Abstract
We argue that well-informed patient-specific decision-making may be carried out as three consecutive tasks: (1) estimating key parameters of a statistical model, (2) using prognostic information to convert these parameters into clinically interpretable values, and (3) specifying joint utility functions to quantify risk–benefit trade-offs between clinical outcomes. Using the management of metastatic clear cell renal cell carcinoma as our motivating example, we explain the role of prognostic covariates that characterize between-patient heterogeneity in clinical outcomes. We show that explicitly specifying the joint utility of clinical outcomes provides a coherent basis for patient-specific decision-making.
Original language | English (US) |
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Article number | 2741 |
Journal | Cancers |
Volume | 13 |
Issue number | 11 |
DOIs | |
State | Published - Jun 1 2021 |
Keywords
- Individualized inferences
- Patient-specific decision-making
- Precision medicine
- Prognostic biomarkers
- Utilities
ASJC Scopus subject areas
- Oncology
- Cancer Research
MD Anderson CCSG core facilities
- Biostatistics Resource Group