TY - JOUR
T1 - How to build and interpret a nomogram for cancer prognosis
AU - Iasonos, Alexia
AU - Schrag, Deborah
AU - Raj, Ganesh V.
AU - Panageas, Katherine S.
PY - 2008/3/10
Y1 - 2008/3/10
N2 - Nomograms are widely used for cancer prognosis, primarily because of their ability to reduce statistical predictive models into a single numerical estimate of the probability of an event, such as death or recurrence, that is tailored to the profile of an individual patient. User-friendly graphical interfaces for generating these estimates facilitate the use of nomograms during clinical encounters to inform clinical decision making. However, the statistical underpinnings of these models require careful scrutiny, and the degree of uncertainty surrounding the point estimates requires attention. This guide provides a nonstatistical audience with a methodological approach for building, interpreting, and using nomograms to estimate cancer prognosis or other health outcomes.
AB - Nomograms are widely used for cancer prognosis, primarily because of their ability to reduce statistical predictive models into a single numerical estimate of the probability of an event, such as death or recurrence, that is tailored to the profile of an individual patient. User-friendly graphical interfaces for generating these estimates facilitate the use of nomograms during clinical encounters to inform clinical decision making. However, the statistical underpinnings of these models require careful scrutiny, and the degree of uncertainty surrounding the point estimates requires attention. This guide provides a nonstatistical audience with a methodological approach for building, interpreting, and using nomograms to estimate cancer prognosis or other health outcomes.
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U2 - 10.1200/JCO.2007.13.5913
DO - 10.1200/JCO.2007.13.5913
M3 - Review article
C2 - 18285606
AN - SCOPUS:51349142764
SN - 0732-183X
VL - 26
SP - 1346
EP - 1354
JO - Journal of Clinical Oncology
JF - Journal of Clinical Oncology
IS - 8
ER -