W Sharieff1, G Okawara, T Tsakiridis, J Wright. 1. Department of Radiation Oncology, Juravinski Cancer Centre, Hamilton Health Sciences, Hamilton, Ontario, Canada; Department of Oncology, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, Division of Radiation Oncology, Cape Breton Regional Cancer Centre, Sydney, Nova Scotia, Canada; Department of Radiation Oncology, Dalhousie University, Halifax, Nova Scotia, Canada. Electronic address: doc.sharieff@utoronto.ca.
Abstract
AIMS: Total dose, dose per fraction, number of fractions and treatment time are important determinants of the biological effect of a radiation regimen. Several randomised clinical trials (RCTs) have tested a variety of dosing regimens in advanced unresected non-small cell lung cancer, but survival remains poor. This work used past RCT data to develop and validate a predictive model that could help in designing new radiation regimens for successful testing in RCTs. MATERIALS AND METHODS: Eleven RCTs that compared radiation regimens alone were used to define the relationship between radiation regimens and 2-year survival. On the basis of this relationship, predictive models were developed. Predicted values were internally and externally validated against observed values from the same 11 RCTs and 21 other RCTs. Scatter plots and Pearson's correlation coefficient (r) were used for validation. Finally, regimens were explored that could improve survival. RESULTS: Increments in the total dose, dose per day and the number of treatment days were associated with improved survival; increments in dose-squared and treatment weeks were associated with reduced survival. The observed and predicted values were similar on internal (r = 0.96) and external validation (r = 0.76). Regimens that delivered a higher total dose over a shorter time had higher survival rates compared with the standard (60 Gy, 30 fractions, 6 weeks); survival may be improved by delivering the standard treatment in 5 weeks rather than 6 weeks. CONCLUSION: The developed model can predict the effect of thoracic radiation on survival in advanced non-small cell lung cancer patients. It is a useful tool for designing new radiation regimens for clinical trials.
AIMS: Total dose, dose per fraction, number of fractions and treatment time are important determinants of the biological effect of a radiation regimen. Several randomised clinical trials (RCTs) have tested a variety of dosing regimens in advanced unresected non-small cell lung cancer, but survival remains poor. This work used past RCT data to develop and validate a predictive model that could help in designing new radiation regimens for successful testing in RCTs. MATERIALS AND METHODS: Eleven RCTs that compared radiation regimens alone were used to define the relationship between radiation regimens and 2-year survival. On the basis of this relationship, predictive models were developed. Predicted values were internally and externally validated against observed values from the same 11 RCTs and 21 other RCTs. Scatter plots and Pearson's correlation coefficient (r) were used for validation. Finally, regimens were explored that could improve survival. RESULTS: Increments in the total dose, dose per day and the number of treatment days were associated with improved survival; increments in dose-squared and treatment weeks were associated with reduced survival. The observed and predicted values were similar on internal (r = 0.96) and external validation (r = 0.76). Regimens that delivered a higher total dose over a shorter time had higher survival rates compared with the standard (60 Gy, 30 fractions, 6 weeks); survival may be improved by delivering the standard treatment in 5 weeks rather than 6 weeks. CONCLUSION: The developed model can predict the effect of thoracic radiation on survival in advanced non-small cell lung cancerpatients. It is a useful tool for designing new radiation regimens for clinical trials.