  In cancer research there is much interest in building and validating outcome
predicting outcomes to support treatment decisions. However, because most
outcome prediction models are developed and validated without regard to the
causal aspects of treatment decision making, many published outcome prediction
models may cause harm when used for decision making, despite being found
accurate in validation studies. Guidelines on prediction model validation and
the checklist for risk model endorsement by the American Joint Committee on
Cancer do not protect against prediction models that are accurate during
development and validation but harmful when used for decision making. We
explain why this is the case and how to build and validate models that are
useful for decision making.
