Positron Emission Tomography-Adjusted Intensity Modulated Radiation Therapy for Locally Advanced Non-Small Cell Lung Cancer

Selective Personalized RadioImmunotherapy for Locally Advanced Non-Small-Cell Lung Cancer Trial (SPRINT)

PURPOSE

Standard therapy for locally advanced non-small-cell lung cancer (LA-NSCLC) is concurrent chemoradiotherapy followed by adjuvant durvalumab. For biomarker-selected patients with LA-NSCLC, we hypothesized that sequential pembrolizumab and risk-adapted radiotherapy, without chemotherapy, would be well-tolerated and effective.

METHODS

Patients with stage III NSCLC or unresectable stage II NSCLC and an Eastern Cooperative Oncology Group performance status of 0-1 were eligible for this trial. Patients with a PD-L1 tumor proportion score (TPS) of ≥50% received three cycles of induction pembrolizumab (200 mg, once every 21 days), followed by a 20-fraction course of risk-adapted thoracic radiotherapy (55 Gy delivered to tumors or lymph nodes with metabolic volume exceeding 20 cc, 48 Gy delivered to smaller lesions), followed by consolidation pembrolizumab to complete a 1-year treatment course. The primary study end point was 1-year progression-free survival (PFS). Secondary end points included response rates after induction pembrolizumab, overall survival (OS), and adverse events.

RESULTS

Twenty-five patients with a PD-L1 TPS of ≥50% were enrolled. The median age was 71, most patients (88%) had stage IIIA or IIIB disease, and the median PD-L1 TPS was 75%. Two patients developed disease progression during induction pembrolizumab, and two patients discontinued pembrolizumab after one infusion because of immune-related adverse events. Using RECIST criteria, 12 patients (48%) exhibited a partial or complete response after induction pembrolizumab. Twenty-four patients (96%) received definitive thoracic radiotherapy. The 1-year PFS rate is 76%, satisfying our efficacy objective. One- and 2-year OS rates are 92% and 76%, respectively. The most common grade 3 adverse events were colitis (n = 2, 8%) and esophagitis (n = 2, 8%), and no higher-grade treatment-related adverse events have occurred.

CONCLUSION

Pembrolizumab and risk-adapted radiotherapy, without chemotherapy, are a promising treatment approach for patients with LA-NSCLC with a PD-L1 TPS of ≥50%.

Exploring causes and consequences of early discontinuation of durvalumab after chemoradiotherapy for non-small cell lung cancer

Introduction

For most locally advanced non-small cell lung cancer (LA-NSCLC) patients who complete definitive chemoradiotherapy (CRT) and do not experience disease progression, one year of adjuvant durvalumab is recommended. Here, we explore causes and consequences of early durvalumab discontinuation.

Materials and Methods

We reviewed patients treated for LA-NSCLC with definitive CRT who began adjuvant durvalumab between 2017 and 2021. Duration of durvalumab receipt and causes for early discontinuation were tabulated. Logistic regression models were utilized to evaluate predictors of early durvalumab discontinuation. Landmark analyses were performed to explore associations between early durvalumab discontinuation and clinical outcomes (progression-free survival (PFS), overall survival (OS)).

Results

Fifty-nine patients were included. Forty-one patients (69%) discontinued durvalumab early, most commonly for disease progression (n = 14) or lung toxicity (n = 10). Multivariable analysis revealed mean heart radiotherapy dose (MHD) was associated with risk of durvalumab discontinuation from progression (HR = 2.34 per 10 Gy, p = 0.052), and there was a trend suggesting an association between MHD and risk of durvalumab discontinuation from lung toxicity (HR = 2.16 per 10 Gy, p = 0.126). Median PFS duration following durvalumab initiation was 14 months, and median OS duration was 32 months. Landmark analyses that excluded patients with progression or death within one year of durvalumab initiation demonstrated improved outcomes for patients who completed one year of durvalumab (2-year PFS 100% v. 40%, p < 0.001; 2-year OS 100% v. 67%, p = 0.862). Improved outcomes were observed for patients who received MHD below the cohort median (9.3 Gy) compared to patients with higher MHD (median PFS 32 months v. 8 months, p < 0.001; 2-year OS 69% v. 44%, p = 0.088).

Conclusion

For LA-NSCLC patients treated with CRT followed by immunotherapy, extent of cardiac irradiation may be a risk factor for immunotherapy discontinuation, disease recurrence, and death.

Overcoming Barriers to Radiation Oncology Access in Low-Resource Settings in the United States

Providing high-quality radiation therapy in medically underserved, low-resource environments can be challenging in the United States. During the American Society of Radiation Oncology 2020 Annual Meeting, the American Society for Radiation Oncology Committee on Health Equity, Diversity, and Inclusion hosted 4 radiation oncologists from both academic and community practices in an educational session. Speakers discussed creative ways to overcome barriers to equitable cancer care and outcomes for their vulnerable patient populations in both rural and urban settings. Successful tactics have included applying for state-sponsored grants, lobbying hospital leadership for equipment upgrades, implementing quality improvement programs specifically targeting the needs of the patient population, studying novel hypofractionation schedules, monitoring toxicities using wearable devices, and expanding transportation options.

KEAP1/NFE2L2 Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with KEAP1/NFE2L2 mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1-mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in KEAP1 and NFE2L2 predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of KEAP1/NFE2L2-mutant tumors.This article is highlighted in the In This Issue feature, p. 1775.

Who Benefits the Most From Adjuvant Durvalumab After Chemoradiotherapy for Non-small Cell Lung Cancer? An Exploratory Analysis

PURPOSE

Adjuvant durvalumab is now recommended for most patients with locally advanced non-small cell lung cancer after concurrent chemoradiotherapy. Herein, we explore the clinical factors that may be associated with the benefit from adjuvant durvalumab.

METHODS AND MATERIALS

Patients with non-small cell lung cancer who were treated with definitive concurrent chemoradiotherapy at our institution between August 2013 and May 2019 were included in this analysis. Clinical and treatment characteristics were tested for associations with progression-free survival (PFS) in Cox models. Interaction terms were added to the PFS Cox models to explore factors that may modulate the effects of adjuvant durvalumab. PFS and overall survival (OS) rates were estimated using the Kaplan-Meier method, and comparisons between patient subgroups were performed using log rank testing.

RESULTS

A total of 105 patients met the eligibility criteria. Thirty-five patients (33%) received adjuvant durvalumab. Treatment with durvalumab was associated with significant improvement in PFS (1-year PFS: 67% vs 39%; log rank P = .006) and OS (1-year OS: 88% vs 76%; log rank P = .041). Exploratory analyses identified the neutrophil-to-lymphocyte ratio (NLR) after radiation therapy (RT) as a factor that may be associated with a benefit from durvalumab. For patients with post-RT NLR exceeding the cohort's median value of 4.3, receipt of adjuvant durvalumab was not associated with a significant PFS improvement (1-year PFS: 45% vs 36%; log rank P = .702). For patients with post-RT NLR <4.3, durvalumab receipt was associated with improved PFS (69% vs 41%; P = .009). High mean RT doses delivered to the heart and esophagus were associated with high post-RT NLR.

CONCLUSIONS

We identified low NLR after chemoradiotherapy as a factor that may be associated with a benefit from adjuvant durvalumab. Validation studies are warranted.

Sensitivity analysis of FDG PET tumor voxel cluster radiomics and dosimetry for predicting mid-chemoradiation regional response of locally advanced lung cancer

We investigated the sensitivity of regional tumor response prediction to variability in voxel clustering techniques, imaging features, and machine learning algorithms in 25 patients with locally advanced non-small cell lung cancer (LA-NSCLC) enrolled on the FLARE-RT clinical trial. Metabolic tumor volumes (MTV) from pre-chemoradiation (PETpre) and mid-chemoradiation fluorodeoxyglucose-positron emission tomography (FDG PET) images (PETmid) were subdivided into K-means or hierarchical voxel clusters by standardized uptake values (SUV) and 3D-positions. MTV cluster separability was evaluated by CH index, and morphologic changes were captured by Dice similarity and centroid Euclidean distance. PETpre conventional features included SUVmean, MTV/MTV cluster size, and mean radiation dose. PETpre radiomics consisted of 41 intensity histogram and 3D texture features (PET Oncology Radiomics Test Suite) extracted from MTV or MTV clusters. Machine learning models (multiple linear regression, support vector regression, logistic regression, support vector machines) of conventional features or radiomic features were constructed to predict PETmid response. Leave-one-out-cross-validated root-mean-squared-error (RMSE) for continuous response regression (ΔSUVmean) and area-under-receiver-operating-characteristic-curve (AUC) for binary response classification were calculated. K-means MTV 2-clusters (MTVhi, MTVlo) achieved maximum CH index separability (Friedman p < 0.001). Between PETpre and PETmid, MTV cluster pairs overlapped (Dice 0.70-0.87) and migrated 0.6-1.1 cm. PETmid ΔSUVmean response prediction was superior in MTV and MTVlo (RMSE = 0.17-0.21) compared to MTVhi (RMSE = 0.42-0.52, Friedman p < 0.001). PETmid ΔSUVmean response class prediction performance trended higher in MTVlo (AUC = 0.83-0.88) compared to MTVhi (AUC = 0.44-0.58, Friedman p = 0.052). Models were more sensitive to MTV/MTV cluster regions (Friedman p = 0.026) than feature sets/algorithms (Wilcoxon signed-rank p = 0.36). Top-ranked radiomic features included GLZSM-LZHGE (large-zone-high-SUV), GTSDM-CP (cluster-prominence), GTSDM-CS (cluster-shade) and NGTDM-CNT (contrast). Top-ranked features were consistent between MTVhi and MTVlo cluster pairs but varied between MTVhi-MTVlo clusters, reflecting distinct regional radiomic phenotypes. Variability in tumor voxel cluster response prediction can inform robust radiomic target definition for risk-adaptive chemoradiation in patients with LA-NSCLC. FLARE-RT trial: NCT02773238.

Cardiac Irradiation Predicts Activity Decline in Patients Receiving Concurrent Chemoradiation for Locally Advanced Lung Cancer

PURPOSE

Many patients with lung cancer are inactive due to their disease and underlying comorbidities, and activity levels can decline further during cancer therapy. Here we explore dosimetric predictors of activity decline in a cohort of patients who underwent continuous activity monitoring during definitive concurrent chemoradiotherapy (CRT) for locally advanced lung cancer.

METHODS AND MATERIALS

We identified patients who participated in prospective clinical trials involving the use of a commercial fitness tracker throughout the course of CRT. For each patient, we applied linear regression to log-transformed daily step counts to compute the weekly rate of activity change from 1 week before radiation therapy (RT) initiation to 2 weeks after RT completion. Clinical and dosimetric factors were tested as predictors of activity change using linear regressions.

RESULTS

Forty-six patient met the eligibility criteria. Median age was 66 years (range, 38-90). Pretreatment Eastern Cooperative Oncology Group performance status was 0, 1, and 2 for 17%, 70%, and 13%, respectively. Mean lung dose ranged from 5.0 to 23.5 Gy, mean esophagus dose from 1.1 to 39.6 Gy, and mean heart dose from 0.6 to 31.5 Gy. Median daily step count average was 5861 (interquartile range, 3540-8282) before RT and 3422 (interquartile range, 2364-5395) 2 weeks after RT completion. Rate of activity change was not significantly associated with age, performance status, or mean RT dose received by lungs or esophagus. In multivariate analysis, mean heart dose was significantly associated with rate of activity decline, with a 3.1% reduction in step count per week for every 10 Gy increase in mean heart dose (95% confidence interval: 0.5-5.7, P = .023).

CONCLUSIONS

Extent of cardiac irradiation is associated with the rate of physical activity decline during CRT for lung cancer. Our novel finding contributes to the growing body of evidence that adverse effects of cardiac irradiation may be manifested at early time points.

18F-Fluorodeoxyglucose PET in Locally Advanced Non-small Cell Lung Cancer: From Predicting Outcomes to Guiding Therapy

PET using 18-fluorodeoxyglucose (FDG) has become an important part of the work-up for non-small cell lung cancer (NSCLC). This article summarizes advancements in using FDG-PET for patients with locally advanced NSCLC treated with definitive radiation therapy (RT). This article discusses prognostication of outcome based on pretreatment or midtreatment PET metrics, using textural image features to predict treatment outcomes, and using PET to define RT target volumes and inform RT dose modifications. The role of PET is evolving and is moving toward using quantitative image information, with the overarching goal of individualizing therapy to improve outcomes for patients with NSCLC.

Predicting per-lesion local recurrence in locally advanced non-small cell lung cancer following definitive radiation therapy using pre- and mid-treatment metabolic tumor volume

BACKGROUND

We evaluated whether pre- and mid-treatment metabolic tumor volume (MTV) predicts per lesion local recurrence (LR) in patients treated with definitive radiation therapy (RT, dose≥60 Gy) for locally advanced non-small cell lung cancer (NSCLC).

METHODS

We retrospectively reviewed records of patients with stage III NSCLC treated from 2006 to 2018 with pre- and mid-RT PET-CT. We measured the MTV of treated lesions on the pre-RT (MTVpre) and mid-RT (MTVmid) PET-CT. LR was defined per lesion as recurrence within the planning target volume. Receiver operating characteristic (ROC) curves, cumulative incidence rates, and uni- and multivariable (MVA) competing risk regressions were used to evaluate the association between MTV and LR.

RESULTS

We identified 111 patients with 387 lesions (112 lung tumors and 275 lymph nodes). Median age was 68 years, 69.4% were male, 46.8% had adenocarcinoma, 39.6% had squamous cell carcinoma, and 95.5% received concurrent chemotherapy. Median follow-up was 38.7 months. 3-year overall survival was 42.3%. 3-year cumulative incidence of LR was 26.8% per patient and 11.9% per lesion. Both MTVpre and MTVmid were predictive of LR by ROC (AUC = 0.71 and 0.76, respectively) and were significantly associated with LR on MVA (P = 0.004 and P = 7.1e-5, respectively). Among lesions at lower risk of LR based on MTVpre, higher MTVmid was associated with LR (P = 0.001).

CONCLUSION

Per-lesion, larger MTVpre and MTVmid predicted for increased risk of LR. MTVmid was more highly predictive of LR than MTVpre and if validated may allow for further discrimination of high-risk lesions at mid-RT informing dose painting strategies.

Voxel Forecast for Precision Oncology: Predicting Spatially Variant and Multiscale Cancer Therapy Response on Longitudinal Quantitative Molecular Imaging

PURPOSE

Prediction of spatially variant response to cancer therapies can inform risk-adaptive management within precision oncology. We developed the "Voxel Forecast" multiscale regression framework for predicting spatially variant tumor response to chemoradiotherapy on fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) imaging.

EXPERIMENTAL DESIGN

Twenty-five patients with locally advanced non-small cell lung cancer, enrolled on the FLARE-RT phase II trial (NCT02773238), underwent FDG PET/CT imaging prior to (PETpre) and during week 3 (PETmid) of concurrent chemoradiotherapy. Voxel Forecast was designed to predict tumor voxel standardized uptake value (SUV) on PETmid from baseline patient-level and voxel-level covariates using a custom generalized least squares (GLS) algorithm. Matérn covariance matrices were fit to patient- specific empirical variograms of distance-dependent intervoxel correlation. Regression coefficients from variogram-based weights and corresponding standard errors were estimated using the jackknife technique. The framework was validated using statistical simulations of known spatially variant tumor response. Mean absolute prediction errors (MAEs) of Voxel Forecast models were calculated under leave-one-patient-out cross-validation.

RESULTS

Patient-level forecasts resulted in tumor voxel SUV MAE on PETmid of 1.5 g/mL while combined patient- and voxel-level forecasts achieved lower MAE of 1.0 g/mL (P < 0.0001). PETpre voxel SUV was the most important predictor of PETmid voxel SUV. Patients with a greater percentage of under-responding tumor voxels were classified as PETmid nonresponders (P = 0.030) with worse overall survival prognosis (P < 0.001).

CONCLUSIONS

Voxel Forecast multiscale regression provides a statistical framework to predict voxel-wise response patterns during therapy. Voxel Forecast can be extended to predict spatially variant response on multimodal quantitative imaging and may eventually guide optimized spatial-temporal dose distributions for precision cancer therapy.