PatientPredict provides individiaul patient predictions regarding risk of disease and treatment for a disease.

Cancer Risk Predications

Your chance of having the disease in the future.


Cancer Treatment Predications

Your choice of reoccurrence and death based on different treatments.




Medical Prediction

Medical prediction that is not grounded in science is said to be an “art”- but to prognosticate falsely is not artful, for even a beautiful painting speaks a truth; rather, for the physician to pretend to know what he does not, is hurtful – to the patient, to the family, and to medicine. Thus, the necessity of the science of prediction. But the science of prediction is more than the science of the body; it is also the science of mathematics and the art of the healer. Although prediction can only be as accurate as our understanding of disease, it is a high calling because it must also give coherence to disparate collections of disease and patient-related facts and it must be facilely communicated to the patient, through the physician’s words, illustrations, and manner in a way that the patient comprehends.

Further, there can be no effective treatment without prediction, for every application of a therapy contains an implicit prediction of benefit; the physician predicts that the patient will benefit from the therapy. It is immaterial whether the treatment is to reduce the patient’s risk of future disease or to treat an existing malady; these are simply two types of predictions, to the same end – namely, patient benefit.

Thus, medicine is governed by the laws of prediction.

Any statement or action related to a future medical event, usually a clinical outcome, is a prediction. Medical prediction includes: the probability that a patient will exhibit the disease over a specified time interval; the probability that the patient currently has the disease; the predicted outcome of the disease over a specified time interval if the patient is not treated; the prediction of which therapy will provide the greatest benefit to the patient over a specified time interval; and the prediction of whether the patient has benefited at this time from a therapy they previously received.

Until recently medicine had not made highly accurate predictions because: (1) it did not possess powerful predictive factors (biological factors directly related to the disease process), (2) statistical methods seemed far removed from the practice of medicine (they were not integrated into the practice of medicine, and (3) there was no interest in, or mechanism for, providing patient’s with complex medical outcome information that was specific to the individual patient (rather than a group of patients). The rise of molecular biology has resulted in major advances in medicine’s ability to make predictions because of its discovery of biological factors that are directly involved in the disease process and are, therefore, powerful predictors of disease outcomes.

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