September 7, 2015

New model to predict effectiveness of prostate cancer treatment developed in Finland

Researchers have developed a model in an international competition for which clinical data was obtained from four pharmaceutical companies.
Researchers have developed a model in an international competition for which clinical data was obtained from four pharmaceutical companies.
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A research team led by the University of Turku has developed an innovative model for predicting the outcome of treatment for castration-resistant prostate cancer.

The model was developed for the Prostate Cancer DREAM 9.5 Challenge in which it proved to be the clear winner. The prognosis model is also considered to be a clear improvement on the model currently in use.

The competition called on researchers to develop a model predicting the success of chemotherapy treatment for metastatic castration-resistant prostate cancer (mCRPC). Castration-resistant prostate cancer has a poor prognosis. Several forms of treatment are available but there has been only marginal success in reducing its mortality rate over the past 20 years. The need for new forms of treatment is critical.

The model created by Finnish researchers predicts the survival of the patient suffering from castration-resistant prostate cancer from the initial situation where the patient is receiving chemotherapy. In practice the model predicts which characteristics need to be present in order for the medication to have the desired effect on a specific patient and when this will not occur. The research team included researchers from the University of Turku’s mathematics, statistics, information technology and pharmaceutical development disciplines, as well as from the Institute for Molecular Medicine (FIMM) and the Helsinki University Central Hospital.

According to the competition organisers the new models may be implemented after they have been presented to the American Joint Committee on Cancer (AJCC). The winning model will also be submitted as part of a leading publication.

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