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. 2016 Dec;5(6):673-680.
doi: 10.21037/tlcr.2016.11.04.

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?

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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?

Abdulhamid Chaikh et al. Transl Lung Cancer Res. 2016 Dec.

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.

Keywords: Point kernel; anisotropic analytical algorithm (AAA); normal tissue complication probability (NTCP) and quality adjusted life years (QALY); tumor control probability (TCP)/uncomplicated tumor control probability (UTCP).

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Conflict of interest statement

The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Irradiation geometries for pencil beam and point kernel. The isodose curves are shown as full curves. Dashed lines indicate no scaling, i.e., constant (depth dependent) lateral range in standard pencil beam algorithms. The AAA is a 3D pencil beam convolution-superposition algorithm that has separate modeling for primary photons, scattered extra-focal photons, and electrons scattered from the beam limiting devices. AAA, anisotropic analytical algorithm.
Figure 2
Figure 2
The principle of a calibration method estimating the calculated QALY (Qc) from DVH and the measured QALY (Qm) obtained from EQ-5D. QALY, quality adjusted life years; DVH, dose volume histograms.
Figure 3
Figure 3
For target volume, the 95% CI for prescription dose and EUD in all plans using pencil beam model as PBCMB and point kernel model as AAA. EUD, equivalent uniform dose; PBC, pencil beam convolution; MB, Modified Batho; AAA, anisotropic analytical algorithm.
Figure 4
Figure 4
For target volume, the cumulative dose volume histograms, from plan 1 and 2, calculated respectively with PBCMB and AAA using the same prescribed dose. PBC, pencil beam convolution; MB, Modified Batho; AAA, anisotropic analytical algorithm.
Figure 5
Figure 5
Bootstrap distributions based on 1,000 replications for TCP, NTCP and Qc with cumulated average values from PBCMB and AAA. TCP, tumor control probability; NTCP, normal tissue complication probability; PBC, pencil beam convolution; MB, Modified Batho; AAA, anisotropic analytical algorithm.
Figure 6
Figure 6
Flowchart illustrating a two-phase strategy to implement and calibrate an NTCP model in the clinic. A better calibration would yield a strong correlation between calculated QALY (Qc) from DVH, and the measured QALY (Qm) from EQ-5D. NTCP, normal tissue complication probability; QALY, quality adjusted life years; DVH, dose volume histograms.

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