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Predictive modelling for late rectal and urinary toxicities after prostate radiotherapy using planned and delivered dose

BACKGROUND AND PURPOSE: Normal tissue complication probability (NTCP) parameters derived from traditional 3D plans may not be ideal in defining toxicity outcomes for modern radiotherapy techniques. This study aimed to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively...

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Detalles Bibliográficos
Autores principales: Ong, Ashley Li Kuan, Knight, Kellie, Panettieri, Vanessa, Dimmock, Mathew, Tuan, Jeffrey Kit Loong, Tan, Hong Qi, Wright, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800591/
https://www.ncbi.nlm.nih.gov/pubmed/36591496
http://dx.doi.org/10.3389/fonc.2022.1084311
Descripción
Sumario:BACKGROUND AND PURPOSE: Normal tissue complication probability (NTCP) parameters derived from traditional 3D plans may not be ideal in defining toxicity outcomes for modern radiotherapy techniques. This study aimed to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively scored clinical data for late gastrointestinal (GI) and genitourinary (GU) toxicities for high-risk prostate cancer patients treated using volumetric-modulated-arc-therapy (VMAT). Dose-volume-histograms (DVH) extracted from planned (D(P)) and accumulated dose (D(A)) were used. MATERIAL AND METHODS: D(P) and D(A) obtained from the DVH of 150 prostate cancer patients with pelvic-lymph-nodes irradiation treated using VMAT were used to generate LKB-NTCP parameters using maximum likelihood estimations. Defined GI and GU toxicities were recorded up to 3-years post RT follow-up. Model performance was measured using Hosmer-Lemeshow goodness of fit test and the mean area under the receiver operating characteristics curve (AUC). Bootstrapping method was used for internal validation. RESULTS: For mild-severe (Grade ≥1) GI toxicity, the model generated similar parameters based on D(A) and D(P) DVH data (D(A)-D(50):71.6 Gy vs D(P)-D(50):73.4; D(A)-m:0.17 vs D(P)-m:0.19 and D(A/P)-n 0.04). The 95% CI for D(A)-D(50) was narrower and achieved an AUC of >0.6. For moderate-severe (Grade ≥2) GI toxicity, D(A)-D(50) parameter was higher and had a narrower 95% CI (D(A)-D(50):77.9 Gy, 95% CI:76.4-79.6 Gy vs D(P)-D(50):74.6, 95% CI:69.1-85.4 Gy) with good model performance (AUC>0.7). For Grade ≥1 late GU toxicity, D(50) and n parameters for D(A) and D(P) were similar (D(A)-D(50): 58.8 Gy vs D(P)-D(50): 59.5 Gy; D(A)-n: 0.21 vs D(P)-n: 0.19) with a low AUC of<0.6. For Grade ≥2 late GU toxicity, similar NTCP parameters were attained from D(A) and D(P) DVH data (D(A)-D(50):81.7 Gy vs D(P)-D(50):81.9 Gy; D(A)-n:0.12 vs D(P)-n:0.14) with an acceptable AUCs of >0.6. CONCLUSIONS: The achieved NTCP parameters using modern RT techniques and accounting for organ motion differs from QUANTEC reported parameters. D(A)-D(50) of 77.9 Gy for GI and D(A)/D(P)-D(50) of 81.7-81.9 Gy for GU demonstrated good predictability in determining the risk of Grade ≥2 toxicities especially for GI derived D(50) and are recommended to incorporate as part of the DV planning constraints to guide dose escalation strategies while minimising the risk of toxicity.