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Background: A total of 10%-20% of patients develop long-term toxicity following radiotherapy for prostate cancer. Identification of common genetic variants associated with susceptibility to radiotoxicity might improve risk prediction and inform functional mechanistic studies.Methods: We conducted an individual patient data meta-analysis of six genome-wide association studies (n = 3871) in men of European ancestry who underwent radiotherapy for prostate cancer. Radiotoxicities (increased urinary frequency, decreased urinary stream, hematuria, rectal bleeding) were graded prospectively. We used grouped relative risk models to test associations with approximately 6 million genotyped or imputed variants (time to first grade 2 or higher toxicity event). Variants with two-sided Pmeta less than 5 × 10-8 were considered statistically significant. Bayesian false discovery probability provided an additional measure of confidence. Statistically significant variants were evaluated in three Japanese cohorts (n = 962). All statistical tests were two-sided.Results: Meta-analysis of the European ancestry cohorts identified three genomic signals: single nucleotide polymorphism rs17055178 with rectal bleeding (Pmeta = 6.2 × 10-10), rs10969913 with decreased urinary stream (Pmeta = 2.9 × 10-10), and rs11122573 with hematuria (Pmeta = 1.8 × 10-8). Fine-scale mapping of these three regions was used to identify another independent signal (rs147121532) associated with hematuria (Pconditional = 4.7 × 10-6). Credible causal variants at these four signals lie in gene-regulatory regions, some modulating expression of nearby genes. Previously identified variants showed consistent associations (rs17599026 with increased urinary frequency, rs7720298 with decreased urinary stream, rs1801516 with overall toxicity) in new cohorts. rs10969913 and rs17599026 had similar effects in the photon-treated Japanese cohorts.Conclusions: This study increases the understanding of the architecture of common genetic variants affecting radiotoxicity, points to novel radio-pathogenic mechanisms, and develops risk models for testing in clinical studies. Further multinational radiogenomics studies in larger cohorts are worthwhile. [ABSTRACT FROM AUTHOR]

Abstract: Background: An unexpected finding from the phase III parotid sparing radiotherapy trial, PARSPORT (ISRCTN48243537, CRUK/03/005), was a statistically significant increase in acute fatigue for those patients who were treated with intensity-modulated radiotherapy (IMRT) compared to standard conventional radiotherapy (CRT). One possible explanation was the difference in dose to central nervous system (CNS) structures due to differing beam portals. Using data from the trial, a dosimetric analysis of individual CNS structures was performed. Method: Dosimetric and toxicity data were available for 67 patients (27 CRT, 40 IMRT). Retrospective delineation of the posterior fossa, brainstem, cerebellum, pituitary gland, pineal gland, hypothalamus, hippocampus and basal ganglia was performed. Dosimetry was reviewed using summary statistics and dose–volume atlases. Results: A statistically significant increase in maximum and mean doses to each structure was observed for patients who received IMRT compared to those who received CRT. Both maximum and mean doses were significantly higher for the posterior fossa, brainstem and cerebellum for the 42 patients who reported acute fatigue of Grade 2 or higher (p ⩽0.01) compared to the 25 who did not. Dose–volume atlases of the same structures indicated that regions representing larger volumes and higher doses to each structure were consistent with a higher incidence of acute fatigue. There was no association between the dose distribution and acute fatigue for the other structures tested. Conclusions: The excess fatigue reported in the IMRT arm of the trial may, at least in part, be attributed to the dose distribution to the posterior fossa, cerebellum and brainstem. Future studies that modify dose delivery to these structures may allow us to test the hypothesis that radiation-induced fatigue is avoidable. [Copyright &y& Elsevier]

Purpose: Radical radiotherapy for prostate cancer is effective but dose limited because of the proximity of normal tissues. Comprehensive dose–volume analysis of the incidence of clinically relevant late rectal toxicities could indicate how the dose to the rectum should be constrained. Previous emphasis has been on constraining the mid-to-high dose range (≥50 Gy). Evidence is emerging that lower doses could also be important. Methods and Materials: Data from a large multicenter randomized trial were used to investigate the correlation between seven clinically relevant rectal toxicity endpoints (including patient- and clinician-reported outcomes) and an absolute 5% increase in the volume of rectum receiving the specified doses. The results were quantified using odds ratios. Rectal dose–volume constraints were applied retrospectively to investigate the association of constraints with the incidence of late rectal toxicity. Results: A statistically significant dose–volume response was observed for six of the seven endpoints for at least one of the dose levels tested in the range of 30–70 Gy. Statistically significant reductions in the incidence of these late rectal toxicities were observed for the group of patients whose treatment plans met specific proposed dose–volume constraints. The incidence of moderate/severe toxicity (any endpoint) decreased incrementally for patients whose treatment plans met increasing numbers of dose–volume constraints from the set of V30≤80%, V40≤65%, V50≤55%, V60≤40%, V65≤30%, V70≤15%, and V75≤3%. Conclusion: Considering the entire dose distribution to the rectum by applying dose–volume constraints such as those tested here in the present will reduce the incidence of late rectal toxicity. [Copyright &y& Elsevier]

Purpose: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue-sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation.Methods and Materials: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogram data. The reduced dose data were input into functional logistic regression models (functional partial least squares-logistic regression [FPLS-LR] and functional principal component-logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate-response associations, assessed using bootstrapping.Results: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/-0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/-0.96, 0.79/-0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models.Conclusions: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling. [ABSTRACT FROM AUTHOR]

Background and purpose Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. Materials and methods Predictive models of severe acute mucositis were generated using radiotherapy dose (dose–volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. Results The dose–volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFC standard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d. = 0.09) and 3.9 (s.d. = 2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. Conclusions The RFC standard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence. [ABSTRACT FROM AUTHOR]

Abstract: Background and purpose: Fatigue during head and neck radiotherapy may be related to radiation dose to the central nervous system (CNS). The impact of patient, tumour, and dosimetric variables on acute fatigue was assessed in nasopharyngeal cancer patients undergoing chemoradiotherapy. Material and methods: Radiation dose to the following retrospectively-delineated CNS structures; brainstem, cerebellum, pituitary gland, pineal gland, hypothalamus, hippocampus and basal ganglia (BG) and clinical variables were related to incidence of ⩾ grade 2 fatigue in 40 patients. Results: Sixty per cent of patients reported fatigue during and following radiotherapy. Dmean and D2 to the BG and Dmean to the pituitary gland were significantly associated with fatigue during radiation (P <0.01). Dmean to the cerebellum was associated with fatigue following radiotherapy and at any time (P <0.01). After adjusting for clinical factors, an association remained between fatigue during radiotherapy and mean dose and D2 to the pituitary gland and BG (P =0.012, 0.036, 0.009 and 0.018) and mean dose to the cerebellum following radiation and at any time (P =0.042 and 0.029). Conclusion: Disruption of connections between BG, cerebellum, and higher cortical centres or disruption of pituitary-regulated hormonal balance may be implicated in the pathophysiology of radiation-related fatigue. [Copyright &y& Elsevier]