Search

Pancreatic cancer is the fourth leading cause of cancer-related death with a 10% 5-year overall survival rate (OS). Radiation therapy (RT) in addition to dose escalation improves the outcome by significantly increasing the OS at 2 and 3 years but is hindered by the toxicity of the duodenum. Our group showed that the insertion of hydrogel spacer reduces duodenal toxicity, but the complex anatomy and the demanding procedure make the benefits highly uncertain. Here, we investigated the feasibility of augmenting the workflow with intraoperative feedback to reduce the adverse effects of the uncertainties.We simulated three scenarios of the virtual spacer for four cadavers with two types of gross tumor volume (GTV) (small and large); first, the ideal injection; second, the nonideal injection that incorporates common spacer placement uncertainties; and third, the corrective injection that uses the simulation result from nonideal injection and is designed to compensate for the effect of uncertainties. We considered two common uncertainties: (1) "Narrowing" is defined as the injection of smaller spacer volume than planned. (2) "Missing part" is defined as failure to inject spacer in the ascending section of the duodenum. A total of 32 stereotactic body radiation therapy (SBRT) plans (33 Gy in 5 fractions) were designed, for four cadavers, two GTV sizes, and two types of uncertainties. The preinjection scenario for each case was compared with three scenarios of virtual spacer placement from the dosimetric and geometric points of view.We found that the overlapping PTV space with the duodenum is an informative quantity for determining the effective location of the spacer. The ideal spacer distribution reduced the duodenal V33Gy for small and large GTV to less than 0.3 and 0.1cc, from an average of 3.3cc, and 1.2cc for the preinjection scenario. However, spacer placement uncertainties reduced the efficacy of the spacer in sparing the duodenum (duodenal V33Gy: 1.3 and 0.4cc). The separation between duodenum and GTV decreased by an average of 5.3 and 4.6 mm. The corrective feedback can effectively bring back the expected benefits from the ideal location of the spacer (averaged V33Gy of 0.4 and 0.1cc).An informative feedback metric was introduced and used to mitigate the effect of spacer placement uncertainties and maximize the benefits of the EUS-guided procedure.

In the management of symptomatic bone metastases, current practice guidelines do not provide clear methodology for selecting palliative radiotherapy (RT) regimens based on specific patient and disease features. Decision support aids may offer an effective means for translating the complex data needed to render individualised treatment decisions, yet no such tools are available for use in this setting. Thus, we describe the development of the Bone Metastases Ensemble Trees for Survival-Decision Support Platform (BMETS-DSP), which aims to optimise selection of evidence-based, individualised palliative RT regimens.The Ottawa Decision Support Framework was used as the theoretical basis for development of BMETS-DSP. First, we utilised stakeholder input and review of the literature to assess determinants underlying the provider decision. Based on this assessment and iterative stakeholder feedback, we developed the web-based, provider-facing BMETS-DSP. Consistent with the underlying theoretical framework, our design also included assessment of decision quality using the International Patient Decision Aids Standards (IPDAS) certification checklist.Stakeholder input and review of 54 evidence-based publications identified the following determinants of the provider decision: estimated prognosis, characteristics of the target symptomatic lesion and the primary cancer type, consideration of alternative interventions, access to patient-specific recommendations, and patient preferences. Based on these determinants, we developed the BMETS-DSP that (1) collects patient-specific data, (2) displays an individualised predicted survival curve, and (3) provides case-specific, evidence-based recommendations regarding RT, open surgery, systemic therapy, and hospice referral to aid in the decision-making process. The finalised tool met IPDAS quality requirements. Preliminary results of a pilot assessment suggest impact of clinical outcomes.We describe the successful development of a provider-facing decision support platform to aid in the provision of palliative RT in better alignment with patient and disease features. Impact of the BMETS-DSP on decision outcomes will be further assessed in a randomised, controlled study.

PURPOSE Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients. MATERIALS AND METHODS CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes. Patients with lung cancer (N = 37) treated with definitive RT without prior RT were prospectively enrolled in the study. Radiomics and dosiomics features were extracted from CT and 3D dose volume, and SWL probability (≥ 0.5 considered as SWL) was predicted. Two physicians predicted whether the patient would have SWL before and after reviewing the CDSS prediction. The physician's prediction performance without and with CDSS and prediction changes before and after using CDSS were compared. RESULTS CDSS showed significantly better prediction accuracy than physicians (0.73 v 0.54) with higher specificity (0.81 v 0.50) but with lower sensitivity (0.55 v 0.64). Physicians changed their original prediction after reviewing CDSS prediction for four cases (three correctly and one incorrectly), for all of which CDSS prediction was correct. Physicians' prediction was improved with CDSS in accuracy (0.54-0.59), sensitivity (0.64-0.73), specificity (0.50-0.54), positive predictive value (0.35-0.40), and negative predictive value (0.76-0.82). CONCLUSION Machine learning–based CDSS showed the potential to improve SWL prediction in lung cancer RT. More investigation on a larger patient cohort is needed to properly interpret CDSS prediction performance and its benefit in clinical decision making.

In radiation therapy, poor contour delineations of Region of Interests (ROI) may result in incorrect radiation dosing and increase the chance of radiation-induced toxicities. To better recognize these contours, we used a feature fusion-based 3-dimensional convolution neural network (3D-CNN), multi-view convolution neural network (MV-CNN), and 3D point cloud to retrospectively detect abnormal bladder contours among prostate cancer patients. We defined three patterns of abnormal bladder contours: (1) discontinuities: missing slices and disparate volumes, (2) surface aberrations: extended or contracted slices, (3) small volume: bladder volume [Formula: see text][Formula: see text]ml. We created virtual samples for discontinuities and surface aberrations by randomly adding pixel to one or more slices outside the original contours and randomly extending or shrinking one or more slices. For both 3D-CNN and MV-CNN methods, we utilized the Local Binary Pattern (LBP) and Canny operators for feature extraction and compared several feature fusion-based approaches, including Original image + LBP processed image, Original image + Canny processed image, Original image + LBP processed image + Canny processed image. For the 3D point cloud, we applied the 3D point cloud segmentation method (Rand LA-Net) and the 3D point cloud classifying method (DGCNN). We had 344 samples available (219 real contours and 125 virtual contours) altogether. All the algorithms were trained on 200 bladder contours, validated on 100 bladders, then tested on 44 real annotated contours. Among all the approaches, the “Original + LBP”-based MV-CNN model achieved the highest accuracy: 100% for predicting discontinuity and small volume, 91.3% for predicting normal contours, and 90.9% for predicting surface aberrations. MV-CNN performed more accurately and efficiently across all the feature fusion methods. In particular, “Original + LBP”-based MV-CNN achieved the highest test accuracy. Our tools can detect anomalies of bladder contours in clinical settings and may improve the process of contour quality assurance (QA).

BACKGROUND: Cancer therapy is associated with severe financial burden. However, the magnitude and longitudinal patient relationship with financial toxicity (FT) in the initial course of therapy is unclear. METHODS: Patients with stage II-IV lung cancer were recruited in a prospective longitudinal study between July 2018 and March 2020. FT was measured via the validated COmprehensive Score for financial Toxicity (COST) at the time of cancer diagnosis and at 6-month follow-up (6MFU). 6MFU data were compared with corresponding baseline data. A lower COST score indicates increased financial hardship. RESULTS: At the time of analysis, 215 agreed to participate. Subsequently, 112 patients completed 6MFU. On average, slightly more FT was observed at diagnosis compared with 6MFU (median COSTbase 25 v COST6M 27; P < .001); however, individual patients experienced large changes in FT. At 6MFU, 27.7% of patients had made financial sacrifices to pay for treatment but only 4.5% refused medical care based on cost. Median reported out-of-pocket (OOP) costs for the initial 6 months of cancer treatment was $2,496 (range, $0-25,900). Risk factors for FT at diagnosis were unique from risk factors at 6MFU. Actual OOP expenses were not correlated with FT; however, inability to predict upcoming treatment expenses resulted in higher FT at 6MFU. DISCUSSION: FT is a pervasive challenge during the initiation of lung cancer treatment. Few patients are willing to sacrifice medical care regardless of the cost. Risk factors for FT evolve, resulting in unique interventional targets throughout therapy.

Background We investigate the time to and clinical factors associated with patient-reported difficulty swallowing in lung cancer patients treated with radiation therapy (RT). Methods Between October 2016 and October 2019, lung cancer patients treated with conventionally fractionated RT at a tertiary cancer center were identified. Weekly, patients reported difficulty swallowing (patient-reported outcome version of the Common Terminology Criteria for Adverse Events [PRO-CTCAE] v.1: 0-none, 1-mild, 2-moderate, 3-severe, 4-very severe). Physicians graded dysphagia (CTCAE v.4: 0-none, 1-symptoms without altered intake, 2-symptomatic; altered eating/swallowing, 3-severely altered eating/swallowing, 4-life-threatening consequences, 5-death). Tumor-related difficulty swallowing was not recorded at baseline; thus, patients reporting ≥moderate symptoms ≤7 days of RT start were excluded. We evaluated the time to new patient reports of ≥moderate difficulty swallowing and CTCAE grade 2+ dysphagia and development over time using the cumulative incidence method. Multivariable logistic regression evaluated associations between clinical factors, esophageal V60, and development of esophageal symptoms. Results Of the 200 patients identified: median age was 69 years, 52% were male, and 89% had stage III+ disease. Patients received a median of 63 Gy with chemotherapy (91.5%). At least moderate difficulty swallowing during RT was reported by 76 of 200 patients (38%); clinicians rated dysphagia as altering oral intake or worse for 26 of 200 (13%). Median time to first report of symptoms was 21 days (interquartile ratio [IQR], 18-34.5) for the 76 patients who reported ≥moderate symptoms and 33 days (IQR, 24-42) in the 26 patients whose provider reported grade 2+ dysphagia. The 30-day incidence of patient-reported ≥moderate swallowing difficulty and provider grade 2+ dysphagia was 26% (95% CI: 20%-32%) and 6% (95% CI: 3%-9%), respectively. Esophageal V60 >7 % was the clinical factor most associated with patient-reported ≥moderate esophageal symptoms (odds ratio 6.1, 95% CI: 3.0-12.3). Conclusions Patients report at least moderate difficulty swallowing more often and earlier than providers report grade 2+ dysphagia. Esophageal V60 ≥7% was most associated with development of moderate severity or worse patient-reported swallowing difficulty.

Purpose The radiation treatment summary provides a clinical and technical overview of a patient's full course of radiation therapy. Despite its importance to multiple stakeholders, there is no widely followed radiation treatment summary template. Methods and Materials The Commission on Cancer convened a multistakeholder workgroup to develop a synoptic radiation treatment summary template. The workgroup included individuals with expertise in radiation, medical and surgical oncology, medical physics, oncology informatics, cancer registry, electronic medical record systems, treatment planning systems, and registry information systems. The workgroup iterated a template until consensus was achieved. Results The consensus radiation treatment summary template is divided into 3 sections that allows for a mix of structured and free text. The first section, "Radiation Course Summary," is meant to provide information that is of broad interest and in a manner that is potentially accessible to patients, their families, and nononcology-trained care team members. The second section, "Anatomic Target Summary," provides information that is potentially useful to oncology-trained care team members who will be primarily interested in which anatomies were irradiated, by what modality, and to what cumulative dose. The third section, "Delivered Prescriptions," summarizes technical information that is primarily of interest and accessible to radiation oncology-trained clinicians, registrars, and researchers. Conclusions We have proposed a consensus template with 3 sections to meet the needs of a diverse set of consumers. We recommend that providers, professional societies, and accreditation bodies with interest in the radiation treatment summary continue collaborative efforts to test, iterate, and drive adoption of a synoptic template.

BACKGROUND: Progressive, metastatic non-small cell lung cancer (NSCLC) often requires the initiation of new systemic therapy. However, in patients with NSCLC that is oligoprogressive (≤3 lesions), local radiotherapy (RT) may allow for the eradication of resistant microclones and, therefore, the continuation of otherwise effective systemic therapy. METHODS: Patients treated from 2008 to 2019 with definitive doses of RT to all sites of intracranial or extracranial oligoprogression without a change in systemic therapy were identified. Radiographic progression-free survival (rPFS) and time to new therapy (TNT) were measured. Associations between baseline clinical and treatment-related variables were correlated with progression-free survival via Cox proportional hazards modeling. RESULTS: Among 198 unique patients, 253 oligoprogressive events were identified. Intracranial progression occurred in 51% of the patients, and extracranial progression occurred in 49%. In the entire cohort, the median rPFS was 7.9 months (95% CI, 6.5-10.0 months), and the median TNT was 8.8 months (95% CI, 7.2-10.9 months). On adjusted modeling, patients with the following disease characteristics were associated with better rPFS: better performance status (P = .003), fewer metastases (P = .03), longer time to oligoprogression (P = .009), and fewer previous systemic therapies (P = .02). Having multiple sites of oligoprogression was associated with worse rPFS (P

PURPOSE: We investigate whether esophageal dose–length parameters (L(dose)) can robustly predict significant weight loss—≥5% weight loss during radiation therapy (RT) compared with the weight before RT—in patients with lung cancer treated with definitive intent. METHODS AND MATERIALS: Patients with lung cancer treated with conventionally fractionated RT between 2010 and 2018 were retro-spectively identified. L(Fdose) and L(Pdose), the length of full- and partial-circumferential esophagus receiving greater than a threshold dose in Gy, respectively, were created. Multivariate logistic regression examined the associations between individual L(dose) and weight loss after adjusting for clinical parameters and correcting for multiple comparisons. Ridge logistic regression examined the relative importance of L(dose) compared with dose–volume (V(dose)), mean dose (D(mean)), and clinical parameters in determining weight loss. Univariate logistic regression examined the unadjusted probability of weight loss for important L(dose) parameters. RESULTS: Among the 214 patients identified, median age was 66.9 years (range, 31.5–88.9 years), 50.5% (n = 108) were male, 68.2% (n = 146) had stage III lung cancer, median RT dose was 63 Gy (range, 60–66 Gy), and 88.3% (n = 189) received concurrent chemotherapy. Esophagus lengths receiving high full-circumferential (L(F50)-L(F60)) and high partial-circumferential doses (L(P60)) were associated with significant weight loss (P ≤.05). L(F65) and L(P65) reached near significance (P = .06 and .053, respectively). L(F65) > L(F60) > L(P65) were the most important dose parameters in determining weight loss compared with other L(dose), V(dose), and D(mean) parameters. CONCLUSIONS: Esophageal L(dose) parameters are an efficient way of interpreting complex dose parameters in relation to weight loss toxicity among patients with lung cancer receiving definitive RT.

To determine whether a combination of data-driven, personalized feedback and implementation of a graduated, sequential intervention model improved key measures of physician workflow and quality in radiation treatment planning.All radiation oncologists across 3 facilities at a single academic institution were prospectively evaluated on 5 predefined metrics of timeliness and accuracy in the treatment-planning process using a web-based institutional data repository and an institutional incident learning system. The study period encompassed 10 quarters from 2014 to 2016, with 2013 serving as a retrospective baseline. Physicians received quarterly individualized reports of their compliance metrics (a practice labeled the Physician Dashboard), and administrative interventions were initiated if20% noncompliance with any metric was exceeded within a quarter. Consecutive quarters of noncompliance resulted in escalating interventions, including progress meetings with department leadership, and culminated in financial penalties. Rates of noncompliance were compared before and after implementation of this model.Three thousand six hundred sixty pre-Dashboard and 9497 post-Dashboard simulations were analyzed. After Dashboard implementation, significant reductions were observed in the rates of simulation orders requiring signature by a covering physician (14.1% vs 7.4%, P.001), and the submission of plan contours ≥1 day (43.1% vs 23.1%, P.001) or ≥2 days (30.8% vs 18.3%, P = .002) after the due date. There was some decrease in rates of inaccurate or incomplete plan submissions (6.2% vs 3.9%, P = .08). Seven of the 12 physicians received at least 1 intervention, with only 2 receiving all levels of intervention.Regular assessment and targeted feedback using the Physician Dashboard significantly improved radiation oncologist compliance with clinically meaningful treatment planning responsibilities at a high-volume academic center.

Purpose Radiation-induced xerostomia is one of the most prevalent symptoms during and after head and neck cancer radiation therapy (RT). We aimed to discover the spatial radiation dose-based (voxel dose) importance pattern in the major salivary glands in relation to the recovery of xerostomia 18 months after RT, and to compare the recovery voxel dose importance pattern to the acute incidence (injury) pattern. Methods and Materials This study included all patients within our database with xerostomia outcomes after completion of curative intensity modulated RT. Common Terminology Criteria for Adverse Events xerostomia grade was used to define recovered versus nonrecovered group at baseline, between end of treatment and 18 months post-RT, and beyond 18 months, respectively. Ridge logistic regression was performed to predict the probability of xerostomia recovery. Voxel doses within geometrically defined parotid glands (PG) and submandibular glands (SMG), demographic characteristics, and clinical factors were included in the algorithm. We plotted the normalized learned weights on the 3-dimensional PG and SMG structures to visualize the voxel dose importance for predicting xerostomia recovery. Results A total of 146 head and neck cancer patients from 2008 to 2016 were identified. The superior region of the ipsilateral and contralateral PG was the most influencial for xerostomia recovery. The area under the receiver operating characteristic curve evaluated using 10-fold cross-validation for ridge logistic regression was 0.68 ± 0.07. Compared with injury, the recovery voxel dose importance pattern was more symmetrical and was influenced by lower dose voxels. Conclusions The superior portion of the 2 PGs (low dose region) are the most influential on xerostomia recovery and seem to be equal in their contribution. The dissimilarity of the influence pattern between injury and recovery suggests different underlying mechanisms. The importance pattern identified by spatial radiation dose and machine learning methods can improve our understanding of normal tissue toxicities in RT. Further external validation is warranted.

Advances in lung cancer therapy have resulted in improved clinical outcomes. Unfortunately, advances can come at a financial cost to patients and their families that poses a significant risk to overall quality of life (QoL). Financial distress has been shown to be associated with increased symptom burden and decreased treatment compliance but the magnitude of financial distress is not well characterized in lung cancer populations.Patients with stage II-IV newly diagnosed lung cancer and starting first-line therapy were recruited at a tertiary academic institution between July 2018 and April 2019. The comprehensive score for financial toxicity (COST) was used to assess financial toxicity and the Functional Assessment of Cancer Therapy-Lung (FACT-L) was used to assess QoL. Associations between financial toxicity and baseline variables were assessed using multivariable linear regression and correlations were assessed using the Pearson correlation.In this study, 143 consecutive patients were approached and 91.6% agreed to participate (N = 131). The median age was 65 years (35-90); 52.7% were male (n = 69), and 75.6% were white (n = 99). The inability to afford basic necessities and having1 month of savings was associated with increased financial toxicity (P0.001) after adjusting for other factors such as age, race, insurance, and income. There was also a trend toward increased financial toxicity among those who were employed but on sick leave (P = 0.06). Increased financial toxicity was correlated with a decrease in QoL (correlation coefficient 0.41, P0.001). Patients' anticipated out-of-pocket (OOP) expenses for the upcoming 6 months ranged from $0 to $50 000 (median $2150). However, there was no correlation between anticipated OOP expenses and either financial toxicity or QoL.These data identify key factors for identifying at-risk patients and builds a framework for exploring the benefit of financial counseling interventions, which may improve QoL and oncologic outcomes.

Objective To explore relationships between dose to periprostatic anatomic structures and erectile dysfunction (ED) outcomes in an institutional cohort treated with prostate brachytherapy. Methods The Sexual Health Inventory for Men (SHIM) instrument was administered for stage cT1-T2 prostate cancer patients treated with Pd-103 brachytherapy over a 10-year interval. Dose volume histograms for regional organs at risk and periprostatic regions were calculated with and without expansions to account for contouring uncertainty. Regression tree analysis clustered patients into ED risk groups. Results We identified 115 men treated with definitive prostate brachytherapy who had 2 years of complete follow-up. On univariate analysis, the subapical region (SAR) caudal to prostate was the only defined region with dose volume histograms parameters significant for potency outcomes. Regression tree analysis separated patients into low ED risk (mean 2-year SHIM 20.03), medium ED risk (15.02), and high ED risk (5.54) groups. Among patients with good baseline function (SHIM ≥ 17), a dose ≥72.75 Gy to 20% of the SAR with 1 cm expansion was most predictive for 2-year potency outcome. On multivariate analysis, regression tree risk group remained significant for predicting potency outcomes even after adjustment for baseline SHIM and age. Conclusion Dose to the SAR immediately caudal to prostate was predictive for potency outcomes in patients with good baseline function. Minimization of dose to this region may improve potency outcomes following prostate brachytherapy.

Key Points Question What is the optimal minimum duration of androgen deprivation therapy (ADT) when treating high-risk prostate cancer with high-dose radiotherapy? Findings This patient-level cohort study of 3 cohorts found a significant interaction between the type of high-dose radiotherapy (external beam radiotherapy with or without a brachytherapy boost) and optimal duration. Prolonging ADT for 18 to 28 months was associated with a 63% reduction in death or metastasis with external beam radiotherapy; when a brachytherapy boost was added, the nonlinear association between ADT and distant metastasis-free survival was broad and spanned 12 months. Meaning The findings of this cohort study suggest that patients receiving external beam radiotherapy alone may benefit from ADT durations of 18 months or more; if a brachytherapy boost is added, a duration of 18 months or possibly less may be optimal., Importance Radiotherapy combined with androgen deprivation therapy (ADT) is a standard of care for high-risk prostate cancer. However, the interplay between radiotherapy dose and the required minimum duration of ADT is uncertain. Objective To determine the specific ADT duration threshold that provides a distant metastasis-free survival (DMFS) benefit in patients with high-risk prostate cancer receiving external beam radiotherapy (EBRT) or EBRT with a brachytherapy boost (EBRT+BT). Design, Settings, and Participants This was a cohort study of 3 cohorts assembled from a multicenter retrospective study (2000-2013); a post hoc analysis of the Randomized Androgen Deprivation and Radiotherapy 03/04 (RADAR; 2003-2007) randomized clinical trial (RCT); and a cross-trial comparison of the RADAR vs the Deprivación Androgénica y Radio Terapía (Androgen Deprivation and Radiation Therapy; DART) 01/05 RCT (2005-2010). In all, the study analyzed 1827 patients treated with EBRT and 1108 patients treated with EBRT+BT from the retrospective cohort; 181 treated with EBRT and 203 with EBRT+BT from RADAR; and 91 patients treated with EBRT from DART. The study was conducted from October 15, 2020, to July 1, 2021, and the data analyses, from January 5 to June 15, 2021. Exposures High-dose EBRT or EBRT+BT for an ADT duration determined by patient-physician choice (retrospective) or by randomization (RCTs). Main Outcomes and Measures The primary outcome was DMFS; secondary outcome was overall survival (OS). Natural cubic spline analysis identified minimum thresholds (months). Results This cohort study of 3 studies totaling 3410 men (mean age [SD], 68 [62-74] years; race and ethnicity not collected) with high-risk prostate cancer found a significant interaction between the treatment type (EBRT vs EBRT+BT) and ADT duration (binned to, This cohort study explores associations between the duration of androgen deprivation therapy and distant metastasis-free survival in men undergoing external beam radiotherapy with and without a brachytherapy boost for treatment of high-risk prostate cancer.

Key Points Question Are external beam radiotherapy, with or without brachytherapy boost, or radical prostatectomy associated with differences in prostate cancer–specific mortality or distant metastasis outcomes in patients with high-risk prostate cancer after accounting for delivery of guideline-concordant multimodality therapy? Findings In this cohort study of 6004 men with high-risk prostate cancer and at least 1 additional adverse clinicopathologic feature, no differences in prostate cancer-specific mortality across treatment modalities were identified among patients who received guideline-concordant multimodality therapy, although differences in time to metastasis were observed. However, significant differences in prostate cancer–specific mortality were identified when guideline-concordant multimodality care was not delivered. Meaning These findings suggest that guideline-concordant multimodality care was associated with better prostate cancer–specific mortality outcomes for patients with high-risk prostate cancer., This cohort study assesses prostate cancer–specific mortality and distant metastasis outcomes among men with high-risk prostate cancer treated with radical prostatectomy or external beam radiotherapy with or without brachytherapy boost., Importance The optimal management strategy for high-risk prostate cancer and additional adverse clinicopathologic features remains unknown. Objective To compare clinical outcomes among patients with high-risk prostate cancer after definitive treatment. Design, Setting, and Participants This retrospective cohort study included patients with high-risk prostate cancer (as defined by the National Comprehensive Cancer Network [NCCN]) and at least 1 adverse clinicopathologic feature (defined as any primary Gleason pattern 5 on biopsy, clinical T3b-4 disease, ≥50% cores with biopsy results positive for prostate cancer, or NCCN ≥2 high-risk features) treated between 2000 and 2014 at 16 tertiary centers. Data were analyzed in November 2020. Exposures Radical prostatectomy (RP), external beam radiotherapy (EBRT) with androgen deprivation therapy (ADT), or EBRT plus brachytherapy boost (BT) with ADT. Guideline-concordant multimodal treatment was defined as RP with appropriate use of multimodal therapy (optimal RP), EBRT with at least 2 years of ADT (optimal EBRT), or EBRT with BT with at least 1 year ADT (optimal EBRT with BT). Main Outcomes and Measures The primary outcome was prostate cancer–specific mortality; distant metastasis was a secondary outcome. Differences were evaluated using inverse probability of treatment weight–adjusted Fine-Gray competing risk regression models. Results A total of 6004 men (median [interquartile range] age, 66.4 [60.9-71.8] years) with high-risk prostate cancer were analyzed, including 3175 patients (52.9%) who underwent RP, 1830 patients (30.5%) who underwent EBRT alone, and 999 patients (16.6%) who underwent EBRT with BT. Compared with RP, treatment with EBRT with BT (subdistribution hazard ratio [sHR] 0.78, [95% CI, 0.63-0.97]; P = .03) or with EBRT alone (sHR, 0.70 [95% CI, 0.53-0.92]; P = .01) was associated with significantly improved prostate cancer–specific mortality; there was no difference in prostate cancer–specific mortality between EBRT with BT and EBRT alone (sHR, 0.89 [95% CI, 0.67-1.18]; P = .43). No significant differences in prostate cancer–specific mortality were found across treatment cohorts among 2940 patients who received guideline-concordant multimodality treatment (eg, optimal EBRT alone vs optimal RP: sHR, 0.76 [95% CI, 0.52-1.09]; P = .14). However, treatment with EBRT alone or EBRT with BT was consistently associated with lower rates of distant metastasis compared with treatment with RP (eg, EBRT vs RP: sHR, 0.50 [95% CI, 0.44-0.58]; P

Nonhomogeneous dose optimization (NHDO) is exploited in stereotactic body radiation therapy (SBRT) to increase dose delivery to the tumor and allow rapid dose falloff to surrounding normal tissues. We investigate changes in plan quality when NHDO is applied to inverse-planned conventionally fractionated radiation therapy (CF-RT) plans in patients with non-small cell lung cancer.Patients with near-central non-small cell lung cancer treated with CF-RT in 2018 at a single institution were identified. CF-RT plans were replanned using NHDO techniques, including normalizing to a lower isodose line, while maintaining clinically acceptable normal tissue constraints and target coverage. Tumor control probabilities were calculated. We compared delivered CF-RT plans using homogenous dose optimization (HDO) versus NHDO using Wilcoxon signed-rank tests. Median values are reported.Thirteen patients were replanned with NHDO techniques. Planning target volume coverage by the prescription dose was similar (NHDO = 96% vs HDO = 97%, P = .3). All normal-tissue dose constraints were met. NHDO plans were prescribed to a lower-prescription isodose line compared with HDO plans (85% vs 97%, P = .001). NHDO increased mean dose to the planning target volume (73 Gy vs 67 Gy), dose heterogeneity, and dose falloff gradient (P .03). NHDO decreased mean dose to surrounding lungs, esophagus, and heart (relative reduction of 6%, 14%, and 15%, respectively; P .05). Other normal tissue objectives improved with NHDO, including total lung V40 and V60, heart V30, and maximum esophageal dose (P .05). Tumor control probabilities doubled from 31.6% to 65.4% with NHDO (P = .001).In select patients, NHDO principles used in SBRT optimization can be applied to CF-RT. NHDO results in increased tumor dose, reduction in select organ-at-risk dose objectives, and better maintenance of target coverage and normal-tissue constraints compared with HDO. Our data demonstrate that principles of NHDO used in SBRT can also improve plan quality in CF-RT.

PURPOSE: In recent years, the American Society for Radiation Oncology (ASTRO) has received requests for a standard list of data elements from other societies, database architects, Electronic Health Record vendors and, most recently, the pharmaceutical industry. These requests point to a growing interest in capturing radiation oncology data within registries and for quality measurement, interoperability initiatives, and research. Identifying a short and consistent list will lead to improved care coordination, a reduction in data entry by practice staff, and a more complete view of the holistic approach required for cancer treatment.METHODS AND MATERIALS: The task force formulated recommendations based on analysis from radiation specific data elements currently in use in registries, accreditation programs, incident learning systems, and electronic health records. The draft manuscript was peer reviewed by 8 reviewers and ASTRO legal counsel and was revised accordingly and posted on the ASTRO website for public comment in April 2019 for 2 weeks. The final document was approved by the ASTRO Board of Directors in June 2019.

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed. (C) 2019 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.

The application of big data to the quality assurance of radiation therapy is multifaceted. Big data can be used to detect anomalies and suboptimal quality metrics through both statistical means and more advanced machine learning and artificial intelligence. The application of these methods to clinical practice is discussed through examples of guideline adherence, contour integrity, treatment delivery mechanics, and treatment plan quality. The ultimate goal is to apply big data methods to direct measures of patient outcomes for care quality. The era of big data and machine learning is maturing and the implementation for quality assurance promises to improve the quality of care for patients.

Purpose To analyze baseline CT/MR-based image features of salivary glands to predict radiation-induced xerostomia 3-months after head-and-neck cancer (HNC) radiotherapy. Methods A retrospective analysis was performed on 266 HNC patients who were treated using radiotherapy at our institution between 2009 and 2018. CT and T1 post-contrast MR images along with NCI-CTCAE xerostomia grade (3-month follow-up) were prospectively collected at our institution. CT and MR images were registered on which parotid/submandibular glands were contoured. Image features were extracted for ipsilateral/contralateral parotid and submandibular glands relative to the location of the primary tumor. Dose-volume-histogram (DVH) parameters were also acquired. Features were pre-selected based on Spearman correlation before modelling by examining the correlation with xerostomia (p

AIM AND BACKGROUND: We describe a successful implementation of a departmental incident learning system (ILS) across a regionally expanding academic radiation oncology department, dovetailing with a structured integration of the safety and quality program across clinical sites. MATERIALS AND METHODS M: Over 6 years between 2011 and 2017, a long-standing departmental ILS was deployed to 4 clinical locations beyond the primary clinical location where it had been established. We queried all events reported to the ILS during this period and analyzed trends in reporting by clinical site. The chi-square test was used to determine whether differences over time in the rate of reporting were statistically significant. We describe a synchronous development of a common safety and quality program over the same period. RESULTS: There was an overall increase in the number of event reports from each location over the time period from 2011 to 2017. The percentage increase in reported events from the first year of implementation to 2017 was 457% in site 1, 166.7% in site 2, 194.3% in site 3, 1025% in site 4, and 633.3% in site 5, with an overall increase of 677.7%. A statistically significant increase in the rate of reporting was seen from the first year of implementation to 2017 (p

Purpose We evaluated patterns of event reporting across five clinical locations within an academic radiation oncology department, with the goal of better understanding variability across sites. Methods and Materials We analyzed 1,351 events reported to a departmental incident learning system over 1 calendar year across the five locations with respect to volume of events, event type, process map location of origin and detection, and event reporter. Results We found marked variability in reporting patterns, including reporting rate, event type, event severity, event location of origin and detection within the departmental process map, and discipline of event reporters. These differences relate both to variability in process and workflow (reflected by frequency of specific workflow events at each site) and in reporting culture (reflected by volume or rate of event reporting, and discipline of event reporter). Conclusions These data highlight the variability in reporting culture even within a single department, and therefore the need to tailor and individualize safety and quality programs to the unique clinical site, with the long-term goal of achieving a common culture of safety while supporting unique processes at individual locations. This work also raises concern about extrapolating single-institution incident learning system results without understanding the unique workflow and culture of clinical sites.

Purpose Patients with head-and-neck cancer (HNC) may experience xerostomia after radiation therapy (RT), which leads to compromised quality of life. The purpose of this study is to explore how the spatial pattern of radiation dose (radiomorphology) in the major salivary glands influences xerostomia in patients with HNC. Methods and materials A data-driven approach using spatially explicit dosimetric predictors, voxel dose (ie, actual radiation dose in voxels in parotid glands [PG] and submandibular glands [SMG]) was used to predict whether patients would develop xerostomia 3 months after RT. Using planned radiation dose data and other nondose covariates including baseline xerostomia grade of 427 patients with HNC in our database, the machine learning methods were used to investigate the influence of dose patterns across subvolumes in PG and SMG on xerostomia. Results Of the 3 supervised learning methods studied, ridge logistic regression yielded the best predictive performance. Ridge logistic regression was also preferred to evaluate the influence pattern of highly correlated dose on xerostomia, which showed a discriminative pattern of influence of doses in the PG and SMG on xerostomia. Moreover, the superior–anterior portion of the contralateral PG and medial portion of the ipsilateral PG were determined to be the most influential regions regarding dose effect on xerostomia. The area under the receiver operating characteristic curve from a 10-fold cross-validation was 0.70 ± 0.04. Conclusions Radiomorphology, combined with machine learning methods, is able to suggest patterns of dose in PG and SMG that are the most influential on xerostomia. The influence pattern identified by this data-driven approach and machine learning methods may help improve RT treatment planning and reduce xerostomia after treatment.

Modern medicine, including the care of the cancer patient, has significantly advanced, with the evidence-based medicine paradigm serving to guide clinical care decisions. Yet we now also recognize the tremendous heterogeneity not only of disease states but of the patient and his or her environment as it influences treatment outcomes and toxicities. These reasons and many others have led to a reevaluation of the generalizability of randomized trials and growing interest in accounting for this heterogeneity under the rubric of precision medicine as it relates to personalizing clinical care predictions, decisions, and therapy for the disease state. For the cancer patient treated with radiation therapy, characterizing the spatial treatment heterogeneity has been a fundamental tenet of routine clinical care facilitated by established database and imaging platforms. Leveraging these platforms to further characterize and collate all clinically relevant sources of heterogeneity that affect the longitudinal health outcomes of the irradiated cancer patient provides an opportunity to generate a critical informatics infrastructure on which precision radiation therapy may be realized. In doing so, data science-driven insight discoveries, personalized clinical decisions, and the potential to accelerate translational efforts may be realized ideally within a network of institutions with locally developed yet coordinated informatics infrastructures. The path toward realizing these goals has many needs and challenges, which we summarize, with many still to be realized and understood. Early efforts by our group have identified the feasibility of this approach using routine clinical data sets and offer promise that this transformation can be successfully realized in radiation oncology.

Purpose/objective(s) Patient reported outcomes (PRO) show promise in predicting which patients are at risk for worst outcomes after chemoradiation (CRT) and may be used to improve symptom management. We investigate if patient-reported symptoms collected during thoracic radiation (TRT) may help identify patients at risk of developing radiation pneumonitis (RP) post-TRT. Materials/methods Between 2016 to 2020, patients with stage III NSCLC treated with definitive-intent TRT at our institution were identified. Patients completed a 10-item symptom-report questionnaire using the PRO Common Terminology Criteria for Adverse Events (PRO-CTCAE v.1.0) weekly during RT and at follow-up. Physicians graded lung-specific symptoms and side-effects using CTCAE v4.0 at the same time-points. RP was defined as radiographic inflammation of the lung within the radiation field attributable to TRT, and excluding other causes. Patient and treatment characteristics were recorded. Descriptive statistics and univariate competing risks analysis were performed to describe and identify variables associated with development of RP. Results Of 131 patients identified: median age was 66 years, 53% were male, and 45.8% patients had co-morbid lung disease. Patients received a median of 63 Gy (Interquartile range (IQR): 60-63 Gy) with chemotherapy (88%). The median mean-lung-dose (MLD) was 14.5 Gy (IQR: 12-17 Gy) and the median lung V20 was 20% (IQR: 20%-30%). After TRT, 61 patients received immunotherapy. In the entire cohort, twenty-four patients (18%) developed any grade RP, of which n = 21 were grade ≥2. The median time to diagnosis of RP after TRT was 3.0 months. Factors associated with the development of RP included: age (HR 1.06, P = 0.0004) and MLD (P = 0.0005). In terms of PROs associated with development of RP: patient reported severe pain was significantly associated (HR 3.4, P = 0.01), while moderate anxiety (HR 2.3, P = 0.06), and cough (HR 4.53, P = 0.06) were non-significantly associated with RP. Physician assessed grade 2 dyspnea where medical intervention was needed was associated with RP (HR 3.43, P = 0.02). Conclusion Patient symptom reports during treatment may be associated with the risk development of RP. Larger studies of prospectively collected PROs during TRT are needed to further explore these potential associations with RP.

Purpose/Objective(s) Palliative radiation may be beneficial for patients with metastatic or locally advanced disease causing malignant airway obstruction (MAO). However, the subset of patients most likely to benefit from palliative airway radiation is unknown. In this study, we seek to report local control and survival outcomes for patients treated with palliative radiation for MAO and provide prognostic factors for improved overall survival. Materials/Methods An IRB approved single institution retrospective review of patients treated with palliative thoracic radiation for MAO from 2008-2016 was undertaken. The primary study endpoint was overall survival (OS) and secondary endpoints included local response and airway specific progression free survival. Kaplan-Meier survival, and Cox proportional hazards regression analyses were performed to identify factors associated with OS. Variables with clinical and univariate significance were modelled using multivariate logistic regression analysis. Results Palliative radiation for MAO was identified for 237 patients (median age of 63.8 yrs). 88.6% of patients were treated for primary lung cancer and 41.6% of those patients had adenocarcinoma histology. At time of analysis, 78.5% patients had died. Median follow-up was 2 months. Out of 116 patients with imaging follow-up: 31.0% had airway specific progression, 68.9% had complete or partial response at last follow up. For those patients with palliative tumor response, median time to progression was 5.0 (Range 1.1-17.8) months. Kaplan-Meier estimate of median overall survival following start of radiation therapy was 5.0 (95% CI 3.8-5.8) months. In multivariable analyses, there was a marginally increased hazard ratio for patients who had dyspnea at rest HR 2.09 (95% CI 0.78-5.62), oxygen requirement at presentation HR 1.28 (95% CI 0.81-2.01), and higher ECOG level 2-4 HR 1.21 (95% CI 0.81-1.80). Conversely, squamous cell histology and treatment with BED10 greater than or equal to 39 (equivalent to the commonly used 30Gy in 10 fraction regimen) were significantly predictive of improved OS, HR 0.56 (95% CI 0.32-0.97) and HR 0.42 (95% CI 0.28-0.64) respectively. Conclusion To our knowledge, this analysis is the largest collection of patients receiving palliative thoracic radiotherapy for MAO. These data show that MAO is a poor prognostic feature for survival, but treatment responses are seen. Increased BED delivered and squamous cell carcinoma, a radiosensitive tumor histology, were associated with improved survival. These results may help to inform optimized patient selection for and outcomes of patients with MAO receiving palliative RT.

PURPOSE/OBJECTIVE(S) Imaging quantified by radiomics has yielded reproducible predictions of both oncologic outcomes and treatment-related toxicity. Much of the correlation with oncologic outcomes has focused on image features from the primary tumor. However, both primary tumor and nodal features can impact outcomes, and it is known that differences in gene expression in primary tumors and nodal metastases provide distinct information regarding survival in head and neck squamous cell carcinomas (HNSCC). Nevertheless, current radiomic biomarkers often make no distinction between primary and nodal radiomic features. Therefore, we hypothesize that combining CT image features of primary tumors and nodal metastases in HNSCC will improve our ability to predict progression-free survival (PFS) compared to primary features alone. MATERIALS/METHODS Pre-treatment CT images were prospectively collected from 115 HNSCC patients undergoing RT at our institution from 2008-2018. PFS was determined at time of last follow-up prior to 2018. Clinical data were systemically captured from patient medical charts. 107 radiomic features were extracted for the primary tumor and the ipsilateral/contralateral nodal regions. Features were pre-selected by literature review for those possibly significant in predicting loco-regional control of HNSCC. Tumor volume, correlation of gray level co-occurrence matrix (Corr-GLCM), run length non-uniformity of gray level of gray level run length matrix (RLN-GLRLM), and coarseness of neighboring gray tone difference matrix (Coarse-NGTDM) for the primary contours; and tumor volume and Corr-GLCM of the nodal contours were included in the model. A regression analysis of pre-selected features was performed using ridge regularization in the training set (n = 93 primary; n = 48 primary & nodal), and a generalized linear model was built with repeated ten-fold cross validation of patients treated from 2008-2017. Model performance was evaluated in a test set (patients treated 2017-2018) using the area under the receiver operating characteristic curve (AUC). Models were built separately for patients with primary tumor only and primary + nodal radiomic features. RESULTS The AUC/sensitivity/specificity on the test set for the model with primary features (n = 22) was 0.91/1.00/0.75, and for the model with primary and nodal features (n = 18) was 0.75/0.60/0.92. The features with the highest coefficients in the combined model included primary Coarse-NGTDM (β = -0.21), primary Corr-GLCM (β = 0.0082), and nodal Corr-GLCM (β = -0.00041). CONCLUSION In a small cohort of HNSCC patients, combining nodal features with primary features did not improve the prediction performance compared to primary features alone. This work suggests that primary tumor radiomic features may influence PFS more than nodal features. Future work is required in a larger cohort to validate these findings.

PURPOSE The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a tertiary-care, academic medical center, but its validity and stability when applied to external data sets are unknown. PATIENTS AND METHODS Patients treated with palliative radiation therapy for SBM from May 2013 to May 2016 at two hospital-based community radiation oncology clinics were included, and medical records were retrospectively reviewed to collect model covariates and survival time. The Kaplan-Meier method was used to estimate overall survival from consultation to death or last follow-up. Model discrimination was estimated using time-dependent area under the curve (tAUC), which was calculated using survival predictions from BMETS based on the initial training data set. RESULTS A total of 216 sites of SBM were treated in 182 patients. Most common histologies were breast (27%), lung (23%), and prostate (23%). Compared with the BMETS training set, the external validation population was older (mean age, 67 v 62 years; P < .001), had more primary breast (27% v 19%; P = .03) and prostate cancer (20% v 12%; P = .01), and survived longer (median, 10.7 v 6.4 months). When the BMETS model was applied to the external data set, tAUC values at 3, 6, and 12 months were 0.82, 0.77, and 0.77, respectively. When refit with data from the combined training and external validation sets, tAUC remained > 0.79. CONCLUSION BMETS maintained high discriminative ability when applied to an external validation set and when refit with new data, supporting its generalizability, stability, and the feasibility of dynamic modeling.

Lymphopenia is associated with decreased survival outcomes in head and neck squamous cell carcinoma (HNSCC). This is a significant concern especially for frail individuals who are more vulnerable to immunological dysregulations. A robust analysis is needed to understand whether we should expend efforts to limit treatment-related hematological toxicities in HNSCC. First, we would like to understand the prognostic significance for baseline (BL) vs. treatment-related lymphopenia (TRL). We want to know if lymphopenia is merely a reflection of the patient’s frailty at baseline, or if this is iatrogenic and therefore can be a target for treatment modifications in a bid to improve survival. Here, we identified 222 newly diagnosed M0 HNSCC patients treated with radiation ± systemic therapy in 2015-2018 at our institution. Clinical frailty is defined by age ≥ 65 or KPS ≤ 70. Using Kaplan Meier estimates and Cox regression with dichotomous variables, we performed multivariate analysis for both overall survival (OS) and progression-free survival (PFS). Important predictors included frailty (p ≤ 0.002) and ≥ 2K/mm3 decrease in absolute lymphocyte counts (ALC) (p ≤ 0.006). BL did not significantly impact OS or PFS (p ≤ 0.37). For TRL, ALC decrease had greater prognostic significance compared with ALC nadirs (p ≤ 0.45). Next, we simplified our survival model to include only frailty and TRL. Overall, fit patients with modest ALC decline (< 2K/mm3) achieved excellent survival outcomes while frail patients with severe ALC decline (≥ 2K/mm3) had inferior outcomes (3-year OS 95% vs. 56%, p < 0.0001; 3-year PFS 84% vs. 42%, p = 0.002). On subgroup analyses, similar outcomes were also identified for HPV+ HNSCC (n = 172, 3-year OS 96% vs. 71%, p = 0.002; 3-year PFS 89% vs. 54% p = 0.03). Finally, we want to know if ALC decline is determined primarily by treatment intensity, or if frail patients are naturally predisposed to greater ALC decline during treatment. In our data, frail patients had more modest ALC decline when compared to fit patients (1.26 ± 0.57 vs. 1.54 ± 0.58 K/mm3 p = 0.0006). In our survival model, we did not observe any first-order interactions between frailty and ALC decline (p = 0.54). The extent of ALC decline was also higher for patients with concurrent administrations of cisplatin (as opposed to radiation alone, p < 0.0001). Thus, we postulate that the extent of ALC decline is determined primarily by treatment intensity. It is possible that frail patients with severe ALC decline have inferior survival outcomes because they cannot maintain immunological balance and respond poorly when there is significant TRL. This opens opportunities to re-evaluate if the risk of TRL is modifiable by limiting the number of concurrent cycles of chemotherapy administered, and by considering radiation dose de-intensification especially for HPV-associated HNSCC. Lastly, TRL becomes an important consideration when immunotherapeutics are grafted onto existing CRT treatment paradigms. Citation Format: Carmen Kut, Todd McNutt, Carole Fakhry, Theodore DeWeese, Harry Quon. Lymphocyte kinetics, frailty and survival outcomes in HNSCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1971.

Background Unplanned hospitalization during cancer treatment is costly, can disrupt treatment, and affect patient quality of life. However, incidence and risks factors for hospitalization during lung cancer radiotherapy are not well characterized. Methods Patients treated with definitive intent radiation (≥45 Gy) for lung cancer between 2008 and 2018 at a tertiary academic institution were identified. In addition to patient, tumor, and treatment related characteristics, specific baseline frailty markers (Charlson comorbidity index, ECOG, patient reported weight loss, BMI, hemoglobin, creatinine, albumin) were recorded. All cancer-related hospitalizations during or within 30 days of completing radiation were identified. Associations between baseline variables and any hospitalization, number of hospitalizations, and overall survival were identified using multivariable linear regression and multivariable Cox proportional-hazards models, respectively. Results Of 270 patients included: median age was 66.6 years (31–88), 50.4% of patients were male (n = 136), 62% were Caucasian (n = 168). Cancer-related hospitalization incidence was 17% (n = 47), of which 21% of patients hospitalized (n = 10/47) had > 1 hospitalization. On multivariable analysis, each 1 g/dL baseline drop in albumin was associated with a 2.4 times higher risk of any hospitalization (95% confidence interval (CI) 1.2–5.0, P = 0.01), and baseline hemoglobin ≤10 was associated with, on average, 2.7 more hospitalizations than having pre-treatment hemoglobin > 10 (95% CI 1.3–5.4, P = 0.01). After controlling for baseline variables, cancer-related hospitalization was associated with 1.8 times increased risk of all-cause death (95% CI: 1.02–3.1, P = 0.04). Conclusions Our data show baseline factors can predict those who may be at increased risk for hospitalization, which was independently associated with increased mortality. Taken together, these data support the need for developing further studies aimed at early and aggressive interventions to decrease hospitalizations during treatment.

Importance In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus. Objective To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer. Design, Setting, and Participants This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019. Exposures Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy. Main Outcomes and Measures Prostate cancer–specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts. Results Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782). Conclusions and Relevance Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.

Background: Lower-dose cone-beam computed tomography protocols for image-guided radiotherapy may permit target localization while minimizing radiation exposure. We prospectively evaluated a lower-dose cone-beam protocol for central nervous system image-guided radiotherapy across a multinational pediatrics consortium. Methods: Seven institutions prospectively employed a lower-dose cone-beam computed tomography central nervous system protocol (weighted average dose 0.7 mGy) for patients ≤21 years. Treatment table shifts between setup with surface lasers versus cone-beam computed tomography were used to approximate setup accuracy, and vector magnitudes for these shifts were calculated. Setup group mean, interpatient, interinstitution, and random error were estimated, and clinical factors were compared by mixed linear modeling. Results: Among 96 patients, with 2179 pretreatment cone-beam computed tomography acquisitions, median age was 9 years (1-20). Setup parameters were 3.13, 3.02, 1.64, and 1.48 mm for vector magnitude group mean, interpatient, interinstitution, and random error, respectively. On multivariable analysis, there were no significant differences in mean vector magnitude by age, gender, performance status, target location, extent of resection, chemotherapy, or steroid or anesthesia use. Providers rated >99% of images as adequate or better for target localization. Conclusions: A lower-dose cone-beam computed tomography protocol demonstrated table shift vector magnitude that approximate clinical target volume/planning target volume expansions used in central nervous system radiotherapy. There were no significant clinical predictors of setup accuracy identified, supporting use of this lower-dose cone-beam computed tomography protocol across a diverse pediatric population with brain tumors.