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Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction
David M Kurtz1, Mohammad S Esfahani2, Florian Scherer2
1Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA.
Cell
|July 9, 2019
Summary
This study introduces the Continuous Individualized Risk Index (CIRI), a novel method for dynamic cancer outcome prediction. CIRI improves personalized medicine by integrating real-time patient data for more accurate risk assessments.
Area of Science:
- Oncology
- Biostatistics
- Computational Biology
Background:
- Accurate long-term outcome prediction in cancer is challenging.
- Traditional models rely on pretreatment factors due to difficulties in serial tumor sampling.
- Advancements in non-invasive diagnostics enable serial tumor assessments.
Purpose of the Study:
- To introduce the Continuous Individualized Risk Index (CIRI) for dynamic, real-time outcome probability determination.
- To demonstrate CIRI's improved predictive accuracy compared to conventional models.
- To showcase CIRI's utility in developing predictive biomarkers for personalized therapy selection.
Main Methods:
- Developed CIRI, a dynamic risk assessment method integrating longitudinal risk predictors.
- Applied CIRI to diffuse large B cell lymphoma patient data.
- Validated CIRI's utility in chronic lymphocytic leukemia and breast adenocarcinoma models.
Main Results:
- CIRI demonstrated improved outcome prediction accuracy in diffuse large B cell lymphoma.
- The method showed broader applicability across different cancer types.
- Proof-of-concept analysis illustrated CIRI's potential for predictive biomarker development.
Conclusions:
- CIRI offers a dynamic approach to cancer outcome prediction, enhancing personalized medicine.
- Dynamic risk assessment facilitates tailored therapeutic strategies.
- CIRI has the potential to enable innovative treatment paradigms in oncology.
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