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Florence Nightingale Colloquium presents Marta Fiocco

vrijdag 11 september 2020
The seminar is targeted at a broad audience, in particular we invite master students, PhD candidates and supervisors interested or involved in the Data Science Research programme as well as colleagues from LIACS and MI to attend. The seminar is organized by the DSO, MI and LIACS.
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Dr. Marta Fiocco Leader of the DASPO (Data Analysis and Survival for Personalised Oncology) group & associate professor at the Mathematical Institute of Leiden University and at Leiden University Medical Centre 

A machine learning approach to study the association between received dose intensity of chemotherapy in cancer trials and survival

In cancer studies, the target received dose intensity (tRDI) of chemotherapy is commonly taken as a proxy for achieved received dose intensity (aRDI), the actual individual dose and time for the regimen. In randomized controlled trials, the gold standard is to analyze treatment effects on patients survival according to the treatment regimen to which patients were allocated (tRDI). However, in practice the actual dose given to a patient may not be equal to the target RDI. This mismatch might be driven by adverse events and unwanted side-effects from the allocated treatment which requires adaptation of the chemotherapy treatment (either delays or dose reductions). Evaluating the mismatch between target and achieved received dose intensity, is crucial to assess study results whenever patients are stratified on allocated treatment. In the first part of the seminar a novel methodology to measure tRDI/aRDI mismatches is presented.

In the second part of the talk a new method to address the association between receiveddose intensity (RDI) and survival outcome at a personalized level is discussed. The effect of RDI on survival has been a central issue in chemotherapy treatment for more than 30 years. There might be a threshold beyond which further increasing of dose intensity provides no additional effect. Investigating the relationship between increased RDI and improved outcome is complicated by the effect of multiple factors such as development of toxicity during treatment. During the talk a possible solution based on a novel, progressively more individualized approach to dose intensity is presented. The motivations for this research was the lack of consensus on the prognostic value of received high dose intensity in osteosarcoma survivorship. In spite of a significant association between high RDI and short-term clinical response, no long-term survival improvement had been shown from treatment intensification in randomized controlled trials so far.

The relevance of this research lies in the use of individual realization of the intended treatment, which depends on individual delays and/or dose reductions reported throughout the treatment. Caution is required to interpret the effect of chemotherapy-regimen on survival outcome at an individual level where the mismatch between target and achieved dose intensity is present.

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