Dataset Information

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.

ABSTRACT:

Background

Development of severe immune-related adverse events (irAEs) is a major predicament to stop treatment with immune checkpoint inhibitors, even though tumor progression is suppressed. However, no effective early phase biomarker has been established to predict irAE until now.

Method

This study retrospectively used the data of four international, multi-center clinical trials to investigate the application of blood test biomarkers to predict irAEs in atezolizumab-treated advanced non-small cell lung cancer (NSCLC) patients. Seven machine learning methods were exploited to dissect the importance score of 21 blood test biomarkers after 1,000 simulations by the training cohort consisting of 80%, 70%, and 60% of the combined cohort with 1,320 eligible patients.

Results

XGBoost and LASSO exhibited the best performance in this study with relatively higher consistency between the training and test cohorts. The best area under the curve (AUC) was obtained by a 10-biomarker panel using the XGBoost method for the 8:2 training:test cohort ratio (training cohort AUC = 0.692, test cohort AUC = 0.681). This panel could be further narrowed down to a three-biomarker panel consisting of C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and thyroid-stimulating hormone (TSH) with a small median AUC difference using the XGBoost method [for the 8:2 training:test cohort ratio, training cohort AUC difference = -0.035 (p < 0.0001), and test cohort AUC difference = 0.001 (p=0.965)].

Conclusion

Blood test biomarkers currently do not have sufficient predictive power to predict irAE development in atezolizumab-treated advanced NSCLC patients. Nevertheless, biomarkers related to adaptive immunity and liver or thyroid dysfunction warrant further investigation.

SUBMITTER: Zhou JG

PROVIDER: S-EPMC9284319 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.

Zhou Jian-Guo JG Wong Ada Hang-Heng AH Wang Haitao H Tan Fangya F Chen Xiaofei X Jin Su-Han SH He Si-Si SS Shen Gang G Wang Yun-Jia YJ Frey Benjamin B Fietkau Rainer R Hecht Markus M Ma Hu H Gaipl Udo S US

Frontiers in immunology 20220630

<h4>Background</h4>Development of severe immune-related adverse events (irAEs) is a major predicament to stop treatment with immune checkpoint inhibitors, even though tumor progression is suppressed. However, no effective early phase biomarker has been established to predict irAE until now.<h4>Method</h4>This study retrospectively used the data of four international, multi-center clinical trials to investigate the application of blood test biomarkers to predict irAEs in atezolizumab-treated adva ...[more]

PMID: 35844547

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Project description:BackgroundIn the context of patients with hepatocellular carcinoma (HCC) treated with systemic therapy, the correlation between the appearance of adverse events (AEs) and reported efficacy outcomes is well-known and widely investigated. From other pathological settings, we are aware of the prognostic and predictive value of the occurrence of immune-related AEs in patients treated with immune-checkpoint inhibitors.ObjectiveThis retrospective multicenter real-world study aims to investigate the potential prognostic value of AEs in patients with HCC treated with atezolizumab plus bevacizumab in the first-line setting.Patients and methodsThe study population consisted of 823 patients from five countries (Italy, Germany, Portugal, Japan, and the Republic of Korea).ResultsOf the patients, 73.3% presented at least one AE during the study period. The most common AEs were proteinuria (29.6%), arterial hypertension (27.2%), and fatigue (26.0%). In all, 17.3% of the AEs were grade (G) 3. One death due to bleeding was reported. The multivariate analysis confirmed the appearance of decreased appetite G < 2 [versus G ≥ 2; hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.13-0.90; p < 0.01] and immunotoxicity G < 2 (versus G ≥ 2; HR: 0.70; 95% CI 0.24-0.99; p = 0.04) as independent prognostic factors for overall survival, and the appearance of decreased appetite G < 2 (versus G ≥ 2; HR: 0.73; 95% CI 0.43-0.95; p = 0.01), diarrhea (yes versus no; HR: 0.57, 95% CI 0.38-0.85; p = 0.01), fatigue (yes versus no; HR: 0.82, 95% CI 0.65-0.95; p < 0.01), arterial hypertension G < 2 (versus G ≥ 2; HR: 0.68, 95% CI 0.52-0.87; p < 0.01), and proteinuria (yes versus no; HR: 0.79, 95% CI 0.64-0.98; p = 0.03) as independent prognostic factors for progression-free survival.ConclusionsAs demonstrated for other therapies, there is also a correlation between the occurrence of AEs and outcomes for patients with HCC for the combination of atezolizumab plus bevacizumab.

Project description:ImportanceImmune-related adverse events (irAEs) secondary to immune checkpoint inhibitor (ICI) therapy reportedly improve overall survival (OS) in patients with non-small cell lung cancer (NSCLC). However, studies have been small and the association between irAE severity and OS remains poorly defined.ObjectiveTo examine the association between irAEs and their severity with OS in patients with locally advanced or metastatic NSCLC receiving ICIs.Design, setting, and participantsThis retrospective observational cohort study included patients with NSCLC receiving ICIs between March 1, 2014, and November 30, 2021, with follow-up until March 31, 2023. Data analysis was completed April 26, 2023. The Alberta Immunotherapy Database, a provincial, multicenter cohort, was used to capture data from patients receiving ICIs in Alberta, Canada. Participants included 803 patients 18 years or older who received at least 1 cycle of ICI (alone or with chemotherapy), agnostic to treatment line.ExposureDeveloping an irAE mandating delay or discontinuation of ICI therapy and/or systematic corticosteroids for management of toxic effects (hereinafter referred to as clinically meaningful irAEs).Main outcomes and measuresThe primary outcome was association between irAEs and OS according to Kaplan-Meier analysis. Clinically meaningful irAEs were identified. Patients with poor prognosis (survival <3 months) who may have died prior to irAE development were excluded from OS analysis, mitigating immortal time bias. Adjusted Cox proportional hazards regression analyses ascertained variables associated with OS.ResultsAmong the 803 patients included in the analysis, the median age of patients with irAEs was 69.7 (IQR, 63.1-75.2) years and the median age of those without irAEs was 67.5 (IQR, 60.4-73.3) years, with comparable sex distribution (139 of 295 men [47.1%] and 156 of 295 women [52.9%] with irAEs vs 254 of 505 men [50.3%] and 251 of 505 women [49.7%] without irAEs). Mitigating immortal time bias (n = 611), irAEs were associated with OS (median OS with irAEs, 23.7 [95% CI, 19.3-29.1] months; median OS without irAEs, 9.8 [95% CI, 8.7-11.4] months; P < .001). No OS difference was associated with treatment in hospital vs as outpatients for an irAE (median OS, 20.8 [95% CI, 11.7-30.6] vs 25.6 [95% CI, 20.1-29.8] months; P = .33). Developing irAEs remained associated with OS in the total cohort after Cox proportional hazards regression with known prognostic characteristics (hazard ratio, 0.53 [95% CI, 0.40-0.70]; P < .001).Conclusions and relevanceIn this cohort study of 803 patients with locally advanced or metastatic NSCLC receiving ICIs, developing a clinically meaningful irAE was associated with improved OS. This association was not compromised by hospitalization for severe toxic effects. Whether and how ICI therapy resumption after an irAE is associated with OS warrants further study.

Project description:BackgroundImmune checkpoint inhibitors (ICIs) have revolutionized the treatment of cancer patients in the last decade, but immune-related adverse events (irAEs) pose significant clinical challenges. Despite advances in the management of these unique toxicities, there remains an unmet need to further characterize the patient-level drivers of irAEs in order to optimize the benefit/risk balance in patients receiving cancer immunotherapy.MethodsAn individual-patient data post-hoc meta-analysis was performed using data from 10,344 patients across 15 Roche sponsored clinical trials with atezolizumab in five different solid tumor types to assess the association between baseline risk factors and the time to onset of irAE. In this study, the overall analysis was conducted by treatment arm, indication, toxicity grade and irAE type, and the study design considered confounder adjustment to assess potential differences in risk factor profiles.ResultsThis analysis demonstrates that the safety profile of atezolizumab is generally consistent across indications in the 15 studies evaluated. In addition, our findings corroborate with prior reviews which suggest that reported rates of irAEs with PD-(L)1 inhibitors are nominally lower than CTLA-4 inhibitors. In our analysis, there were no remarkable differences in the distribution of toxicity grades between indications, but some indication-specific differences regarding the type of irAE were seen across treatment arms, where pneumonitis mainly occurred in lung cancer, and hypothyroidism and rash had a higher prevalence in advanced renal cell carcinoma compared to all other indications. Results showed consistency of risk factors across indications and by toxicity grade. The strongest and most consistent risk factors were mostly organ-specific such as elevated liver enzymes for hepatitis and thyroid stimulating hormone (TSH) for thyroid toxicities. Another strong but non-organ-specific risk factor was ethnicity, which was associated with rash, hepatitis and pneumonitis. Further understanding the impact of ethnicity on ICI associated irAEs is considered as an area for future research.ConclusionsOverall, this analysis demonstrated that atezolizumab safety profile is consistent across indications, is clinically distinguishable from comparator regimens without checkpoint inhibition, and in line with literature, seems to suggest a nominally lower reported rates of irAEs vs CTLA-4 inhibitors. This analysis demonstrates several risk factors for irAEs by indication, severity and location of irAE, and by patient ethnicity. Additionally, several potential irAE risk factors that have been published to date, such as demographic factors, liver enzymes, TSH and blood cell counts, are assessed in this large-scale meta-analysis, providing a more consistent picture of their relevance. However, given the small effects size, changes to clinical management of irAEs associated with the use of Anti-PDL1 therapy are not warranted.

Dataset Information

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.

Background

Method

Results

Conclusion

Publications

Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods.

Similar Datasets

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