Dataset Information

Efficacy of first-line immune checkpoint inhibitor and anti-angiogenic agent combination therapy for Kirsten rat sarcoma viral antigen-mutant advanced non-small-cell lung cancer: a systematic review and network meta-analysis.

ABSTRACT:

Background

Recent advancements in advanced non-small-cell lung cancer (NSCLC) treatment have significantly improved primary therapy outcomes owing to the emergence of various molecular targeted therapies and immune checkpoint inhibitors (ICIs). However, for Kirsten rat sarcoma viral antigen (KRAS) mutations, molecular targeted drugs, such as sotorasib, are not applicable as first-line treatments, and the optimal primary treatment remains unclear. Therefore, we aimed to investigate the efficacy of ICI combination therapy as first-line treatment for KRAS-mutant NSCLC.

Methods

We conducted a systematic search for phase 3 randomized controlled trials (RCTs) that presented data on KRAS mutation status in advanced NSCLC. The primary endpoints were progression-free survival (PFS) and overall survival (OS). A random-effects network meta-analysis was conducted to perform direct and indirect comparisons among treatment groups.

Results

Six RCTs were eligible for inclusion. In the network meta-analysis for KRAS-mutant NSCLC, Chemo + bevacizumab (Bev) + ICI was associated with improved PFS (hazard ratio [HR] 0.38, 95% confidence interval [CI] 0.22-0.64), followed by Chemo + ICI + ICI (HR 0.66, 95% CI 0.47-0.93) and Chemo + ICI (HR 0.67, 95% CI 0.49-0.91). The most beneficial effect on OS was observed with Chemo + Bev + ICI (HR 0.50, 95% CI 0.34-0.73), followed by Chemo + ICI + ICI (HR 0.64, 95% CI 0.48-0.87) and Chemo + ICI (HR 0.72, 95% CI 0.56-0.92). Regarding OS in wild-type KRAS, ICI + ICI (HR 0.73, 95% CI 0.50-1.07) produced the most favorable effects, followed by Chemo + ICI (HR 0.79, 95% CI 0.63-0.99).

Conclusion

The efficacy of Chemo + Bev + ICI is potentially high for improving PFS and OS in KRAS-mutant NSCLC. In advanced NSCLC, the presence or absence of KRAS mutations may need to be considered when administering first-line treatment.

SUBMITTER: Tsukada A

PROVIDER: S-EPMC11367661 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature

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Publications

Efficacy of first-line immune checkpoint inhibitor and anti-angiogenic agent combination therapy for Kirsten rat sarcoma viral antigen-mutant advanced non-small-cell lung cancer: a systematic review and network meta-analysis.

Tsukada Akinari A Morita Chie C Shimizu Yosuke Y Uemura Yukari Y Naka Go G Takasaki Jin J Nokihara Hiroshi H Izumi Shinyu S Hojo Masayuki M

Thoracic cancer 20240731 25

<h4>Background</h4>Recent advancements in advanced non-small-cell lung cancer (NSCLC) treatment have significantly improved primary therapy outcomes owing to the emergence of various molecular targeted therapies and immune checkpoint inhibitors (ICIs). However, for Kirsten rat sarcoma viral antigen (KRAS) mutations, molecular targeted drugs, such as sotorasib, are not applicable as first-line treatments, and the optimal primary treatment remains unclear. Therefore, we aimed to investigate the ef ...[more]

PMID: 39086088

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Project description:ObjectiveTo develop and validate radiomics models based on multiphasic CT in predicting Kirsten rat sarcoma virus (KRAS) gene mutation status in patients with colorectal cancer (CRC).Materials and methodsA total of 231 patients with pathologically confirmed CRC were retrospectively enrolled and randomly divided into training(n=184) and test groups(n=47) in a ratio of 4:1. A total of 1316 quantitative radiomics features were extracted from non-contrast phase (NCP), arterial-phase (AP) and venous-phase (VP) CT for each patient. Four steps were applied for feature selection including Spearman correlation analysis, variance threshold, least absolute contraction and selection operator, and multivariate stepwise regression analysis. Clinical and pathological characteristics were also assessed. Subsequently, three classification methods, logistic regression (LR), support vector machine (SVM) and random tree (RT) algorithm, were applied to develop seven groups of prediction models (NCP, AP, VP, AP+VP, AP+VP+NCP, AP&VP, AP&VP&NCP) for KRAS mutation prediction. The performance of these models was evaluated by receiver operating characteristics curve (ROC) analysis.ResultsAmong the three groups of single-phase models, the AP model, developed by LR algorithm, showed the best prediction performance with an AUC value of 0.811 (95% CI:0.685-0.938) in the test cohort. Compared with the single-phase models, the dual-phase (AP+VP) model with the LR algorithm showed better prediction performance (AUC=0.826, 95% CI:0.700-0.952). The performance of multiphasic (AP+VP+NCP) model with the LR algorithm (AUC=0.811, 95%CI: 0.679-0.944) is comparable to the model with the SVM algorithm (AUC=0.811, 95%CI: 0.695-0.918) in the test cohort, but the sensitivity, specificity, and accuracy of the multiphasic (AP+VP+NCP) model with the LR algorithm were 0.810, 0.808, 0.809 respectively, which were highest among these seven groups of prediction models in the test cohort.ConclusionThe CT radiomics models have the potential to predict KRAS mutation in patients with CRC; different phases may affect the predictive efficacy of radiomics model, of which arterial-phase CT is more informative. The combination of multiphasic CT images can further improve the performance of radiomics model.

Project description:BackgroundKirsten rat sarcoma (KRAS) mutation drives resistance to anti-epidermal growth factor receptor (anti-EGFR)-targeted therapies in rectal cancer. Amide proton transfer-weighted magnetic resonance imaging (APTw MRI) might be a supplement to the evaluation of KRAS mutation because the APTw value can reflect mobile cellular protein content in vivo. This study aimed to determine whether APTw MRI could predict KRAS mutation in rectal cancer and compare this technique with diffusion-weighted imaging (DWI).MethodsThis retrospective study reviewed 153 consecutive patients with rectal cancer from April 2019 to June 2021 in our hospital. Among them, a total of 55 patients who did not undergo neoadjuvant chemoradiotherapy and underwent preoperative APTw MRI, DWI, and postoperative KRAS tests were included in this study. In two-dimensional APTw images, two radiologists manually delineated three regions of interest (ROIs) along tumor contour in the largest slice and the adjacent two slices of tumor respectively. The mean APTw value within a ROI was calculated, and the values of three ROIs were averaged for each patient. In consecutive DWI images, two radiologists depicted the ROIs of the whole lesion, and the mean apparent diffusion coefficient (ADC) was generated. The intraclass correlation coefficient (ICC), Shapiro-Wilk test and Student's t-test were used for statistical analyses. Receiver operating characteristic (ROC) curves were constructed for APTw and ADC values respectively, and the area under the curve (AUC) was used to evaluate the diagnostic performance for the prediction of KRAS mutation.ResultsAmong these 55 patients, KRAS mutation occurred in 21 patients. The ICCs of two independent raters for APTw and ADC values were 0.937 [95% confidence interval (CI), 0.914-0.953] and 0.976 (95% CI, 0.959-0.986), respectively. ADC values did not show a statistically significant difference between the KRAS-mutant group and the wild type (WT) group (P=0.733). KRAS-mutant tumors exhibited a higher APTw value than WT tumors in patients with rectal non-mucinous adenocarcinoma (3.324%±0.685% vs. 2.230%±0.833%, P<0.001). The AUC of the APTw value was 0.827 (95% CI, 0.701-0.916), with a cutoff value of 2.4% (sensitivity, 95.2%; specificity, 55.9%).ConclusionsDWI cannot differentiate mutant KRAS genes from WT genes in patients with rectal cancer, but APTw MRI has potential for evaluating KRAS mutation in rectal cancer. The APTw value had moderate diagnostic performance in the prediction of KRAS mutation with a high sensitivity but a low specificity. APTw MRI might be a promising supplement to KRAS genomic analysis in rectal cancer patients.

Dataset Information

Efficacy of first-line immune checkpoint inhibitor and anti-angiogenic agent combination therapy for Kirsten rat sarcoma viral antigen-mutant advanced non-small-cell lung cancer: a systematic review and network meta-analysis.

Background

Methods

Results

Conclusion

Publications

Efficacy of first-line immune checkpoint inhibitor and anti-angiogenic agent combination therapy for Kirsten rat sarcoma viral antigen-mutant advanced non-small-cell lung cancer: a systematic review and network meta-analysis.

Similar Datasets

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