Radiotherapy-associated cardiac toxicity studies in patients with locally advanced non-small cell lung cancer (NSCLC) have been limited by small sample size and nonvalidated cardiac endpoints.
The ...purpose of this analysis was to ascertain whether cardiac radiation dose is a predictor of major adverse cardiac events (MACE) and all-cause mortality (ACM).
This retrospective analysis included 748 consecutive locally advanced NSCLC patients treated with thoracic radiotherapy. Fine and Gray and Cox regressions were used to identify predictors for MACE and ACM, adjusting for lung cancer and cardiovascular prognostic factors, including pre-existing coronary heart disease (CHD).
After a median follow-up of 20.4 months, 77 patients developed ≥1 MACE (2-year cumulative incidence, 5.8%; 95% confidence interval CI: 4.3% to 7.7%), and 533 died. Mean radiation dose delivered to the heart (mean heart dose) was associated with a significantly increased risk of MACE (adjusted hazard ratio HR: 1.05/Gy; 95% CI: 1.02 to 1.08/Gy; p < 0.001) and ACM (adjusted HR: 1.02/Gy; 95% CI: 1.00 to 1.03/Gy; p = 0.007). Mean heart dose (≥10 Gy vs. <10 Gy) was associated with a significantly increased risk of ACM in CHD-negative patients (178 vs. 118 deaths; HR: 1.34; 95% CI: 1.06 to 1.69; p = 0.014) with 2-year estimates of 52.2% (95% CI: 46.1% to 58.5%) versus 40.0% (95% CI: 33.5% to 47.4%); but not among CHD-positive patients (112 vs. 82 deaths; HR: 0.94; 95% CI: 0.70 to 1.25; p = 0.66) with 2-year estimates of 54.6% (95% CI: 46.8% to 62.7%) versus 50.8% (95% CI: 41.5% to 60.9%), respectively (p for interaction = 0.028).
Despite the competing risk of cancer-specific death in locally advanced NSCLC patients, cardiac radiation dose exposure is a modifiable cardiac risk factor for MACE and ACM, supporting the need for early recognition and treatment of cardiovascular events and more stringent avoidance of high cardiac radiotherapy dose.
Multiple prospective Radiation Therapy Oncology Group (RTOG) protocols have evaluated bladder-preserving combined-modality therapy (CMT) for muscle-invasive bladder cancer (MIBC), reserving ...cystectomy for salvage treatment. We performed a pooled analysis of long-term outcomes in patients with MIBC enrolled across multiple studies.
Four hundred sixty-eight patients with MIBC were enrolled onto six RTOG bladder-preservation studies, including five phase II studies (RTOG 8802, 9506, 9706, 9906, and 0233) and one phase III study (RTOG 8903). Overall survival (OS) was estimated using the Kaplan-Meier method, and disease-specific survival (DSS), muscle-invasive and non-muscle-invasive local failure (LF), and distant metastasis (DM) were estimated by the cumulative incidence method.
The median age of patients was 66 years (range, 34 to 93 years), and clinical T stage was T2 in 61%, T3 in 35%, and T4a in 4% of patients. Complete response to CMT was documented in 69% of patients. With a median follow-up of 4.3 years among all patients and 7.8 years among survivors (n = 205), the 5- and 10-year OS rates were 57% and 36%, respectively, and the 5- and 10-year DSS rates were 71% and 65%, respectively. The 5- and 10-year estimates of muscle-invasive LF, non-muscle-invasive LF, and DM were 13% and 14%, 31% and 36%, and 31% and 35%, respectively.
This pooled analysis of multicenter, prospective RTOG bladder-preserving CMT protocols demonstrates long-term DSS comparable to modern immediate cystectomy studies, for patients with similarly staged MIBC. Given the low incidence of late recurrences with long-term follow-up, CMT can be considered as an alternative to radical cystectomy, especially in elderly patients not well suited for surgery.
•Radiographic patterns of symptomatic radiation pneumonitis (RP) were characterized.•AIP/ARDS pattern is a predictive marker for high-grade RP and RP-related death.•Radiographic patterns of RP help ...to predict the clinical severity and outcome.
Investigate the spectrum of radiographic patterns of radiation pneumonitis (RP) in lung cancer patients and identify imaging markers for high-grade RP and RP-related death.
Eighty-two patients with lung cancer treated with conventional chest radiotherapy who had symptomatic RP were identified from the radiation oncology database. The imaging features of RP were studied for association with high-grade RP (Grade ≥3) and RP-related death (Grade 5).
RP was Grade 2 in 60 (73%), Grade 3 in 15 (18%), and Grade 5 in 7 patients (9%). Lower performance status (p = 0.04), squamous cell histology (p = 0.03), and FEV1 ≤ 2 (p = 0.009) were associated with high-grade pneumonitis. Older age (p = 0.03) and squamous cell histology (p = 0.03) were associated with RP-related death. The CT findings included ground-glass and reticular opacities in all patients, with traction bronchiectasis in 77 (94%) and consolidation in 74 (90%). The most common radiographic pattern of RP was cryptogenic organizing pneumonia (COP) pattern (n = 54), followed by acute interstitial pneumonia (AIP)/acute respiratory distress syndrome (ARDS) pattern (n = 10). Higher extent of lung involvement, diffuse distribution, and AIP/ARDS pattern were associated with high-grade pneumonitis and RP-related death. AIP/ARDS pattern was a significant factor for high-grade pneumonitis (OR:12.62, p = 0.01) in multivariable analyses adjusting for clinical variables.
COP pattern was the most common radiographic pattern for symptomatic RP in lung cancer patients. AIP/ARDS pattern was significantly associated with high-grade RP and RP-related deaths, and was an independent marker for high-grade RP. The recognition of the radiographic patterns of RP can help to effectively contribute to patient management.
Oxidative stress is caused by an imbalance between the production of reactive oxygen species (ROS) and the ability of an organism to eliminate these toxic intermediates. Although the ...Parkinson-susceptibility gene, Parkinson protein 7/DJ-1 (DJ-1), has been linked to the regulation of oxidative stress, the exact mechanism by which this occurs and its in vivo relevance have remained elusive. In the heart, oxidative stress is a major contributor to the development of heart failure (HF). Therefore, we hypothesized that DJ-1 inhibits the pathological consequences of ROS production in the heart, the organ with the highest oxidative burden. We report that DJ-1 is highly expressed in normal heart tissue but is markedly reduced in end-stage human HF. DJ-1-deficient mice subjected to oxidative stress by transaortic banding exhibited exaggerated cardiac hypertrophy and susceptibility to developing HF. This was accompanied by a Trp53 (p53)-dependent decrease in capillary density, an excessive oxidation of DNA, and increased cardiomyocyte apoptosis, key events in the development of HF. Impaired mitochondrial biogenesis and progressive respiratory chain deficiency were also evident in cardiomyocytes lacking DJ-1. Our results provide compelling in vivo evidence that DJ-1 is a unique and nonredundant antioxidant that functions independent of other antioxidative pathways in the cellular defense against ROS.
Abstract Background and purpose Radiomics can quantify tumor phenotype characteristics non-invasively by applying advanced imaging feature algorithms. In this study we assessed if pre-treatment ...radiomics data are able to predict pathological response after neoadjuvant chemoradiation in patients with locally advanced non-small cell lung cancer (NSCLC). Materials and Methods 127 NSCLC patients were included in this study. Fifteen radiomic features selected based on stability and variance were evaluated for its power to predict pathological response. Predictive power was evaluated using area under the curve (AUC). Conventional imaging features (tumor volume and diameter) were used for comparison. Results Seven features were predictive for pathologic gross residual disease (AUC > 0.6, p -value < 0.05), and one for pathologic complete response (AUC = 0.63, p -value = 0.01). No conventional imaging features were predictive (range AUC = 0.51–0.59, p -value > 0.05). Tumors that did not respond well to neoadjuvant chemoradiation were more likely to present a rounder shape (spherical disproportionality, AUC = 0.63, p -value = 0.009) and heterogeneous texture (LoG 5 mm 3D – GLCM entropy, AUC = 0.61, p -value = 0.03). Conclusion We identified predictive radiomic features for pathological response, although no conventional features were significantly predictive. This study demonstrates that radiomics can provide valuable clinical information, and performed better than conventional imaging features.
Patients with non-small-cell lung cancer (NSCLC) that is resistant to PD-1 and PD-L1 (PDL-1)-targeted therapy have poor outcomes. Studies suggest that radiotherapy could enhance antitumour immunity. ...Therefore, we investigated the potential benefit of PD-L1 (durvalumab) and CTLA-4 (tremelimumab) inhibition alone or combined with radiotherapy.
This open-label, multicentre, randomised, phase 2 trial was done by the National Cancer Institute Experimental Therapeutics Clinical Trials Network at 18 US sites. Patients aged 18 years or older with metastatic NSCLC, an Eastern Cooperative Oncology Group performance status of 0 or 1, and progression during previous PD(L)-1 therapy were eligible. They were randomly assigned (1:1:1) in a web-based system by the study statistician using a permuted block scheme (block sizes of three or six) without stratification to receive either durvalumab (1500 mg intravenously every 4 weeks for a maximum of 13 cycles) plus tremelimumab (75 mg intravenously every 4 weeks for a maximum of four cycles) alone or with low-dose (0·5 Gy delivered twice per day, repeated for 2 days during each of the first four cycles of therapy) or hypofractionated radiotherapy (24 Gy total delivered over three 8-Gy fractions during the first cycle only), 1 week after initial durvalumab–tremelimumab administration. Study treatment was continued until 1 year or until progression. The primary endpoint was overall response rate (best locally assessed confirmed response of a partial or complete response) and, along with safety, was analysed in patients who received at least one dose of study therapy. The trial is registered with ClinicalTrials.gov, NCT02888743, and is now complete.
Between Aug 24, 2017, and March 29, 2019, 90 patients were enrolled and randomly assigned, of whom 78 (26 per group) were treated. This trial was stopped due to futility assessed in an interim analysis. At a median follow-up of 12·4 months (IQR 7·8–15·1), there were no differences in overall response rates between the durvalumab–tremelimumab alone group (three 11·5%, 90% CI 1·2–21·8 of 26 patients) and the low-dose radiotherapy group (two 7·7%, 0·0–16·3 of 26 patients; p=0·64) or the hypofractionated radiotherapy group (three 11·5%, 1·2–21·8 of 26 patients; p=0·99). The most common grade 3–4 adverse events were dyspnoea (two 8% in the durvalumab–tremelimumab alone group; three 12% in the low-dose radiotherapy group; and three 12% in the hypofractionated radiotherapy group) and hyponatraemia (one 4% in the durvalumab–tremelimumab alone group vs two 8% in the low-dose radiotherapy group vs three 12% in the hypofractionated radiotherapy group). Treatment-related serious adverse events occurred in one (4%) patient in the durvalumab–tremelimumab alone group (maculopapular rash), five (19%) patients in the low-dose radiotherapy group (abdominal pain, diarrhoea, dyspnoea, hypokalemia, and respiratory failure), and four (15%) patients in the hypofractionated group (adrenal insufficiency, colitis, diarrhoea, and hyponatremia). In the low-dose radiotherapy group, there was one death from respiratory failure potentially related to study therapy.
Radiotherapy did not increase responses to combined PD-L1 plus CTLA-4 inhibition in patients with NSCLC resistant to PD(L)-1 therapy. However, PD-L1 plus CTLA-4 therapy could be a treatment option for some patients. Future studies should refine predictive biomarkers in this setting.
The US National Institutes of Health and the Dana-Farber Cancer Institute.
Although palliative chemotherapy is the standard of care for patients with diagnoses of stage IV non-small cell lung cancer (NSCLC), patients with a small metastatic burden, "oligometastatic" ...disease, may benefit from more aggressive local therapy.
We identified 186 patients (26% of stage IV patients) prospectively enrolled in our institutional database from 2002 to 2012 with oligometastatic disease, which we defined as 5 or fewer distant metastatic lesions at diagnosis. Univariate and multivariable Cox proportional hazards models were used to identify patient and disease factors associated with improved survival. Using propensity score methods, we investigated the effect of definitive local therapy to the primary tumor on overall survival.
Median age at diagnosis was 61 years of age; 51% of patients were female; 12% had squamous histology; and 33% had N0-1 disease. On multivariable analysis, Eastern Cooperate Oncology Group performance status ≥ 2 (hazard ratio HR, 2.43), nodal status, N2-3 (HR, 2.16), squamous pathology, and metastases to multiple organs (HR, 2.11) were associated with a greater hazard of death (all P<.01). The number of metastatic lesions and radiologic size of the primary tumor were not significantly associated with overall survival. Definitive local therapy to the primary tumor was associated with prolonged survival (HR, 0.65, P=.043).
Definitive local therapy to the primary tumor appears to be associated with improved survival in patients with oligometastatic NSCLC. Select patient and tumor characteristics, including good performance status, nonsquamous histology, and limited nodal disease, may predict for improved survival in these patients.
Pneumonitis is a potential consequence of both lung-directed radiation and immune checkpoint blockade (ICB), particularly treatment with PD-1/PD-L1 inhibitors. Significant morbidity and mortality can ...result, and severe pneumonitis attributed to ICB precludes continued therapy. Thus, discriminating between radiation- and ICB- related pneumonitis is of importance for the increasing number of patients receiving both treatments. Furthermore, data are limited regarding the interplay between radiation- and ICB-induced lung injury, and which biomarkers might be associated with toxicity.
We report longitudinal clinical and radiologic data, and circulating biomarkers in a melanoma patient treated with axillary radiation followed by ICB who developed consolidation and ground glass opacities (GGO) within the radiation field suggestive of radiation-pneumonitis followed by consolidation outside of the radiation field suggestive of ICB-related pneumonitis. Of note, symptomatic radiation-pneumonitis developed despite a low radiation dose to the lung (V20 < 8%), and ICB-related pneumonitis was limited to the ipsilateral lung, suggesting additive effect of radiation and ICB in the development of lung injury. Circulating biomarker analyses demonstrated increases in CXCR2, IL1ra and IL2ra that coincided with the development of symptomatic pneumonitis.
These data highlight the imaging findings associated with radiation and ICB-related lung toxicity, and anecdotally describe a clinical course with circulating biomarker correlates. This information can help guide clinical evaluation and future research investigations into the toxicity of combined radiation immunotherapy approaches.
PET-based radiomics have been used to noninvasively quantify the metabolic tumor phenotypes; however, little is known about the relationship between these phenotypes and underlying somatic mutations. ...This study assessed the association and predictive power of
F-FDG PET-based radiomic features for somatic mutations in non-small cell lung cancer patients.
Three hundred forty-eight non-small cell lung cancer patients underwent diagnostic
F-FDG PET scans and were tested for genetic mutations. Thirteen percent (44/348) and 28% (96/348) of patients were found to harbor epidermal growth factor receptor (EGFR) or Kristen rat sarcoma viral (KRAS) mutations, respectively. We evaluated 21 imaging features: 19 independent radiomic features quantifying phenotypic traits and 2 conventional features (metabolic tumor volume and maximum SUV). The association between imaging features and mutation status (e.g., EGFR-positive EGFR+ vs. EGFR-negative) was assessed using the Wilcoxon rank-sum test. The ability of each imaging feature to predict mutation status was evaluated by the area under the receiver operating curve (AUC) and its significance was compared with a random guess (AUC = 0.5) using the Noether test. All
values were corrected for multiple hypothesis testing by controlling the false-discovery rate (FDR
, FDR
) with a significance threshold of 10%.
Eight radiomic features and both conventional features were significantly associated with EGFR mutation status (FDR
= 0.01-0.10). One radiomic feature (normalized inverse difference moment) outperformed all other features in predicting EGFR mutation status (EGFR+ vs. EGFR-negative, AUC = 0.67, FDR
= 0.0032), as well as differentiating between KRAS-positive and EGFR+ (AUC = 0.65, FDR
= 0.05). None of the features was associated with or predictive of KRAS mutation status (KRAS-positive vs. KRAS-negative, AUC = 0.50-0.54).
Our results indicate that EGFR mutations may drive different metabolic tumor phenotypes that are captured in PET images, whereas KRAS-mutated tumors do not. This proof-of-concept study sheds light on genotype-phenotype interactions, using radiomics to capture and describe the phenotype, and may have potential for developing noninvasive imaging biomarkers for somatic mutations.
Manual segmentation of tumors and organs-at-risk (OAR) in 3D imaging for radiation-therapy planning is time-consuming and subject to variation between different observers. Artificial intelligence ...(AI) can assist with segmentation, but challenges exist in ensuring high-quality segmentation, especially for small, variable structures, such as the esophagus. We investigated the effect of variation in segmentation quality and style of physicians for training deep-learning models for esophagus segmentation and proposed a new metric, edge roughness, for evaluating/quantifying slice-to-slice inconsistency. This study includes a real-world cohort of 394 patients who each received radiation therapy (mainly for lung cancer). Segmentation of the esophagus was performed by 8 physicians as part of routine clinical care. We evaluated manual segmentation by comparing the length and edge roughness of segmentations among physicians to analyze inconsistencies. We trained eight multiple- and individual-physician segmentation models in total, based on U-Net architectures and residual backbones. We used the volumetric Dice coefficient to measure the performance for each model. We proposed a metric, edge roughness, to quantify the shift of segmentation among adjacent slices by calculating the curvature of edges of the 2D sagittal- and coronal-view projections. The auto-segmentation model trained on multiple physicians (MD1-7) achieved the highest mean Dice of 73.7 ± 14.8%. The individual-physician model (MD7) with the highest edge roughness (mean ± SD: 0.106 ± 0.016) demonstrated significantly lower volumetric Dice for test cases compared with other individual models (MD7: 58.5 ± 15.8%, MD6: 67.1 ± 16.8%, p < 0.001). A multiple-physician model trained after removing the MD7 data resulted in fewer outliers (e.g., Dice ≤ 40%: 4 cases for MD1-6, 7 cases for MD1-7, N
= 394). While we initially detected this pattern in a single clinician, we validated the edge roughness metric across the entire dataset. The model trained with the lowest-quantile edge roughness (MD
-Q1, N
= 62) achieved significantly higher Dice (N
= 270) than the model trained with the highest-quantile ones (MD
-Q4, N
= 62) (MD
-Q1: 67.8 ± 14.8%, MD
-Q4: 62.8 ± 15.7%, p < 0.001). This study demonstrates that there is significant variation in style and quality in manual segmentations in clinical care, and that training AI auto-segmentation algorithms from real-world, clinical datasets may result in unexpectedly under-performing algorithms with the inclusion of outliers. Importantly, this study provides a novel evaluation metric, edge roughness, to quantify physician variation in segmentation which will allow developers to filter clinical training data to optimize model performance.
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