Dataset Information

Predictive Role of Prior Radiotherapy and Immunotherapy-Related Adverse Effects in Advanced NSCLC Patients Receiving Anti-PD-1/L1 Therapy.

ABSTRACT: The present study evaluated the impact of prior radiotherapy (RT) on patients with advanced non-small cell lung cancer (NSCLC) receiving therapy with immune checkpoint inhibitors (ICIs) and further assessed the prognostic factors in patients receiving both RT and ICI. Patients diagnosed with NSCLC at the Catholic Medical Center and Asan Medical Center between January 2016 and October 2020 and who received immunotherapy were retrospectively reviewed. Among 240 patients, poor Eastern Cooperative Oncology Group (ECOG) score, high PD-L1 expression, and ICI-related adverse events (AE) were significantly associated with progression-free survival (PFS) (HR, 2.654; 95% CI, 1.484-4.749; p = 0.001; HR, 0.645; 95% CI, 0.449-0.926, p = 0.017; HR, 0.430; 95% CI, 0.229-0.808; p = 0.009, respectively). Among patients who received both RT and immunotherapy, poor ECOG status, squamous cell carcinoma, and ICI-related AE were significant factors associated with poor PFS (HR, 2.430; 95% CI, 1.464-4.034; p = 0.001; HR, 0.667; 95% CI, 0.455-0.978, p = 0.038; HR, 0.520; 95% CI, 0.284-0.953, p = 0.034, respectively). The present study showed that prior RT showed no significant independent association with primary outcomes in patients with advanced NSCLC receiving immunotherapy. In patients who received both RT and immunotherapy, clinical parameters, including ICI-related AEs, were independently predictive of PFS.

SUBMITTER: Lim JU

PROVIDER: S-EPMC8397093 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Predictive Role of Prior Radiotherapy and Immunotherapy-Related Adverse Effects in Advanced NSCLC Patients Receiving Anti-PD-1/L1 Therapy.

Lim Jeong Uk JU Kim Soo Han SH Kang Hye Seon HS Kim Sung Kyoung SK Kim Ju Sang JS Kim Jin Woo JW Kim Seung Joon SJ Yeo Chang Dong CD Choi Chang Min CM

Journal of clinical medicine 20210821 16

The present study evaluated the impact of prior radiotherapy (RT) on patients with advanced non-small cell lung cancer (NSCLC) receiving therapy with immune checkpoint inhibitors (ICIs) and further assessed the prognostic factors in patients receiving both RT and ICI. Patients diagnosed with NSCLC at the Catholic Medical Center and Asan Medical Center between January 2016 and October 2020 and who received immunotherapy were retrospectively reviewed. Among 240 patients, poor Eastern Cooperative O ...[more]

PMID: 34442015

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Project description:Background and aimThe objective of this retrospective, observational, noninterventional cohort study was to investigate prognostic factors of overall survival (OS) in patients with advanced non-small cell lung cancer (aNSCLC) and to develop a novel prognostic model.MethodsA total of 4049 patients with aNSCLC diagnosed between January 2011 and February 2020 who received atezolizumab, nivolumab, or pembrolizumab as second-line monotherapy were selected from a real-world deidentified database to build the cohort. Patients could not have received first-line treatment with clinical study drug(s) nor immune checkpoint inhibitors including anti-programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1), and anti-cytotoxic T-lymphocyte-associated protein 4 therapies.ResultsPatients had a median age of 69 years; 45% were female, 75% White, 70% had stage IV at initial diagnosis, and 70% had nonsquamous histology. A Cox proportional hazards model with lasso regularization was used to build a prognostic model for OS using 18 baseline demographic and clinical factors based on the real-world data cohort. The risk-increasing prognostic factors were abnormally low albumin and chloride levels, Eastern Cooperative Oncology Group performance status score ≥ 2, and abnormally high levels of alkaline phosphatase and white blood cells. The risk-decreasing prognostic factors were PD-L1 positivity, longer time from advanced diagnosis to start of first-line therapy, and higher systolic blood pressure. The performance of the model was validated using data from the OAK trial, and the c-index for the OAK trial validation cohort was 0.65 and 0.67 for the real-world data cohort.ConclusionsBased on baseline demographic and clinical factors from a real-world setting, this prognostic model was developed to discriminate the risk of death in patients with aNSCLC treated with checkpoint inhibitors as second-line monotherapy, and it performed well in the real-world data and clinical trial cohorts.

Project description:BackgroundIdentifying predictive non-invasive biomarkers of immunotherapy response is crucial to avoid premature treatment interruptions or ineffective prolongation. Our aim was to develop a non-invasive biomarker for predicting immunotherapy clinical durable benefit, based on the integration of radiomics and clinical data monitored through early anti-PD-1/PD-L1 monoclonal antibodies treatment in patients with advanced non-small cell lung cancer (NSCLC).MethodsIn this study, 264 patients with pathologically confirmed stage IV NSCLC treated with immunotherapy were retrospectively collected from two institutions. The cohort was randomly divided into a training (n = 221) and an independent test set (n = 43), ensuring the balanced availability of baseline and follow-up data for each patient. Clinical data corresponding to the start of treatment was retrieved from electronic patient records, and blood test variables after the first and third cycles of immunotherapy were also collected. Additionally, traditional radiomics and deep-radiomics features were extracted from the primary tumors of the computed tomography (CT) scans before treatment and during patient follow-up. Random Forest was used to implementing baseline and longitudinal models using clinical and radiomics data separately, and then an ensemble model was built integrating both sources of information.ResultsThe integration of longitudinal clinical and deep-radiomics data significantly improved clinical durable benefit prediction at 6 and 9 months after treatment in the independent test set, achieving an area under the receiver operating characteristic curve of 0.824 (95% CI: [0.658,0.953]) and 0.753 (95% CI: [0.549,0.931]). The Kaplan-Meier survival analysis showed that, for both endpoints, the signatures significantly stratified high- and low-risk patients (p-value< 0.05) and were significantly correlated with progression-free survival (PFS6 model: C-index 0.723, p-value = 0.004; PFS9 model: C-index 0.685, p-value = 0.030) and overall survival (PFS6 models: C-index 0.768, p-value = 0.002; PFS9 model: C-index 0.736, p-value = 0.023).ConclusionsIntegrating multidimensional and longitudinal data improved clinical durable benefit prediction to immunotherapy treatment of advanced non-small cell lung cancer patients. The selection of effective treatment and the appropriate evaluation of clinical benefit are important for better managing cancer patients with prolonged survival and preserving quality of life.

Dataset Information

Predictive Role of Prior Radiotherapy and Immunotherapy-Related Adverse Effects in Advanced NSCLC Patients Receiving Anti-PD-1/L1 Therapy.

Publications

Predictive Role of Prior Radiotherapy and Immunotherapy-Related Adverse Effects in Advanced NSCLC Patients Receiving Anti-PD-1/L1 Therapy.

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