Selecting the best cancer risk prediction models [ 2017 - ]

Also known as: 5016123

Research Grant

[Cite as]

Researchers: Dr Robert MacInnis (Principal investigator) ,  A/Pr Roger Milne Dr Mary Beth Terry Dr Tu Nguyen-Dumont Prof Ingrid Winship

Brief description Risk prediction models incorporating multiple risk factors (including genetic markers) are a recognised method to identify individuals at high risk of developing breast or colorectal cancer, but it is uncertain which model(s) currently perform best in a population setting. We aim to compare the predictive ability of each available model. Knowing which model performs best will facilitate early diagnosis, reduce overall costs by better targeting interventions and improve cancer survival.

Funding Amount $509,601.00

Funding Scheme Project Grants

Notes Standard Project Grant

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