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Russian mathematicians develop children cancer treatment model

December 22, 2015, 18:33 UTC+3 MOSCOW

According to a researcher, the procedure they have developed can be easily adapted to any subgroup analysis, and is not limited to hematology and medicine

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© Donat Sorokin/ITAR-TASS

MOSCOW, December 22. /TASS/. Mathematicians from Russian High School of Economics (HSE) have developed a model which can help treat children cancer, Sergei Kuznetsov, head of the HSE School of Data Analysis and Artificial Intelligence, told TASS.

Alexander Karachunsky, deputy director for Research of the Federal Research Center of Pediatric Hematology, Oncology, and Immunology (the Dmitry Rogachev Center) contacted the HSE School of Data Analysis and Artificial Intelligence in 2011, he said.

"He expressed hope that HSE mathematicians and programmers could help doctors with data analysis and modeling of disease progression and treatment response. And he asked us to find out why certain drugs and therapies help some patients, but don’t help others others. The medics were interested in how the treatment response might vary depending on the patient's physiology, such as the state of the internal organs and blood, and the role of genetics," Kuznetsov said.

A team of HSE mathematicians was asked to systematize and analyze patients' personal data to inform better treatment choices. The researchers set out to develop a methodology for identifying patient subgroups with significant differences in terms of response to certain treatments, specifically two types of chemotherapy. The study compared patients with similar physiological profiles receiving different types of treatment.

The study was based on data from 1,773 patients aged under 18 and diagnosed with acute lymphoblastic leukemia. The calculation takes into account the patient' gender, age at the moment of diagnosis, status of internal organs (liver, spleen, central nervous system) and other factors. Mathematical modeling helps to identify any links between different combinations of these characteristics and their correlation with the treatment effect.

The researchers came up with a procedure for identifying patient subgroups responding differently to two types of treatment. "Identifying smaller groups with significant differences between them is fairly easy, but only clinical trials can fully confirm the hypotheses," Kuznetsov said. Conducting such clinical trials is the key objective of the Center's medics today. In addition to this, the researchers are now addressing a few remaining questions, for example, how to modify the process for comparing three or more different treatment strategies, how to take into account adverse events such as recurrence and metastasis, and others. According to Kuznetsov, the procedure they have developed can be easily adapted to any subgroup analysis, and is not limited to hematology and medicine.

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