Murcia), Hospital Virgen del Rocío (Seville), Hospital del Niño Jesús (Madrid), Hospital Virgen de las Nieves (Granada), Hospital Virgen de la Salud (Toledo), and others.
What data do we collect?
Our collaborators collect retrospectively the data used routinely for the integrated diagnosis of ALLs. Also, the raw flow-cytometry data are being collected since this contains a lot of biological information (6-10 markers of 100,000 – 1,000,000 cells) that is not exploited in full.
What are the expected benefits for patients?
The idea is to explore whether novel mathematical algorithms can be used to develop prognoses and predictive biomarkers on ALL based on the data, specifically for improving the initial patient classification. Also, to design personalized treatment schedules and/or combinations that could either avoid relapses or diminish toxicity in patients with favorable prognoses.
When will the results be available?
Protocol has been approved and the first papers providing biomarkers of relapse on diagnosis have been published in 2020 and 2021.
