The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model
BackgroundInflammation and immune evasion are associated with tumorigenesis and progression. The Systemic Inflammation Response Index (SIRI) has been proposed as a pre-treatment peripheral blood biomarker. This study aims to compare the relationship between SIRI, various serum biomarkers, and the pr...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1516737/full |
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| author | Chunhan Tang Chunhan Tang Min Zhang Hongyuan Jia Tianlei Wang Tianlei Wang Hongwei Wu Hongwei Wu Ke Xu Ke Xu Tao Ren Tao Ren Long Liang |
| author_facet | Chunhan Tang Chunhan Tang Min Zhang Hongyuan Jia Tianlei Wang Tianlei Wang Hongwei Wu Hongwei Wu Ke Xu Ke Xu Tao Ren Tao Ren Long Liang |
| author_sort | Chunhan Tang |
| collection | DOAJ |
| description | BackgroundInflammation and immune evasion are associated with tumorigenesis and progression. The Systemic Inflammation Response Index (SIRI) has been proposed as a pre-treatment peripheral blood biomarker. This study aims to compare the relationship between SIRI, various serum biomarkers, and the prognosis of NSCLC patients before and after treatment.MethodsA retrospective study was conducted on advanced NSCLC patients treated with anti-PD-1 drugs from December 2018 to September 2021. Peripheral blood markers were measured pre- and post-treatment, and hazard ratios were calculated to assess the association between serum biomarkers and progression-free survival (PFS) and overall survival (OS). Kaplan-Meier curves and Cox proportional hazards models were employed for survival analysis. A nomogram model was built based on multivariate Cox proportional hazards regression analysis using the R survival package, with internal validation via the bootstrap method (1,000 resamples). Predictive performance was expressed using the concordance index (C-index), and calibration plots illustrated predictive accuracy.The application value of the model was evaluated by decision curve analysis (DCA).ResultsAmong 148 advanced NSCLC patients treated with PD-1 inhibitors, the median PFS was 12.9 months (range: 5.4–29.2 months), and the median OS was 19.9 months (range: 9.6–35.2 months). Univariate analysis identified pre- and post-treatment SIRI, mGRIm-Score, and PNI as independent prognostic factors for both PFS and OS (p < 0.05). Multivariate analysis demonstrated that high post-SIRI and post-mGRIm-Score independently predicted poor PFS (P < 0.001, P = 0.004) and OS (P = 0.048, P = 0.001). The C-index of the nomogram model for OS was 0.720 (95% CI: 0.693–0.747) and for PFS was 0.715 (95% CI: 0.690–0.740). Internal validation via bootstrap resampling (B = 1,000) showed good agreement between predicted and observed OS and PFS at 1, 2, and 3 years, as depicted by calibration plots.ConclusionSIRI is an important independent predictor of early progression in advanced NSCLC patients treated with PD-1 inhibitors and may assist in identifying patients who will benefit from PD-1 inhibitors therapy in routine clinical practice. |
| format | Article |
| id | doaj-art-e4b5a174cf77437e8803097d3ebdffbf |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-e4b5a174cf77437e8803097d3ebdffbf2025-08-20T02:32:27ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-12-011510.3389/fimmu.2024.15167371516737The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram modelChunhan Tang0Chunhan Tang1Min Zhang2Hongyuan Jia3Tianlei Wang4Tianlei Wang5Hongwei Wu6Hongwei Wu7Ke Xu8Ke Xu9Tao Ren10Tao Ren11Long Liang12Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, Meishan Traditional Chinese Medicine Hospital, Meishan, Sichuan, ChinaDepartment of Radiation Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Afliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, ChinaClinical Medical College, Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, ChinaClinical Medical College, Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, ChinaClinical Medical College, Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, ChinaClinical Medical College, Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Oncology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, ChinaDepartment of Radiation Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Afliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, ChinaBackgroundInflammation and immune evasion are associated with tumorigenesis and progression. The Systemic Inflammation Response Index (SIRI) has been proposed as a pre-treatment peripheral blood biomarker. This study aims to compare the relationship between SIRI, various serum biomarkers, and the prognosis of NSCLC patients before and after treatment.MethodsA retrospective study was conducted on advanced NSCLC patients treated with anti-PD-1 drugs from December 2018 to September 2021. Peripheral blood markers were measured pre- and post-treatment, and hazard ratios were calculated to assess the association between serum biomarkers and progression-free survival (PFS) and overall survival (OS). Kaplan-Meier curves and Cox proportional hazards models were employed for survival analysis. A nomogram model was built based on multivariate Cox proportional hazards regression analysis using the R survival package, with internal validation via the bootstrap method (1,000 resamples). Predictive performance was expressed using the concordance index (C-index), and calibration plots illustrated predictive accuracy.The application value of the model was evaluated by decision curve analysis (DCA).ResultsAmong 148 advanced NSCLC patients treated with PD-1 inhibitors, the median PFS was 12.9 months (range: 5.4–29.2 months), and the median OS was 19.9 months (range: 9.6–35.2 months). Univariate analysis identified pre- and post-treatment SIRI, mGRIm-Score, and PNI as independent prognostic factors for both PFS and OS (p < 0.05). Multivariate analysis demonstrated that high post-SIRI and post-mGRIm-Score independently predicted poor PFS (P < 0.001, P = 0.004) and OS (P = 0.048, P = 0.001). The C-index of the nomogram model for OS was 0.720 (95% CI: 0.693–0.747) and for PFS was 0.715 (95% CI: 0.690–0.740). Internal validation via bootstrap resampling (B = 1,000) showed good agreement between predicted and observed OS and PFS at 1, 2, and 3 years, as depicted by calibration plots.ConclusionSIRI is an important independent predictor of early progression in advanced NSCLC patients treated with PD-1 inhibitors and may assist in identifying patients who will benefit from PD-1 inhibitors therapy in routine clinical practice.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1516737/fullsystemic inflammation response indexnon-small cell lung cancerimmunotherapynomogram modelprognostic |
| spellingShingle | Chunhan Tang Chunhan Tang Min Zhang Hongyuan Jia Tianlei Wang Tianlei Wang Hongwei Wu Hongwei Wu Ke Xu Ke Xu Tao Ren Tao Ren Long Liang The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model Frontiers in Immunology systemic inflammation response index non-small cell lung cancer immunotherapy nomogram model prognostic |
| title | The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| title_full | The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| title_fullStr | The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| title_full_unstemmed | The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| title_short | The systemic inflammation response index (SIRI) predicts survival in advanced non-small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| title_sort | systemic inflammation response index siri predicts survival in advanced non small cell lung cancer patients undergoing immunotherapy and the construction of a nomogram model |
| topic | systemic inflammation response index non-small cell lung cancer immunotherapy nomogram model prognostic |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1516737/full |
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