Mathematical algorithms with demonstrable clinical utility – the spark for personalized prostate cancer treatment?
Jonathan James | | Quick Read
Prostate cancer is a major malady – in fact, 8 percent of the worldwide cancer burden (1). Primarily a disease of old age, the prognosis for patients is variable; some tumors remain indolent for the rest of a person’s life, whereas others progress relentlessly. Characterizing this diverse disease continues to provide considerable challenges – and David Thurtle, Academic Clinical Fellow in the University of Cambridge’s School of Clinical Medicine, believes the resulting uncertainty hinders patient care. “We wanted to create something objective and standardized, capable of helping men in this difficult position,” he says. Now, in a paper published in PLoS Medicine, Thurtle and his team present a new model – PREDICT – intended to provide a better theoretical basis for clinical decision-making (2).
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