Survival Prediction Model for Palliative Bone Metastasis Radiotherapy
This tool can be used at the time of consultation for palliative radiotherapy to symptomatic bone metastases in order to estimate patient survival
time following consultation. Providers can enter values for the patient, disease, and treatment variables listed below, and a predicted survival
plot will be displayed, based on the Bone Metastases Ensemble Trees for Survival (BMETS) machine learning model (publication pending).
Briefly, the BMETS model was built using a database of 397 patients seen in Radiation Oncology consultation for symptomatic bone metastasis at the
Johns Hopkins Hospital between 2007 and 2013. Each patient’s chart was retrospectively reviewed to collect demographic, disease, and treatment
information felt to be potentially useful in predicting survival. His or her actual survival time following consultation was documented. The BMETS
model was then built using a random survival forests algorithm to predict survival time following consultation based on 27 patient-specific
characteristics.
Enter your patient’s information below. If a value is unknown, leave the entry blank or unselected.
Values marked with
are required fields.
The BMETS model is intended to help health care providers when estimating survival time for patients. The BMETS model is not intended to be a
substitute for medical evaluation, advice, or treatment and should only be used in the context of a clinical discussion with a qualified health
care provider. While the model is calibrated to be as accurate as possible across patients, the predicted survival time may underestimate or overestimate
an individual patient’s actual survival time. This model has undergone internal and limited external validation procedures. However, given the range
of clinical presentations and the rapidly changing nature of health care, the model may produce inaccurate or outdated predictions for specific patients.
Particular caution should be used when applying these data to patient populations that vary significantly from the source population described in the
primary manuscript. As such, health care providers should use their own clinical discretion when interpreting these results for individual patients.
The Johns Hopkins University School of Medicine (JHUSOM) expressly disclaims all representations and warranties related to the BMETS model, including
representations and warranties of accuracy, fitness for use, reliability, validity, or non-infringement of third party intellectual property rights.
JHUSOM does not save user information or other data entered into this web platform. By accepting these terms of use, you are agreeing that JHUSOM will
not be liable for health care decisions or outcomes rendered from the use of the BMETS model.
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Estimated Survival from the Time of Palliative Radiotherapy Consultation
The interactive orange plot above demonstrates the predicted survival curve within the 12 months following radiation oncology consultation for the specific
patient based on the characteristics selected above. The blue curves demonstrate the predicted survival for all other patients with symptomatic bone metastases
in the BMETS database, arranged from lowest (dark blue) to highest (light blue) predicted survival. These blue curves are displayed for comparison purposes and
to demonstrate the effective prediction limits of BMETS. NOTE: The plot displaying the patient’s predicted survival reflects a predicted value from the BMETS
model. While the model is calibrated to be as accurate as possible across all patients within the prediction limits, the predicted survival time may underestimate
or overestimate an individual patient’s actual survival time. PLEASE EXERCISE PARTICULAR CAUTION when interpreting specific survival probability values that fall
close to or outside of the blue curves, as such values may be outside of the BMETS prediction limits. Specifically outside of these prediction limits, the model
tends to overestimate true survival among patients with very low BMETS-predicted survival probabilities at shorter survival times and may underestimate true survival
among patients with higher BMETS-predicted survival probabilities at long survival times.
Click here for a tutorial on using and interpreting output for the predicted survival plot..
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