Original Article
Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?
Abstract
Background: The equivalent uniform dose (EUD) radiobiological model can be applied for lung cancer treatment plans to estimate the tumor control probability (TCP) and the normal tissue complication probability (NTCP) using different dose calculation models. Then, based on the different calculated doses, the quality adjusted life years (QALY) score can be assessed versus the uncomplicated tumor control probability (UTCP) concept in order to predict the overall outcome of the different treatment plans.
Methods: Nine lung cancer cases were included in this study. For the each patient, two treatments plans were generated. The doses were calculated respectively from pencil beam model, as pencil beam convolution (PBC) turning on 1D density correction with Modified Batho’s (MB) method, and point kernel model as anisotropic analytical algorithm (AAA) using exactly the same prescribed dose, normalized to 100% at isocentre point inside the target and beam arrangements. The radiotherapy outcomes and QALY were compared. The bootstrap method was used to improve the 95% confidence intervals (95% CI) estimation. Wilcoxon paired test was used to calculate P value.
Results: Compared to AAA considered as more realistic, the PBCMB overestimated the TCP while underestimating NTCP, P<0.05. Thus the UTCP and the QALY score were also overestimated.
Conclusions: To correlate measured QALY’s obtained from the follow-up of the patients with calculated QALY from DVH metrics, the more accurate dose calculation models should be first integrated in clinical use. Second, clinically measured outcomes are necessary to tune the parameters of the NTCP model used to link the treatment outcome with the QALY. Only after these two steps, the comparison and the ranking of different radiotherapy plans would be possible, avoiding over/under estimation of QALY and any other clinic-biological estimates.
Methods: Nine lung cancer cases were included in this study. For the each patient, two treatments plans were generated. The doses were calculated respectively from pencil beam model, as pencil beam convolution (PBC) turning on 1D density correction with Modified Batho’s (MB) method, and point kernel model as anisotropic analytical algorithm (AAA) using exactly the same prescribed dose, normalized to 100% at isocentre point inside the target and beam arrangements. The radiotherapy outcomes and QALY were compared. The bootstrap method was used to improve the 95% confidence intervals (95% CI) estimation. Wilcoxon paired test was used to calculate P value.
Results: Compared to AAA considered as more realistic, the PBCMB overestimated the TCP while underestimating NTCP, P<0.05. Thus the UTCP and the QALY score were also overestimated.
Conclusions: To correlate measured QALY’s obtained from the follow-up of the patients with calculated QALY from DVH metrics, the more accurate dose calculation models should be first integrated in clinical use. Second, clinically measured outcomes are necessary to tune the parameters of the NTCP model used to link the treatment outcome with the QALY. Only after these two steps, the comparison and the ranking of different radiotherapy plans would be possible, avoiding over/under estimation of QALY and any other clinic-biological estimates.
