Search

Purpose: To evaluate the efficacy of prominent machine learning algorithms in predicting normal tissue complication probability using clinical data obtained from 2 distinct disease sites and to create a software tool that facilitates the automatic determination of the optimal algorithm to model any given labeled data set. Methods and Materials: We obtained 3 sets of radiation toxicity data (478 patients) from our clinic: gastrointestinal toxicity, radiation pneumonitis, and radiation esophagitis. These data comprised clinicopathological and dosimetric information for patients diagnosed with non-small cell lung cancer and anal squamous cell carcinoma. Each data set was modeled using 11 commonly employed machine learning algorithms (elastic net, least absolute shrinkage and selection operator [LASSO], random forest, random forest regression, support vector machine, extreme gradient boosting, light gradient boosting machine, k-nearest neighbors, neural network, Bayesian-LASSO, and Bayesian neural network) by randomly dividing the data set into a training and test set. The training set was used to create and tune the model, and the test set served to assess it by calculating performance metrics. This process was repeated 100 times by each algorithm for each data set. Figures were generated to visually compare the performance of the algorithms. A graphical user interface was developed to automate this whole process. Results: LASSO achieved the highest area under the precision-recall curve (0.807 ± 0.067) for radiation esophagitis, random forest for gastrointestinal toxicity (0.726 ± 0.096), and the neural network for radiation pneumonitis (0.878 ± 0.060). The area under the curve was 0.754 ± 0.069, 0.889 ± 0.043, and 0.905 ± 0.045, respectively. The graphical user interface was used to compare all algorithms for each data set automatically. When averaging the area under the precision-recall curve across all toxicities, Bayesian-LASSO was the best model. Conclusions: Our results show that there is no best algorithm for all data sets. Therefore, it is important to compare multiple algorithms when training an outcome prediction model on a new data set. The graphical user interface created for this study automatically compares the performance of these 11 algorithms for any data set.

We present two cases of cardiac metastases adjacent to the right ventricle in a 55-year-old male and a 61-year-old female, both treated with magnetic resonance (MR)-guided adaptive stereotactic radiation therapy (SBRT). The prescribed regimen was 30Gy delivered in 3 fractions using a 1.5 Tesla magnetic resonance linear accelerator (MR-linac). Patients exhibited favorable tolerance to the treatment, with no observed acute toxicity.

Background/Objectives: We assessed the influence of local patients and clinical characteristics on the performance of commercial deep learning (DL) segmentation models for head-and-neck (HN), breast, and prostate cancers. Methods: Clinical computed tomography (CT) scans and clinically approved contours of 210 patients (53 HN, 49 left breast, 55 right breast, and 53 prostate cancer) were used to train and validate segmentation models integrated within a vendor-supplied DL training toolkit and to assess the performance of both vendor-pretrained and custom-trained models. Four custom models (HN, left breast, right breast, and prostate) were trained and validated with 30 (training)/5 (validation) HN, 34/5 left breast, 39/5 right breast, and 30/5 prostate patients to auto-segment a total of 24 organs at risk (OARs). Subsequently, both vendor-pretrained and custom-trained models were tested on the remaining patients from each group. Auto-segmented contours were evaluated by comparing them with clinically approved contours via the Dice similarity coefficient (DSC) and mean surface distance (MSD). The performance of the left and right breast models was assessed jointly according to ipsilateral/contralateral locations. Results: The average DSCs for all structures in vendor-pretrained and custom-trained models were as follows: 0.81 ± 0.12 and 0.86 ± 0.11 in HN; 0.67 ± 0.16 and 0.80 ± 0.11 in the breast; and 0.87 ± 0.09 and 0.92 ± 0.06 in the prostate. The corresponding average MSDs were 0.81 ± 0.76 mm and 0.76 ± 0.56 mm (HN), 4.85 ± 2.44 mm and 2.42 ± 1.49 mm (breast), and 2.17 ± 1.39 mm and 1.21 ± 1.00 mm (prostate). Notably, custom-trained models showed significant improvements over vendor-pretrained models for 14 of 24 OARs, reflecting the influence of data/contouring variations in segmentation performance. Conclusions: These findings underscore the substantial impact of institutional preferences and clinical practices on the implementation of vendor-pretrained models. We also found that a relatively small amount of institutional data was sufficient to train customized segmentation models with sufficient accuracy.

Abstract This study aimed to compare the predictive performance of different modeling methods in developing normal tissue complication probability (NTCP) models for predicting radiation-induced esophagitis (RE) in non–small cell lung cancer (NSCLC) patients receiving proton radiotherapy. The dataset was composed of 328 NSCLC patients receiving passive-scattering proton therapy and 41.6% of the patients experienced ≥ grade 2 RE. Five modeling methods were used to build NTCP models: standard Lyman–Kutcher–Burman (sLKB), generalized LKB (gLKB), multivariable logistic regression using two variable selection procedures-stepwise forward selection (Stepwise-MLR), and least absolute shrinkage and selection operator (LASSO-MLR), and support vector machines (SVM). Predictive performance was internally validated by a bootstrap approach for each modeling method. The overall performance, discriminative ability, and calibration were assessed using the Negelkerke R2, area under the receiver operator curve (AUC), and Hosmer–Lemeshow test, respectively. The LASSO-MLR model showed the best discriminative ability with an AUC value of 0.799 (95% confidence interval (CI): 0.763–0.854), and the best overall performance with a Negelkerke R2 value of 0.332 (95% CI: 0.266–0.486). Both of the optimism-corrected Negelkerke R2 values of the SVM and sLKB models were 0.301. The optimism-corrected AUC of the gLKB model (0.796) was higher than that of the SVM model (0.784). The sLKB model had the smallest optimism in the model variation and discriminative ability. In the context of classification and probability estimation for predicting the NTCP for radiation-induced esophagitis, the MLR model developed with LASSO provided the best predictive results. The simplest LKB modeling had similar or even better predictive performance than the most complex SVM modeling, and it was least likely to overfit the training data. The advanced machine learning approach might have limited applicability in clinical settings with a relatively small amount of data.

Purpose: In patients treated with chemoradiation for esophageal cancer (EC), randomized trial data demonstrate that proton beam therapy (PBT) reduces toxicities and postoperative complications (POCs) compared with intensity-modulated radiation therapy (IMRT). However, whether radiation therapy modality affects postoperative health care resource utilization remains unknown. Materials and Methods: We examined 287 patients with EC who received chemoradiation (prescribed 50.4 Gy/GyE) followed by esophagectomy, including a real-world observational cohort of 237 consecutive patients treated from 2007 to 2013 with PBT (n = 81) versus IMRT (n = 156); and an independent, contemporary comparison cohort of 50 patients from a randomized trial treated from 2012 to 2019 with PBT (n = 21) versus IMRT (n = 29). Postoperative complications were abstracted from medical records. Health care charges were obtained from institutional claims and adjusted for inflation (2021 dollars). Charge differences (Δ = $PBT − $IMRT) were compared by treatment using adjusted generalized linear models with the gamma distribution. Results: Baseline PBT versus IMRT characteristics were not significantly different. In the observational cohort, during the neoadjuvant chemoradiation phase, health care charges were higher for PBT versus IMRT (Δ =+ $71,959; 95% confidence interval [CI], $62,274–$82,138; P < .001). There was no difference in surgical charges (Δ =−$2234; 95% CI, −$6003 to $1695; P = .26). However, during postoperative hospitalization following esophagectomy, health care charges were lower for PBT versus IMRT (Δ = −$25,115; 95% CI, −$37,625 to −$9776; P = .003). In the comparison cohort, findings were analogous: Charges were higher for PBT versus IMRT during chemoradiation (Δ =+$61,818; 95% CI, $49,435–$75,069; P < .001), not different for surgery (Δ = −$4784; 95% CI, −$6439 to $3487; P = .25), and lower for PBT postoperatively (Δ = −$27,048; 95% CI, −$41,974 to −$5300; P = .02). Lower postoperative charges for PBT were especially seen among patients with any POCs in the contemporary comparison (Δ =−$176,448; 95% CI, −$209,782 to −$78,813; P = .02). Conclusion: Higher up-front chemoradiation resource utilization for PBT in patients with EC was partially offset postoperatively, moderated by reduction in POC risks. Results extend existing clinical evidence of toxicity reduction with PBT.

IntroductionChemoradiotherapy (CRT) has been associated with increased incidence of cardiovascular (CV) adverse events (CVAE). Coronary artery calcium scoring (CAC) has shown to predict coronary events beyond the traditional CV risk factors. This study examines whether CAC, measured on standard of care, non-contrast chest CT (NCCT) imaging, predicts the development of CVAE in patients with non-small cell lung cancer (NSCLC) treated with CRT.MethodsPatients with NSCLC treated with CRT at MD Anderson Cancer Center from 7/2009 until 4/2014 and who had at least one NCCT scan within 6 months from their first CRT were identified. CAC scoring was performed on NCCT scans by an expert cardiologist and a cardiac radiologist following the 2016 SCCT/STR guidelines. CVAE were graded based on the most recent Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. CVAE were also grouped into (i) coronary/vascular events, (ii) arrhythmias, or (iii) heart failure. All CVAE were adjudicated by a board-certified cardiologist.ResultsOut of a total of 193 patients, 45% were female and 91% Caucasian. Mean age was 64 ± 9 years and mean BMI 28 ± 6 kg/m2. Of 193 patients, 74% had CAC >0 Agatston units (AU), 49% CAC ≥100 AU and 36% CAC ≥300 AU. Twenty-nine patients (15%) developed a grade ≥2 CVAE during a median follow-up of 24.3 months (IQR: 10.9–51.7). Of those, 11 (38%) were coronary/vascular events. In the multivariate cox regression analysis, controlling for mean heart dose and pre-existing CV disease, higher CAC score was independently associated with development of a grade ≥2 CVAE [HR: 1.04 (per 100 AU), 95% CI: 1.01–1.08, p = 0.022] and with worse overall survival (OS; CAC ≥100 vs.

Radiation therapy (RT)-induced cardiopulmonary toxicities remain dose-limiting toxicities for patients receiving radiation dosages to the thorax, especially for lung cancer. Means of monitoring and predicting for those receiving RT or concurrent chemoradiation therapy before treatment begins in individual patients could benefit early intervention to prevent or minimize RT-induced side effects. Another aspect of an individual’s susceptibility to the adverse effects of thoracic irradiation is the immune system as reflected by phenotypic factors (patterns of cytokine expressions), genotypic factors (single nucleotide variants SNVs; formerly single nucleotide polymorphisms [SNPs]), and aspects of quantitative cellular imaging. Levels of transcription, production, and functional activity of cytokines are often influenced by SNVs that affect coding regions in the promoter or regulatory regions of cytokine genes. SNVs can also lead to changes in the expression of the inflammatory cytokines, interferons, interleukins (IL-6, IL-17) and tumor necrosis factors (TNF-α) at the protein level. RT-induced cardiopulmonary toxicities could be quantified by the uptake of 18F-fluorodeoxyglucose (FDG), however, FDG is a sensitive but not specific biomarker in differential diagnosis between inflammation/infection and tumor recurrence. FDG is suitable for initial diagnosis of predisposed tissue injuries in non-small cell lung cancer (NSCLC). 99mTc-ethylenedicysteine-glucosamine (99mTc-EC-G) was able to measure tumor DNA proliferation and myocardial ischemia via hexosamine biosynthetic pathways (HBP). Thus, 99mTc-EC-G could be an alternative to FDG in the assessment of RT doses and select patients in HBP-directed targets for optimal outcomes. This article reviewed correlative analyses of pro-inflammatory cytokines, genotype SNVs, and cellular imaging to improve the diagnosis, prognosis, monitoring, and prediction of RT-induced cardiopulmonary toxicities in NSCLC.

Radiation therapy (RT) to the chest increases the patients’ risk of cardiovascular disease (CVD). A complete understanding of the mechanisms by which RT induces CVD could lead to specific preventive, therapeutic approaches. It is becoming evident that both genotoxic chemotherapy agents and radiation induce mitochondrial dysfunction and cellular senescence. Notably, one of the common phenotypes observed in cancer survivors is accelerated senescence, and immunosenescence is closely related to both cancer risk and CVD development. Therefore, suppression of immunosenescence can be an ideal target to prevent cancer treatment-induced CVD. However, the mechanism(s) by which cancer treatments induce immunosenescence are incompletely characterized. We isolated peripheral blood mononuclear cells (PBMCs) before and 3 months after RT from 16 thoracic cancer patients. We characterized human immune cell lineages and markers of senescence, DNA damage response (DDR), efferocytosis, and determinants of clonal hematopoiesis of indeterminant potential (CHIP), using mass cytometry (CyTOF). We found that the frequency of the B cell subtype was decreased after RT. Unsupervised clustering of the CyTOF data identified 138 functional subsets of PBMCs. Compared with baseline, RT increased TBX21 (T-bet) expression in the largest B cell subset of Ki67–/DNMT3a+naïve B cells, and T-bet expression was correlated with phosphorylation of p90RSK expression. CD38 expression was also increased in naïve B cells (CD27–) and CD8+ effector memory CD45RA T cells (TEMRA). In vitro, we found the critical role of p90RSK activation in upregulating (1) CD38+/T-bet+ memory and naïve B, and myeloid cells, (2) senescence-associated β-gal staining, and (3) mitochondrial reactive oxygen species (ROS) after ionizing radiation (IR). These data suggest the crucial role of p90RSK activation in immunosenescence. The critical role of p90RSK activation in immune cells and T-bet induction in upregulating atherosclerosis formation has been reported. Furthermore, T-bet directly binds to the CD38 promoter region and upregulates CD38 expression. Since both T-bet and CD38 play a significant role in the process of immunosenescence, our data provide a cellular and molecular mechanism that links RT-induced p90RSK activation and the immunosenescence with T-bet and CD38 induction observed in thoracic cancer patients treated by RT and suggests that targeting the p90RSK/T-bet/CD38 pathway could play a role in preventing the radiation-associated CVD and improving cancer prognosis by inhibiting immunosenescence.

Purpose: To investigate the incidence and prognosis of severe radiation-induced lymphopenia (sRIL) after postoperative radiotherapy (PORT) for resected NSCLC. Patients and methods: Between 1998 and 2017, 170 patients treated with PORT for NSCLC were retrospectively reviewed. Lymphopenia was divided into tertiles with severe lymphopenia defined as absolute lymphocyte counts (ALC)

Introduction: Durvalumab after concurrent chemoradiation (CCRT) for NSCLC improves survival, but only in a subset of patients. We investigated the effect of severe radiation-induced lymphopenia (sRIL) on survival in these patients. Methods: Outcomes after CCRT (2010–2019) or CCRT followed by durvalumab (2018–2019) were reviewed. RIL was defined by absolute lymphocyte count (ALC) nadir in samples collected at end of CCRT; sRIL was defined as nadir ALC less than 0.23 × 109/L (the lowest tertile). Progression-free survival (PFS) and overall survival (OS) were calculated by the Kaplan-Meier method. Cox proportional hazard modeling evaluated associations between clinical variables and survival. Results: Of 309 patients, 192 (62%) received CCRT only and 117 (38%) CCRT plus durvalumab. Multivariable logistic regression analysis indicated that sRIL was associated with planning target volume (OR = 1.002, p = 0.001), stage IIIB disease (OR = 2.77, p = 0.04), and baseline ALC (OR = 0.36, p < 0.01). Durvalumab extended median PFS (23.3 versus 14.1 mo, p = 0.003) and OS (not reached versus 30.8 mo, p < 0.01). sRIL predicted poorer PFS and OS in both treatment groups. Among patients with sRIL, durvalumab did not improve survival (median = 24.6 mo versus 18.1 mo CCRT only, p = 0.079). On multivariable analyses, sRIL (OR = 1.81, p < 0.01) independently predicted poor survival. Conclusions: Severe RIL compromises survival benefits from durvalumab after CCRT for NSCLC. Measures to mitigate RIL after CCRT may be warranted to enhance the benefit of consolidation durvalumab.

Abstract Background Cancer Associated Macrophage-Like cells (CAMLs) are polynucleated circulating stromal cells found in the bloodstream of numerous solid-tumor malignancies. Variations within CAML size have been associated with poorer progression free survival (PFS) and overall survival (OS) in a variety of cancers; however, no study has evaluated their clinical significance in esophageal cancer (EC). Methods To examine this significance, we ran a 2 year prospective pilot study consisting of newly diagnosed stage I-III EC patients (n = 32) receiving chemoradiotherapy (CRT). CAML sizes were sequentially monitored prior to CRT (BL), ~ 2 weeks into treatment (T1), and at the first available sample after the completion of CRT (T2). Results We found CAMLs in 88% (n = 28/32) of all patient samples throughout the trial, with a sensitivity of 76% (n = 22/29) in pre-treatment screening samples. Improved 2 year PFS and OS was found in patients with CAMLs

Purpose: To evaluate the safety and efficacy of definitive chemoradiotherapy (CRT) for patients with clinical T1N0M0 esophageal adenocarcinoma. Methods and Materials: This was a retrospective study of patients with clinical T1N0 adenocarcinoma of the esophagus treated with curative-intent CRT between 2004 and 2017 at 2 tertiary care centers. Patients received CRT instead of esophagectomy owing to medical comorbidities or patient preference. Toxicities were evaluated according to Common Terminology Criteria for Adverse Events version 4.03. The Kaplan-Meier method was used to estimate overall, progression-free, and disease-specific survivals. Results: Twenty-eight patients were included for analysis. Median age was 76 years (range 55-90). The majority of patients were male (93%) and had a history of Barrett’s esophagus (71%). Tumor characteristics included distal esophagus location (93%), clinical stage T1b (86%), and median length of 2 cm (range, 1-9). Prior endoscopic resection was performed in 57%.The median follow-up was 44 months (range, 4-146). The acute grade 3 adverse events were observed in 7 patients (25%). One patient died of complications potentially related to chemoradiation. Eight patients (29%) had disease progression at a median of 7.6 months after CRT. First site of progression was local only (14%), local and regional (11%), or distant (4%). Salvage locally directed treatment was performed in 3 of 4 patients with local-only recurrence. The 3-year overall survival, progression-free, and disease-specific rates were 78%, 62%, and 81%, respectively. Conclusion: CRT is a safe and effective curative treatment strategy for select patients with clinical T1N0M0 esophageal adenocarcinoma.

PURPOSEKey to achieving better population-based outcomes for patients with lung cancer is the improvement of medical imaging and nuclear medicine infrastructure globally. This paper aims to outline why and spark relevant health systems strengthening.METHODSThe paper synthesizes the global lung cancer landscape, imaging referral guidelines (including resource-stratified ones), the reliance of TNM staging upon imaging, relevant multinational health technology assessments, and precisely how treatment selection and in turn patient outcomes hinge upon imaging findings. The final discussion presents data on current global gaps in both diagnostics (including imaging) and therapies and how, informed by such data, improved population-based outcomes are tangible through strategic planning.RESULTSImaging findings are central to appropriate lung cancer patient management and can variably lead to life-prolonging interventions and/or to life-enhancing palliative measures. Early-stage lung cancer can be treated with curative intent but, unfortunately, most patients with lung cancer still present at advanced stages and many patients lack access to both diagnostics and therapies. Furthermore, half of lung cancer cases occur in low- and middle-income countries. The role of medical imaging and nuclear medicine in lung cancer management, as outlined herein, may help inform strategic planning.CONCLUSIONLung cancer is the number one cancer killer worldwide. The essential role that medical imaging and nuclear medicine play in early diagnosis and disease staging cannot be overstated, pivotal in selecting the many patients for whom measurably improved outcomes are attainable. Prevention synergized with patient-centered, compassionate, high-quality lung cancer management provision mandate that strategic population-based planning, including universal health coverage strategies, should extend well beyond the scope of disease prevention to include both curative and noncurative treatment options for the millions afflicted with lung cancer.

Radiotherapy is known to influence immune function, including T cell receptor (TCR) repertoire. We evaluated the TCR repertoire before and after stereotactic body radiotherapy (SBRT) for stage I non-small-cell lung cancer (NSCLC) and explored correlations between TCR indexes and distant failure after SBRT. TCR repertoires were analyzed in peripheral blood mononuclear cells (PBMCs) collected before and after SBRT from 19 patients. TCR combinational diversity in V and J genes was assessed with multiplex PCR of genomic DNA from PBMCs and tested for associations with clinical response. All patients received definitive SBRT to a biologically effective dose of >=100 Gy. The number of unique TCR clones was decreased after SBRT versus before, but clonality and the Shannon Entropy did not change. Four patients (21%) developed distant metastases after SBRT (median 7 months); those patients had lower Shannon Entropy in post-SBRT samples than patients without metastasis. Patients with a low change in Shannon Entropy from before to after SBRT [(post-SBRT Shannon Entropy minus baseline Shannon)/(baseline Shannon) * 100] had poorer metastasis-free survival than those with high change in Shannon Entropy (P

Abstract Purpose To quantify tumor anatomic change of non-small cell lung cancer (NSCLC) patients given passive-scattering proton therapy (PSPT) and intensity-modulated radiation therapy (IMRT) through 6–7 weeks of treatment, and analyze the correlation between anatomic change and the need to adopt adaptive radiotherapy (ART). Materials and methods Weekly 4D CT sets of 32 patients (8/8 IMRT with/without ART, 8/8 PSPT with/without ART) acquired during treatment, were registered to the planning CT using an in-house developed deformable registration algorithm. The anatomic change was quantified as the mean variation of the region of interest (ROI) relative to the planning CT by averaging the magnitude of deformation vectors of all voxels within the ROI contour. Mean variations of GTV and CTV were compared between subgroups classified by ART status and treatment modality using the independent t-test. Logistic regression analysis was performed to clarify the effect of anatomic change on the probability of ART adoption. Results There was no significant difference (p = 0.679) for the time-averaged mean CTV variations from the planning CT between IMRT (7.61 ± 2.80 mm) and PSPT (7.21 ± 2.67 mm) patients. However, a significant difference (p = 0.001) was observed between ART (8.93 ± 2.19 mm) and non-ART (5.90 ± 2.33 mm) patients, when treatment modality was not considered. Mean CTV variation from the planning CT in all patients increases significantly (p

Purpose: To analyze associations between heart and lung dose and overall survival (OS) in patients with esophageal cancer who received concurrent chemo-radiotherapy (CCRT) with or without surgery. Patients and methods: Patients received intensity-modulated radiation therapy (median dose 50.4 Gy) from 2004 through 2016. Cutoff points for continuous variables were calculated using the method of Contal and O’Quigley. Kaplan-Meier method with log-rank tests was used to calculate survival. OS was analyzed with both univariate and multivariable Cox models. Results: In all, 560 patients were analyzed; median follow-up time was 29.3 months, and 5-year OS rate was 41.7%. Heart V30 >45% and mean lung dose (MLD) >10 Gy were found to be independently associated with worse survival after adjustment for other clinical and dosimetric factors (P 45% (P = 0.046); 18.8% of patients with MLD ≤10 Gy had pulmonary complications vs. 27% for MLD >10 Gy (P = 0.020). Having cardiac complications was associated with worse survival (5-year OS rates 27.6% with vs. 43.2% without, P = 0.012), and having pulmonary complications was associated with worse survival as well (5-year OS rates 23.1% with vs. 47.4% without, P

Purpose: Clinical trial enrollment has declined globally as a result of the coronavirus disease 2019 (COVID-19) pandemic. This underscores the importance of structured methods to continue critical medical research safely and efficiently. Methods and Materials: We report the effect of a phased trial reopening strategy, remote research staffing, and telemedicine on cancer trial enrollment at one of the largest radiation oncology academic cancer centers. In phase 1, trials investigating definitive therapeutic benefit were opened, followed by trials not increasing patient exposure or pulmonary toxicity risk in phase 2. During phase 2.5, multicenter trials reopened and limited research staff were allowed on site. Results: Despite initial enrollment declines during the early pandemic, the percentage of new patients enrolling in clinical trials from March to August 2020 was 8.8%, and represented a 10.5% relative increase from 2019. Monthly accrual enrollment from March to August 2019 ranged from 42 to 71, compared with enrollment during COVID-19 from 23 to 73 patients (P < .001). Conclusions: Through a phased approach to trial reopening and adaptive techniques, the division of radiation oncology maintained cancer trial accrual during the COVID-19 pandemic. The experience may help centers maintain accrual, preserve clinical trial integrity, and minimize risk to patients and staff.

Purpose: This study hypothesized that insurance denial would lead to bias and loss of statistical power when evaluating the results from an intent-to-treat (ITT), per-protocol, and as-treated analyses using a simulated randomized clinical trial comparing proton therapy to intensity modulated radiation therapy where patients incurred increasing rates of insurance denial. Methods and Materials: Simulations used a binary endpoint to assess differences between treatment arms after applying ITT, per-protocol, and as-treated analyses. Two scenarios were developed: 1 with clinical success independent of age and another assuming dependence on age. Insurance denial was assumed possible for patients

Purpose: Ensuring high-quality data for clinical trials in radiotherapy requires the generation of contours that comply with protocol definitions. The current workflow includes a manual review of the submitted contours, which is time-consuming and subjective. In this study, we developed an automated quality assurance (QA) system for lung cancer based on a segmentation model trained with deep active learning.Methods: The data included a gold atlas with 36 cases and 110 cases from the “NRG Oncology/RTOG 1308 Trial”. The first 70 cases enrolled to the RTOG 1308 formed the candidate set, and the remaining 40 cases were randomly assigned to validation and test sets (each with 20 cases). The organs-at-risk included the heart, esophagus, spinal cord, and lungs. A preliminary convolutional neural network segmentation model was trained with the gold standard atlas. To address the deficiency of the limited training data, we selected quality images from the candidate set to be added to the training set for fine-tuning of the model with deep active learning. The trained robust segmentation models were used for QA purposes. The segmentation evaluation metrics derived from the validation set, including the Dice and Hausdorff distance, were used to develop the criteria for QA decision making. The performance of the strategy was assessed using the test set.Results: The QA method achieved promising contouring error detection, with the following metrics for the heart, esophagus, spinal cord, left lung, and right lung: balanced accuracy, 0.96, 0.95, 0.96, 0.97, and 0.97, respectively; sensitivity, 0.95, 0.98, 0.96, 1.0, and 1.0, respectively; specificity, 0.98, 0.92, 0.97, 0.94, and 0.94, respectively; and area under the receiving operator characteristic curve, 0.96, 0.95, 0.96, 0.97, and 0.94, respectively.Conclusions: The proposed system automatically detected contour errors for QA. It could provide consistent and objective evaluations with much reduced investigator intervention in multicenter clinical trials.

Small cell lung cancer (SCLC) may evolve under treatment. But tumor tissues are often not available to study evolution of SCLC. Here, the authors utilize circulating tumor DNA to investigate the genomic evolution and subclonal architecture of SCLC during therapy.

Objective: The DNA repair capacity (DRC) of tumor cells is an important contributor to resistance to radiation and platinum-based drugs. Because DRC may be affected by tumor cell metabolism, we measured DRC in lymphocytes from patients with non–small-cell lung cancer (NSCLC) and compared the findings with the maximum standardized uptake value (SUVmax) on18F-fluorodeoxyglucose positron emission tomography (FDG PET) after (chemo)radiation therapy. Methods: This study included 151 patients with stage IA-IV NSCLC who had FDG PET at a single institution and donated blood samples before chemotherapy. We assessed the correlation of DRC, measured in peripheral T lymphocytes by a host-cell reactivation assay with SUVmax and their associations with overall survival (OS) time by hazards ratios calculated with a Cox proportional hazards regression model. Results: SUVmax of the primary tumor at diagnosis was inversely associated with lymphocyte DRC (r = −0.175, P = 0.032), particularly among patients with advanced disease (r = −0.218, P = 0.015). However, ΔSUVmax of primary tumor was not significantly associated with DRC (r = 0.005, P = 0.968). SUVmax of regional lymph nodes at diagnosis (r = −0.307, P = 0.0008) and after (chemo)radiation treatment (r = −0.329, P = 0.034) and SUVmax of the primary tumor after (chemo)radiation treatment (r = −0.253, P = 0.045) were also inversely associated with OS time. Conclusion: DRC was inversely associated with primary tumor SUVmax before treatment but not with ΔSUVmax after (chemo)radiation. Keywords: DNA repair capacity, Standardized uptake value, 18F-fluorodeoxyglucose positron emission tomography, Outcome, Non–small-cell lung cancer

PURPOSE Clinical efficiency is a key component of value-based health care. Our objective here was to identify workflow inefficiencies by using time-driven activitybased costing (TDABC) and evaluate the implementation of a new clinical workflow in high-volume outpatient radiation oncology clinics. METHODS Our quality improvement study was conducted with the Departments of GI, Genitourinary (GU), and Thoracic Radiation Oncology at a large academic cancer center and four community network sites. TDABC was used to create process maps and optimize workflow for outpatient consults. Patient encounter metrics were captured with a real-time status function in the electronic medical record. Time metrics were compared using Mann-Whitney U tests. RESULTS Individual patient encounter data for 1,328 consults before the intervention and 1,234 afterward across all sections were included. The median overall cycle time was reduced by 21% in GI (19 minutes), 18% in GU (16 minutes), and 12% at the community sites (9 minutes). The median financial savings per consult were $52 in US dollars (USD) for the GI, $33 USD for GU, $30 USD for thoracic, and $42 USD for the community sites. Patient satisfaction surveys (from 127 of 228 patients) showed that 99% of patients reported that their providers spent adequate time with them and 91% reported being seen by a care provider in a timely manner. CONCLUSION TDABC can effectively identify opportunities to improve clinical efficiency. Implementing workflow changes on the basis of our findings led to substantial reductions in overall encounter cycle times across several departments, as well as high patient satisfaction and significant financial savings. [ABSTRACT FROM AUTHOR]

Objective: Single-nucleotide polymorphisms (SNPs) in the ataxia telangiectasia–mutated gene ATM have been linked with pneumonitis after radiotherapy for lung cancer but have not been evaluated in terms of pulmonary function impairment. Here we investigated potential associations between SNPs in ATM and changes in diffusing capacity of the lung for carbon monoxide (DLCO) in patients with non–small-cell lung cancer (NSCLC) after radiotherapy. Methods: From November 1998 through June 2009, 448 consecutive patients with inoperable primary NSCLC underwent definitive (≥60 Gy) radiotherapy, with or without chemotherapy. After excluding patients with a history of thoracic surgery, radiation, or lung cancer; without DNA samples available for analysis; or without pulmonary function testing within the 12 months before and the 12 months after radiotherapy, 100 patients were identified who are the subjects of this study. We genotyped two SNPs of ATM previously found to be associated with radiation-induced pneumonitis (rs189037 and rs228590) and evaluated potential correlations between these SNPs and impairment (decreases) in DLCO by using logistic regression analysis. Results: Univariate and multivariate analyses showed that the AA genotype of ATM rs189037 was associated with decreased DLCO after definitive radiotherapy than the GG/AG genotypes [univariate coefficient, −0.122; 95% confidence interval (CI), −0.236 to −0.008; P = 0.037; and multivariate coefficient, −0.102; 95% CI, −0.198 to −0.005; P = 0.038]. No such correlations were found for rs228590 (univariate coefficient, −0.096; 95% CI, −0.208 to 0.017; P = 0.096). Conclusions: The AA genotype of ATM rs189037 was associated with higher risk of lung injury than were the GG/AG genotypes in patients with NSCLC treated with radiotherapy. This finding should be validated prospectively with other patient populations. Keywords: Non–small-cell lung cancer, Radiation therapy, Ataxia telangiectasia-mutated gene, Single-nucleotide polymorphisms

Abstract Background Given the generally incurable nature of metastatic non-small cell lung cancer (mNSCLC), patients and their romantic partners are at risk for existential/spiritual distress. Although a handful of dyadic psychosocial interventions for lung cancer patients and their caregivers exist, none of them target spiritual well-being. Informed by the mindfulness-based intervention literature and our pilot work in couples affected by lung cancer, we developed a brief couple-based mind-body (CBMB) intervention. The primary aim of this research protocol is to determine the feasibility of implementing the CBMB intervention versus an active control (AC) or wait list control (WLC) group in patients with mNSCLC and their partners using a randomized controlled trial design. Methods Seventy-five patients with mNSCLC receiving treatment and their partners are randomized to the CBMB intervention, an AC or a WLC group. Those in the CBMB intervention and AC groups receive four intervention sessions of 60 min each over 4 weeks and complete weekly homework assignments. The first session is delivered in person, and the remaining sessions are delivered via videoconference. The dyads in the AC group discuss cancer-related and personal growth concerns with the interventionist but are not taught coping skills. Patients and partners in all groups complete baseline assessments of quality of life (QOL) prior to randomization. Follow-up assessments are performed 4 weeks and then again 3 months later. The primary outcome is feasibility (i.e., ≥ 30% of eligible couples consent, ≥ 70% of enrolled couples are retained, and ≥ 50% of all CBMB and AC sessions are attended). We will also perform primarily descriptive analyses of the self-reported outcomes (e.g., spiritual well-being and psychological distress) and explore potential intervention mediators (i.e., compassion, communication, mindfulness, and closeness) to inform a larger, future trial. Discussion This trial will provide important information regarding the feasibility of a behavioral intervention in a vulnerable yet understudied population using videoconferencing and descriptive data regarding spiritual well-being and other indices of QOL in both mNSCLC patients and their partners. Trial registration ClinicalTrials.gov NCT02596490

Purpose: In patients with esophageal cancer (EC), intensity modulated radiation therapy (IMRT) improves dose sparing to the heart and lung, with some evidence showing clinical benefit. Herein, we report our cumulative clinical experience with the use of IMRT for EC. Methods and materials: This is a retrospective analysis of 587 patients with nonmetastatic EC who were treated consecutively with IMRT from January 2004 to June 30, 2013. All patients with stage I-IVA (American Joint Committee on Cancer 2002) received concurrent chemoradiation therapy either preoperatively or definitively. The Kaplan-Meier method was used to compute overall survival (OS) and locoregional recurrence-free survival and disease-free survival. The Common Terminology Criteria for Adverse Events, Version 4.0 were used to grade acute and subacute complications. Results: The median radiation dose was 50.4 Gy in 28 daily fractions. As of July 2015, the median follow-up was 31.4 months (range, 2.9-130.7 months) for all patients and 61.8 months (range, 7.7-130.7 months) for survivors. The median OS was 38.9 months, and the 1-, 3-, and 5-year OS rates were 86.7%, 51.8%, and 41.2%, respectively. The 1-, 3-, and 5-year locoregional recurrence-free survival rates were 77.6%, 68.2%, and 66.1%, respectively, and the 1-, 3-, and 5-year disease-free survival rates were 58.6%, 43.7%, and 41.4%, respectively. Outcomes for both trimodality and bimodality treated patients were better than the outcomes reported in the literature. Eight patients (1.4%) experienced grade ≥3 pneumonitis, and 74 patients (13%) developed grade ≥3 esophagitis. For patients who underwent surgery, the most common postoperative complications were pneumonia (9.6%), anastomotic leakage (11.1%), and atrial fibrillation (12.5%). Conclusions: This is the largest, single institutional study to date on the long-term outcomes of treatment with IMRT for EC. For photon-based radiation therapy, IMRT yields excellent outcomes and should be considered for the treatment of EC.

Abstract Personalized cancer therapy seeks to tailor treatment to an individual patient’s biology. Therefore, a means to characterize radiosensitivity is necessary. In this study, we investigated radiosensitivity in the normal esophagus using an imaging biomarker of radiation-response and esophageal toxicity, esophageal expansion, as a method to quantify radiosensitivity in 134 non-small-cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiosensitivity. Patients within the cluster of higher response and lower dose were labelled as radiosensitive. This information was used as a variable in toxicity prediction modelling (lasso logistic regression). The resultant model performance was quantified and compared to toxicity prediction modelling without utilizing radiosensitivity information. The esophageal expansion-response was highly variable between patients, even for similar radiation doses. K-Means clustering was able to identify three patient subgroups of radiosensitivity: radiosensitive, radio-normal, and radioresistant groups. Inclusion of the radiosensitive variable improved lasso logistic regression models compared to model performance without radiosensitivity information. Esophageal radiosensitivity can be quantified using esophageal expansion and K-Means clustering to improve toxicity prediction modelling. Finally, this methodology may be applied in clinical trials to validate pre-treatment biomarkers of esophageal toxicity.

Background: Increased uptake of fluorodeoxyglucose (FDG) by lung tissue could reflect inflammatory changes related to radiation pneumonitis (RP). In this secondary analysis of a clinical trial, we examined potential associations between posttreatment lung FDG uptake and RP severity in patients with non-small cell lung cancer (NSCLC) for up to 12 months after concurrent chemoradiation (CRT). Methods: Subjects were 152 patients with NSCLC who had received concurrent CRT as part of the prospective trial NCT00915005. The following lung FDG variables were evaluated after CRT: maximum, mean, and peak standardized uptake values (SUVmax, SUVmean, SUVpeak) and global lung glycolysis (GLG; lung SUVmean × lung volume). RP severity was scored with the Common Terminology Criteria for Adverse Events v3.0. Results: Significant associations were noted between PET findings and RP severity at 1–6 months (all P 0.05). Lung FDG uptake at 1–3 months after treatment predicted later development of grade ≥2 RP (all P

Abstract Radiomics is the use of quantitative imaging features extracted from medical images to characterize tumor pathology or heterogeneity. Features measured at pretreatment have successfully predicted patient outcomes in numerous cancer sites. This project was designed to determine whether radiomics features measured from non–small cell lung cancer (NSCLC) change during therapy and whether those features (delta-radiomics features) can improve prognostic models. Features were calculated from pretreatment and weekly intra-treatment computed tomography images for 107 patients with stage III NSCLC. Pretreatment images were used to determine feature-specific image preprocessing. Linear mixed-effects models were used to identify features that changed significantly with dose-fraction. Multivariate models were built for overall survival, distant metastases, and local recurrence using only clinical factors, clinical factors and pretreatment radiomics features, and clinical factors, pretreatment radiomics features, and delta-radiomics features. All of the radiomics features changed significantly during radiation therapy. For overall survival and distant metastases, pretreatment compactness improved the c-index. For local recurrence, pretreatment imaging features were not prognostic, while texture-strength measured at the end of treatment significantly stratified high- and low-risk patients. These results suggest radiomics features change due to radiation therapy and their values at the end of treatment may be indicators of tumor response.

BACKGROUND: MUC5B is glycoprotein secreted by bronchial glands. A promoter variant in MUC5B, rs35705950, was previously found to be strongly associated with the incidence of idiopathic pulmonary fibrosis (IPF) and also the overall survival (OS) of such patients. Patients with IPF and patients with radiation pneumonitis (RP) have the similar pathologic process and clinical symptoms. However, the role of rs35705950 in patients receiving thoracic radiotherapy remains unclear. PATIENTS AND METHODS: In total, 664 patients with NSCLC receiving definitive radiotherapy (total dose ≥60 Gy) were included in our study. RP was scored via the Common Terminology Criteria for Adverse Events v3.0. OS was the second end point. MUC5B rs35705950 was genotyped, and Kaplan-Meier and Cox regression analyses were used to evaluate associations between MUC5B rs35705950 and the risk of RP or OS. RESULTS: The median patient age was 66 years (range 35-88); most (488 [73.2%]) had stage III of the disease. Until the last follow-up, 250 patients developed grade ≥ 2 RP, 82 patients developed grade ≥ 3 RP, and 440 patients died. The median mean lung dose was 17.9 Gy (range 0.15-32.74). No statistically significant associations were observed between genotypes of MUC5B rs35705950 and the incidence of RP ≥ grade 2 either in univariate analysis (hazard ratio [HR] 1.009, 95% confidence interval [CI] 0.728-1.399, P = .958) or in multivariate analysis (HR 0.921, 95% CI 0.645-1.315, P = .65). Similar results were also observed for RP ≥ grade 3, while TT/GT genotypes in MUC5B were significantly associated with poor OS in both univariate analysis (HR 1.287, 95% CI 1.009-1.640, P = .042) and multivariate analysis (HR 1.561, 95% CI 1.193-2.042, P = .001). CONCLUSION: MUC5B promoter polymorphism could be prognostic of the OS among NSCLC patients receiving definitive radiotherapy, although no significant associations were found with the risk of RP.

Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD (p = 0.027). Multivariable logistic modeling resulted in a single variable model including S20Gy, the relative skin surface receiving more than 20 Gy (OR = 31.4). The cut off for S20Gy was 1.1% of the BSA. LKB model parameters were TD50 = 9.5 Gy, m = 0.24, n = 0.62. Both NTCP models showed comparably high prediction and calibration performances. Despite skin toxicity has long been considered a potential limiting factor in the clinical use of PSPT, no significant differences in RD incidence was found between RT modalities. Once externally validated, the availability of NTCP models for prediction of severe RD may advance treatment planning optimization.

The original version of this Article contained an error in Fig. 2, in which the left y-axis labels ‘tDNA’ and ‘ctDNA’ were inadvertently inverted. This has been corrected in the PDF and HTML versions of the Article.

Our randomized clinical study comparing stereotactic body radiotherapy (SBRT) and stereotactic body proton therapy (SBPT) for early stage non-small cell lung cancer (NSCLC) was closed prematurely owing to poor enrollment, largely because of lack of volumetric imaging and difficulty in obtaining insurance coverage for the SBPT group. In this article, we describe technology improvements in our new proton therapy center, particularly in image guidance with cone beam CT (CBCT) and CT on rail (CTOR), as well as motion management with real-time gated proton therapy (RGPT) and optical surface imaging. In addition, we have a treatment planning system that provides better treatment plan optimization and more accurate dose calculation. We expect to re-start the SBPT program, including for early stage NSCLC as well as for other disease sites soon after starting patient treatment at our new proton therapy center. [ABSTRACT FROM AUTHOR]

Transforming growth factor (TGF) -β1 signaling is involved in cancer-cell metastasis. We investigated whether single nucleotide polymorphisms (SNPs) at TGFβ1 were associated with overall survival (OS) and distant metastasis-free survival (DMFS) in patients with non-small cell lung cancer (NSCLC) treated with definitive radiotherapy, with or without chemotherapy.We genotyped TGFβ1 SNPs at rs1800469 (C-509T), rs1800471 (G915C), and rs1982073 (T+29C) by polymerase chain reaction-restriction fragment length polymorphism in blood samples from 205 NSCLC patients who had had definitive radiotherapy at one institution in November 1998-January 2005. We also tested whether the TGF-β1 rs1982073 (T+29C) SNP affected the migration and invasion of A549 and PC9 lung cancer cells.Median follow-up time for all patients was 17 months (range, 1-97 months; 39 months for patients alive at the time of analysis). Multivariate analysis showed that the TGFβ1 rs1800469 CT/CC genotype was associated with poor OS (hazard ratio [HR] = 1.463 [95% confidence interval {CI} = 1.012-2.114], P = 0.043) and shorter DMFS (HR = 1.601 [95% CI = 1.042-2.459], P = 0.032) and that the TGFβ1 rs1982073 CT/CC genotype predicted poor DMFS (HR = 1.589 [95% CI = 1.009-2.502], P = 0.046) and poor brain MFS (HR = 2.567 [95% CI = 1.155-5.702], P = 0.021) after adjustment for age, sex, race, performance status, smoking status, tumor histology and volume, stage, receipt of concurrent radiochemotherapy, number of chemotherapy cycles, and radiation dose. Transfection with TGFβ1+29C (vs. +29T) stimulated the migration and invasion of A549 and PC9 cells, suggesting that TGFβ1+29C may be linked with increased metastatic potential.TGFβ1 genotypes at rs1800469 and rs1982073 could be useful for predicting DMFS among patients with NSCLC treated with definitive radiation therapy. These findings require validation in larger prospective trials and thorough mechanistic studies.

PurposeBrain metastasis (BM) from non-small cell lung cancer (NSCLC) is relatively common, but identifying which patients will develop brain metastasis has been problematic. We hypothesized that genotype variants in the TGF-β signaling pathway could be a predictive biomarker of brain metastasis.Patients and methodsWe genotyped 33 SNPs from 13 genes in the TGF-β signaling pathway and evaluated their associations with brain metastasis risk by using DNA from blood samples from 161 patients with NSCLC. Kaplan-Meier analysis was used to assess brain metastasis risk; Cox hazard analyses were used to evaluate the effects of various patient and disease characteristics on the risk of brain metastasis.ResultsThe median age of the 116 men and 45 women in the study was 58 years; 62 (39%) had stage IIIB or IV disease. Within 24 months after initial diagnosis of lung cancer, brain metastasis was found in 60 patients (37%). Of these 60 patients, 16 had presented with BM at diagnosis. Multivariate analysis showed the GG genotype of SMAD6: rs12913975 and TT genotype of INHBC: rs4760259 to be associated with a significantly higher risk of brain metastasis at 24 months follow-up (hazard ratio [HR] 2.540, 95% confidence interval [CI] 1.204-5.359, P = 0.014; and HR 1.885, 95% CI 1.086-3.273, P = 0.024), compared with the GA or CT/CC genotypes, respectively. When we analyzed combined subgroups, these rates showed higher for those having both the GG genotype of SMAD6: rs12913975 and the TT genotype of INHBC: rs4760259 (HR 2.353, 95% CI 1.390-3.985, P = 0.001).ConclusionsWe found the GG genotype of SMAD6: rs12913975 and TT genotype of INHBC: rs4760259 to be associated with risk of brain metastasis in patients with NSCLC. This finding, if confirmed, can help to identify patients at high risk of brain metastasis.

BackgroundNo selection criteria for helical tomotherapy (HT) based stereotactic ablative radiotherapy (SABR) to treat early stage non-small cell lung cancer (NSCLC) or solitary lung metastases has been established. In this study, we investigate the dosimetric selection criteria for HT based SABR delivering 70 Gy in 10 fractions to avoid severe toxicity in the treatment of centrally located lesions when adequate target dose coverage is desired.Materials and methods78 HT-SABR plans for solitary lung lesions were created to prescribe 70 Gy in 10 fractions to the planning target volume (PTV). The PTV was set to have ≥95% PTV receiving 70 Gy in each case. The cases for which dose constraints for ≥1 OAR could not be met without compromising the target dose coverage were compared with cases for which all target and OAR dose constraints were met.ResultsThere were 23 central lesions for which OAR dose constraints could not be met without compromising PTV dose coverage. Comparing to cases for which optimal HT-based SABR plans were generated, they were associated with larger tumor size (5.72±1.96 cm vs. 3.74±1.49 cm, pConclusionDelivery of 70 Gy in 10 fractions with HT to meet all the given OAR and PTV dose constraints are most likely when the following parameters are met: lung lesions ≤3.78 cm (11.98 cc), ≤2 immediately adjacent OARs which are ≥0.45 cm from the gross lesion and ≥0.21 cm from the PTV.

The repair of DNA double-strand breaks (DSBs) is the major mechanism to maintain genomic stability in response to irradiation. We hypothesized that genetic polymorphisms in DSB repair genes may affect clinical outcomes among non-small cell lung cancer (NSCLC) patients treated with definitive radio(chemo)therapy. We genotyped six potentially functional single nucleotide polymorphisms (SNPs) (i.e., RAD51 -135G>C/rs1801320 and -172G>T/rs1801321, XRCC2 4234G>C/rs3218384 and R188H/rs3218536 G>A, XRCC3 T241M/rs861539 and NBN E185Q/rs1805794) and estimated their associations with overall survival (OS) and radiation pneumonitis (RP) in 228 NSCLC patients. We found a predictive role of RAD51 -135G>C SNP in RP development (adjusted hazard ratio [HR] = 0.52, 95% confidence interval [CI], 0.31-0.86, P = 0.010 for CG/CC vs. GG). We also found that RAD51 -135G>C and XRCC2 R188H SNPs were independent prognostic factors for overall survival (adjusted HR = 1.70, 95% CI, 1.14-2.62, P = 0.009 for CG/CC vs. GG; and adjusted HR = 1.70; 95% CI, 1.02-2.85, P = 0.043 for AG vs. GG, respectively) and that the SNP-survival association was most pronounced in the presence of RP. Our study suggests that HR genetic polymorphisms, particularly RAD51 -135G>C, may influence overall survival and radiation pneumonitis in NSCLC patients treated with definitive radio(chemo)therapy. Large studies are needed to confirm our findings.

Treatment of non-small cell lung cancer (NSCLC) with radiotherapy or chemoradiotherapy is often accompanied by the development of esophagitis and pneumonitis. Identifying patients who might be at increased risk for normal tissue toxicity would help in determination of the optimal radiation dose to avoid these events. We profiled 59 single nucleotide polymorphisms (SNPs) from 37 inflammation-related genes in 173 NSCLC patients with stage IIIA/IIIB (dry) disease who were treated with definitive radiation or chemoradiation. For esophagitis risk, nine SNPs were associated with a 1.5- to 4-fold increase in risk, including three PTGS2 (COX2) variants: rs20417 (HR:1.93, 95% CI:1.10-3.39), rs5275 (HR:1.58, 95% CI:1.09-2.27), and rs689470 (HR:3.38, 95% CI:1.09-10.49). Significantly increased risk of pneumonitis was observed for patients with genetic variation in the proinflammatory genes IL1A, IL8, TNF, TNFRSF1B, and MIF. In contrast, NOS3:rs1799983 displayed a protective effect with a 45% reduction in pneumonitis risk (HR:0.55, 95% CI:0.31-0.96). Pneumonitis risk was also modulated by polymorphisms in anti-inflammatory genes, including genetic variation in IL13. rs20541 and rs180925 each resulted in increased risk (HR:2.95, 95% CI:1.14-7.63 and HR:3.23, 95% CI:1.03-10.18, respectively). The cumulative effect of these SNPs on risk was dose-dependent, as evidenced by a significantly increased risk of either toxicity with an increasing number of risk genotypes (P

Objective: To discern recurrence risk stratification and investigate its influence on postoperative surveillance in patients with esophageal adenocarcinoma (EAC) after neoadjuvant chemoradiotherapy (CRT). Background: Reports documenting recurrence risk stratification in EAC after neoadjuvant CRT are scarce. Methods: Between 1998 and 2014, 601 patients with EAC who underwent neoadjuvant CRT followed by esophagectomy were included for analysis. The pattern, site, timing, and frequency of the first recurrence and potential prognostic factors for developing recurrences were analyzed. This cohort was used as the training set to propose a recurrence risk stratification system, and the stratification was further validated in another cohort of 172 patients. Results: A total of 150 patients (25.0%) achieved pathologic complete response (pCR) after neoadjuvant CRT and the rest were defined as the non-pCR group (n = 451) in the training cohort. After a median follow-up of 63.6 months, the pCR group demonstrated a significantly lower locoregional (4.7% vs 19.1%) and distant recurrence rate (22.0% vs.44.6%) than the nonpCR group (P < 0.001). Based on independent prognostic factors, patients were stratified into 4 recurrence risk categories: pCR with clinical stage I/II, pCR with clinical stage III, non-pCR with pN0, and non-pCR with pN+, with corresponding 5-year recurrence-free survival rates of 88.7%, 65.8%, 55.3%, and 33.0%, respectively (P < 0.001). The risk stratification was reproducible in the validation cohort. Conclusions: We proposed a recurrence risk stratification system for EAC patients based on pathologic response and pretreatment clinical stage. Riskbased postoperative surveillance strategies could be developed for different risk categories. [ABSTRACT FROM AUTHOR]