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Correlating Dose Variables with Local Tumor Control in Stereotactic Body Radiation Therapy for Early-Stage Non-Small
Rainer J Klement1, Jan-Jakob Sonke2, Michael Allgäuer3
1Department of Radiotherapy and Radiation Oncology, Leopoldina Hospital Schweinfurt, Schweinfurt, Germany.
Summary
For stereotactic body radiation therapy (SBRT) in lung cancer, the average biologically effective dose (BEDave) best predicts local tumor control. Focusing on mean gross tumor volume dose may improve SBRT prescription and outcomes.
Area of Science:
- Radiation Oncology
- Medical Physics
- Oncology
Background:
- Stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC) exhibits significant variability in prescription and dose inhomogeneity.
- Optimizing SBRT requires understanding dose metrics that correlate with treatment efficacy.
Purpose of the Study:
- To identify the optimal dose metric for predicting local tumor control probability in NSCLC SBRT.
- To inform recommendations for standardized SBRT prescription practices.
Main Methods:
- Analysis of 1500 SBRT treatments from retrospective databases.
- Calculation of three biologically effective doses (BEDs): BEDmin, BEDmax, and BEDave.
- Correlation of BED parameters with local recurrence risk using Cox regression, logistic regression, and fast and frugal trees.
Main Results:
- BEDave demonstrated the strongest correlation with local recurrence risk in univariable Cox and logistic regression analyses.
- Multivariable classification identified BEDmax as the most significant predictor, followed closely by BEDave.
- Local control rates at 12 and 36 months were high (96.8% and 89.0%, respectively).
Conclusions:
- The average biologically effective dose (BEDave) generally correlates better with tumor control probability than BEDmax or BEDmin.
- Mean gross tumor volume dose may serve as a viable SBRT prescription target, potentially offering improved outcomes.
- Further research is needed to validate the emphasis on mean GTV dose over PTV coverage dose.
