Validation of prediction models for radiation-induced late rectal bleeding: Evidence from a large pooled population of prostate cancer patients.

PURPOSE: To validate published models for the risk estimate of grade ≥ 1 (G1+), grade ≥ 2 (G2+) and grade = 3 (G3) late rectal bleeding (LRB) after radical radiotherapy for prostate cancer in a large pooled population from three prospective trials. MATERIALS AND METHODS: The external validation population included patients from Europe, and Oceanian centres enrolled between 2003 and 2014. Patients received 3DCRT or IMRT at doses between 66-80 Gy. IMRT was administered with conventional or hypofractionated schemes (2.35-2.65 Gy/fr). LRB was prospectively scored using patient-reported questionnaires (LENT/SOMA scale) with a 3-year follow-up. All Normal Tissue Complication Probability (NTCP) models published until 2021 based on the Equivalent Uniform Dose (EUD) from the rectal Dose Volume Histogram (DVH) were considered for validation. Model performance in validation was evaluated through calibration and discrimination. RESULTS: Sixteen NTCP models were tested on data from 1633 patients. G1+ LRB was scored in 465 patients (28.5%), G2+ in 255 patients (15.6%) and G3 in 112 patients (6.8%). The best performances for G2+ and G3 LRB highlighted the importance of the medium-high doses to the rectum (volume parameters n = 0.24 and n = 0.18, respectively). Good performance was seen for models of severe LRB. Moreover, a multivariate model with two clinical factors found the best calibration slope. CONCLUSION: Five published NTCP models developed on non-contemporary cohorts were able to predict a relative increase in the toxicity response in a more recent validation population. Compared to QUANTEC findings, dosimetric results pointed toward mid-high doses of rectal DVH. The external validation cohort confirmed abdominal surgery and cardiovascular diseases as risk factors.

Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging.

PURPOSE: Hypoxia has been linked to radioresistance. Strategies to safely dose escalate dominant intraprostatic lesions have shown promising results, but further dose escalation to overcome the effects of hypoxia require a novel approach to constrain the dose in normal tissue.to safe levels. In this study, we demonstrate a biologically targeted radiotherapy (BiRT) approach that can utilise multiparametric magnetic resonance imaging (mpMRI) to target hypoxia for favourable treatment outcomes. METHODS: mpMRI-derived tumour biology maps, developed via a radiogenomics study, were used to generate individualised, hypoxia-targeting prostate IMRT plans using an ultra- hypofractionation schedule. The spatial distribution of mpMRI textural features associated with hypoxia-related genetic profiles was used as a surrogate of tumour hypoxia. The effectiveness of the proposed approach was assessed by quantifying the potential benefit of a general focal boost approach on tumour control probability, and also by comparing the dose to organs at risk (OARs) with hypoxia-guided focal dose escalation (DE) plans generated for five patients. RESULTS: Applying an appropriately guided focal boost can greatly mitigate the impact of hypoxia. Statistically significant reductions in rectal and bladder dose were observed for hypoxia-targeting, biologically optimised plans compared to isoeffective focal DE plans. CONCLUSION: Results of this study suggest the use of mpMRI for voxel-level targeting of hypoxia, along with biological optimisation, can provide a mechanism for guiding focal DE that is considerably more efficient than application of a general, dose-based optimisation, focal boost.

Increased Dose to Organs in Urinary Tract Associates With Measures of Genitourinary Toxicity in Pooled Voxel-Based Analysis of 3 Randomized Phase III Trials.

Purpose: Dose information from organ sub-regions has been shown to be more predictive of genitourinary toxicity than whole organ dose volume histogram information. This study aimed to identify anatomically-localized regions where 3D dose is associated with genitourinary toxicities in healthy tissues throughout the pelvic anatomy. Methods and Materials: Dose distributions for up to 656 patients of the Trans-Tasman Radiation Oncology Group 03.04 RADAR trial were deformably registered onto a single exemplar CT dataset. Voxel- based multiple comparison permutation dose difference testing, Cox regression modeling and LASSO feature selection were used to identify regions where 3D dose-increase was associated with late grade ≥ 2 genitourinary dysuria, incontinence and frequency, and late grade ≥ 1 haematuria. This was externally validated by registering dose distributions from the RT01 (up to n = 388) and CHHiP (up to n = 247) trials onto the same exemplar and repeating the voxel-based tests on each of these data sets. All three datasets were then combined, and the tests repeated. Results: Voxel-based Cox regression and multiple comparison permutation dose difference testing revealed regions where increased dose was correlated with genitourinary toxicity. Increased dose in the vicinity of the membranous and spongy urethra was associated with dysuria for all datasets. Haematuria was similarly correlated with increased dose at the membranous and spongy urethra, for the RADAR, CHHiP, and combined datasets. Some evidence was found for the association between incontinence and increased dose at the internal and external urethral sphincter for RADAR and the internal sphincter alone for the combined dataset. Incontinence was also strongly correlated with dose from posterior oblique beams. Patients with fields extending inferiorly and posteriorly to the CTV, adjacent to the membranous and spongy urethra, were found to experience increased frequency. Conclusions: Anatomically-localized dose-toxicity relationships were determined for late genitourinary symptoms in the urethra and urinary sphincters. Low-intermediate doses to the extraprostatic urethra were associated with risk of late dysuria and haematuria, while dose to the urinary sphincters was associated with incontinence.

Reduced Dose Posterior to Prostate Correlates With Increased PSA Progression in Voxel-Based Analysis of 3 Randomized Phase 3 Trials.

PURPOSE: Reducing margins during treatment planning to decrease dose to healthy organs surrounding the prostate can risk inadequate treatment of subclinical disease. This study aimed to investigate whether lack of dose to subclinical disease is associated with increased disease progression by using high-quality prostate radiation therapy clinical trial data to identify anatomically localized regions where dose variation is associated with prostate-specific antigen progression (PSAP). METHODS AND MATERIALS: Planned dose distributions for 683 patients of the Trans-Tasman Radiation Oncology Group 03.04 Randomized Androgen Deprivation and Radiotherapy (RADAR) trial were deformably registered onto a single exemplar computed tomography data set. These were divided into high-risk and intermediate-risk subgroups for analysis. Three independent voxel-based statistical tests, using permutation testing, Cox regression modeling, and least absolute shrinkage selection operator feature selection, were applied to identify regions where dose variation was associated with PSAP. Results from the intermediate-risk RADAR subgroup were externally validated by registering dose distributions from the RT01 (n = 388) and Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer Trial (CHHiP) (n = 253) trials onto the same exemplar and repeating the tests on each of these data sets. RESULTS: Voxel-based Cox regression revealed regions where reduced dose was correlated with increased prostate-specific androgen progression. Reduced dose in regions associated with coverage at the posterior prostate, in the immediate periphery of the posterior prostate, and in regions corresponding to the posterior oblique beams or posterior lateral beam boundary, was associated with increased PSAP for RADAR and RT01 patients, but not for CHHiP patients. Reduced dose to the seminal vesicle region was also associated with increased PSAP for RADAR intermediate-risk patients. CONCLUSIONS: Ensuring adequate dose coverage at the posterior prostate and immediately surrounding posterior region (including the seminal vesicles), where aggressive cancer spread may be occurring, may improve tumor control. It is recommended that particular care be taken when defining margins at the prostate posterior, acknowledging the trade-off between quality of life due to rectal dose and the preferences of clinicians and patients.

Relationships between rectal and perirectal doses and rectal bleeding or tenesmus in pooled voxel-based analysis of 3 randomised phase III trials.

BACKGROUND AND PURPOSE: This study aimed to identify anatomically-localised regions where planned radiotherapy dose is associated with gastrointestinal toxicities in healthy tissues throughout the pelvic anatomy. MATERIALS AND METHODS: Planned dose distributions for up to 657 patients of the Trans Tasman Radiation Oncology Group 03.04 RADAR trial were deformably registered onto a single exemplar computed tomography dataset. Voxel-based multiple comparison permutation dose difference testing, Cox regression modelling and LASSO feature selection were used to identify regions where dose-increase was associated with grade ≥2 rectal bleeding (RB) or tenesmus, according to the LENT/SOMA scale. This was externally validated by registering dose distributions from the RT01 (n = 388) and CHHiP (n = 241) trials onto the same exemplar and repeating the tests on each of these data sets, and on all three datasets combined. RESULTS: Voxel-based Cox regression and permutation dose difference testing revealed regions where increased dose was correlated with gastrointestinal toxicity. Grade ≥2 RB was associated with posteriorly extended lateral beams that manifested high doses (>55 Gy) in a small rectal volume adjacent to the clinical target volume. A correlation was found between grade ≥2 tenesmus and increased low-intermediate dose (∼25 Gy) at the posterior beam region, including the posterior rectum and perirectal fat space (PRFS). CONCLUSIONS: The serial response of the rectum with respect to RB has been demonstrated in patients with posteriorly extended lateral beams. Similarly, the parallel response of the PRFS with respect to tenesmus has been demonstrated in patients treated with the posterior beam.

Rectal and Urethro-Vesical Subregions for Toxicity Prediction After Prostate Cancer Radiation Therapy: Validation of Voxel-Based Models in an Independent Population.

PURPOSE: Recent voxel-based studies have shown that the dose to specific rectal and urethro-vesical subregions is predictive of toxicities after prostate cancer intensity modulated radiation therapy. The objective of this study was to validate the discriminatory power of these subregions with respect to the whole organs in a large independent population. METHODS AND MATERIALS: The validation cohort consisted of 450 patients from the TROG03.04-RADAR trial treated with 3-dimensional conformal radiation therapy at 66 to 74 Gy. Previous voxel-based analyses identified an inferoanterior rectal subregion as predictive of rectal bleeding and 5 subregions in the urethra and the posterior and superior part of the bladder as predictive of urinary incontinence, dysuria, retention, and hematuria. In the validation cohort, these subregions were segmented in each patient's anatomy. Dose-volume histograms (DVHs) of the whole organs and the 6 subregions were compared bin-wise between patients with and without toxicities. The discriminatory power of DVHs for grade ≥2 toxicity endpoints was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS: Subregion DVHs were significantly different between patients with and without toxicities for late rectal bleeding (V44-V74), acute urinary incontinence (V68-V72), late dysuria (V56-V68), and late retention (V14-V64). The dose to the rectal subregion and the whole rectum were equally predictive of rectal bleeding (V68; AUC = 0.61). The doses to 3 out of the 5 urethro-vesical subregions were found to be more predictive than the dose to the whole bladder: in the urethra for acute incontinence (V71 AUC = 0.69 vs V71 AUC = 0.66), in the posterior part of the bladder for late dysuria (V65 AUC = 0.66 vs V68 AUC = 0.59), and late retention (V39 AUC = 0.74 vs no significant AUC). CONCLUSIONS: Three subregions located in the urethra and the bladder were successfully validated as more predictive of urinary toxicity than the whole bladder for urinary incontinence, retention, and dysuria. Sparing the posterior part of the bladder in particular in treatment planning may reduce the risk of late urinary retention.

Similarity clustering-based atlas selection for pelvic CT image segmentation.

PURPOSE: To demonstrate selection of a small representative subset of images from a pool of images comprising a potential atlas (PA) pelvic CT set to be used for autosegmentation of a separate target image set. The aim is to balance the need for the atlas set to represent anatomical diversity with the need to minimize resources required to create a high quality atlas set (such as multiobserver delineation), while retaining access to additional information available for the PA image set. METHODS: Preprocessing was performed for image standardization, followed by image registration. Clustering was used to select the subset that provided the best coverage of a target dataset as measured by postregistration image intensity similarities. Tests for clustering robustness were performed including repeated clustering runs using different starting seeds and clustering repeatedly using 90% of the target dataset chosen randomly. Comparisons of coverage of a target set (comprising 711 pelvic CT images) were made for atlas sets of five images (chosen from a PA set of 39 pelvic CT and MR images) (a) at random (averaged over 50 random atlas selections), (b) based solely on image similarities within the PA set (representing prospective atlas development), (c) based on similarities within the PA set and between the PA and target dataset (representing retrospective atlas development). Comparisons were also made to coverage provided by the entire PA set of 39 images. RESULTS: Exemplar selection was highly robust with exemplar selection results being unaffected by choice of starting seed with very occasional change to one of the exemplar choices when the target set was reduced. Coverage of the target set, as measured by best normalized cross-correlation similarity of target images to any exemplar image, provided by five well-selected atlas images (mean = 0.6497) was more similar to coverage provided by the entire PA set (mean = 0.6658) than randomly chosen atlas subsets (mean = 0.5977). This was true both of the mean values and the shape of the distributions. Retrospective selection of atlases (mean = 0.6497) provided a very small improvement over prospective atlas selection (mean = 0.6431). All differences were significant (P < 1.0E-10). CONCLUSIONS: Selection of a small representative image set from one dataset can be utilized to develop an atlas set for either retrospective or prospective autosegmentation of a different target dataset. The coverage provided by such a judiciously selected subset has the potential to facilitate propagation of numerous retrospectively defined structures, utilizing additional information available with multimodal imaging in the atlas set, without the need to create large atlas image sets.

Multi-observer contouring of male pelvic anatomy: Highly variable agreement across conventional and emerging structures of interest.

INTRODUCTION: This study quantified inter-observer contouring variations for multiple male pelvic structures, many of which are of emerging relevance for prostate cancer radiotherapy progression and toxicity response studies. METHODS: Five prostate cancer patient datasets (CT and T2-weighted MR) were distributed to 13 observers for contouring. CT structures contoured included the clinical target volume (CTV), seminal vesicles, rectum, colon, bowel bag, bladder and peri-rectal space (PRS). MR contours included CTV, trigone, membranous urethra, penile bulb, neurovascular bundle and multiple pelvic floor muscles. Contouring variations were assessed using the intraclass correlation coefficient (ICC), Dice similarity coefficient (DSC), and multiple additional metrics. RESULTS: Clinical target volume (CT and MR), bladder, rectum and PRS contours showed excellent inter-observer agreement (median ICC = 0.97; 0.99; 1.00; 0.95; 0.90, DSC = 0.83 ± 0.05; 0.88 ± 0.05; 0.93 ± 0.03; 0.81 ± 0.07; 0.80 ± 0.06, respectively). Seminal vesicle contours were more variable (ICC = 0.75, DSC = 0.73 ± 0.14), while colon and bowel bag contoured volumes were consistent (ICC = 0.97; 0.97), but displayed poor overlap (DSC = 0.58 ± 0.22; 0.67 ± 0.21). Smaller MR structures showed significant inter-observer variations, with poor overlap for trigone, membranous urethra, penile bulb, and left and right neurovascular bundles (DSC = 0.44 ± 0.22; 0.41 ± 0.21; 0.66 ± 0.21; 0.16 ± 0.17; 0.15 ± 0.15). Pelvic floor muscles recorded moderate to strong inter-observer agreement (ICC = 0.50-0.97), although large outlier variations were observed. CONCLUSIONS: Inter-observer contouring variation was significant for multiple pelvic structures contoured on MR.

Estimation of Hounsfield unit conversion parameters for pelvic CT images.

Linear scaling is used to convert raw computed tomography (CT) pixel values into Hounsfield units corresponding to different tissue values. Analysis of a benchmarking study, presented here, where the same CT scan was imported into and then exported from multiple radiotherapy treatment planning systems, found inconsistencies in HU scaling parameter values exported along with the images, particularly when images were exported using the Radiation Therapy Oncology Group format. Several methods of estimating conversion parameters, based on estimating pixel values corresponding to air and water within the image, for pelvic CT images from a large multi-centre trial were compared against original Digital Imaging and Communications in Medicine export parameters. In general using the mean of a sample region at the centroid of the bladder to estimate the value of water was more accurate than using the minimum or maximum or a single value at the centroid. Accuracy of methods of air estimation tested were dependent in part on features of the CT scanners and treatment planning systems, making it difficult to pick one method as superior that was independent of scanner and treatment planning system type. Based on the above analysis, methods for estimating air and water were selected for use in performing linear scaling of a set of pelvic CT images prior to their use in an interpatient image registration application. The selected methods were validated against a more recent and homogeneous dataset. Estimation error was found to be much lower within the validation set.

Association between treatment planning and delivery factors and disease progression in prostate cancer radiotherapy: Results from the TROG 03.04 RADAR trial.

BACKGROUND AND PURPOSE: To evaluate the impact of treatment planning and delivery factors on treatment outcome as measured by post-treatment disease progression. MATERIALS AND METHODS: Accruing 813 external beam radiotherapy participants during 2003-2007, the RADAR trial collected a comprehensive range of clinical treatment factor data for each participant. Both the Fine and Gray competing risks modelling and the Kaplan-Meier (KM) analysis were undertaken to determine the impact of these factors on local-composite progression (LCP), with 709 participants available for analysis. RESULTS: Participants with treatments involving 7 or more beams experienced significantly higher incidence of LCP, with a sub-hazard ratio (relative to 3-beam participants) of 3.056 (CI: 1.446-6.458, p < 0.0034). Participants treated with a more rigorous dose calculation algorithm also displayed significantly higher incidence of LCP, with a sub-hazard ratio of 1.686 (CI: 1.334-2.132, p < 0.0001). The KM analysis resulted in the same groups showing a higher incidence of LCP, with log-rank test results of p = 0.0005 and p = 0.0008 respectively. CONCLUSIONS: The RADAR dataset has enabled a successful secondary analysis in which the impact of technical modifications has been assessed, challenging several established hypotheses. Increasingly precise treatments should be complemented with increasing accuracy to avoid potential geometric miss.

Association between measures of treatment quality and disease progression in prostate cancer radiotherapy: An exploratory analysis from the TROG 03.04 RADAR trial.

INTRODUCTION: Quality assurance methods are incorporated into multicentre radiotherapy clinical trials for ensuring consistent application of trial protocol and quantifying treatment uncertainties. The study's purpose was to determine whether post-treatment disease progression is associated with measures of the quality of radiotherapy treatment. METHODS: The TROG 03.04 RADAR trial tested the impact of androgen deprivation on prostate cancer patients receiving dose-escalated external beam radiation therapy. The trial incorporated a plan-review process and Level III dosimetric intercomparison at each centre, from which variables suggestive of treatment quality were collected. Kaplan-Meier statistics and Fine and Gray competing risk modelling were employed to test for associations between quality-related variables and the participant outcome local composite progression. RESULTS: Increased 'dose-difference' at the prostatic apex and at the anterior rectal wall, between planned and measured dose, was associated with reduced progression. Participants whose treatment plans included clinical target volume (CTV) to planning target volume (PTV) margins exceeding protocol requirements also experienced reduced progression. Other quality-related variables, including total accrual from participating centres, measures of target coverage and other variations from protocol, were not significantly associated with progression. CONCLUSIONS: This analysis has revealed the association of several treatment quality factors with disease progression. Increased dose and dose margin coverage in the prostate region can reduce disease progression. Extensive and rigorous monitoring has helped to maximise treatment quality, reducing the incidence of quality-indicator outliers, and thus reduce the chance of observing significant associations with progression rates.

Modeling Urinary Dysfunction After External Beam Radiation Therapy of the Prostate Using Bladder Dose-Surface Maps: Evidence of Spatially Variable Response of the Bladder Surface.

PURPOSE: We assessed the association of the spatial distribution of dose to the bladder surface, described using dose-surface maps, with the risk of urinary dysfunction. METHODS AND MATERIALS: The bladder dose-surface maps of 754 participants from the TROG 03.04-RADAR trial were generated from the volumetric data by virtually cutting the bladder at the sagittal slice, intersecting the bladder center-of-mass through to the bladder posterior and projecting the dose information on a 2-dimensional plane. Pixelwise dose comparisons were performed between patients with and without symptoms (dysuria, hematuria, incontinence, and an International Prostate Symptom Score increase of ≥10 [ΔIPSS10]). The results with and without permutation-based multiple-comparison adjustments are reported. The pixelwise multivariate analysis findings (peak-event model for dysuria, hematuria, and ΔIPSS10; event-count model for incontinence), with adjustments for clinical factors, are also reported. RESULTS: The associations of the spatially specific dose measures to urinary dysfunction were dependent on the presence of specific symptoms. The doses received by the anteroinferior and, to lesser extent, posterosuperior surface of the bladder had the strongest relationship with the incidence of dysuria, hematuria, and ΔIPSS10, both with and without adjustment for clinical factors. For the doses to the posteroinferior region corresponding to the area of the trigone, the only symptom with significance was incontinence. CONCLUSIONS: A spatially variable response of the bladder surface to the dose was found for symptoms of urinary dysfunction. Limiting the dose extending anteriorly might help reduce the risk of urinary dysfunction.

Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.

Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facilitates predicting outcomes or possible harmful side effects of radiation therapy treatment. Manual segmentation of the perirectal space is time consuming and challenging in the presence of inter-patient anatomical variability and may suffer from inter- and intra-observer variabilities. However automatic or semi-automatic segmentation of the perirectal space in CT images is a challenging task due to inter patient anatomical variability, contrast variability and imaging artifacts. In the model presented here, a volume of interest is obtained in a multi-atlas based segmentation approach. Un-supervised learning in the volume of interest with a Gaussian-mixture-modeling based clustering approach is adopted to achieve a soft segmentation of the perirectal space. Probabilities from soft clustering are further refined by rigid registration of the multi-atlas mask in a probabilistic domain. A maximum a posteriori approach is adopted to achieve a binary segmentation from the refined probabilities. A mean volume similarity value of 97% and a mean surface difference of 3.06 ± 0.51 mm is achieved in a leave-one-patient-out validation framework with a subset of a clinical trial dataset. Qualitative results show a good approximation of the perirectal space volume compared to the ground truth.

Independent external validation of predictive models for urinary dysfunction following external beam radiotherapy of the prostate: Issues in model development and reporting.

BACKGROUND AND PURPOSE: Most predictive models are not sufficiently validated for prospective use. We performed independent external validation of published predictive models for urinary dysfunctions following radiotherapy of the prostate. MATERIALS/METHODS: Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed. RESULTS: 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients. CONCLUSIONS: Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models.

Statistical-learning strategies generate only modestly performing predictive models for urinary symptoms following external beam radiotherapy of the prostate: A comparison of conventional and machine-learning methods.

PURPOSE: Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate. METHODS: The performance of logistic regression, elastic-net, support-vector machine, random forest, neural network, and multivariate adaptive regression splines (MARS) to predict urinary symptoms was analyzed using data from 754 participants accrued by TROG03.04-RADAR. Predictive features included dose-surface data, comorbidities, and medication-intake. Four symptoms were analyzed: dysuria, haematuria, incontinence, and frequency, each with three definitions (grade ≥ 1, grade ≥ 2 and longitudinal) with event rate between 2.3% and 76.1%. Repeated cross-validations producing matched models were implemented. A synthetic minority oversampling technique was utilized in endpoints with rare events. Parameter optimization was performed on the training data. Area under the receiver operating characteristic curve (AUROC) was used to compare performance using sample size to detect differences of ≥0.05 at the 95% confidence level. RESULTS: Logistic regression, elastic-net, random forest, MARS, and support-vector machine were the highest-performing statistical-learning strategies in 3, 3, 3, 2, and 1 endpoints, respectively. Logistic regression, MARS, elastic-net, random forest, neural network, and support-vector machine were the best, or were not significantly worse than the best, in 7, 7, 5, 5, 3, and 1 endpoints. The best-performing statistical model was for dysuria grade ≥ 1 with AUROC ± standard deviation of 0.649 ± 0.074 using MARS. For longitudinal frequency and dysuria grade ≥ 1, all strategies produced AUROC>0.6 while all haematuria endpoints and longitudinal incontinence models produced AUROC<0.6. CONCLUSIONS: Logistic regression and MARS were most likely to be the best-performing strategy for the prediction of urinary symptoms with elastic-net and random forest producing competitive results. The predictive power of the models was modest and endpoint-dependent. New features, including spatial dose maps, may be necessary to achieve better models.

Urinary symptoms following external beam radiotherapy of the prostate: Dose-symptom correlates with multiple-event and event-count models.

BACKGROUND AND PURPOSE: This study aimed to compare urinary dose-symptom correlates after external beam radiotherapy of the prostate using commonly utilised peak-symptom models to multiple-event and event-count models which account for repeated events. MATERIALS AND METHODS: Urinary symptoms (dysuria, haematuria, incontinence and frequency) from 754 participants from TROG 03.04-RADAR trial were analysed. Relative (R1-R75 Gy) and absolute (A60-A75Gy) bladder dose-surface area receiving more than a threshold dose and equivalent uniform dose using exponent a (range: a ∈[1 … 100]) were derived. The dose-symptom correlates were analysed using; peak-symptom (logistic), multiple-event (generalised estimating equation) and event-count (negative binomial regression) models. RESULTS: Stronger dose-symptom correlates were found for incontinence and frequency using multiple-event and/or event-count models. For dysuria and haematuria, similar or better relationships were found using peak-symptom models. Dysuria, haematuria and high grade (⩾ 2) incontinence were associated to high dose (R61-R71 Gy). Frequency and low grade (⩾ 1) incontinence were associated to low and intermediate dose-surface parameters (R13-R41Gy). Frequency showed a parallel behaviour (a=1) while dysuria, haematuria and incontinence showed a more serial behaviour (a=4 to a ⩾ 100). Relative dose-surface showed stronger dose-symptom associations. CONCLUSIONS: For certain endpoints, the multiple-event and event-count models provide stronger correlates over peak-symptom models. Accounting for multiple events may be advantageous for a more complete understanding of urinary dose-symptom relationships.

Dosimetry, clinical factors and medication intake influencing urinary symptoms after prostate radiotherapy: An analysis of data from the RADAR prostate radiotherapy trial.

PURPOSE/OBJECTIVE: To identify dosimetry, clinical factors and medication intake impacting urinary symptoms after prostate radiotherapy. MATERIAL AND METHODS: Data describing clinical factors and bladder dosimetry (reduced with principal component (PC) analysis) for 754 patients treated with external beam radiotherapy accrued by TROG 03.04 RADAR prostate radiotherapy trial were available for analysis. Urinary symptoms (frequency, incontinence, dysuria and haematuria) were prospectively assessed using LENT-SOMA to a median of 72months. The endpoints assessed were prevalence (grade ⩾1) at the end of radiotherapy (representing acute symptoms), at 18-, 36- and 54-month follow-ups (representing late symptoms) and peak late incidence including only grade ⩾2. Impact of factors was assessed using multivariate logistic regression models with correction for over-optimism. RESULTS: Baseline symptoms, non-insulin dependent diabetes mellitus, age and PC1 (correlated to the mean dose) impact symptoms at >1 timepoints. Associations at a single timepoint were found for cerebrovascular condition, ECOG status and non-steroidal anti-inflammatory drug intake. Peak incidence analysis shows the impact of baseline, bowel and cerebrovascular condition and smoking status. CONCLUSIONS: The prevalence and incidence analysis provide a complementary view for urinary symptom prediction. Sustained impacts across time points were found for several factors while some associations were not repeated at different time points suggesting poorer or transient impact.

Radiation dose escalation or longer androgen suppression for locally advanced prostate cancer? Data from the TROG 03.04 RADAR trial.

BACKGROUND: The relative effects of radiation dose escalation (RDE) and androgen suppression (AS) duration on local prostatic progression (LP) remain unclear. METHODS: We addressed this in the TROG 03.04 RADAR trial by incorporating a RDE programme by stratification at randomisation. Men were allocated 6 or 18 months AS±18 months zoledronate (Z). The main endpoint was a composite of clinically diagnosed LP or PSA progression with a PSA doubling time ⩾6 months. Fine and Gray competing risk modelling with adjustment for site clustering produced cumulative incidence estimates at 6.5 years for each RDE group. RESULTS: Composite LP declined coherently in the 66, 70 and 74 Gy external beam dosing groups and was lowest in the high dose rate brachytherapy boost (HDRB) group. At 6.5 years, adjusted cumulative incidences were 22%, 15%, 13% and 7% respectively. Compared to 6 months AS, 18 months AS also significantly reduced LP (p<0.001). Post-radiation urethral strictures were documented in 45 subjects and increased incrementally in the dosing groups. Crude incidences were 0.8%, 0.9%, 3.8% and 12.7% respectively. CONCLUSION: RDE and increasing AS independently reduce LP and increase urethral strictures. The risks and benefits to the individual must be balanced when selecting radiation dose and AS duration.

Gastrointestinal dose-histogram effects in the context of dose-volume-constrained prostate radiation therapy: analysis of data from the RADAR prostate radiation therapy trial.

PURPOSE: To use a high-quality multicenter trial dataset to determine dose-volume effects for gastrointestinal (GI) toxicity following radiation therapy for prostate carcinoma. Influential dose-volume histogram regions were to be determined as functions of dose, anatomical location, toxicity, and clinical endpoint. METHODS AND MATERIALS: Planning datasets for 754 participants in the TROG 03.04 RADAR trial were available, with Late Effects of Normal Tissues (LENT) Subjective, Objective, Management, and Analytic (SOMA) toxicity assessment to a median of 72 months. A rank sum method was used to define dose-volume cut-points as near-continuous functions of dose to 3 GI anatomical regions, together with a comprehensive assessment of significance. Univariate and multivariate ordinal regression was used to assess the importance of cut-points at each dose. RESULTS: Dose ranges providing significant cut-points tended to be consistent with those showing significant univariate regression odds-ratios (representing the probability of a unitary increase in toxicity grade per percent relative volume). Ranges of significant cut-points for rectal bleeding validated previously published results. Separation of the lower GI anatomy into complete anorectum, rectum, and anal canal showed the impact of mid-low doses to the anal canal on urgency and tenesmus, completeness of evacuation and stool frequency, and mid-high doses to the anorectum on bleeding and stool frequency. Derived multivariate models emphasized the importance of the high-dose region of the anorectum and rectum for rectal bleeding and mid- to low-dose regions for diarrhea and urgency and tenesmus, and low-to-mid doses to the anal canal for stool frequency, diarrhea, evacuation, and bleeding. CONCLUSIONS: Results confirm anatomical dependence of specific GI toxicities. They provide an atlas summarizing dose-histogram effects and derived constraints as functions of anatomical region, dose, toxicity, and endpoint for informing future radiation therapy planning.