A process to reanalyze clinical DNA sequencing data for biomarker matching in the Lung-MAP Master Protocol.

For cancer clinical trials that require central confirmation of tumor genomic profiling, exhaustion of tissue from standard-of-care testing may prevent enrollment. For Lung-MAP, a master protocol that requires results from a defined centralized clinical trial assay to assign patients to a therapeutic substudy, we developed a process to repurpose existing commercial vendor raw genomic data for eligibility: genomic data reanalysis (GDR). Molecular results for substudy assignment were successfully generated for 369 of the first 374 patients (98.7%) using GDR for Lung-MAP, with a median time from request to result of 9 days. During the same period, 691 of 791 (87.4%) tissue samples received successfully yielded results, in a median of 14 days beyond sample acquisition. GDR is a scalable bioinformatic pipeline that expedites reanalysis of existing data for clinical trials in which validated integral biomarker testing is required for participation.

Edge roughness quantifies impact of physician variation on training and performance of deep learning auto-segmentation models for the esophagus.

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, Ntotal = 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 (MDER-Q1, Ntrain = 62) achieved significantly higher Dice (Ntest = 270) than the model trained with the highest-quantile ones (MDER-Q4, Ntrain = 62) (MDER-Q1: 67.8 ± 14.8%, MDER-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.

Surgical management of non-small cell lung cancer with limited metastatic disease involving only the brain.

OBJECTIVE: The optimal primary site treatment modality for non-small cell lung cancer with brain oligometastases is not well established. This study sought to evaluate the long-term survival of patients with non-small cell lung cancer with isolated brain metastases undergoing multimodal therapy with or without thoracic surgery. METHODS: Patients with cT1-3, N0-1, M1b-c non-small cell lung cancer with synchronous limited metastatic disease involving only the brain treated with brain stereotactic radiosurgery or neurosurgical resection in the National Cancer Database (2010-2017) were included. Long-term overall survival of patients who underwent multimodal therapy including thoracic surgery ("Thoracic Surgery") versus systemic therapy with or without radiation to the lung ("No Thoracic Surgery") was evaluated using Kaplan-Meier analysis, Cox proportional hazards modeling, and propensity score matching. RESULTS: Of the 1240 patients with non-small cell lung cancer with brain-only metastases who received brain stereotactic radiosurgery or neurosurgery and met study inclusion criteria, 270 (21.8%) received primary site resection. The Thoracic Surgery group had improved overall survival compared with the No Thoracic Surgery group in Kaplan-Meier analysis (P < .001) and after multivariable-adjusted Cox proportional hazards modeling (P < .001). In a propensity score-matched analysis of 175 patients each in the Thoracic Surgery and No Thoracic Surgery groups, matching on 13 common prognostic variables, thoracic surgery was associated with better survival (P = .012). CONCLUSIONS: In this national analysis, patients with cT1-3, N0-1, M1b-c non-small cell lung cancer with isolated limited brain metastases had better overall survival after multimodal therapy including thoracic surgery compared with systemic therapy without surgery. Multimodal thoracic treatment including surgery can be considered for carefully selected patients with non-small cell lung cancer and limited brain metastases.

Widening the therapeutic window for central and ultra-central thoracic oligometastatic disease with stereotactic MR-guided adaptive radiation therapy (SMART).

BACKGROUND/PURPOSE: Central/ultra-central thoracic tumors are challenging to treat with stereotactic radiotherapy due potential high-grade toxicity. Stereotactic MR-guided adaptive radiation therapy (SMART) may improve the therapeutic window through motion control with breath-hold gating and real-time MR-imaging as well as the option for daily online adaptive replanning to account for changes in target and/or organ-at-risk (OAR) location. MATERIALS/METHODS: 26 central (19 ultra-central) thoracic oligoprogressive/oligometastatic tumors treated with isotoxic (OAR constraints-driven) 5-fraction SMART (median 50 Gy, range 35-60) between 10/2019-10/2022 were reviewed. Central tumor was defined as tumor within or touching 2 cm around proximal tracheobronchial tree (PBT) or adjacent to mediastinal/pericardial pleura. Ultra-central was defined as tumor abutting the PBT, esophagus, or great vessel. Hard OAR constraints observed were ≤ 0.03 cc for PBT V40, great vessel V52.5, and esophagus V35. Local failure was defined as tumor progression/recurrence within the planning target volume. RESULTS: Tumor abutted the PBT in 31 %, esophagus in 31 %, great vessel in 65 %, and heart in 42 % of cases. 96 % of fractions were treated with reoptimized plan, necessary to meet OAR constraints (80 %) and/or target coverage (20 %). Median follow-up was 19 months (27 months among surviving patients). Local control (LC) was 96 % at 1-year and 90 % at 2-years (total 2/26 local failure). 23 % had G2 acute toxicities (esophagitis, dysphagia, anorexia, nausea) and one (4 %) had G3 acute radiation dermatitis. There were no G4-5 acute toxicities. There was no symptomatic pneumonitis and no G2 + late toxicities. CONCLUSION: Isotoxic 5-fraction SMART resulted in high rates of LC and minimal toxicity. This approach may widen the therapeutic window for high-risk oligoprogressive/oligometastatic thoracic tumors.

Pneumonitis in Patients Receiving Thoracic Radiotherapy and Osimertinib: A Multi-Institutional Study.

Introduction: Thoracic radiotherapy (TRT) is increasingly used in patients receiving osimertinib for advanced NSCLC, and the risk of pneumonitis is not established. We investigated the risk of pneumonitis and potential risk factors in this population. Methods: We performed a multi-institutional retrospective analysis of patients under active treatment with osimertinib who received TRT between April 2016 and July 2022 at two institutions. Clinical characteristics, including whether osimertinib was held during TRT and pneumonitis incidence and grade (Common Terminology Criteria for Adverse Events version 5.0) were documented. Logistic regression analysis was performed to identify risk factors associated with grade 2 or higher (2+) pneumonitis. Results: The median follow-up was 10.2 months (range: 1.9-53.2). Of 102 patients, 14 (13.7%) developed grade 2+ pneumonitis, with a median time to pneumonitis of 3.2 months (range: 1.5-6.3). Pneumonitis risk was not significantly increased in patients who continued osimertinib during TRT compared with patients who held osimertinib during TRT (9.1% versus 15.0%, p = 0.729). Three patients (2.9%) had grade 3 pneumonitis, none had grade 4, and two patients had grade 5 events (2.0%, diagnosed 3.2 mo and 4.4 mo post-TRT). Mean lung dose was associated with the development of grade 2+ pneumonitis in multivariate analysis (OR = 1.19, p = 0.021). Conclusions: Although the overall rate of pneumonitis in patients receiving TRT and osimertinib was relatively low, there was a small risk of severe toxicity. The mean lung dose was associated with an increased risk of developing pneumonitis. These findings inform decision-making for patients and providers.

Serum miRNA-based signature indicates radiation exposure and dose in humans: A multicenter diagnostic biomarker study.

PURPOSE: Mouse and non-human primate models showed that serum miRNAs may be used to predict the biological impact of radiation doses. We hypothesized that these results can be translated to humans treated with total body irradiation (TBI), and that miRNAs may be used as clinically feasible biodosimeters. METHODS: To test this hypothesis, serial serum samples were obtained from 25 patients (pediatric and adults) who underwent allogeneic stem-cell transplantation and profiled for miRNA expression using next-generation sequencing. miRNAs with diagnostic potential were quantified with qPCR and used to build logistic regression models with lasso penalty to reduce overfitting, identifying samples drawn from patients who underwent total body irradiation to a potentially lethal dose. RESULTS: Differential expression results were consistent with previous studies in mice and non-human primates. miRNAs with detectable expression in this and two prior animal sets allowed for distinction of the irradiated from non-irradiated samples in mice, macaques and humans, validating the miRNAs as radiation-responsive through evolutionarily conserved transcriptional regulation mechanisms. Finally, we created a model based on the expression of miR-150-5p, miR-30b-5p and miR-320c normalized to two references and adjusted for patient age with an AUC of 0.9 (95%CI:0.83-0.97) for identifying samples drawn after irradiation; a separate model differentiating between high and low radiation dose achieved AUC of 0.85 (95%CI: 0.74-0.96). CONCLUSIONS: We conclude that serum miRNAs reflect radiation exposure and dose for humans undergoing TBI and may be used as functional biodosimeters for precise identification of people exposed to clinically significant radiation doses.

Radiation-induced circulating microRNAs linked to echocardiography parameters after radiotherapy.

Introduction: Patients treated with radiotherapy to the chest region are at risk of cardiac sequelae, however, identification of those with greatest risk of complications remains difficult. Here, we sought to determine whether short-term changes in circulating miRNA expression are related to measures of cardiac dysfunction in follow-up. Materials and methods: Two parallel patient cohorts were enrolled and followed up for 3 years after completion of RT to treat left-sided breast cancer. In the primary group (N=28) we used a a panel of 752 miRNAs to identify miRNAs associated with radiation and cardiac indices at follow up. In the second, independent cohort (N=56) we validated those candidate miRNAs with a targeted qPCR panel. In both cohorts. serum samples were collected before RT, 24h after the last dose and 1 month after RT; cardiac echocardiography was performed 2.5-3 year after RT. Results: Seven miRNAs in the primary group showed marked changes in serum miRNAs immediately after RT compared to baseline and associations with cardiopulmonary dose-volume histogram metrics. Among those miRNAs: miR-15b-5p, miR-22-3p, miR-424-5p and miR-451a were confirmed to show significant decrease of expression 24 hours post-RT in the validation cohort. Moreover, miR-29c, miR-451 and miR-424 were correlated with the end-diastolic diameter of the left ventricle, which was also confirmed in multivariable analysis adjusting for RT-associated factors. Conclusion: We identified a subset of circulating miRNAs predictive for cardiac function impairment in patients treated for left-sided breast cancer, although longer clinical observation could determine if these can be used to predict major clinical endpoints.

Fate and Efficacy of Engineered Allogeneic Stem Cells Targeting Cell Death and Proliferation Pathways in Primary and Brain Metastatic Lung Cancer.

Primary and metastatic lung cancer is a leading cause of cancer-related death and novel therapies are urgently needed. Epidermal growth factor receptor (EGFR) and death receptor (DR) 4/5 are both highly expressed in primary and metastatic non-small cell lung cancer (NSCLC); however, targeting these receptors individually has demonstrated limited therapeutic benefit in patients. In this study, we created and characterized diagnostic and therapeutic stem cells (SC), expressing EGFR-targeted nanobody (EV) fused to the extracellular domain of death DR4/5 ligand (DRL) (EVDRL) that simultaneously targets EGFR and DR4/5, in primary and metastatic NSCLC tumor models. We show that EVDRL targets both cell surface receptors, and induces caspase-mediated apoptosis in a broad spectrum of NSCLC cell lines. Utilizing real-time dual imaging and correlative immunohistochemistry, we show that allogeneic SCs home to tumors and when engineered to express EVDRL, alleviate tumor burden and significantly increase survival in primary and brain metastatic NSCLC. This study reports mechanistic insights into simultaneous targeting of EGFR- and DR4/5 in lung tumors and presents a promising approach for translation into the clinical setting.

Smart Radiotherapy Biomaterials for Image-Guided In Situ Cancer Vaccination.

Recent studies have highlighted the potential of smart radiotherapy biomaterials (SRBs) for combining radiotherapy and immunotherapy. These SRBs include smart fiducial markers and smart nanoparticles made with high atomic number materials that can provide requisite image contrast during radiotherapy, increase tumor immunogenicity, and provide sustained local delivery of immunotherapy. Here, we review the state-of-the-art in this area of research, the challenges and opportunities, with a focus on in situ vaccination to expand the role of radiotherapy in the treatment of both local and metastatic disease. A roadmap for clinical translation is outlined with a focus on specific cancers where such an approach is readily translatable or will have the highest impact. The potential of FLASH radiotherapy to synergize with SRBs is discussed including prospects for using SRBs in place of currently used inert radiotherapy biomaterials such as fiducial markers, or spacers. While the bulk of this review focuses on the last decade, in some cases, relevant foundational work extends as far back as the last two and half decades.

Association of Patient Experience of Care and Radiation Therapy Initiation Among Women With Early-Stage Breast Cancer.

PURPOSE: For women diagnosed with early-stage breast cancer, lumpectomy followed by radiation therapy (RT) has been a guideline-recommended treatment. However, lumpectomy followed by hormonal therapy is also an approved treatment for certain women. It is unclear what patient-driven factors are related to decisions to receive RT. This study examined relationships between patient-reported experience of care, an important dimension of health care quality, and receipt of RT after lumpectomy. METHODS AND MATERIALS: We used National Cancer Institute Surveillance, Epidemiology, and End Results data linked to the CMS Medicare Consumer Assessment of Healthcare Providers and Systems patient surveys (SEER-CAHPS) to examine experiences of care among women diagnosed with local/regional stage breast cancer 2000 to 2017 who received lumpectomy, were enrolled in fee-for-service Medicare, completed a CAHPS survey ≤18 months after diagnosis, and survived for this study period. Experience of care was assessed by patient-provided scores for physicians, doctor communication, care coordination, and other aspects of care. Multivariable logistic regression models assessed associations of receipt of external beam RT with care experience and patient sociodemographic and clinical characteristics. RESULTS: The study population included 824 women; 655 (79%) received RT. Women with higher experience of care scores for their personal doctor were significantly more likely to have received any RT (odds ratio [OR], 1.18; P = .033). Nonsignificant trends were observed for associations of increased RT with higher CAHPS measures of doctor communications (OR, 1.15; P = .055) and care coordination (OR, 1.24; P = .051). In contrast, women reporting higher scores for Part D prescription drug plans were significantly less likely to have received RT (OR, 0.78; P = .030). CONCLUSIONS: Patient experience of care was significantly associated with receipt of RT after lumpectomy among women with breast cancer. Health care organization leaders may want to consider incorporating experience of care into quality improvement initiatives and other activities that aim to improve patient decision-making, care, and outcomes.

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes.

PURPOSE: There is an unmet need to empirically explore and understand drivers of cancer disparities, particularly social determinants of health. We explored natural language processing methods to automatically and empirically extract clinical documentation of social contexts and needs that may underlie disparities. METHODS: This was a retrospective analysis of 230,325 clinical notes from 5,285 patients treated with radiotherapy from 2007 to 2019. We compared linguistic features among White versus non-White, low-income insurance versus other insurance, and male versus female patients' notes. Log odds ratios with an informative Dirichlet prior were calculated to compare words over-represented in each group. A variational autoencoder topic model was applied, and topic probability was compared between groups. The presence of machine-learnable bias was explored by developing statistical and neural demographic group classifiers. RESULTS: Terms associated with varied social contexts and needs were identified for all demographic group comparisons. For example, notes of non-White and low-income insurance patients were over-represented with terms associated with housing and transportation, whereas notes of White and other insurance patients were over-represented with terms related to physical activity. Topic models identified a social history topic, and topic probability varied significantly between the demographic group comparisons. Classification models performed poorly at classifying notes of non-White and low-income insurance patients (F1 of 0.30 and 0.23, respectively). CONCLUSION: Exploration of linguistic differences in clinical notes between patients of different race/ethnicity, insurance status, and sex identified social contexts and needs in patients with cancer and revealed high-level differences in notes. Future work is needed to validate whether these findings may play a role in cancer disparities.

Lobar or Sublobar Resection for Peripheral Stage IA Non-Small-Cell Lung Cancer.

BACKGROUND: The increased detection of small-sized peripheral non-small-cell lung cancer (NSCLC) has renewed interest in sublobar resection in lieu of lobectomy. METHODS: We conducted a multicenter, noninferiority, phase 3 trial in which patients with NSCLC clinically staged as T1aN0 (tumor size, ≤2 cm) were randomly assigned to undergo sublobar resection or lobar resection after intraoperative confirmation of node-negative disease. The primary end point was disease-free survival, defined as the time between randomization and disease recurrence or death from any cause. Secondary end points were overall survival, locoregional and systemic recurrence, and pulmonary functions. RESULTS: From June 2007 through March 2017, a total of 697 patients were assigned to undergo sublobar resection (340 patients) or lobar resection (357 patients). After a median follow-up of 7 years, sublobar resection was noninferior to lobar resection for disease-free survival (hazard ratio for disease recurrence or death, 1.01; 90% confidence interval [CI], 0.83 to 1.24). In addition, overall survival after sublobar resection was similar to that after lobar resection (hazard ratio for death, 0.95; 95% CI, 0.72 to 1.26). The 5-year disease-free survival was 63.6% (95% CI, 57.9 to 68.8) after sublobar resection and 64.1% (95% CI, 58.5 to 69.0) after lobar resection. The 5-year overall survival was 80.3% (95% CI, 75.5 to 84.3) after sublobar resection and 78.9% (95% CI, 74.1 to 82.9) after lobar resection. No substantial difference was seen between the two groups in the incidence of locoregional or distant recurrence. At 6 months postoperatively, a between-group difference of 2 percentage points was measured in the median percentage of predicted forced expiratory volume in 1 second, favoring the sublobar-resection group. CONCLUSIONS: In patients with peripheral NSCLC with a tumor size of 2 cm or less and pathologically confirmed node-negative disease in the hilar and mediastinal lymph nodes, sublobar resection was not inferior to lobectomy with respect to disease-free survival. Overall survival was similar with the two procedures. (Funded by the National Cancer Institute and others; CALGB 140503 ClinicalTrials.gov number, NCT00499330.).

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study.

BACKGROUND: Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain confined to in silico validation in small internal cohorts, without external validation or data on real-world clinical utility. We developed a strategy for the clinical validation of deep learning models for segmenting primary non-small-cell lung cancer (NSCLC) tumours and involved lymph nodes in CT images, which is a time-intensive step in radiation treatment planning, with large variability among experts. METHODS: In this observational study, CT images and segmentations were collected from eight internal and external sources from the USA, the Netherlands, Canada, and China, with patients from the Maastro and Harvard-RT1 datasets used for model discovery (segmented by a single expert). Validation consisted of interobserver and intraobserver benchmarking, primary validation, functional validation, and end-user testing on the following datasets: multi-delineation, Harvard-RT1, Harvard-RT2, RTOG-0617, NSCLC-radiogenomics, Lung-PET-CT-Dx, RIDER, and thorax phantom. Primary validation consisted of stepwise testing on increasingly external datasets using measures of overlap including volumetric dice (VD) and surface dice (SD). Functional validation explored dosimetric effect, model failure modes, test-retest stability, and accuracy. End-user testing with eight experts assessed automated segmentations in a simulated clinical setting. FINDINGS: We included 2208 patients imaged between 2001 and 2015, with 787 patients used for model discovery and 1421 for model validation, including 28 patients for end-user testing. Models showed an improvement over the interobserver benchmark (multi-delineation dataset; VD 0·91 [IQR 0·83-0·92], p=0·0062; SD 0·86 [0·71-0·91], p=0·0005), and were within the intraobserver benchmark. For primary validation, AI performance on internal Harvard-RT1 data (segmented by the same expert who segmented the discovery data) was VD 0·83 (IQR 0·76-0·88) and SD 0·79 (0·68-0·88), within the interobserver benchmark. Performance on internal Harvard-RT2 data segmented by other experts was VD 0·70 (0·56-0·80) and SD 0·50 (0·34-0·71). Performance on RTOG-0617 clinical trial data was VD 0·71 (0·60-0·81) and SD 0·47 (0·35-0·59), with similar results on diagnostic radiology datasets NSCLC-radiogenomics and Lung-PET-CT-Dx. Despite these geometric overlap results, models yielded target volumes with equivalent radiation dose coverage to those of experts. We also found non-significant differences between de novo expert and AI-assisted segmentations. AI assistance led to a 65% reduction in segmentation time (5·4 min; p<0·0001) and a 32% reduction in interobserver variability (SD; p=0·013). INTERPRETATION: We present a clinical validation strategy for AI models. We found that in silico geometric segmentation metrics might not correlate with clinical utility of the models. Experts' segmentation style and preference might affect model performance. FUNDING: US National Institutes of Health and EU European Research Council.

Targeting DNA Repair with Combined Inhibition of NHEJ and MMEJ Induces Synthetic Lethality in TP53-Mutant Cancers.

DNA repair pathway inhibitors are a new class of anticancer drugs that are advancing in clinical trials. Peposertib is an inhibitor of DNA-dependent protein kinase (DNA-PK), which is a key driver of nonhomologous end-joining (NHEJ). To identify regulators of response to peposertib, we performed a genome-wide CRISPR knockout screen and found that loss of POLQ (polymerase theta, POLθ) and other genes in the microhomology-mediated end-joining (MMEJ) pathway are key predictors of sensitivity to DNA-PK inhibition. Simultaneous disruption of two DNA repair pathways via combined treatment with peposertib plus a POLθ inhibitor novobiocin exhibited synergistic synthetic lethality resulting from accumulation of toxic levels of DNA double-strand break end resection. TP53-mutant tumor cells were resistant to peposertib but maintained elevated expression of POLQ and increased sensitivity to novobiocin. Consequently, the combination of peposertib plus novobiocin resulted in synthetic lethality in TP53-deficient tumor cell lines, organoid cultures, and patient-derived xenograft models. Thus, the combination of a targeted DNA-PK/NHEJ inhibitor with a targeted POLθ/MMEJ inhibitor may provide a rational treatment strategy for TP53-mutant solid tumors. SIGNIFICANCE: Combined inhibition of NHEJ and MMEJ using two nontoxic, targeted DNA repair inhibitors can effectively induce toxic DNA damage to treat TP53-deficient cancers.

Alliance A082002 -a randomized phase II/III trial of modern immunotherapy-based systemic therapy with or without SBRT for PD-L1-negative, advanced non-small cell lung cancer.

INTRODUCTION: Treatment of advanced stage non-small cell lung cancer (NSCLC) has changed dramatically due to immunotherapy. However, patients without Programmed Death-Ligand 1 (PD-L1) protein expression often benefit less from immunotherapy. This trial is designed to test if stereotactic body radiation therapy (SBRT) to a single tumor site can significantly enhance the outcome of patients with advanced stage PD-L1(-) NSCLC when added to systemic therapy including immunotherapy. MATERIALS AND METHODS: Alliance A082002 is based on subgroup analysis from the randomized phase II PEMBRO-RT trial., PEMBRO-RT compared pembrolizumab alone or with SBRT and revealed improved progression-free and overall survival (PFS and OS, respectively) in PD-L1(-) patients when adding SBRT (8 Gy x 3 fractions). In A082002, patients without PD-L1 expression will be randomized to SBRT (8 Gy x3) plus systemic therapy vs. systemic therapy alone. The primary endpoint of the phase II portion of the trial is PFS and will require 100 patients. The primary endpoint of the phase III portion of the trial is OS and will require an additional 284 patients. This trial will clarify whether adding SBRT to systemic therapy can improve PFS and OS in a larger multi-institutional cohort. Several systemic treatment options are allowed including either immunotherapy alone or chemo-immunotherapy. CONCLUSIONS: This phase II/III Alliance trial A082002 will test whether the addition of SBRT to a single tumor site will enhance the anti-tumor activity of systemic immunotherapy or chemo-immunotherapy in patients with stage IV PD-L1(-) NSCLC. It is now open in the National Clinical Trials Network (NCTN).

Rates of Guideline-Concordant Surgery and Adjuvant Chemotherapy Among Patients With Early-Stage Lung Cancer in the US ALCHEMIST Study (Alliance A151216).

Importance: Standard treatment for resectable non-small cell lung cancer (NSCLC) includes anatomic resection with adequate lymph node dissection and adjuvant chemotherapy for appropriate patients. Historically, many patients with early-stage NSCLC have not received such treatment, which may affect the interpretation of the results of adjuvant therapy trials. Objective: To ascertain patterns of guideline-concordant treatment among patients enrolled in a US-wide screening protocol for adjuvant treatment trials for resected NSCLC. Design, Setting, and Participants: This retrospective cohort study included 2833 patients with stage IB to IIIA NSCLC (per American Joint Committee on Cancer 7th edition criteria) who enrolled in the Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial (ALCHEMIST) screening study (Alliance for Clinical Trials in Oncology A151216) from August 18, 2014, to April 1, 2019, and who did not enroll in a therapeutic adjuvant clinical trial; patients had tumors of at least 4 cm and/or with positive lymph nodes. Statistical analysis was conducted from June 1, 2020, through October 1, 2021. Exposures: Care patterns were ascertained overall and by sociodemographic and clinical factors, including age, sex, race and ethnicity, educational level, marital status, geography, histologic characteristics, stage, genomic variant status, smoking history, and comorbidities. Main Outcomes and Measures: Five outcomes are reported: whether patients (1) had anatomic surgical resection, (2) had adequate lymph node dissection (≥1 N1 nodal station plus ≥3 N2 nodal stations), (3) received any adjuvant chemotherapy, (4) received any cisplatin-based adjuvant chemotherapy, and (5) received at least 4 cycles of adjuvant chemotherapy. Results: Of the 2833 patients (1505 women [53%]; mean [SD] age, 66.5 [9.2] years) included in this analysis, 2697 (95%) had anatomic surgical resection, 1513 (53%) had adequate lymph node dissection, 1617 (57%) received any adjuvant chemotherapy, 1237 (44%) received at least 4 cycles of adjuvant platinum-based chemotherapy, and 965 (34%) received any cisplatin-based adjuvant chemotherapy. Rates were similar across race and ethnicity. Conclusions and Relevance: This cohort study found that among participants in a screening protocol for adjuvant clinical trials for resected early-stage NSCLC, just 53% underwent adequate lymph node dissection, and 57% received adjuvant chemotherapy, despite indications for such treatment. These results may affect the interpretation of adjuvant trials. Efforts are needed to optimize the use of proven therapies for early-stage NSCLC. Trial Registration: ClinicalTrials.gov Identifier: NCT02194738.

The clinician's guide to radiotherapy complications.

Radiotherapy is one of the oldest cancer treatment modalities, used for over 100 years. As its efficacy has been steadily increasing due to the introduction of novel treatment methods, adverse events (AEs) still pose a major obstacle limiting the therapeutic benefits in some patients and negatively impacting treatment outcomes. In light of the technological progress, the focus has been shifted from improving the efficacy to safeguarding patients from the most severe AEs through improvements of safety and accuracy of radiation delivery. Currently, with radiation therapy being an effective treatment associated with frequent therapeutic success and leading to increased and prolonged survival, the problem of treatment­related AEs is growing as there are numerous survivors whose health and quality of life may be adversely affected. Due to the limited access to radiation oncologists, patients presenting with AEs are often referred to other professionals for advice, and as survivorship prolongs, the AEs may aggravate current patient comorbidities or reveal undiagnosed diseases. Thus, it is important that doctors other than oncologists be familiar with the fundamentals of radiation therapy-related AEs and their management. In this review, we present the most common and severe AEs of radiotherapy associated with damage to the nervous, respiratory, cardiovascular, gastrointestinal, and urogenital systems. We also describe the pathogenesis of these AEs, and provide guidelines for prevention, risk assessment, diagnosis, and treatment. Novel findings and future perspectives in this field are also elucidated, including examples of ongoing clinical trials aimed not only at improving treatment outcomes but also at reducing the risk of radiotherapy complications in cancer treatment survivors.

Elevated Coronary Artery Calcium Quantified by a Validated Deep Learning Model From Lung Cancer Radiotherapy Planning Scans Predicts Mortality.

PURPOSE: Coronary artery calcium (CAC) quantified on computed tomography (CT) scans is a robust predictor of atherosclerotic coronary disease; however, the feasibility and relevance of quantitating CAC from lung cancer radiotherapy planning CT scans is unknown. We used a previously validated deep learning (DL) model to assess whether CAC is a predictor of all-cause mortality and major adverse cardiac events (MACEs). METHODS: Retrospective analysis of non-contrast-enhanced radiotherapy planning CT scans from 428 patients with locally advanced lung cancer is performed. The DL-CAC algorithm was previously trained on 1,636 cardiac-gated CT scans and tested on four clinical trial cohorts. Plaques ≥ 1 cubic millimeter were measured to generate an Agatston-like DL-CAC score and grouped as DL-CAC = 0 (very low risk) and DL-CAC ≥ 1 (elevated risk). Cox and Fine and Gray regressions were adjusted for lung cancer and cardiovascular factors. RESULTS: The median follow-up was 18.1 months. The majority (61.4%) had a DL-CAC ≥ 1. There was an increased risk of all-cause mortality with DL-CAC ≥ 1 versus DL-CAC = 0 (adjusted hazard ratio, 1.51; 95% CI, 1.01 to 2.26; P = .04), with 2-year estimates of 56.2% versus 45.4%, respectively. There was a trend toward increased risk of major adverse cardiac events with DL-CAC ≥ 1 versus DL-CAC = 0 (hazard ratio, 1.80; 95% CI, 0.87 to 3.74; P = .11), with 2-year estimates of 7.3% versus 1.2%, respectively. CONCLUSION: In this proof-of-concept study, CAC was effectively measured from routinely acquired radiotherapy planning CT scans using an automated model. Elevated CAC, as predicted by the DL model, was associated with an increased risk of mortality, suggesting a potential benefit for automated cardiac risk screening before cancer therapy begins.

Dosimetric Planning Tradeoffs to Reduce Heart Dose Using Machine Learning-Guided Decision Support Software in Patients with Lung Cancer.

PURPOSE: Cardiac toxicity is a well-recognized risk after radiation therapy (RT) in patients with non-small cell lung cancer (NSCLC). However, the extent to which treatment planning optimization can reduce mean heart dose (MHD) without untoward increases in lung dose is unknown. METHODS AND MATERIALS: Retrospective analysis of RT plans from 353 consecutive patients with locally advanced NSCLC treated with intensity modulated RT (IMRT) or 3-dimensional conformal RT. Commercially available machine learning-guided clinical decision support software was used to match RT plans. A leave-one-out predictive model was used to examine lung dosimetric tradeoffs necessary to achieve a MHD reduction. RESULTS: Of all 232 patients, 91 patients (39%) had RT plan matches showing potential MHD reductions of >4 to 8 Gy without violating the upper limit of lung dose constraints (lung volume [V] receiving 20 Gy (V20 Gy) <37%, V5 Gy <70%, and mean lung dose [MLD] <20 Gy). When switching to IMRT, 75 of 103 patients (72.8%) had plan matches demonstrating improved MHD (average 2.0 Gy reduction, P < .0001) without violating lung constraints. Examining specific lung dose tradeoffs, a mean ≥3.7 Gy MHD reduction was achieved with corresponding absolute increases in lung V20 Gy, V5 Gy, and MLD of 3.3%, 5.0%, and 1.0 Gy, respectively. CONCLUSIONS: Nearly 40% of RT plans overall, and 73% when switched to IMRT, were predicted to have reductions in MHD >4 Gy with potentially clinically acceptable tradeoffs in lung dose. These observations demonstrate that decision support software for optimizing heart-lung dosimetric tradeoffs is feasible and may identify patients who might benefit most from more advanced RT technologies.

Surgical complications and clinical outcomes after dose-escalated trimodality therapy for non-small cell lung cancer in the era of intensity-modulated radiotherapy.

BACKGROUND: Trimodality therapy (TMT) with preoperative chemoradiation followed by surgical resection is used for locally-advanced non-small-cell lung cancer (LA-NSCLC). Traditionally, preoperative radiation doses ≤54 Gy are used due to concerns regarding excess morbidity, but little is known about outcomes and toxicities after TMT with intensity-modulated radiotherapy (IMRT) to higher doses. METHODS: A retrospective analysis of patients who received planned TMT with IMRT for LA-NSCLC at Brigham and Women's Hospital/Dana-Farber Cancer Institute between 2008 and 2017 was performed. Clinical and treatment characteristics, pathologic response, and surgical toxicity were assessed. Kaplan-Meier method and log-rank test was used for survival outcomes. Cox proportional-hazards regression was used for multivariable analysis. RESULTS: Forty-six patients received less than definitive doses of <60 Gy and 30 patients received definitive doses ≥60 Gy. Surgical outcomes, pathologic complete response, and postoperative toxicity did not differ significantly between the groups. With median follow-up of 3.6 years (range: 0.4-11.4), three-year locoregional recurrence-free survival (78.0% vs. 68.3%, p = 0.51) and overall survival (OS) (61.0% vs. 69.4%, p = 0.32) was not significantly different between patients receiving <60 Gy and ≥60 Gy, respectively. On multivariable analysis, older age, clinical stage, and length of hospital stay (LOS) >7 days were associated with OS. CONCLUSIONS: With IMRT, there was no increased rate of surgical complications in patients receiving higher doses of radiation. Survival outcomes or LOS did not differ based on radiation dose, but increased LOS was associated with worse OS. Larger prospective studies are needed to further examine outcomes after IMRT in patients with LA-NSCLC receiving TMT.