Predicting 2-Year Survival for Radiation Regimens in Advanced Non-small Cell Lung Cancer

• Published in: Clinical oncology (Royal College of Radiologists (Great Britain)) 2013-12, Vol.25 (12), p.697-705
• Main Authors: Sharieff, W, Okawara, G, Tsakiridis, T, Wright, J
• Format: Article
• Language: English
• Subjects: Biological equivalent dose; Carcinoma, Non-Small-Cell Lung - drug therapy; Carcinoma, Non-Small-Cell Lung - mortality; Carcinoma, Non-Small-Cell Lung - radiotherapy; Dose Fractionation; Dose-Response Relationship, Drug; dose–response study; Female; Hematology, Oncology and Palliative Medicine; Humans; Lung Neoplasms - drug therapy; Lung Neoplasms - mortality; Lung Neoplasms - radiotherapy; Male; Models, Biological; non-small cell lung cancer; predictive modelling; radiation therapy; Radiology; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted - methods; Randomized Controlled Trials as Topic; Reproducibility of Results; Risk Factors; Survival Rate; Treatment Outcome
• ISSN: 0936-6555; 1433-2981
• DOI: 10.1016/j.clon.2013.07.011

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.