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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 Radiation-induced skin dermatitis (RISD) is a common outcome experienced by adult patients with head and neck cancer (HNC) who have undergone radiation therapy. There is no standardized recommended agent for the prevention or management of RISD. Objectives The primary objective of this study was to retrospectively evaluate for effectiveness of a botanical topical agent, CamWell® Herb to Soothe® cream, on RISD. Methods 112 patients with HNC undergoing radiation therapy self-reported their RISD topical skin care agent during treatment as standard of care, CamWell used prophylactically, or CamWell use started after the first week of treatment. The primary endpoint was impact of RISD on the patient, as measured by mean Skindex-16 score throughout treatment. Measures were completed weekly. Findings The mean Skindex score was statistically significantly lower for the prophylactic group than for the standard-of-care group. CamWell may have played a role in managing RISD when compared to standard-of-care agents.

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.

BACKGROUND Patients with stage IV oligometastatic (≤ 3 sites) non-small-cell lung cancer have a progression-free survival (PFS) and overall survival benefit when all sites of metastatic disease and the primary tumor are treated radically with consolidative radiotherapy (cRT). However, the optimal selection of patients most likely from cRT is yet to be defined. PATIENTS AND METHODS Patients with metastatic non-small-cell lung cancer treated with definitive radiotherapy to all metastatic sites and primary tumor (2008-2019) were retrospectively identified. Univariable Cox proportional-hazards model was used to compare outcomes with demographic and clinical characteristics. A predictive nomogram model for selection of patients most likely to benefit from cRT was constructed. RESULTS There were 91 patients identified with a total of 114 metastases treated. Median PFS from the start of cRT was 10.9 months (95% confidence interval [CI], 8.1-16.6), while the median survival time was 37.0 months (95% CI, 31.3-NR). On univariable modeling, patients with squamous histology (hazard ratio, 4.16; 95% CI, 1.99-8.71; P < .001) and those treated with non-stereotactic body radiotherapy hypofractionated therapy (hazard ratio, 5.43; 95% CI, 2.10-14.01; P < .001) had worse overall survival, while patients with targetable mutations (hazard ratio, 0.49; 95% CI, 0.25-0.98; P = .04) had a longer survival. Using a predictive nomogram model, patients with a solitary site of metastasis, targetable mutations, intracranial disease, and metachronous timing of oligometastases had a larger PFS benefit from cRT. CONCLUSION cRT is associated with favorable outcomes in PFS and overall survival. These results may aid in patient counseling, selection for aggressive local therapy, and stratification in future prospective clinical trials.

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

Objectives Definitive intent treatment of isolated locoregional recurrence (iLR) for non-small cell lung cancer (NSCLC) is becoming more common. This study explores outcomes associated with the definitive local treatment of iLR and compares these outcomes to newly diagnosed locally advanced NSCLC (LA-NSCLC) patients. Materials and methods Patients with NSCLC treated with curative therapy between 2008 and 2019 at a tertiary academic institution were screened for iLR treated with subsequent definitive salvage therapy. Progression free survival (PFS), time to distant metastasis (TTDM), and overall survival (OS) were calculated via Kaplan–Meier methodology. Clinical outcomes were compared to a separate group of patients with de novo LA-NSCLC after adjusting for propensity score (PS). Results Sixty five cases of definitively salvaged iLR were compared to 302 patients with de novo LA-NSCLC. Most patients were treated with chemoradiotherapy (83.1% in iLR, 74.5% in LA-NSCLC). The median PFS, TTDM, and OS for the iLR cohort was 16.7 months (95% CI: 9.6–24.7), 35.8 months (95% CI: 17.1-NR), and 49.5 months (95% CI: 30.1-NR), respectively. After adjusting for PS, the iLR group was no different from the LA-NSCLC group in risk for progression (HR 0.78, 95% CI: 0.53–1.16, p = 0.22), distant metastasis (HR 0.81, 95% CI: 0.52–1.27, p = 0.36), or death (HR 0.90, 95% CI: 0.47–1.73, p = 0.75). Patterns of failure did not different significantly between groups. In the iLR cohort, patients with older age (HR 1.06, 95 CI: 1.01–1.10, p = 0.01) had a higher risk of death on multivariate analysis. Conclusion To our knowledge, this is the first report that compares the definitive treatment of iLR to de novo LA-NSCLC. When treated with definitive local therapy, patients with iLR had no difference in clinical outcomes from de novo LA-NSCLC. The use of curative local therapy according to a LA-NSCLC paradigm is advisable in patients with iLR of NSCLC for whom definitive therapy is feasible.

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.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein (Cas)-mediated gene disruption has revolutionized biomedical research as well as plant and animal breeding. However, most disease-causing mutations and agronomically important genetic variations are single base polymorphisms (single-nucleotide polymorphisms) that require precision genome editing tools for correction of the sequences. Although homology-directed repair of double-stranded breaks (DSBs) can introduce precise changes, such repairs are inefficient in differentiated animal and plant cells. Base editing and prime editing are two recently developed genome engineering approaches that can efficiently introduce precise edits into target sites without requirement of DSB formation or donor DNA templates. They have been applied in several plant species with promising results. Here, we review the extensive literature on improving the efficiency, target scope, and specificity of base editors and prime editors in plants. We also highlight recent progress on base editing in plant organellar genomes and discuss how these precision genome editing tools are advancing basic plant research and crop breeding.

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.

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.

CRISPR/Cas9 genome editing relies on sgRNA-target DNA base pairing and a short downstream PAM sequence to recognize target DNA. The strict protospacer adjacent motif (PAM) requirement hinders applications of the CRISPR/Cas9 system since it restricts the targetable sites in the genomes. xCas9 and SpCas9-NG are two recently engineered SpCas9 variants that can recognize more relaxed NG PAMs, implying a great potential in addressing the issue of PAM constraint. Here we use stable transgenic lines to evaluate the efficacies of xCas9 and SpCas9-NG in performing gene editing and base editing in rice. We found that xCas9 can efficiently induce mutations at target sites with NG and GAT PAM sequences in rice. However, base editors containing xCas9 failed to edit most of the tested target sites. SpCas9-NG exhibited a robust editing activity at sites with various NG PAMs without showing any preference for the third nucleotide after NG. Moreover, we showed that xCas9 and SpCas9-NG have higher specificity than SpCas9 at the CGG PAM site. We further demonstrated that different forms of cytosine or adenine base editors containing SpCas9-NG worked efficiently in rice with broadened PAM compatibility. Taken together, our work has yielded versatile genome-engineering tools that will significantly expand the target scope in rice and other crops.

Traditional Chinese Medicine (TCM) multiple-acupoints stimulation is widely used to improve dysphagia among post-stroke patients. However, prior research in evidence-based acupuncture mostly focused on the treatment effects of single acupoint's on dysphagia, while the evidence of optimal sequence of multiple-acupoints stimulation remains limited. In this paper, we developed an evaluation method of hybrid knowledge (deterministic knowledge and the experiential group decision knowledge) sequences based on segmentation mechanism of sub-sequence fragments, and then, we proposed a Monte Carlo Tree Search (MCTS) sequential decision-making method under the hybrid knowledge. Thereafter, we applied this proposed sequential decision-making approach to optimizing sequential decision-making schema of multiple-acupoints stimulation, to treat dysphagia among post-stroke patients. Finally, we verified the validity and the feasibility of this method by comparing it to other sequential decision-making search methods.

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: Two prior cohort studies suggested that choline, but not betaine intake is associated with an increased risk of advanced prostate cancer (PCa). Given that evidence remains limited, we evaluated whether intakes of choline and derivative betaine are associated with total and lethal PCa risk and PCa death in men with PCa. METHODS: We included 6,528 men (24.4% African American) without a cancer diagnosis at baseline (1987–1989) followed through 2012. Dietary intake was assessed using a food frequency questionnaire coupled with a nutrient database. We used Cox proportional hazards regression to estimate hazards ratios (HRs) and 95% confidence intervals (CIs) of total and lethal PCa risk overall and by race. RESULTS: Choline intake was not associated with total (N=811) or lethal (N=95) PCa risk overall or by race. Betaine intake was inversely associated with lethal (tertile 3 versus 1, HR: 0.59, 95% CI: 0.35–1.00, p-trend=0.04), but not total PCa risk; patterns for lethal PCa were similar by race. Neither nutrient was associated with PCa death in men with PCa. CONCLUSIONS: Choline intake was not associated with total or lethal PCa or with PCa death in men with PCa. Betaine intake was inversely associated with lethal, but not total PCa risk or with PCa death in men with PCa. Our results do not support the hypothesis that higher choline intake increases lethal PCa risk, but do suggest that higher betaine intake may be associated with lower lethal PCa risk. Further investigation with a larger number of lethal cases is needed.

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.

Background Limited prior data suggest that preexisting liver disease is associated with adverse outcomes among patients with coronavirus disease 2019 (COVID-19). Fibrosis-4 (FIB-4) is a noninvasive index of readily available laboratory measurements that represents hepatic fibrosis. We evaluated the association between FIB-4 at the early stage of infection and COVID-19 outcomes. Methods FIB-4 was evaluated at admission in a cohort of 267 patients admitted with early-stage COVID-19 confirmed through reverse-transcription polymerase chain reaction assay. Hazard of ventilator use and of high-flow oxygen was estimated using Cox regression models controlled for covariates. Risks of progression to severe disease and of death/prolonged hospitalization were estimated using multivariable logistic regression models. Results Forty-one (15%) patients progressed to severe disease, 36 (14%) required high-flow oxygen support, 10 (4%) required mechanical ventilator support, and 1 died. FIB-4 between 1.45 and 3.25 was associated with a greater than 5-fold (95% confidence interval [CI], 1.2–28) increased hazard of high-flow oxygen use, a greater than 4-fold (95% CI, 1.5–14.6) increased odds of progression to severe disease, and an over 3-fold (95% CI, 1.4–7.7) increased odds of death or prolonged hospitalization. FIB-4 >3.25 was associated with a greater than 12-fold (95% CI, 2.3–68. 7) increased hazard of high-flow oxygen use and an over 11-fold (95% CI, 3.1–45) increased risk of progression to severe disease. All associations were independent of sex, number of comorbidities, and inflammatory markers (D-dimer, C-reactive protein). Conclusions FIB-4 at the early-stage of COVID-19 had an independent and dose-dependent association with adverse outcomes during hospitalization. FIB-4 provided significant prognostic value for estimating adverse outcomes among COVID-19 patients.

Background Metastasectomy is standard of care for pediatric patients with metastatic sarcoma with limited disease. For patients with unresectable disease, stereotactic body radiotherapy (SBRT) may serve as an alternative. Herein, the authors report the results of a prospective, multi-institutional phase 2 trial of SBRT in children and young adults with metastatic sarcoma. Methods Patients aged >3 years and ≤40 years with unresected, osseous metastatic nonrhabdomyosarcoma sarcomas of soft tissue and bone were eligible. Patients received SBRT to a dose of 40 Gray (Gy) in 5 fractions. Local control (LC), progression-free survival (PFS), and overall survival (OS) were calculated using the Kaplan-Meier method. Results Fourteen patients with a median age of 17 years (range, 4-25 years) were treated to 37 distinct metastatic lesions. With a median follow-up of 6.8 months (30.5 months in surviving patients), the Kaplan-Meier patient-specific and lesion-specific LC rates at 6 months were 89% and 95%, respectively. The median PFS was 6 months and the median OS was 24 months. In a post hoc analysis, PFS (median, 9.3 months vs 3.7 months; log-rank P = .03) and OS (median not reached vs 12.7 months; log-rank P = .02) were improved when all known sites of metastatic disease were consolidated with SBRT compared with partial consolidation. SBRT was well tolerated, with 2 patients experiencing grade 3 toxicities. Conclusions SBRT achieved high rates of LC in pediatric patients with inoperable metastatic nonrhabdomyosarcoma sarcomas of soft tissue and bone. These results suggest that the ability to achieve total consolidation of metastatic disease with SBRT is associated with improved PFS and OS.

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.

Additional file 1: Table S1. Baseline variables and risk of multiple hospitalizations.

In this study, we analyzed baseline CT- and MRI-based image features of salivary glands to predict radiation-induced xerostomia after head-and-neck cancer (HNC) radiotherapy. A retrospective analysis was performed on 216 HNC patients who were treated using radiotherapy at a single institution between 2009 and 2016. CT and T1 post-contrast MR images along with NCI-CTCAE xerostomia grade (3-month follow-up) were prospectively collected at our institution. 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 that were correlated with xerostomia (p

Xerostomia is a common consequence of radiotherapy in head and neck cancer. The objective was to compare the regional radiation dose distribution in patients that developed xerostomia within 6 months of radiotherapy and those recovered from xerostomia within 18 months post-radiotherapy. We developed a feature generation pipeline to extract dose volume histogram features from geometrically defined ipsilateral/contralateral parotid glands, submandibular glands, and oral cavity surrogates for each patient. Permutation tests with multiple comparisons were performed to assess the dose difference between injury vs. non-injury and recovery vs. non-recovery. Ridge logistic regression models were applied to predict injury and recovery using clinical features along with dose features (D10-D90) of the subvolumes extracted from oral cavity and salivary gland contours + 3 mm peripheral shell. Model performances were assessed by the area under the receiver operating characteristic curve (AUC) using nested cross-validation. We found that different regional dose/volume metrics patterns exist for injury vs. recovery. Compared to injury, recovery has increased importance to the subvolumes receiving lower dose. Within the subvolumes, injury tends to have increased importance towards D10 from D90. This suggests that different threshold for xerostomia injury and recovery. Injury is induced by the subvolumes receiving higher dose, and the ability to recover can be preserved by further reducing the dose to subvolumes receiving lower dose.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement of IMRT was analyzed, and dichotomized at 5% WL. Each patient had a planning CT and contours of gross tumor volume (GTV) and esophagus (ESO). A total of 355 features including clinical parameter (CP), GTV and ESO (GTV&ESO) dose-volume histogram (DVH), GTV radiomics, and GTV&ESO dosiomics features were extracted. R&D features were categorized as first- (L1), second- (L2), higher-order (L3) statistics, and three combined groups, L1 + L2, L2 + L3 and L1 + L2 + L3. Multi-view texture analysis was performed to identify optimal R&D input features. In the training set (194 earlier patients), feature selection was performed using Boruta algorithm followed by collinearity removal based on variance inflation factor. Machine-learning models were developed using Laplacian kernel support vector machine (lpSVM), deep neural network (DNN) and their averaged ensemble classifiers. Prediction performance was tested on an independent test set (194 more recent patients), and compared among seven different input conditions: CP-only, DVH-only, R&D-only, DVH + CP, R&D + CP, R&D + DVH and R&D + DVH + CP. Combined GTV L1 + L2 + L3 radiomics and GTV&ESO L3 dosiomics were identified as optimal input features, which achieved the best performance with an ensemble classifier (AUC = 0.710), having statistically significantly higher predictability compared with DVH and/or CP features (p < 0.05). When this performance was compared to that with full R&D-only features which reflect traditional single-view data, there was a statistically significant difference (p < 0.05). Using optimized multi-view R&D input features is beneficial for predicting early WL in lung cancer radiotherapy, leading to improved performance compared to using conventional DVH and/or CP features.

e19406 Background: Financial toxicity (FT), or the cost-related side effect of cancer therapy, has been linked to poor clinical outcomes, greater symptom burden, and worse quality of life. While the repercussions of FT have been thoroughly explored, the longitudinal patient relationship with FT in the initial course of therapy is unknown. Methods: Patients with stage II – IV lung cancer were recruited in a prospective longitudinal non-interventional study between July 2018 and January 2020. FT was measured via the COST score, a validated questionnaire for benchmarking FT, at a) the time of cancer diagnosis and then later at b) 6-month follow up (6MFU). In this model, a lower COST score indicates increased financial hardship. Completed 6MFU data was compared to corresponding baseline data for each patient. Linear regression analysis was used to compare patient characteristics with baseline COST (COSTbase) and 6-month COST (COST6M) scores. Results: At the time of analysis, 209 patients were screened and 194 (95.1%) patients agreed to participate and complete the baseline survey. Subsequently, 93 patients completed the 6MFU survey, 32 patients had died, and 7 patients were lost to follow up. The remaining 62 patients have not met the study end point to date. Of the 93 patients that completed the 6MFU and baseline survey, the median age was 65 (range 35-89), 50.5% were male, and 76.3% were Caucasian. Over the first six months of therapy 36.5% overestimated OOP expenses by > $1000 and 22.5% reported a decrease in total monetary savings, but only 4.3% of patients made decisions about health care based on cost of care. FT was present at both time points but was worse at diagnosis than at 6MFU (median COSTbase 25 [range 1-44] vs. median COST6M 27 [range 0-44]; p = 0.04). Linear regression correlated risk factors with FT at baseline ( < 1 month monetary savings, employed but on sick leave, and inability to afford basic necessities; all p < 0.001) that were different from risk factors at 6MFU (paying much more than expected OOP and sacrificing spending to meet medical costs; p < 0.001). There was no significant difference between estimated OOP costs at baseline (median $2550 [range $0 - $500,000]) and actual OOP costs (median $2496 [range $0 – 25,900]; p = 0.25). Conclusions: FT toxicity is pervasive at both diagnosis and at 6-month follow up, however, the magnitude of toxicity changes with time. Few patients are willing to sacrifice medical care regardless of the cost. Risk factors for FT evolve, suggesting that different groups may benefit from financial intervention at diagnosis versus 6MFU.

Background Women with or at high risk of diabetes have unique health concerns across their life course. Effective methods are needed to engage women living with diabetes to develop and carry out a patient-centered research agenda. Objective This study aimed to (1) describe the creation of DiabetesSistersVoices, a virtual patient community for women living with and at risk for diabetes and (2) assess the feasibility and acceptability of DiabetesSistersVoices for engaging women in talking about their experiences, health care, and research priorities. Methods We partnered with a national advocacy organization to create DiabetesSistersVoices and to develop recruitment strategies, which included use of social media, Web-based newsletters, and weblinks through partnering organizations. Study inclusion criteria were as follows: Being a woman aged ≥18 years, residing in the United States, and self-reporting a diagnosis of diabetes or risk of diabetes. Eligible participants were given access to DiabetesSistersVoices and completed online surveys at enrollment and 6 months. We assessed trends in participants' activities, including posting questions, sharing experiences about living with diabetes, and searching for posted resources. Results We enrolled 332 women (white: 86.5%; type 1 diabetes: 76.2%; median age: 51 years [interquartile range: 31 to 59 years]) over 8 months. Most (41.6%, 138/332) were classified as being active users (ie, posting) of the virtual community, 36.1% (120/332) as observers (ie, logged in but no posts), and 22.3% (74/332) as never users (ie, completed baseline surveys but then never logged in). Online activities were constant during the study, although participants had the highest website usage during the first 10 weeks after their enrollment. Conclusions We demonstrated the feasibility and acceptability of an online patient community for women living with diabetes by showing durability of recruitment and online usage over 6 months of testing. Next steps are to address barriers to joining a virtual patient community for women of color and women with type 2 diabetes to enhance inclusiveness and gain diverse perspectives to inform diabetes research.

Table S1. GLM summary including odds ratios (OR) and 95% confidence interval (CI) for the prediction of xerostomia. (DOCX 21 kb)