Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model.

BACKGROUND: Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors. METHODS: The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines. RESULTS: Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202). CONCLUSION: In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance. PLAIN LANGUAGE SUMMARY: Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Real-World Efficacy and Safety of Amivantamab for EGFR-Mutant NSCLC.

INTRODUCTION: Amivantamab-vmjw (amivantamab) is a bispecific EGFR/MET antibody approved for patients with advanced NSCLC with EGFR exon 20 insertion mutations, after prior therapy. Nevertheless, the benefits and safety of amivantamab in other EGFR-mutant lung cancer, with or without osimertinib, and with concurrent radiation therapy, are less known. METHODS: We queried the MD Anderson Lung Cancer GEMINI, Fred Hutchinson Cancer Research Center, University of California Davis Comprehensive Cancer Center, and Stanford Cancer Center's database for patients with EGFR-mutant NSCLC treated with amivantamab, not on a clinical trial. The data analyzed included initial response, duration of treatment, and concomitant radiation safety in overall population and prespecified subgroups. RESULTS: A total of 61 patients received amivantamab. Median age was 65 (31-81) years old; 72.1% were female; and 77% were patients with never smoking history. Median number of prior lines of therapies was four. On the basis of tumor's EGFR mutation, 39 patients were in the classical mutation cohort, 15 patients in the exon 20 cohort, and seven patients in the atypical cohort. There were 37 patients (58.7%) who received amivantamab concomitantly with osimertinib and 25 patients (39.1%) who received concomitant radiation. Furthermore, 54 patients were assessable for response in the overall population; 19 patients (45.2%) had clinical response and disease control rate (DCR) was 64.3%. In the classical mutation cohort of the 33 assessable patients, 12 (36.4%) had clinical response and DCR was 48.5%. In the atypical mutation cohort, six of the seven patients (85.7%) had clinical response and DCR was 100%. Of the 13 assessable patients in the exon 20 cohort, five patients (35.7%) had clinical response and DCR was 64.3%. Adverse events reported with amivantamab use were similar as previously described in product labeling. No additional toxicities were noted when amivantamab was given with radiation with or without osimertinib. CONCLUSIONS: Our real-world multicenter analysis revealed that amivantamab is a potentially effective treatment option for patients with EGFR mutations outside of exon 20 insertion mutations. The combination of osimertinib with amivantamab is safe and feasible. Radiation therapy also seems safe when administered sequentially or concurrently with amivantamab.

Optimizing Lung Cancer Screening With Risk Prediction: Current Challenges and the Emerging Role of Biomarkers.

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.Lung cancer screening has been demonstrated to reduce lung cancer mortality, but its benefits must be weighed against the potential harms of unnecessary procedures, false-positive radiological findings, and overdiagnosis. Individuals at highest risk of lung cancer are more likely to maximize benefits while minimizing harm from screening. Although current lung cancer screening guidelines recommended by the US Preventive Services Task Force (USPSTF) only consider age and smoking history for screening eligibility, National Comprehensive Cancer Network and other society guidelines recommend screening on the basis of individualized risk assessment including family history, environmental exposures, and presence of chronic lung disease. Risk prediction models have been developed to integrate various risk factors into an individualized risk prediction score. Previous evidence showed that risk prediction model-based screening eligibility could improve sensitivity for detecting lung cancer cases without reducing specificity. Furthermore, recent advances in lung cancer biomarkers have enhanced the performance of risk prediction in identifying lung cancer cases relative to the USPSTF criteria. These risk prediction models can be used to guide shared decision-making discussions before proceeding with lung cancer screening. This study aims to provide a concise overview of these prediction models and the emerging role of biomarker testing in risk prediction to facilitate conversations with patients. The goal was to assist clinicians in assessing individual patient risk, leading to more informed decision making.

Phase II Randomized Trial of Carboplatin, Pemetrexed, and Bevacizumab With and Without Atezolizumab in Stage IV Nonsquamous Non-Small-Cell Lung Cancer Patients Who Harbor a Sensitizing EGFR Mutation or Have Never Smoked.

INTRODUCTION: Patients with non-small-cell lung cancer (NSCLC) who have never smoked or have tumors with mutations in EGFR generally derive minimal benefit from single-agent PD-1/PD-L1 checkpoint inhibitors. Prior data indicate that adding PD-L1 inhibition to anti-VEGF and cytotoxic chemotherapy may be a promising approach to overcoming immunotherapy resistance in these patients, however prospective validation is needed. This trial in progress (NCT03786692) is evaluating patients with stage IV NSCLC who have never smoked or who have tumors with sensitizing EGFR alterations to determine if a 4-drug combination of atezolizumab, carboplatin, pemetrexed, and bevacizumab can improve outcomes compared to carboplatin, pemetrexed and bevacizumab without atezolizumab. METHODS: This is a randomized, phase II, multicenter study evaluating carboplatin, pemetrexed, bevacizumab with and without atezolizumab in 117 patients with stage IV nonsquamous NSCLC. Randomization is 2 to 1 favoring the atezolizumab containing arm. Eligible patients include: 1) those with tumors with sensitizing EGFR alterations in exons 19 or 21 or 2) patients who have never smoked and have wild-type tumors (ie, no EGFR, ALK or ROS1 alterations). Patients are defined as having never smoked if they have smoked less than 100 cigarettes in a lifetime. Patients with EGFR-mutated tumors must have disease progression or intolerance to prior tyrosine kinase inhibitor (TKI) therapy. The primary endpoint is progression-free survival (PFS). Secondary endpoints include overall survival (OS), response rate, duration of response, and time to response. CONCLUSION: This phase II trial is accruing patients at U.S. sites through the National Comprehensive Cancer Network (NCCN). The trial opened in August 2019 and accrual is expected to be completed in the Fall of 2024.

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study.

BACKGROUND: Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holistically capture the underlying cancer biology. We aimed to investigate the application of deep learning on chest CT scans to derive an imaging signature of response to immune checkpoint inhibitors and evaluate its added value in the clinical context. METHODS: In this retrospective modelling study, 976 patients with metastatic, EGFR/ALK negative NSCLC treated with immune checkpoint inhibitors at MD Anderson and Stanford were enrolled from Jan 1, 2014, to Feb 29, 2020. We built and tested an ensemble deep learning model on pretreatment CTs (Deep-CT) to predict overall survival and progression-free survival after treatment with immune checkpoint inhibitors. We also evaluated the added predictive value of the Deep-CT model in the context of existing clinicopathological and radiological metrics. FINDINGS: Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histology, age, sex, and race. In univariate analysis, Deep-CT outperformed the conventional risk factors, including histology, smoking status, and PD-L1 expression, and remained an independent predictor after multivariate adjustment. Integrating the Deep-CT model with conventional risk factors demonstrated significantly improved prediction performance, with overall survival C-index increases from 0·70 (clinical model) to 0·75 (composite model) during testing. On the other hand, the deep learning risk scores correlated with some radiomics features, but radiomics alone could not reach the performance level of deep learning, indicating that the deep learning model effectively captured additional imaging patterns beyond known radiomics features. INTERPRETATION: This proof-of-concept study shows that automated profiling of radiographic scans through deep learning can provide orthogonal information independent of existing clinicopathological biomarkers, bringing the goal of precision immunotherapy for patients with NSCLC closer. FUNDING: National Institutes of Health, Mark Foundation Damon Runyon Foundation Physician Scientist Award, MD Anderson Strategic Initiative Development Program, MD Anderson Lung Moon Shot Program, Andrea Mugnaini, and Edward L C Smith.

Monotherapy Administration of Sorafenib in Patients With Non-Small Cell Lung Cancer (MISSION) Trial: A Phase III, Multicenter, Placebo-Controlled Trial of Sorafenib in Patients with Relapsed or Refractory Predominantly Nonsquamous Non-Small-Cell Lung Cancer after 2 or 3 Previous Treatment Regimens.

INTRODUCTION: Sorafenib monotherapy has shown benefits in phase II trials as third-/fourth-line treatment in patients with non-small-cell lung cancer (NSCLC). METHODS: The phase III, multinational, double-blind, placebo-controlled Monotherapy admInistration of Sorafenib in patientS wIth nOn-small-cell luNg cancer (MISSION) trial randomized patients with advanced relapsed/refractory NSCLC, following two or three prior treatment regimens, to sorafenib 400 mg twice a day (n = 350) or matching placebo (n = 353) plus best supportive care. The primary end point was overall survival (OS); secondary end points included progression-free survival (PFS) and time to progression. Epidermal growth factor receptor and KRAS mutation status was analyzed in archival tumor and/or circulating tumor DNA from blood samples obtained during screening. RESULTS: Median OS was similar in the sorafenib and placebo groups (8.2 versus 8.3 mo; hazard ratio [HR], 0.99; 95% confidence interval [CI], 0.84-1.17; p = 0.47). Median PFS (2.8 versus 1.4 mo; HR, 0.61; 95% CI, 0.51-0.72; p < 0.0001), and time to progression (2.9 versus 1.4 mo; HR, 0.54; 95% CI, 0.45-0.65; p < 0.0001) were significantly greater with sorafenib than with placebo. Among the 89 patients with epidermal growth factor receptor mutations, OS (13.9 versus 6.5 mo; HR, 0.48; 95% CI, 0.30-0.76; p = 0.002) and PFS (2.7 versus 1.4 mo; HR, 0.27; 95% CI, 0.16-0.46; p < 0.001) were significantly higher with sorafenib than placebo. PFS was significantly longer with sorafenib than placebo in patients with either wild-type or mutated KRAS, but OS was similar. Common drug-related adverse events were rash/desquamation, diarrhea, and fatigue, consistent with the safety profile of sorafenib. CONCLUSIONS: Third-/fourth-line sorafenib therapy did not significantly increase OS in patients with relapsed/refractory NSCLC, despite significantly increasing PFS.

A double-blind randomized discontinuation phase-II study of sorafenib (BAY 43-9006) in previously treated non-small-cell lung cancer patients: eastern cooperative oncology group study E2501.

INTRODUCTION: Sorafenib is a raf kinase and angiogenesis inhibitor with activity in multiple cancers. This phase-II study in heavily pretreated non-small-cell lung cancer (NSCLC) patients (≥ 2 prior therapies) used a randomized discontinuation design. METHODS: Patients received 400 mg of sorafenib orally twice daily for two cycles (2 months) (step 1). Responding patients on step 1 continued on sorafenib; progressing patients went off study, and patients with stable disease were randomized to placebo or sorafenib (step 2), with crossover from placebo allowed upon progression. The primary endpoint of this study was the proportion of patients having stable or responding disease 2 months after randomization. RESULTS: There were 299 patients evaluated for step 1; of these, 81 eligible patients were randomized on step 2 and received sorafenib (n = 50) or placebo (n = 31). The 2-month disease control rates after randomization were 54% and 23% for patients initially receiving sorafenib and placebo, respectively, p = 0.005. The hazard ratio for progression on step 2 was 0.51 (95% [confidence interval] CI 0.30, 0.87, p = 0.014) favoring sorafenib. A trend in favor of overall survival with sorafenib was also observed (13.7 versus 9.0 months from time of randomization), hazard ratio 0.67 (95% CI 0.40-1.11), p = 0.117. A dispensing error occurred, which resulted in the unblinding of some patients, but not before completion of the 8-week initial step 2 therapy. Toxicities were manageable and as expected. CONCLUSIONS: The results of this randomized discontinuation trial suggest that sorafenib has single-agent activity in a heavily pretreated, enriched patient population with advanced NSCLC. These results support further investigation with sorafenib as a single agent in larger, randomized studies in NSCLC.

Ramucirumab, a fully human mAb to the transmembrane signaling tyrosine kinase VEGFR-2 for the potential treatment of cancer.

Angiogenesis is essential for tumor growth, invasion and metastasis, and is mediated, at least in part, by a large family of VEGF ligands and receptors. Ramucirumab, which is being developed by ImClone Systems Inc, is a fully human mAb that binds human VEGFR-2, thus blocking VEGF binding and inhibiting angiogenesis. Proof-of-concept preclinical studies with the mouse mAb DC-101 supported this hypothesis, and ramucirumab inhibited cell proliferation in vitro, as well as tumor progression in mouse xenograft models of human cancer. Ramucirumab was well tolerated on weekly and fortnightly schedules in phase I clinical trials in patients with advanced cancers; mechanism-related DLTs were hypertension and deep venous thrombosis. Stable disease was also observed in several patients treated on either schedule, and several patients on the weekly schedule exhibited partial responses. At the time of publication, ramucirumab was undergoing assessment in phase II trials as a monotherapy in hepatocellular, renal cell and ovarian carcinomas. Ramucirumab was also in phase II trials in combination with dacarbazine in melanoma, with mitoxantrone/prednisone in prostate cancer, with carboplatin/paclitaxel in NSCLC and with oxaliplatin/folinic acid/5-fluorouracil in colorectal cancer. A phase III trial in combination with docetaxel in breast cancer was also ongoing. Pending results from these trials, ramucirumab may be a useful addition to current antiangiogenic therapies. The results are awaited with interest.