The normal tissue complication probability model-based approach considering uncertainties for the selective use of radiation modality in primary liver cancer patients

Abstract

To predict the probability of radiation-induced liver toxicity (RILT) and implement the normal tissue complication probability (NTCP) model-based approach considering confidence intervals (CIs) to select patients for new treatment techniques, such as proton beam therapy, based on a certain NTCP reduction (DNTCP) threshold for primary liver cancer patients. Methods and materials: Common Toxicity Criteria for Adverse Events (CTCAE) grade !2 RILT was scored. The Lyman NTCP models predicting the probability of CTCAE grade !2 RILT as a function of the fractionsize adjusted mean liver dose (MLD), using reference fraction size = 2 Gy/fraction and a/b ratio = 2 Gy, were fitted using the maximum likelihood method. At certain combinations of MLDs, DNTCP with a CI was evaluated by the delta method. Results: Of the 239 patients, the incidence of CTCAE grade !2 RILT was 55% (46% in the Child-Pugh (CP)-A vs. 81% in the CP-B/C, p < 0.001). Among 180 CP-A patients, 40% who had viral hepatitis infections experienced toxicity vs. 32% in the nonhepatitis subgroup. The MLD was 18 Gy in the toxicity group vs. 16.1 Gy in the nontoxicity group (p = 0.002). The estimated NTCP model parameters specific to the patient subgroups and the DNTCP with CI assuming a particular CP classification and viral hepatitis infection status were considerably different which possible changed treatment decision. Conclusions: Patients with CP-A and viral hepatitis infection or CP-B/C cirrhosis had greater susceptibility to CTCAE grade !2 RILT. The estimated NTCP and DNTCP for individual patients along with a consideration of uncertainties improve the reliability of the NTCP model-based approach.

Intensity modulated proton therapy compared to volumetric modulated arc therapy in the irradiation of young female patients with hodgkin’s lymphoma. Assessment of risk of toxicity and secondary cancer induction

“…The absence of validated multivariate models applicable for HL patients prevented to implement the selection strategies suggested by Langendijk and realized by Rwigema or Cheng [9][10][11]13] for head and neck or Prayongrat [14] for liver. This is a clear need and intensive investigations shall be performed in the near future in this area to provide reliable model.…”

“…It is absolutely obvious that, given the small sample size of the study, the approach suggested here cannot be considered more than a feasibility aiming to pave the path for more appropriate and comprehensive models in view of any clinical applicability [9][10][11][12][13][14][15]. Fig.…”

“…The practical implementation of the model-based approach requires well designed data collection in order to fit the dose-effect relationships into multivariate models and to-date only few examples of validated models exist [11][12][13][14]. Considering the long life expectancy of the HL patients, the models used for treatment technique selection should incorporate also the risk of secondary cancer induction and the number of years lost due to any kind of late effects [15].…”

Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer

“…In addition, there have been normal tissue complication probability (NTCP) models for predicting risk of RILD based on dose–volume statistics and mathematical models, among which the most common is the Lyman–Kutcher–Burman (LKB) model [ 3–7 ]. A number of clinical risk factors other than the dosimetric profile were reported for RILD, including male gender, Child–Pugh (CP) classification, viral hepatitis infection, presence of portal vein thrombosis (PVT), and prior and concurrent treatments [ 3 , 5 , 7–9 ]. It was also reported that worsening of liver function not related to irradiation is often difficult to be distinguished from RILD; confounding factors, such as other locoregional treatments, worsening of cirrhosis itself or other hepatotoxic effects, may also be related to the hepatic toxicities [ 10 ].…”

“…Uncertainty in dose delivery and model parameters were associated with model uncertainty, which significantly affected the accuracy of a model-based approach [ 24 ]. There has been a previous study assessing the uncertainty or the confidence interval (CI) for the LKB model [ 7 ], but not for a multivariable NTCP model for RILD. Underestimation of NTCP and ∆NTCP can lead to the loss of the opportunity to benefit from PBT, whereas overly cautious practice might cause unnecessary use of this high-cost treatment.…”