Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.

BACKGROUND AND PURPOSE: Survival is frequently assessed using Cox proportional hazards (CPH) regression; however, CPH may be too simplistic as it assumes a linear relationship between covariables and the outcome. Alternative, non-linear machine learning (ML)-based approaches, such as random survival forests (RSFs) and, more recently, deep learning (DL) have been proposed; however, these techniques are largely black-box in nature, limiting explainability. We compared CPH, RSF and DL to predict overall survival (OS) of non-small cell lung cancer (NSCLC) patients receiving radiotherapy using pre-treatment covariables. We employed explainable techniques to provide insights into the contribution of each covariable on OS prediction. MATERIALS AND METHODS: The dataset contained 471 stage I-IV NSCLC patients treated with radiotherapy. We built CPH, RSF and DL OS prediction models using several baseline covariable combinations. 10-fold Monte-Carlo cross-validation was employed with a split of 70%:10%:20% for training, validation and testing, respectively. We primarily evaluated performance using the concordance index (C-index) and integrated Brier score (IBS). Local interpretable model-agnostic explanation (LIME) values, adapted for use in survival analysis, were computed for each model. RESULTS: The DL method exhibited a significantly improved C-index of 0.670 compared to the CPH and a significantly improved IBS of 0.121 compared to the CPH and RSF approaches. LIME values suggested that, for the DL method, the three most important covariables in OS prediction were stage, administration of chemotherapy and oesophageal mean radiation dose. CONCLUSION: We show that, using pre-treatment covariables, a DL approach demonstrates superior performance over CPH and RSF for OS prediction and use explainable techniques to provide transparency and interpretability.

A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis.

BACKGROUND: Retroperitoneal sarcomas are tumours with a poor prognosis. Upfront characterisation of the tumour is difficult, and under-grading is common. Radiomics has the potential to non-invasively characterise the so-called radiological phenotype of tumours. We aimed to develop and independently validate a CT-based radiomics classification model for the prediction of histological type and grade in retroperitoneal leiomyosarcoma and liposarcoma. METHODS: A retrospective discovery cohort was collated at our centre (Royal Marsden Hospital, London, UK) and an independent validation cohort comprising patients recruited in the phase 3 STRASS study of neoadjuvant radiotherapy in retroperitoneal sarcoma. Patients aged older than 18 years with confirmed primary leiomyosarcoma or liposarcoma proceeding to surgical resection with available contrast-enhanced CT scans were included. Using the discovery dataset, a CT-based radiomics workflow was developed, including manual delineation, sub-segmentation, feature extraction, and predictive model building. Separate probabilistic classifiers for the prediction of histological type and low versus intermediate or high grade tumour types were built and tested. Independent validation was then performed. The primary objective of the study was to develop radiomic classification models for the prediction of retroperitoneal leiomyosarcoma and liposarcoma type and histological grade. FINDINGS: 170 patients recruited between Oct 30, 2016, and Dec 23, 2020, were eligible in the discovery cohort and 89 patients recruited between Jan 18, 2012, and April 10, 2017, were eligible in the validation cohort. In the discovery cohort, the median age was 63 years (range 27-89), with 83 (49%) female and 87 (51%) male patients. In the validation cohort, median age was 59 years (range 33-77), with 46 (52%) female and 43 (48%) male patients. The highest performing model for the prediction of histological type had an area under the receiver operator curve (AUROC) of 0·928 on validation, based on a feature set of radiomics and approximate radiomic volume fraction. The highest performing model for the prediction of histological grade had an AUROC of 0·882 on validation, based on a radiomics feature set. INTERPRETATION: Our validated radiomics model can predict the histological type and grade of retroperitoneal sarcomas with excellent performance. This could have important implications for improving diagnosis and risk stratification in retroperitoneal sarcomas. FUNDING: Wellcome Trust, European Organisation for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group, the National Institutes for Health, and the National Institute for Health and Care Research Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research.

Stereotactic arrhythmia radioablation: A multicenter pre-post intervention safety evaluation of the implantable cardioverter-defibrillator function.

BACKGROUND: Stereotactic arrhythmia radioablation (STAR) appears to be beneficial in selected patients with therapy-refractory ventricular tachycardia (VT). However, high-dose radiotherapy used for STAR-treatment may affect functioning of the patients' implantable cardioverter defibrillator (ICD) by direct effects of radiation on ICD components or cardiac tissue. Currently, the effect of STAR on ICD functioning remains unknown. METHODS: A retrospective pre-post multicenter study evaluating ICD functioning in the 12-month before and after STAR was performed. Patients with (non)ischemic cardiomyopathies with therapy-refractory VT and ICD who underwent STAR were included and the occurrence of ICD-related adverse events was collected. Evaluated ICD parameters included sensing, capture threshold and impedance. A linear mixed-effects model was used to investigate the association between STAR, radiotherapy dose and changes in lead parameters over time. RESULTS: In total, 43 patients (88% male) were included in this study. All patients had an ICD with an additional right atrial lead in 34 (79%) and a ventricular lead in 17 (40%) patients. Median ICD-generator dose was 0.1 Gy and lead tip dose ranged from 0-32 Gy. In one patient (2%), a reset occurred during treatment, but otherwise, STAR and radiotherapy dose were not associated with clinically relevant alterations in ICD leads parameters. CONCLUSIONS: STAR treatment did not result in major ICD malfunction. Only one radiotherapy related adverse event occurred during the study follow-up without patient harm. No clinically relevant alterations in ICD functioning were observed after STAR in any of the leads. With the reported doses STAR appears to be safe.

PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation.

Functional lung imaging modalities such as hyperpolarized gas MRI ventilation enable visualization and quantification of regional lung ventilation; however, these techniques require specialized equipment and exogenous contrast, limiting clinical adoption. Physiologically-informed techniques to map proton (1H)-MRI ventilation have been proposed. These approaches have demonstrated moderate correlation with hyperpolarized gas MRI. Recently, deep learning (DL) has been used for image synthesis applications, including functional lung image synthesis. Here, we propose a 3D multi-channel convolutional neural network that employs physiologically-informed ventilation mapping and multi-inflation structural 1H-MRI to synthesize 3D ventilation surrogates (PhysVENeT). The dataset comprised paired inspiratory and expiratory 1H-MRI scans and corresponding hyperpolarized gas MRI scans from 170 participants with various pulmonary pathologies. We performed fivefold cross-validation on 150 of these participants and used 20 participants with a previously unseen pathology (post COVID-19) for external validation. Synthetic ventilation surrogates were evaluated using voxel-wise correlation and structural similarity metrics; the proposed PhysVENeT framework significantly outperformed conventional 1H-MRI ventilation mapping and other DL approaches which did not utilize structural imaging and ventilation mapping. PhysVENeT can accurately reflect ventilation defects and exhibits minimal overfitting on external validation data compared to DL approaches that do not integrate physiologically-informed mapping.

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regional lung ventilation with exceptional detail within a single breath. However, this modality requires specialized equipment and exogenous contrast, which limits widespread clinical adoption. CT ventilation imaging employs various metrics to model regional ventilation from non-contrast CT scans acquired at multiple inflation levels and has demonstrated moderate spatial correlation with hyperpolarized gas MRI. Recently, deep learning (DL)-based methods, utilizing convolutional neural networks (CNNs), have been leveraged for image synthesis applications. Hybrid approaches integrating computational modeling and data-driven methods have been utilized in cases where datasets are limited with the added benefit of maintaining physiological plausibility. PURPOSE: To develop and evaluate a multi-channel DL-based method that combines modeling and data-driven approaches to synthesize hyperpolarized gas MRI lung ventilation scans from multi-inflation, non-contrast CT and quantitatively compare these synthetic ventilation scans to conventional CT ventilation modeling. METHODS: In this study, we propose a hybrid DL configuration that integrates model- and data-driven methods to synthesize hyperpolarized gas MRI lung ventilation scans from a combination of non-contrast, multi-inflation CT and CT ventilation modeling. We used a diverse dataset comprising paired inspiratory and expiratory CT and helium-3 hyperpolarized gas MRI for 47 participants with a range of pulmonary pathologies. We performed six-fold cross-validation on the dataset and evaluated the spatial correlation between the synthetic ventilation and real hyperpolarized gas MRI scans; the proposed hybrid framework was compared to conventional CT ventilation modeling and other non-hybrid DL configurations. Synthetic ventilation scans were evaluated using voxel-wise evaluation metrics such as Spearman's correlation and mean square error (MSE), in addition to clinical biomarkers of lung function such as the ventilated lung percentage (VLP). Furthermore, regional localization of ventilated and defect lung regions was assessed via the Dice similarity coefficient (DSC). RESULTS: We showed that the proposed hybrid framework is capable of accurately replicating ventilation defects seen in the real hyperpolarized gas MRI scans, achieving a voxel-wise Spearman's correlation of 0.57 ± 0.17 and an MSE of 0.017 ± 0.01. The hybrid framework significantly outperformed CT ventilation modeling alone and all other DL configurations using Spearman's correlation. The proposed framework was capable of generating clinically relevant metrics such as the VLP without manual intervention, resulting in a Bland-Altman bias of 3.04%, significantly outperforming CT ventilation modeling. Relative to CT ventilation modeling, the hybrid framework yielded significantly more accurate delineations of ventilated and defect lung regions, achieving a DSC of 0.95 and 0.48 for ventilated and defect regions, respectively. CONCLUSION: The ability to generate realistic synthetic ventilation scans from CT has implications for several clinical applications, including functional lung avoidance radiotherapy and treatment response mapping. CT is an integral part of almost every clinical lung imaging workflow and hence is readily available for most patients; therefore, synthetic ventilation from non-contrast CT can provide patients with wider access to ventilation imaging worldwide.

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1 H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters. PURPOSE: Develop a generalizable CNN for lung segmentation in 1 H-MRI, robust to pathology, acquisition protocol, vendor, and center. STUDY TYPE: Retrospective. POPULATION: A total of 809 1 H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6-85); 42% females) and 31 healthy participants (median age (range): 34 (23-76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1 H-MRI. ASSESSMENT: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. STATISTICAL TESTS: Kruskal-Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland-Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant. RESULTS: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880-0.987), Average HD of 1.63 mm (0.65-5.45) and XOR of 0.079 (0.025-0.240) on the testing set and a DSC of 0.973 (0.866-0.987), Average HD of 1.11 mm (0.47-8.13) and XOR of 0.054 (0.026-0.255) on external validation data. DATA CONCLUSION: The 3D CNN generated accurate 1 H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI.

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and quantification of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. Here, we evaluate several 3D convolutional neural networks to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 759 helium-3 (3He) or xenon-129 (129Xe) volumetric scans and corresponding expert segmentations from 341 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined 3He and 129Xe MRI scans using a 3D nn-UNet outperformed other DL methods, achieving a mean ± SD Dice coefficient of 0.963 ± 0.018, average boundary Hausdorff distance of 1.505 ± 0.969 mm, Hausdorff 95th percentile of 5.754 ± 6.621 mm and relative error of 0.075 ± 0.039. Moreover, limited differences in performance were observed between 129Xe and 3He scans in the testing set. Combined training on 129Xe and 3He yielded statistically significant improvements over the conventional methods (p < 0.0001). In addition, we observed very strong correlation and agreement between DL and expert segmentations, with Pearson correlation of 0.99 (p < 0.0001) and Bland-Altman bias of - 0.8%. The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and artefacts. This approach is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing.

Postoperative radiotherapy versus no postoperative radiotherapy in patients with completely resected non-small-cell lung cancer and proven mediastinal N2 involvement (Lung ART): an open-label, randomised, phase 3 trial.

BACKGROUND: In patients with non-small-cell lung cancer (NSCLC), the use of postoperative radiotherapy (PORT) has been controversial since 1998, because of one meta-analysis showing a deleterious effect on survival in patients with pN0 and pN1, but with an unclear effect in patients with pN2 NSCLC. Because many changes have occurred in the management of patients with NSCLC, the role of three-dimensional (3D) conformal PORT warrants further investigation in patients with stage IIIAN2 NSCLC. The aim of this study was to establish whether PORT should be part of their standard treatment. METHODS: Lung ART is an open-label, randomised, phase 3, superiority trial comparing mediastinal PORT to no PORT in patients with NSCLC with complete resection, nodal exploration, and cytologically or histologically proven N2 involvement. Previous neoadjuvant or adjuvant chemotherapy was allowed. Patients aged 18 years or older, with an WHO performance status of 0-2, were recruited from 64 hospitals and cancer centres in five countries (France, UK, Germany, Switzerland, and Belgium). Patients were randomly assigned (1:1) to either the PORT or no PORT (control) groups via a web randomisation system, and minimisation factors were the institution, administration of chemotherapy, number of mediastinal lymph node stations involved, histology, and use of pre-treatment PET scan. Patients received PORT at a dose of 54 Gy in 27 or 30 daily fractions, on five consecutive days a week. Three dimensional conformal radiotherapy was mandatory, and intensity-modulated radiotherapy was permitted in centres with expertise. The primary endpoint was disease-free survival, analysed by intention to treat at 3 years; patients from the PORT group who did not receive radiotherapy and patients from the control group with no follow-up were excluded from the safety analyses. This trial is now closed. This trial is registered with ClinicalTrials.gov number, NCT00410683. FINDINGS: Between Aug 7, 2007, and July 17, 2018, 501 patients, predominantly staged with 18F-fluorodeoxyglucose (18F-FDG) PET (456 [91%]; 232 (92%) in the PORT group and 224 (90%) in the control group), were enrolled and randomly assigned to receive PORT (252 patients) or no PORT (249 patients). At the cutoff date of May 31, 2019, median follow-up was 4·8 years (IQR 2·9-7·0). 3-year disease-free survival was 47% (95% CI 40-54) with PORT versus 44% (37-51) without PORT, and the median disease-free survival was 30·5 months (95% CI 24-49) in the PORT group and 22·8 months (17-37) in the control group (hazard ratio 0·86; 95% CI 0·68-1·08; p=0·18). The most common grade 3-4 adverse events were pneumonitis (13 [5%] of 241 patients in the PORT group vs one [<1%] of 246 in the control group), lymphopenia (nine [4%] vs 0), and fatigue (six [3%] vs one [<1%]). Late-grade 3-4 cardiopulmonary toxicity was reported in 26 patients (11%) in the PORT group versus 12 (5%) in the control group. Two patients died from pneumonitis, partly related to radiotherapy and infection, and one patient died due to chemotherapy toxicity (sepsis) that was deemed to be treatment-related, all of whom were in the PORT group. INTERPRETATION: Lung ART evaluated 3D conformal PORT after complete resection in patients who predominantly had been staged using (18F-FDG PET-CT and received neoadjuvant or adjuvant chemotherapy. 3-year disease-free survival was higher than expected in both groups, but PORT was not associated with an increased disease-free survival compared with no PORT. Conformal PORT cannot be recommended as the standard of care in patients with stage IIIAN2 NSCLC. FUNDING: French National Cancer Institute, Programme Hospitalier de Recherche Clinique from the French Health Ministry, Gustave Roussy, Cancer Research UK, Swiss State Secretary for Education, Research, and Innovation, Swiss Cancer Research Foundation, Swiss Cancer League.

Cardiac stereotactic ablative radiotherapy for control of refractory ventricular tachycardia: initial UK multicentre experience.

BACKGROUND: Options for patients with ventricular tachycardia (VT) refractory to antiarrhythmic drugs and/or catheter ablation remain limited. Stereotactic radiotherapy has been described as a novel treatment option. METHODS: Seven patients with recurrent refractory VT, deemed high risk for either first time or redo invasive catheter ablation, were treated across three UK centres with non-invasive cardiac stereotactic ablative radiotherapy (SABR). Prior catheter ablation data and non-invasive mapping were combined with cross-sectional imaging to generate radiotherapy plans with aim to deliver a single 25 Gy treatment. Shared planning and treatment guidelines and prospective peer review were used. RESULTS: Acute suppression of VT was seen in all seven patients. For five patients with at least 6 months follow-up, overall reduction in VT burden was 85%. No high-grade radiotherapy treatment-related side effects were documented. Three deaths (two early, one late) occurred due to heart failure. CONCLUSIONS: Cardiac SABR showed reasonable VT suppression in a high-risk population where conventional treatment had failed.

Observational cohort study in older women with early breast cancer: Use of radiation therapy and impact on health-related quality of life and mortality.

BACKGROUND: Radiotherapy reduces in-breast recurrence risk in early breast cancer (EBC) in older women. This benefit may be small and should be balanced against treatment effect and holistic patient assessment. This study described treatment patterns according to fitness and impact on health-related quality-of-life (HRQoL). METHODS: A multicentre, observational study of EBC patients aged ≥ 70 years, undergoing breast-conserving surgery (BCS) or mastectomy, was undertaken. Associations between radiotherapy use, surgery, clinico-pathological parameters, fitness based on geriatric parameters and treatment centre were determined. HRQoL was measured using the European Organisation for the Research and Treatment of Cancer (EORTC) questionnaires. RESULTS: In 2013-2018 2811 women in 56 UK study centres underwent surgery with a median follow-up of 52 months. On multivariable analysis, age and tumour risk predicted radiotherapy use. Among healthier patients (based on geriatric assessments) with high-risk tumours, 534/613 (87.1%) having BCS and 185/341 (54.2%) having mastectomy received radiotherapy. In less fit individuals with low-risk tumours undergoing BCS, 149/207 (72.0%) received radiotherapy. Radiotherapy effects on HRQoL domains, including breast symptoms and fatigue were seen, resolving by 18 months. CONCLUSION: Radiotherapy use in EBC patients ≥ 70 years is affected by age and recurrence risk, whereas geriatric parameters have limited impact regardless of type of surgery. There was geographical variation in treatment, with some fit older women with high-risk tumours not receiving radiotherapy, and some older, low-risk, EBC patients receiving radiotherapy after BCS despite evidence of limited benefit. The impact on HRQoL is transient.

Bridging The Age Gap: observational cohort study of effects of chemotherapy and trastuzumab on recurrence, survival and quality of life in older women with early breast cancer.

BACKGROUND: Chemotherapy improves outcomes for high risk early breast cancer (EBC) patients but is infrequently offered to older individuals. This study determined if there are fit older patients with high-risk disease who may benefit from chemotherapy. METHODS: A multicentre, prospective, observational study was performed to determine chemotherapy (±trastuzumab) usage and survival and quality-of-life outcomes in EBC patients aged ≥70 years. Propensity score-matching adjusted for variation in baseline age, fitness and tumour stage. RESULTS: Three thousands four hundred sixteen women were recruited from 56 UK centres between 2013 and 2018. Two thousands eight hundred eleven (82%) had surgery. 1520/2811 (54%) had high-risk EBC and 2059/2811 (73%) were fit. Chemotherapy was given to 306/1100 (27.8%) fit patients with high-risk EBC. Unmatched comparison of chemotherapy versus no chemotherapy demonstrated reduced metastatic recurrence risk in high-risk patients(hazard ratio [HR] 0.36 [95% CI 0.19-0.68]) and in 541 age, stage and fitness-matched patients(adjusted HR 0.43 [95% CI 0.20-0.92]) but no benefit to overall survival (OS) or breast cancer-specific survival (BCSS) in either group. Chemotherapy improved survival in women with oestrogen receptor (ER)-negative cancer (OS: HR 0.20 [95% CI 0.08-0.49];BCSS: HR 0.12 [95% CI 0.03-0.44]).Transient negative quality-of-life impacts were observed. CONCLUSIONS: Chemotherapy was associated with reduced risk of metastatic recurrence, but survival benefits were only seen in patients with ER-negative cancer. Quality-of-life impacts were significant but transient. TRIAL REGISTRATION: ISRCTN 46099296.

Stereotactic ablative body radiotherapy in patients with oligometastatic cancers: a prospective, registry-based, single-arm, observational, evaluation study.

BACKGROUND: Stereotactic ablative body radiotherapy (SABR) is increasingly being used to treat oligometastatic cancers, but high-level evidence to provide a basis for policy making is scarce. Additional evidence from a real-world setting is required. We present the results of a national study of patients with extracranial oligometastases undergoing SABR, representing the largest dataset, to our knowledge, on outcomes in this population so far. METHODS: In 2015, National Health Service (NHS) England launched a Commissioning through Evaluation scheme that funded a prospective, registry-based, single-arm, observational, evaluation study of patients with solid cancer and extracranial oligometastases treated with SABR. Prescribed doses ranged from 24-60 Gy administered in three to eight fractions. The study was done at 17 NHS radiotherapy centres in England. Patients were eligible for the scheme if aged 18 years or older with confirmed primary carcinoma (excluding haematological malignancies), one to three extracranial metastatic lesions, a disease-free interval from primary tumour development to metastases of longer than 6 months (with the exception of synchronous colorectal liver metastases), a WHO performance status of 2 or lower, and a life expectancy of at least 6 months. The primary outcome was overall survival at 1 year and 2 years from the start of SABR treatment. The study is now completed. FINDINGS: Between June 15, 2015, and Jan 30, 2019, 1422 patients were recruited from 17 hospitals in England. The median age of the patients was 69 years (IQR 62-76), and the most common primary tumour was prostate cancer (406 [28·6%] patients). Median follow-up was 13 months (IQR 6-23). Overall survival was 92·3% (95% CI 90·5-93·9) at 1 year and 79·2% (76·0-82·1) at 2 years. The most common grade 3 adverse event was fatigue (28 [2·0%] of 1422 patients) and the most common serious (grade 4) event was increased liver enzymes (nine [0·6%]). Notreatment-related deaths were reported. INTERPRETATION: In patients with extracranial oligometastatic cancer, use of SABR was associated with high overall survival and low toxicity. 'The study findings complement existing evidence from a randomised, phase 2 trial, and represent high-level, real-world evidence supporting the use of SABR in this patient cohort, with a phase 3 randomised, controlled trial to confirm these findings underway. Based on the selection criteria in this study, SABR was commissioned by NHS England in March, 2020, as a treatment option for patients with oligometastatic disease. FUNDING: NHS England Commissioning through Evaluation scheme.

Bridging the age gap in breast cancer. Impacts of omission of breast cancer surgery in older women with oestrogen receptor positive early breast cancer. A risk stratified analysis of survival outcomes and quality of life.

BACKGROUND: Age-related breast cancer treatment variance is widespread with many older women having primary endocrine therapy (PET), which may contribute to inferior survival and local control. This propensity-matched study determined if a subgroup of older women may safely be offered PET. METHODS: Multicentre, prospective, UK, observational cohort study with propensity-matched analysis to determine optimal allocation of surgery plus ET (S+ET) or PET in women aged ≥70 with breast cancer. Data on fitness, frailty, cancer stage, grade, biotype, treatment and quality of life were collected. Propensity-matching (based on age, health status and cancer stage) adjusted for allocation bias when comparing S+ET with PET. FINDINGS: A total of 3416 women (median age 77, range 69-102) were recruited from 56 breast units-2854 (88%) had ER+ breast cancer: 2354 had S+ET and 500 PET. Median follow-up was 52 months. Patients treated with PET were older and frailer than patients treated with S+ET. Unmatched overall survival was inferior in the PET group (hazard ratio, (HR) 0.27, 95% confidence interval (CI) 0.23-0.33, P < 0.001). Unmatched breast cancer-specific survival (BCSS) was also inferior in patients treated with PET (HR: 0.41, CI: 0.29-0.58, P < 0.001 for BCSS). In the matched analysis, PET was still associated with an inferior overall survival (HR = 0.72, 95% CI: 0.53-0.98, P = 0.04) but not BCSS (HR = 0.74, 95% CI: 0.40-1.37, P = 0.34) although at 4-5 years subtle divergence of the curves commenced in favor of surgery. Global health status diverged at certain time points between groups but over 24 months was similar when adjusted for baseline variance. INTERPRETATION: For the majority of older women with early ER+ breast cancer, surgery is oncologically superior to PET. In less fit, older women, with characteristics similar to the matched cohort of this study (median age 81 with higher comorbidity and functional impairment burdens, the BCSS survival differential disappears at least out to 4-5 year follow-up, suggesting that for those with less than 5-year predicted life-expectancy (>90 years or >85 with comorbidities or frailty) individualised decision making regarding PET versus S+ET may be appropriate and safe to offer. The Age Gap online decision tool may support this decision-making process (https://agegap.shef.ac.uk/). TRIAL REGISTRATION NUMBER: ISRCTN: 46099296.

Bridging the Age Gap in breast cancer: Impact of chemotherapy on quality of life in older women with early breast cancer.

INTRODUCTION: Older patients with early breast cancer (EBC) derive modest survival benefit from chemotherapy but have increased toxicity risk. Data on the impact of chemotherapy for EBC on quality of life in older patients are limited, but this is a key determinant of treatment acceptance. We aimed to investigate its effect on quality of life in older patients enrolled in the Bridging the Age Gap study. MATERIALS AND METHODS: A prospective, multicentre, observational study of EBC patients ≥70 years old was conducted in 2013-2018 at 56 UK hospitals. Demographics, patient, tumour characteristics, treatments and adverse events were recorded. Quality of life was assessed using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaires (EORTC-QLQ) C30, BR23 and ELD 15 plus the Euroqol-5D (eq-5d) over 24 months and analysed at each time point using baseline adjusted linear regression analysis and propensity score-matching. RESULTS: Three thousand and four hundred sixteen patients were enrolled in the study; 1520 patients undergoing surgery and who had high-risk EBC were included in this analysis. 376/1520 (24.7%) received chemotherapy. At 6 months, chemotherapy had a significant negative impact in several EORTC-QLQ-C30 domains, including global health score, physical, role, social functioning, cognition, fatigue, nausea/vomiting, dyspnoea, appetite loss, diarrhoea and constipation. Similar trends were documented on other scales (EORTC-QLQ-BR23, EORTC-QLQ-ELD15 and EQ-5D-5L). Its impact was no longer significant at 18-24 months in unmatched and matched cohorts. CONCLUSIONS: The negative impact of chemotherapy on quality-of-life is clinically and statistically significant at 6 months but resolves by 18 months, which is crucial to inform decision-making for older patients contemplating chemotherapy. TRIAL REGISTRATION NUMBER ISRCTN: 46099296.

Isotoxic Intensity Modulated Radiation Therapy in Stage III Non-Small Cell Lung Cancer: A Feasibility Study.

PURPOSE: Not all patients with stage III non-small cell lung cancer (NSCLC) are suitable for concurrent chemoradiation therapy (CRT). Local failure rate is high for sequential concurrent CRT. As such, there is a rationale for treatment intensification. METHODS AND MATERIALS: Isotoxic intensity modulated radiation therapy (IMRT) is a multicenter feasibility study that combines different intensification strategies including hyperfractionation, acceleration, and dose escalation facilitated by IMRT. Patients with unresectable stage III NSCLC, Eastern Cooperative Oncology Group (ECOG) performance status (PS) of 0 to 2, and unsuitable for concurrent CRT were recruited. A minimum of 2 cycles of platinum-based chemotherapy was compulsory before starting radiation therapy (RT). Radiation dose was increased until a maximum dose of 79.2 Gy was reached or 1 or more of the organs at risk met predefined constraints. RT was delivered in 1.8-Gy fractions twice daily, and an RT quality assurance program was implemented. The primary objective was the delivery of isotoxic IMRT to a dose >60 Gy equivalent dose in 2-Gy fractions (EQD2 assuming an α/ß ratio of 10 Gy for acute reacting tissues). RESULTS: Thirty-seven patients were recruited from 7 UK centers. Median age was 69.9 years (range, 46-86 years). The male-to-female ratio was 17:18. ECOG PS was 0 to 5 in 14.2% of patients; PS was 1 to 27 in 77.1% of patients; PS was 2 to 3 in 8.6% of patients. Stage IIIA:IIIB ratio was 22:13 (62.9%:37.1%). Of 37 patients, 2 (5.4%) failed to achieve EQD2 > 60 Gy. Median prescribed tumor dose was 77.4 Gy (range, 61.2-79.2 Gy). A maximum dose of 79.2Gy was achieved in 14 patients (37.8%). Grade 3 esophagitis was reported in 2 patients, and no patients developed grade 3 to 4 pneumonitis. There were 3 grade 5 events: acute radiation pneumonitis, bronchopulmonary hemorrhage, and acute lung infection. Median follow-up at time of analysis was 25.4 months (range, 8.0-44.2) months for 11 of 35 survivors. The median survival was 18.1 months (95% confidence interval [CI], 13.9-30.6), 2-year overall survival was 33.6% (95% CI, 17.9-50.1), and progression-free survival was 23.9% (95% CI, 11.3-39.1). CONCLUSIONS: Isotoxic IMRT is a well-tolerated and feasible approach to treatment intensification.

Radical accelerated radiotherapy for non-small cell lung cancer (NSCLC): A 5-year retrospective review of two dose fractionation schedules.

BACKGROUND AND PURPOSE: Numerous fractionation regimes are used for inoperable NSCLC patients not suitable for stereotactic ablative radiotherapy. Continuous hyperfractionated accelerated radiotherapy (CHART, 54 Gy, 36 fractions over 12 days) and hypofractionated accelerated radiotherapy (55 Gy, 20 fractions over 4 weeks) are recommended UK schedules. In this single-centre retrospective analysis, we compare both fractionation schemes for patients treated at our institution from 2010 to 15. MATERIALS AND METHODS: Clinical demographic, tumour and survival data were collected alongside radiotherapy dosimetric data from the Varian Eclipse Scripting application programming interface. Differences were assessed using independent samples t-tests. Multivariate survival analysis was performed using Cox regression. RESULTS: We identified 563 eligible patients; 43% received CHART and 57% hypofractionated radiotherapy. Median age was 71 years, 56% were male, 95% PET staged with 53% WHO performance status 0-1. 30%, 14%, 50% and 6% were stage I, II, III and IV, respectively. 38% of patients underwent induction chemotherapy. 99% completed their prescribed radiotherapy treatment. Overall response rate was 50% with a 6.5% 90-day mortality rate. Median disease-free survival was 19 months, 50% recurred locally. Median overall survival was 22.5 months with 48% alive at 2 years. Multivariate analysis identified histology, stage, performance status, chemotherapy and radiotherapy response as independent predictors of survival; no significant differences between radiotherapy regimes were observed. CONCLUSION: In our centre, CHART and hypofractionated accelerated radiotherapy produce similar outcomes. Dose escalation studies are in progress to develop these schedules to match outcomes reported in concurrent chemo-radiation studies.

The clinical role of VeriStrat testing in patients with advanced non-small cell lung cancer considered unfit for first-line platinum-based chemotherapy.

PURPOSE: We previously demonstrated that the median survival of patients with poor prognosis non-small cell lung cancer (NSCLC) considered unfit for first-line platinum chemotherapy was <4 months. We evaluated whether VeriStrat could be used as a prognostic or predictive biomarker in this population. EXPERIMENTAL DESIGN: We conducted a randomised double-blind trial among patients with untreated advanced NSCLC considered unfit for platinum chemotherapy because of poor performance status (PS) or multiple comorbidities. All patients received active supportive care (ASC) and were treated with either oral erlotinib or placebo daily. Five hundred twenty-seven patients had plasma samples for VeriStrat classification: good (VeriStrat Good [VSG]) or poor (VeriStrat Poor [VSP]). Main end-point was overall survival. RESULTS: Fifty-five percent patients had VSG, and 83% had Eastern Cooperative Oncology Group (ECOG) 2-3 at baseline. VeriStrat was strongly associated with survival. Among patients managed with ASC only, the adjusted hazard ratio (HR) was 0.54 (p < 0.001) for VSG versus VSP. The association was consistent across patient factors: HR = 0.25 (p = 0.004) and HR = 0.56 (p < 0.001) for ECOG 0-1 and 2-3, respectively, HR = 0.49 (0070 < 0.001) for age≥75 years and HR = 0.59 (p = 0.007) for stage IV. Several ECOG 2-3 patients had long survival: 2-year survival was 8% for VSG patients who had ASC, compared with 0% for VSP. VeriStrat status did not predict benefit from erlotinib treatment because the HRs for erlotinib versus placebo were similar between VSG and VSP patients. CONCLUSIONS: VeriStrat was not a predictive marker for survival when considering first-line erlotinib for patients with NSCLC who had poor PS and were not recommended for platinum doublet therapies. However, VeriStrat was an independent prognostic marker of survival. It represents an objective measurement that could be considered alongside other patient factors to provide a more refined assessment of prognosis for this particular patient group. VSG patients could be selected for treatment trials because of better survival, while VSP patients can continue to be treated conservatively or offered trials of less toxic agents. TRIAL REGISTRATION ISRCTN NUMBER: ISRCTN02370070.