Normal tissue complication probability (NTCP) models of acute urinary toxicity (AUT) following carbon ion radiotherapy (CIRT) for prostate cancer.

Abstract

PURPOSE:

To estimate the Lyman Kutcher Burman (LKB) and multivariate NTCP models predicting the AUT of prostate cancer treated with CIRT.

MATERIALS AND METHODS:

A cohort of 154 prostate adenocarcinoma patients were retrospectively analyzed. The AUT levels were graded according to CTCAE 4.03. Based on dosimetric parameters and/or clinical factors, a set of variables with best-fit values determined in the two models was validated by the area under the receiver operating characteristic curve (AUC) and used to correlate the predicted and observed NTCP rates for both levels and related endpoints.

RESULT:

59 (38.3%) patients experienced AUT. For LKB model, the equivalent uniform doses (EUDs) were calculated to be 62.0 GyE (following V61.5 > 1.7%) and 61.2 GyE (following maximum dose > 63.0 GyE) with predicted NTCP rates of 37.0% (AUC: 0.71) and 15.6% (AUC: 0.65) for AUT G1&2 and G2 of bladder. While for the multivariate model, the predicted NTCP rates was 37.1% (AUC: 0.70) and 20.2% (AUC: 0.64) for AUT G1&2 and G2, associated with V61 and V65, respectively. Nocturia was associated with bladder volume and maximum dose for G1&2, with patient's age and maximum bladder dose for G2. Other predictable endpoints were associated with V≥61. The predicted NTCPs agree with the observed complication rates for bladder and its wall.

CONCLUSIONS:

The LKB model successfully predicted the NTCP rates of both AUT levels and urgency urination. The multivariate model predicted well on both levels and nocturia. Decreasing high bladder dose volume may reduce the incidence of AUT.

• Authors: Yongqiang Li, Ping Li, Wenchien Hsi, Zhengshan Hong, Shen Fu, Qing Zhang
• Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology (Radiother Oncol) Vol. 156 Pg. 69-79 (03 2021) ISSN: 1879-0887 [Electronic] Ireland
• PMID: 33309999 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2020 Elsevier B.V. All rights reserved.

Topics

• Heavy Ion Radiotherapy
• Humans
• Male
• Probability
• Prostatic Neoplasms (radiotherapy)
• Radiation Injuries (epidemiology, etiology)
• Radiotherapy Dosage
• Radiotherapy Planning, Computer-Assisted
• Retrospective Studies