A 59-year-old woman presented to the gastroenterology clinic in 2012 for evaluation of epigastric pain for several months. She also reported heartburn for several years which was well controlled with acid suppression therapy. She denied any smoking or excessive alcohol intake. An esophagogastroduodenoscopy revealed a dark discolored area about 1 × 1 cm at 32 cm (Figure A) with a Z-line at 39 cm from the incisors. Biopsies from the area showed squamous mucosa with scattered melanotic cells (Figure B hematoxylin and eosin stain and Figure C HMB45 stain) and no evidence of dysplasia or malignancy which was consistent with esophageal melanocytosis. Since then, she had periodic surveillance endoscopies which showed a lack of any neoplastic progression based on the endoscopic appearance and histology in the past ten years. Esophageal melanocytosis is a rare condition characterized by melanocytic proliferation in the esophageal squamous epithelium and increased deposition of melanin in the esophageal mucosa. The etiology is not known but chronic irritation from gastroesophageal reflux disease is thought to be an inciting factor. It is generally considered as a benign incidental finding; however, cases progressing to malignant melanoma have been reported. Therefore, endoscopic surveillance or in selected cases, endoscopic resection can be considered.

Aims. Giardia is sometimes missed by the pathologist, and we sought to determine how often this occurs at our institution—a large tertiary care center with a subspecialty gastrointestinal pathology service and what certain clinical and histologic clues can be used to flag cases with a higher likelihood of infection, targeting them for greater scrutiny. Methods and Results We identified a set of patients who tested positive for Giardia with a stool-based test, and who also received a small bowel biopsy at a similar time-point. These biopsies were retrospectively reviewed for Giardia, finding 8 positive cases. The organism was prospectively detected in 4 cases (50%) but overlooked in the remaining 4 cases (50%). Three of the 4 cases missed cases showed only rare organisms. The detected cases tended to more frequently have prominent lymphoid aggregates (3 detected cases, 0 overlooked cases) and intraepithelial lymphocytosis (3 detected cases, 0 overlooked cases). Certain clinical and histologic clues can be used to flag cases with a higher likelihood of infection. Specifically, we found abnormalities of the mucosa (active inflammation, intraepithelial lymphocytosis, villous expansion, prominent lymphoid aggregates) in each case, and 4 of 8 cases were from immunocompromised patients. Finally, 2 of 8 cases were terminal ileum biopsies. Conclusions Biopsies with a histologic abnormality or those from immunocompromised patients should receive greater attention. Routinely looking for Giardia at that terminal ileum is necessary.

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.

PurposeFor patients with localized pancreatic cancer (PC) with vascular involvement, prediction of resectability is critical to define optimal treatment. However, the current definitions of borderline resectable (BR) and locally advanced (LA) disease leave considerable heterogeneity in outcomes within these classifications. Moreover, factors beyond vascular involvement likely affect the ability to undergo resection. Herein, we share our experience developing a model that incorporates detailed radiologic, patient, and treatment factors to predict surgical resectability in patients with BR and LA PC who undergo stereotactic body radiation therapy (SBRT).Methods and materialsPatients with BR or LA PC who were treated with SBRT between 2010 and 2016 were included. The primary endpoint was margin negative resection, and predictors included age, sex, race, treatment year, performance status, initial staging, tumor volume and location, baseline and pre-SBRT carbohydrate antigen 19-9 levels, chemotherapy regimen and duration, and radiation dose. In addition, we characterized the relationship between tumors and key arteries (superior mesenteric, celiac, and common hepatic arteries), using overlap volume histograms derived from computed tomography data. A classification and regression tree was built, and leave-one-out cross-validation was performed. Prediction of surgical resection was compared between our model and staging in accordance with the National Comprehensive Care Network guidelines using McNemar’s test.ResultsA total of 191 patients were identified (128 patients with LA and 63 with BR), of which 87 patients (46%) underwent margin negative resection. The median total dose was 33 Gy. Predictors included the chemotherapy regimen, amount of arterial involvement, and age. Importantly, radiation dose that covers 95% of gross tumor volume (GTV D95), was a key predictor of resectability in certain subpopulations, and the model showed improved accuracy in the prediction of margin negative resection compared with National Comprehensive Care Network guideline staging (75% vs 63%; P < .05).ConclusionsWe demonstrate the ability to improve prediction of surgical resectabiliy beyond the current staging guidelines, which highlights the value of assessing vascular involvement in a continuous manner. In addition, we show an association between radiation dose and resectability, which suggests the potential importance of radiation to allow for resection in certain populations. External data are needed for validation and to increase the robustness of the model.

PURPOSE:In radiotherapy, it is necessary to characterize dose over the patient anatomy to target areas and organs at risk. Current tools provide methods to describe dose in terms of percentage of volume and magnitude of dose, but are limited by assumptions of anatomical homogeneity within a region of interest (ROI) and provide a non-spatially aware description of dose. A practice termed radio-morphology is proposed as a method to apply anatomical knowledge to parametrically derive new shapes and substructures from a normalized set of anatomy, ensuring consistently identifiable spatially aware features of the dose across a patient set. METHODS:Radio-morphologic (RM) features are derived from a three-step procedure: anatomy normalization, shape transformation, and dose calculation. Predefined ROI's are mapped to a common anatomy, a series of geometric transformations are applied to create new structures, and dose is overlaid to the new images to extract dosimetric features; this feature computation pipeline characterizes patient treatment with greater anatomic specificity than current methods. RESULTS:Examples of applications of this framework to derive structures include concentric shells based around expansions and contractions of the parotid glands, separation of the esophagus into slices along the z-axis, and creating radial sectors to approximate neurovascular bundles surrounding the prostate. Compared to organ-level dose-volume histograms (DVHs), using derived RM structures permits a greater level of control over the shapes and anatomical regions that are studied and ensures that all new structures are consistently identified. Using machine learning methods, these derived dose features can help uncover dose dependencies of inter- and intra-organ regions. Voxel-based and shape-based analysis of the parotid and submandibular glands identified regions that were predictive of the development of high-grade xerostomia (CTCAE grade 2 or greater) at 3-6 months post treatment. CONCLUSIONS:Radio-morphology is a valuable data mining tool that approaches radiotherapy data in a new way, improving the study of radiotherapy to potentially improve prognostic and predictive accuracy. Further applications of this methodology include the use of parametrically derived sub-volumes to drive radiotherapy treatment planning.

OBJECTIVES:Perineural invasion (PNI) has not yet gained universal acceptance as an independent predictor of adverse outcomes for prostate cancer treated with external beam radiotherapy (EBRT). We analyzed the prognostic influence of PNI for a large institutional cohort of prostate cancer patients who underwent EBRT with and without androgen deprivation therapy (ADT). MATERIAL AND METHODS:We, retrospectively, reviewed prostate cancer patients treated with EBRT from 1993 to 2007 at our institution. The primary endpoint was biochemical failure-free survival (BFFS), with secondary endpoints of metastasis-free survival (MFS), prostate cancer-specific survival (PCSS), and overall survival (OS). Univariate and multivariable Cox proportional hazards models were constructed for all survival endpoints. Hazard ratios for PNI were analyzed for the entire cohort and for subsets defined by NCCN risk level. Additionally, Kaplan-Meier survival curves were generated for all survival endpoints after stratification by PNI status, with significant differences computed using the log-rank test. RESULTS:Of 888 men included for analysis, PNI was present on biopsy specimens in 187 (21.1%). PNI was associated with clinical stage, pretreatment PSA level, biopsy Gleason score, and use of ADT (all P<0.01). Men with PNI experienced significantly inferior 10-year BFFS (40.0% vs. 57.8%, P = 0.002), 10-year MFS (79.7% vs. 89.0%, P = 0.001), and 10-year PCSS (90.9% vs. 95.9%, P = 0.009), but not 10-year OS (67.5% vs. 77.5%, P = 0.07). On multivariate analysis, PNI was independently associated with inferior BFFS (P<0.001), but not MFS, PCSS, or OS. In subset analysis, PNI was associated with inferior BFFS (P = 0.04) for high-risk patients and with both inferior BFFS (P = 0.01) and PCSS (P = 0.05) for low-risk patients. Biochemical failure occurred in 33% of low-risk men with PNI who did not receive ADT compared to 8% for low-risk men with PNI treated with ADT (P = 0.01). CONCLUSION:PNI was an independently significant predictor of adverse survival outcomes in this large institutional cohort, particularly for patients with NCCN low-risk disease. PNI should be carefully considered along with other standard prognostic factors when treating these patients with EBRT. Supplementing EBRT with ADT may be beneficial for select low-risk patients with PNI though independent validation with prospective studies is recommended.

Purpose: In patients with non-small cell lung cancer (NSCLC) who undergo trimodality therapy (chemoradiation followed by surgical resection), it is unknown whether limiting preoperative radiation dose to the uninvolved lung reduces postsurgical morbidity. This study evaluated whether radiation fall-off dose parameters to the contralateral lung that is unaffected by NSCLC are associated with postoperative complications in NSCLC patients treated with trimodality therapy. Methods and materials: We retrospectively reviewed NSCLC patients who underwent trimodality therapy between March 2008 and October 2016, with available restored digital radiation plans. Fischer's exact test was used to assess associations between patient and treatment characteristics and the development of treatment-related toxicity. Spearman rank correlation was used to measure the strength of association between dosimetric parameters. Results: Forty-six patients were identified who received trimodality therapy with intensity modulated radiation (median, 59.4 Gy; range, 45-70) and concurrent platinum doublet chemotherapy, followed by surgical resection. The median age was 64.9 years (range, 45.6-81.6). The median follow-up time was 1.9 years (range, 0.3-8.4). Twenty-four (52.2%) patients developed any-grade pulmonary toxicity and 14 (30.4%) patients developed grade 2+ pulmonary toxicity. There was an increased incidence of any-grade pulmonary toxicity in patients with contralateral lung volume receiving at least 20 Gy (V20) >= 7% compared with <7% (90%, n = 9 vs 41.7%, n = 15;P = .01). Similarly, contralateral lung V10 >= 20% was associated with an increased rate of any-grade pulmonary toxicity compared with V 10 <20% (80%, n = 12 vs 38.7%, n = 12; P = .01). Pneumonectomy/bilobectomy was associated with grade 2+ pulmonary toxicity (P = .04). Conclusions: Patients who received a higher radiation fall-off dose volume parameter (V20 >= 7% and V10 >= 20%) to the contralateral uninvolved lung had a higher incidence of any-grade postoperative pulmonary toxicity. Limiting radiation fall-off dose to the uninvolved lung may be an important modifiable radiation parameter in limiting postoperative toxicity in trimodality patients. (C) 2018 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

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.

The capture of high-quality treatment data and outcomes is necessary in order to learn from our clinical experiences with big data analytics. In radiotherapy, there are several practical challenges to overcome. Practical aspects of data collection are discussed pointing to a need for a culture change in clinical practice to one that captures structured patient-related data in routine care in a prospective manner. Radiation dosimetry and the contoured anatomy must also be captured routinely to represent the best estimate of delivered radiation. The quality and integrity present in the data are critical which poses opportunities to introduce electronic validity checking to improve them. Similarly, data completeness and methods and technology to improve the efficiency and sufficiency of data capture can be introduced. In the manuscript, the types of clinical data are discussed including patient reports, images, biospecimens, treatments, and symptom management. With a data-driven culture, the realization of a learning health system is possible unlocking the potential of big data and its influence on clinical decision-making and hypothesis generation.

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinically acquired data with machine learning to advance the initiatives of precision medicine. The LHS is comprehensive and can be used for clinical decision support, discovery, and hypothesis derivation. These developing uses can positively impact the ultimate management and therapeutic course for patients. The conceptual model for each use of clinical data, however, is different, and an overview of the implications is discussed. With advancements in technologies and culture to improve the efficiency, accuracy, and breadth of measurements of the patient condition, the concept of an LHS may be realized in precision radiation therapy.

Techniques to limit the occurrence of high grade toxicities following treatment are limited, often resulting in a decrease in quality of life of surviving patients. The goal of this study was to design a model to predict high grade xerostomia using the distribution of dose across the patient anatomy. The use of shape-based dose features was proposed to parameterize relevant regions of interest and characterize the dose distribution at a higher resolution than organ-level dose-volume histograms (DVH), in doing so, improving the overall quality of treatment plans by identifying high value areas of the anatomy. Three-dimensional contoured masks of the parotid glands, dose grids, and outcome data from a cohort of head-and-neck cancer patients treated from 2008-2015 at one institution were gathered from a learning health system database. The set of selected regions of interest (ROI's) were registered to a common anatomy (or atlas) using a coherent point drift deformable registration algorithm, and were then scaled and divided, identifying key sections of the structure that could be identified by predetermined parameters. The parotids were manipulated according to an expansion of 0.2 cm, a contraction of 0.5 cm, and sectioning along the x, y, and z axes with the origin at the center of mass, producing 24 sub-structures for each parotid (48 per patient). Dose grids were then mapped onto the sub-structures and DVH curves were calculated for each region, producing a feature set that characterized the dose to sections of the ROI. Various classification algorithms were used to test the accuracy of each feature set when predicting the worsening of xerostomia grade > 1 at a time frame of 6 to 12 months following treatment. Using the feature set generated for 117 patients parameterized by an expansion, contraction, and sectioning into octants along the major axes, a random forest classifier with 40 estimators was able to accurately predict the increase in xerostomia grade at a rate of 75.22% (sensitivity: 96.15%, specificity: 33.33%). Linear discriminant analysis yielded an accuracy of 72.65% (sensitivity: 79.48%, specificity: 58.97%). Further outcomes of this analysis identified the key factors to be the pre-treatment xerostomia grade and D25 to the anterior-inferior regions of the ipsilateral parotid, when predicting the occurrence severe outcomes. The results of this experiment support the validity of the use of shape-based models to characterize dose to a patient's anatomy. Areas near the surface of the anterior-inferior region in the ipsilateral parotid that were exposed to a high dose were deemed to have the greatest effect on the development of high-grade post-treatment xerostomia. The use of shape-based dose features provides an effective method to correlate the relationship between delivered dose and post-treatment outcomes.

Purpose: To develop consensus contouring guidelines for postoperative stereotactic body radiation therapy (SBRT) for spinal metastases. Methods and Materials: Ten spine SBRT specialists representing 10 international centers independently contoured the clinical target volume (CTV), planning target volume (PTV), spinal cord, and spinal cord planning organ at risk volume (PRV) for 10 representative clinical scenarios in postoperative spine SBRT for metastatic solid tumor malignancies. Contours were imported into the Computational Environment for Radiotherapy Research. Agreement between physicians was calculated with an expectation minimization algorithm using simultaneous truth and performance level estimation with k statistics. Target volume definition guidelines were established by finding optimized confidence level consensus contours using histogram agreement analyses. Results: Nine expert radiation oncologists and 1 neurosurgeon completed contours for all 10 cases. The mean sensitivity and specificity were 0.79 (range, 0.71-0.89) and 0.94 (range, 0.90-0.99) for the CTV and 0.79 (range, 0.70-0.95) and 0.92 (range, 0.87-0.99) for the PTV), respectively. Mean k agreement, which demonstrates the probability that contours agree by chance alone, was 0.58 (range, 0.43-0.70) for CTV and 0.58 (range, 0.37-0.76) for PTV (P<.001 for all cases). Optimized consensus contours were established for all patients with 80% confidence interval. Recommendations for CTV include treatment of the entire preoperative extent of bony and epidural disease, plus immediately adjacent bony anatomic compartments at risk of microscopic disease extension. In particular, a "donut-shaped" CTV was consistently applied in cases of preoperative circumferential epidural extension, regardless of extent of residual epidural extension. Otherwise more conformal anatomic-based CTVs were determined and described. Spinal instrumentation was consistently excluded from the CTV. Conclusions: We provide consensus contouring guidelines for common scenarios in postoperative SBRT for spinal metastases. These consensus guidelines are subject to clinical validation. (C) 2016 Elsevier Inc. All rights reserved.

Background: In men undergoing definitive radiation for prostate cancer, it is unclear whether early biochemical response can provide additional prognostic value beyond pre-treatment risk stratification. Methods: Prostate cancer patients consecutively treated with definitive radiation at our institution by a single provider from 1993 to 2006 and who had an end-of-radiation (EOR) PSA ( n =688, median follow-up 11.2 years). We analyzed the association of an EOR PSA level, obtained during the last week of radiation, with survival outcomes. Multivariable-adjusted cox proportional hazards models were constructed to assess associations between a detectable EOR PSA (defined as ⩾0.1 ng ml −1 ) and biochemical failure-free survival (BFFS), metastasis-free survival (MFS), prostate cancer-specific survival (PCSS) and overall survival (OS). Kaplan–Meier survival curves were constructed, with stratification by EOR PSA. Results: At the end of radiation, the PSA level was undetectable in 30% of patients. Men with a detectable EOR PSA experienced inferior 10-year BFFS (49.7% versus 64.4%, P <0.001), 10-year MFS (84.8% versus 92.0%, P =0.003), 10-year PCSS (94.3% versus 98.2%, P =0.007) and 10-year OS (75.8% versus 82.5%, P =0.01), as compared to men with an undetectable EOR PSA. Among National Comprehensive Care Network (NCCN) intermediate- and high-risk men who were treated with definitive radiation and androgen deprivation therapy (ADT), a detectable EOR PSA was more strongly associated with PCSS than initial NCCN risk level (EOR PSA: HR 5.89, 95% CI 2.37–14.65, P <0.001; NCCN risk level: HR 2.01, 95% CI 0.74–5.42, P =0.168). Main study limitations are retrospective study design and associated biases. Conclusions: EOR PSA was significantly associated with survival endpoints in men who received treatment with definitive radiation and ADT. Whether the EOR PSA can be used to modulate treatment intensity merits further investigation.

It is unknown whether limiting radiation fall-off dose to the uninvolved lung will reduce surgical morbidity in lung cancer patients who ultimately undergo surgical resection. The goal of this study was to evaluate the correlation between contralateral lung dose delivered during neoadjuvant chemoradiation and post-operative pulmonary complications in stage III non–small cell lung cancer (NSCLC) patients. This study includes patients with stage III NSCLCs treated at our institution with resection after chemoradiation (trimodality therapy) from 2007 to 2016. Dose volume histogram (DVH) data from restored electronic radiation plans and patient charts were retrospectively reviewed through an IRB approved study. Analysis was restricted to patients with available DVH data. Fisher’s exact test was used to assess associations between patient/treatment characteristics and post-treatment pulmonary toxicity. Actuarial overall survival (OS), progression-free survival (PFS), and local control (LC) were determined by the Kaplan-Meier method. All patients (n=42) received neoadjuvant chemoradiation with intensity modulated radiation (median 50.4 Gy, range 45-70) and concurrent platinum doublet chemotherapy. The median age was 68.9 (range 49.8-84.5), and the median follow-up time was 1.9 years (range, 0.5-8.4). Of the patients, 76.2% were former/current smokers, and 40.5% had underlying lung conditions. Median baseline FEV1 was 85.5% predicted (range, 52.9-132.2); median baseline DLCO was 88.2% predicted (range, 43.9-160.1). 23.8% (n=10) patients developed grade 2 or higher pulmonary complications. These consisted of pneumonitis (n=3), respiratory failure (n=5), and pleural effusion (n=6). Fifty percent (n=21) developed pulmonary complications of any grade. Pneumonectomy/bi-lobectomy was associated with pulmonary toxicity (P = 0.013). Patients were categorized as having received a high or low mean lung dose (MLD) to the contralateral lung based on the median value within our study population (less or more than 5.6 Gy). For patients who received contralateral MLD <5.6 Gy, 14.3% developed grade 2 or higher lung complications (n=3) while 33.3% of patients who received contralateral MLD > 5.6 Gy developed grade 2 or higher lung complications (n=7). Three-year OS was 65.8%. Three-year PFS was 60.2%. Three-year LC was 81.2%. 14.3% of patients had pathologic complete response. Our descriptive analysis demonstrates that patients who received a higher radiation dose to the contralateral uninvolved lung had a higher incidence of post-operative pulmonary toxicity. Dosimetric consideration of radiation fall-off dose to the uninvolved lung may be an important consideration in limiting post-operative toxicity in patients who undergo trimodality therapy. However, further analysis in a larger study population is needed to clarify associations.

Head and neck cancer treatment-related dysphagia (HNCTD) is associated with significant morbidity and mortality risks. Risk reduction efforts, however, are complicated by the heterogeneity associated with HNCTD. Our group recently demonstrated in a pilot cross-sectional analysis that HNCTD as measured by the MD Anderson Dysphagia Inventory (MDADI) and the Sydney Swallow Questionnaire (SSQ) could be quantified by three unique clusters suggesting the potential to develop a HNCTD signature. In this follow-up study, we sought to determine if this finding was reproducible in an independent patient population. Following our pilot study, we prospectively collected through the web interface to our Oncospace database a cohort of patients seen in follow-up care after radiotherapy from December 2015 to January 2017. These patients were not included in our pilot cohort. Patients concurrently completed the MDADI and the SSQ. Spearman correlation coefficient was calculated. Unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis was performed. The number of clusters as well as the mean, standard deviation (SD), and range of each cluster were compared to our pilot study. We identified 323 subjects in this follow-up study with no missing data, and with a mean follow-up length of 809 days (range: 58 - 2746). The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.71, p < 0.001). K-means cluster analysis demonstrated that three unique cohorts (elbow criterion) could again be identified with CLUSPLOT analysis confirming that 100% of variances were explained. Twenty-eight patients were identified in the cluster (group 1) with the highest SSQ scores and the lowest MDADI scores (SSQ mean: 935.3, SD: 193.3; range: 711.0 – 1443.5); 96 patients were identified in the intermediate group (group 2) for both assessments (SSQ mean: 386.9, SD: 102.6; range: 244.6 – 646.5); 199 patients (group 3) were identified as having the highest MDADI scores and lowest SSQ scores (SSQ mean: 100.2, SD: 64.6; range: 2.0 – 242.0). The mean MDADI was < 65 (mean: 54.6, SD: 15.4) in group 1 and > 65 in groups 2 (mean: 74.8, SD: 12.7) and 3 (mean: 88.5, SD: 9.9). This data was consistent with our pilot study as well as independently published data on the clinical significance of MDADI scores. This analysis provides independent validation of our pilot study demonstrating that HNCTD can be classified into three unique groups. This supports the utilization of a HNCTD signature based on both MDADI and SSQ as an objective and reliable outcome measure in future clinical studies.

BACKGROUND: To evaluate the relationship between PSA testing history and high-risk disease among older men diagnosed with prostate cancer.METHODS: Records from 1993 to 2014 were reviewed for men who underwent radiotherapy for prostate cancer at age 75 years or older. Patients were classified into one of four groups based on PSA-testing history: (1) no PSA testing; (2) incomplete/ineffective PSA testing; (3) PSA testing; or (4) cannot be determined. Outcomes of interest were National Comprehensive Cancer Network (NCCN) risk group (that is, low, intermediate or high risk) and biopsy grade at diagnosis. Multivariable logistic regression was used to determine the association between PSA testing history and high-risk cancer.RESULTS: PSA-testing history was available in 274 (94.5%) of 290 subjects meeting study criteria. In total, 148 men (54.0%) underwent PSA testing with follow-up biopsy, 72 (26.3%) underwent PSA testing without appropriate follow-up, and 54 men (19.7%) did not undergo PSA testing. Patients who underwent PSA testing were significantly less likely to be diagnosed with NCCN high-risk cancer (23.0% vs 51.6%, P < 0.001). On multivariable analysis, men with no/incomplete PSA testing had more than three-fold increased odds of high-risk disease at diagnosis (odds ratio 3.39, 95% confidence interval 1.96-5.87, P < 0.001) as compared to the tested population.CONCLUSIONS: Older men who underwent no PSA testing or incomplete testing were significantly more likely to be diagnosed with high-risk prostate cancer than those who were previously screened. It is reasonable to consider screening in healthy older men likely to benefit from early detection and treatment.

Objective: We explore whether a knowledge-discovery approach building a Classification and Regression Tree (CART) prediction model for weight loss (WL) in head and neck cancer (HNC) patients treated with radiation therapy (RT) is feasible. Methods and materials: HNC patients from 2007 to 2015 were identified from a prospectively collected database Oncospace. Two prediction models at different time points were developed to predict weight loss >= 5 kg at 3 months post-RT by CART algorithm: (1) during RT planning using patient demographic, delineated dose data, planning target volume-organs at risk shape relationships data and (2) at the end of treatment (EOT) using additional on-treatment toxicities and quality of life data. Results: Among 391 patients identified, WL predictors during RT planning were International Classification of Diseases diagnosis; dose to masticatory and superior constrictor muscles, larynx, and parotid; and age. At EOT, patient-reported oral intake, diagnosis, N stage, nausea, pain, dose to larynx, parotid, and low-dose planning target volume-larynx distance were significant predictive factors. The area under the curve during RT and EOT was 0.773 and 0.821, respectively. Conclusions: We demonstrate the feasibility and potential value of an informatics infrastructure that has facilitated insight into the prediction of WL using the CART algorithm. The prediction accuracy significantly improved with the inclusion of additional treatment-related data and has the potential to be leveraged as a strategy to develop a learning health system. (C) 2018 Published by Elsevier Inc. on behalf of the American Society for Radiation Oncology.

Since publication of the CROSS study, the majority of patients with locally advanced esophageal cancer are treated with neoadjuvant chemoradiotherapy prior to esophagectomy (trimodality therapy, TMT). The stomach, specifically the fundus and greater curvature, is used to re-create neo-esophagus and is often located in the pre-operative radiation (RT) field. This study aims to determine if RT to the stomach and its substructures correlate with anastomotic complication (AC). From 2007 to 2016, patients with esophageal cancer treated with TMT at a tertiary academic institution with restored digital RT plans were included in this IRB approved study. Clinical and pathologic data were obtained retrospectively. The stomach and its substructures were contoured on the preoperative RT planning scans and dosimetric parameters were extracted. AC was defined as a leak and/or a stricture. Fisher-exact and Wilcoxon rank-sum tests were used. 96 patients were included in the analysis. The median age was 63 (55-70); 82% of patients were male. Majority of the tumors were located in the distal esophagus (52%) and gastroesophageal junction (GEJ, 30%) versus 15% and 3% in the middle and proximal esophagus, respectively. Adenocarcinoma was the predominant histology (80%). Carboplatin and paclitaxel was used in majority of the patients (36%). Median RT dose was 45 Gy (range, 41.4-54 Gy). Transhiatal esophagectomy was the common surgery performed (50%), followed by Ivor-Lewis (33%), 3-incision (14%) and other (3%). AC developed in 57% of the patients (47 strictures,49%; 16 leaks, 17%; 8 both, 8%). Diabetes (DM) was more common in patients with AC (n=16, 29% vs. n=7, 17%, p=0.172). Esophagectomy type was associated with AC (p<0.000). The predominant type of surgery in patients with AC was transhiatal (62%) followed by 3-incision (18%), Ivor-Lewis (16%) and others (4%). The mean dose to the stomach, fundus, and greater curvature was 27 Gy (18-35 Gy), 33 Gy (23-45 Gy), and 23 Gy (13-33 Gy), respectively. RT dose to the stomach and its substructures were not associated with AC (p>0.05). Of the 47 patients with distal/GEJ tumor location and esophagectomies with cervical anastomoses, 72% of them developed AC (31 strictures, 66%; 11 leaks, 23%; 8= both, 17%). DM was more common in patients with AC (n=9, 27% vs. 0%, p=0.047). RT was not associated with AC (p>0.05). Our analysis does not demonstrate an association between RT to gastric substructures that form the neo-esophagus and AC. However, it does show an increased risk of AC in patients who undergo esophagectomies with cervical anastomosis. In this population, the majority with a leak had anastomosis in the neck and distal esophageal or GEJ tumor undergoing cervical anastomosis. Patients with distal tumors may be better served with anastomosis in the thorax rather than neck. Further analysis in a larger study population is needed to clarify associations.

Risk of late normal tissue toxicities such as xerostomia place significant quality of life and economic burdens on surviving patients. Preventing this toxicity remains limited. The aim of this study is to build a robust comprehensive xerostomia risk prediction model as the foundation for a personalized learning health system (LHS) by incorporating a wide range of clinical, demographic, and dosimetric factors contained within our treatment planning and clinical information database to gain insights into reducing this risk. Head and neck cancer patients treated with intensity modulated radiation therapy from 2008-2015 were selected. Patient demographic, clinical, and dosimetric factors were queried. Exploratory data analyses were conducted to assess baseline characteristics by the outcome status. Parametric and nonparametric analyses were performed to comprehensively examine risk factors predicting for the primary endpoint of grade ≥2 vs <2 xerostomia. Risk factors that individually predicted severe xerostomia included age, chemotherapy, HPV infection, weight loss, submandibular D70, and parotid D95. In univariate analysis, the oldest age (age >55 years) group was 9.37 times more likely to develop severe xerostomia (P=0.035). Chemotherapy (OR=1.76, P=0.048), increased weight loss (OR=2.14, P=0.002), patients with combined submandibular D70 over 55 Gy (OR=1.84, P=0.045), and combined parotid D95 over 9 Gy (OR=1.82, P=0.019) had a higher risk for severe xerostomia. In a nonparametric decision tree analysis, ten-fold cross-validation demonstrated that the combined parotid D95 was the dominant classifier node. For patients receiving a combined parotid D95<9 Gy, weight loss ≥9 kg and age >55 years further increased the risk of severe xerostomia. For patients receiving a combined parotid D95≥9 Gy, current/past smokers vs never smokers and combined parotid volume <56 mL vs ≥56 mL also influenced the risk of severe xerostomia. The area under receiver-operating characteristic (AUC) curve for the final model was 0.71 in the training set and 0.69 in the testing set, demonstrating good performance to predict severe xerostomia. The model using the combined parotid D95 (AUC=0.71) vs the combined mean parotid dose (AUC=0.62) demonstrated significantly improved prediction for severe xerostomia. Our xerostomia risk model identified both the influence of patient age and several modifiable treatment factors. These observations support the use of this model as a foundation for the development of a personalized xerostomia LHS. The low dose bath to the parotid gland was identified to be particularly significant and offer insight into new clinical strategies to reduce xerostomia.