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Zhu M, Zhang LT, Lai W, Yang F, Zhou D, Xu R, Tong G. Prognostic value of inflammatory and nutritional indexes among patients with unresectable advanced gastric cancer receiving immune checkpoint inhibitors combined with chemotherapy-a retrospective study. PeerJ 2024; 12:e18659. [PMID: 39713151 PMCID: PMC11660861 DOI: 10.7717/peerj.18659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 11/17/2024] [Indexed: 12/24/2024] Open
Abstract
Background Recent studies have revealed that inflammatory factors and nutritional status of patients with advanced gastric cancer (AGC) are related to the efficacy of drug therapy and patient prognosis. This study seeks to evaluate the correlation between inflammatory markers, nutritional status, and clinical outcomes of immune checkpoint inhibitor (ICI)-based therapies among inoperable AGC patients. Method This retrospective study included 88 AGC patients who received ICIs combined with chemotherapy. Inflammatory and nutritional indicators from patients before and after two cycles of treatment were collected. Finally, the correlations between these indicators and the clinical response and survival of AGC patients with ICI treatment were examined. Results The results revealed that an Eastern Cooperative Oncology Group performance status (ECOG PS) score of 0, neutrophil count to lymphocyte count ratio (NLR) < 2.84, platelet count to lymphocyte count ratio (PLR) < 82.23, lymphocyte count to monocyte count ratio ≥ 2.35, the hemoglobin, albumin, lymphocyte and platelet score (HALP) ≥ 31.17, prognostic nutritional index (PNI) ≥ 46.53, albumin ≥ 41.65, the decreased HALP group and the decreased PNI group were significantly correlated with improved objective response rate. Additionally, an ECOG PS score of 0, NLR < 2.84 and the decreased HALP group was associated with a superior disease control rate. Meanwhile, an ECOG PS score of 0 (progression-free survival (PFS): P = 0.003; overall survival (OS): P = 0.001) and decreased PLR following treatment (PFS: P = 0.011; OS: P = 0.008) were significant independent predictors of PFS and OS. Lastly, a systemic immune inflammation index ≥ 814.8 was also a positive independent predictor of OS among AGC patients. Conclusion Our study supports the potential of inflammatory and nutritional factors to serve as predictors of the efficacy and prognosis in patients undergoing ICI-based therapies for AGC. However, further investigations are necessary to validate these findings.
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Affiliation(s)
- Meiqin Zhu
- Department of Medical Oncology, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Lin-Ting Zhang
- Department of Oncology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shantou University Medical College, Shantou, Guangdong, China
| | - Wenjuan Lai
- Nursing Department, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Fang Yang
- Department of Oncology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Danyang Zhou
- Department of Oncology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Ruilian Xu
- Department of Medical Oncology, Shenzhen People’s Hospital, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Gangling Tong
- Department of Oncology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shantou University Medical College, Shantou, Guangdong, China
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Li HW, Zhu ZY, Sun YF, Yuan CY, Wang MH, Wang N, Xue YW. Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors. World J Gastroenterol 2024; 30:4354-4366. [PMID: 39494097 PMCID: PMC11525865 DOI: 10.3748/wjg.v30.i40.4354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 09/19/2024] [Accepted: 09/27/2024] [Indexed: 10/16/2024] Open
Abstract
BACKGROUND Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC. AIM To investigate biomarkers that predict prognosis in GC patients treated with ICIs and develop accurate predictive models. METHODS Data from 273 patients diagnosed with GC and distant metastasis, who un-derwent ≥ 1 cycle(s) of ICIs therapy were included in this study. Patients were randomly divided into training and test sets at a ratio of 7:3. Training set data were used to develop the machine learning models, and the test set was used to validate their predictive ability. Shapley additive explanations were used to provide insights into the best model. RESULTS Among the 273 patients with GC treated with ICIs in this study, 112 died within 1 year, and 129 progressed within the same timeframe. Five features related to overall survival and 4 related to progression-free survival were identified and used to construct eXtreme Gradient Boosting (XGBoost), logistic regression, and decision tree. After comprehensive evaluation, XGBoost demonstrated good accuracy in predicting overall survival and progression-free survival. CONCLUSION The XGBoost model aided in identifying patients with GC who were more likely to benefit from ICIs therapy. Patient nutritional status may, to some extent, reflect prognosis.
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Affiliation(s)
- Hong-Wei Li
- Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Zi-Yu Zhu
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Yu-Fei Sun
- Department of Anesthesia, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Chao-Yu Yuan
- Department of Computer Science and Technology, Heilongjiang University, Harbin 150000, Heilongjiang Province, China
| | - Mo-Han Wang
- Department of Computer Science and Technology, Heilongjiang University, Harbin 150000, Heilongjiang Province, China
| | - Nan Wang
- Department of Computer Science and Technology, Heilongjiang University, Harbin 150000, Heilongjiang Province, China
| | - Ying-Wei Xue
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
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Xia Y, Wang Y, Yuan S, Hu J, Zhang L, Xie J, Zhao Y, Hao J, Ren Y, Wu S. Development and validation of nomograms to predict clinical outcomes of preeclampsia. Front Endocrinol (Lausanne) 2024; 15:1292458. [PMID: 38549768 PMCID: PMC10972945 DOI: 10.3389/fendo.2024.1292458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/14/2024] [Indexed: 04/02/2024] Open
Abstract
Background Preeclampsia (PE) is one of the most severe pregnancy-related diseases; however, there is still a lack of reliable biomarkers. In this study, we aimed to develop models for predicting early-onset PE, severe PE, and the gestation duration of patients with PE. Methods Eligible patients with PE were enrolled and divided into a training (n = 253) and a validation (n = 108) cohort. Multivariate logistic and Cox models were used to identify factors associated with early-onset PE, severe PE, and the gestation duration of patients with PE. Based on significant factors, nomograms were developed and evaluated using the area under the curve (AUC) and a calibration curve. Results In the training cohort, multiple gravidity experience (p = 0.005), lower albumin (ALB; p < 0.001), and higher lactate dehydrogenase (LDH; p < 0.001) were significantly associated with early-onset PE. Abortion history (p = 0.017), prolonged thrombin time (TT; p < 0.001), and higher aspartate aminotransferase (p = 0.002) and LDH (p = 0.003) were significantly associated with severe PE. Abortion history (p < 0.001), gemellary pregnancy (p < 0.001), prolonged TT (p < 0.001), higher mean platelet volume (p = 0.014) and LDH (p < 0.001), and lower ALB (p < 0.001) were significantly associated with shorter gestation duration. Three nomograms were developed and validated to predict the probability of early-onset PE, severe PE, and delivery time for each patient with PE. The AUC showed good predictive performance, and the calibration curve and decision curve analysis demonstrated clinical practicability. Conclusion Based on the clinical features and peripheral blood laboratory indicators, we identified significant factors and developed models to predict early-onset PE, severe PE, and the gestation duration of pregnant women with PE, which could help clinicians assess the clinical outcomes early and design appropriate strategies for patients.
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Affiliation(s)
- Yan Xia
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Yao Wang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Shijin Yuan
- Department of Medical Oncology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaming Hu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Lu Zhang
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Jiamin Xie
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Yang Zhao
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
| | - Jiahui Hao
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yanwei Ren
- Department of Gynaecology and Obstetrics, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shengjun Wu
- Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Hangzhou, China
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Wu Y, Lv C, Lin M, Hong Y, Du B, Yao N, Zhu Y, Ji X, Li J, Lai J. Novel nomogram for predicting survival in advanced non-small cell lung cancer receiving anti-PD-1 plus chemotherapy with or without antiangiogenic therapy. Front Immunol 2023; 14:1297188. [PMID: 38022521 PMCID: PMC10663364 DOI: 10.3389/fimmu.2023.1297188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Background This study aimed to develop and validate a novel nomogram to predict survival in advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD-1) inhibitor plus chemotherapy with or without antiangiogenic therapy. Methods A total of 271 patients with advanced NSCLC who received anti-PD-1 plus chemotherapy with or without antiangiogenic therapy were enrolled in our center and randomized into the training cohort (n = 133) and the internal validation cohort (n = 138). Forty-five patients from another center were included as an independent external validation cohort. The nomogram was created based on the multivariate Cox regression analysis to predict overall survival (OS) and progression-free survival (PFS). The performance of the nomogram was assessed using the concordance index (C-index), the time-dependent area under the receiver operating (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA). Results Four factors significantly associated with OS were utilized to create a nomogram to predict OS: Eastern Cooperative Oncology Group performance status (ECOG PS), programmed cell death-ligand 1 (PD-L1) expression, chemotherapy cycle, and pretreatment lactate dehydrogenase-albumin ratio (LAR). Six variables significantly associated with PFS were incorporated into the development of a nomogram for predicting PFS: ECOG PS, histology, PD-L1 expression, chemotherapy cycle, pretreatment platelet to lymphocyte (PLR), and pretreatment LAR. The C-indexes of the nomogram for predicting OS and PFS were 0.750 and 0.747, respectively. The AUCs for predicting the 6-month, 12-month, and 18-month OS and PFS were 0.847, 0.791, and 0.776 and 0.810, 0.787, and 0.861, respectively. The calibration curves demonstrated a good agreement between predictions and actual observations. The DCA curves indicated that the nomograms had good net benefits. Furthermore, the nomogram model was well-validated in the internal and external cohorts. Conclusion The novel nomogram for predicting the prognosis of advanced NSCLC receiving anti-PD-1 plus chemotherapy with or without antiangiogenic therapy may help guide clinical treatment decisions.
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Affiliation(s)
- Yahua Wu
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Chengliu Lv
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Mingqian Lin
- Department of Radiation Oncology, Fujian Medical University Cancer Hospital, Fuzhou, China
| | - Yaping Hong
- Department of Radiation Oncology, Fujian Medical University Cancer Hospital, Fuzhou, China
| | - Bin Du
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Na Yao
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yingjiao Zhu
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiaohui Ji
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiancheng Li
- Department of Radiation Oncology, Fujian Medical University Cancer Hospital, Fuzhou, China
| | - Jinhuo Lai
- Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China
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Ancel J, Dormoy V, Raby BN, Dalstein V, Durlach A, Dewolf M, Gilles C, Polette M, Deslée G. Soluble biomarkers to predict clinical outcomes in non-small cell lung cancer treated by immune checkpoints inhibitors. Front Immunol 2023; 14:1171649. [PMID: 37283751 PMCID: PMC10239865 DOI: 10.3389/fimmu.2023.1171649] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/11/2023] [Indexed: 06/08/2023] Open
Abstract
Lung cancer remains the first cause of cancer-related death despite many therapeutic innovations, including immune checkpoint inhibitors (ICI). ICI are now well used in daily practice at late metastatic stages and locally advanced stages after a chemo-radiation. ICI are also emerging in the peri-operative context. However, all patients do not benefit from ICI and even suffer from additional immune side effects. A current challenge remains to identify patients eligible for ICI and benefiting from these drugs. Currently, the prediction of ICI response is only supported by Programmed death-ligand 1 (PD-L1) tumor expression with perfectible results and limitations inherent to tumor-biopsy specimen analysis. Here, we reviewed alternative markers based on liquid biopsy and focused on the most promising biomarkers to modify clinical practice, including non-tumoral blood cell count such as absolute neutrophil counts, platelet to lymphocyte ratio, neutrophil to lymphocyte ratio, and derived neutrophil to lymphocyte ratio. We also discussed soluble-derived immune checkpoint-related products such as sPD-L1, circulating tumor cells (detection, count, and marker expression), and circulating tumor DNA-related products. Finally, we explored perspectives for liquid biopsies in the immune landscape and discussed how they could be implemented into lung cancer management with a potential biological-driven decision.
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Affiliation(s)
- Julien Ancel
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Valérian Dormoy
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
| | - Béatrice Nawrocki Raby
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
| | - Véronique Dalstein
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Anne Durlach
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Maxime Dewolf
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Christine Gilles
- Laboratory of Tumor and Development Biology, GIGA-Cancer, University of Liège, Liège, Belgium
| | - Myriam Polette
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Gaëtan Deslée
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
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Liu A, Zhang G, Yang Y, Xia Y, Li W, Liu Y, Cui Q, Wang D, Zhao J, Yu J. A clinical nomogram based on absolute count of lymphocyte subsets for predicting overall survival in patients with non-small cell lung cancer. Int Immunopharmacol 2023; 114:109391. [PMID: 36508919 DOI: 10.1016/j.intimp.2022.109391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/26/2022] [Accepted: 10/24/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND The absolute count of lymphocyte subsets (ACLS) is correlated to the prognosis of multiple malignancies. This study aimed to combine the ACLS with the clinicopathological parameters to develop a nomogram to accurately predict the prognosis of non-small cell lung cancer (NSCLC) patients. METHODS This retrospective study included a training cohort (n = 1685) and validation cohort (n = 337) with NSCLC patients treated in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine between January 2018 and January 2021. Cox regression were conducted to identify factors associated with overall survival. The nomogram was built based on 10 significant factors, and evaluated by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. RESULTS In the training cohort, the multivariate cox proportional hazard regression analysis showed that the independent factors for overall survival (OS) included age, brain metastases, hepatic metastases, respiratory system diseases, clinical stages, surgery, absolute count (AC) of CD3+, CD4+, CD8+, and NK cells, which were all applied in the nomogram. The C-index of the nomogram to predict OS was 0.777 (95% CI, 0.751-0.802) in training cohort and 0.822 (95% CI, 0.798-0.846) in validation cohort. The area under the ROC showed a good discriminative ability in both cohorts. Calibration curves presented an excellent consistence between the nomogram predicted probability and actual observation. CONCLUSIONS We established a prognostic nomogram to predict OS of the NSCLC patient. This nomogram provided a more quantitative, scientific and objective basis for accurate diagnosis and individual management of NSCLC patients.
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Affiliation(s)
- Aqing Liu
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Guan Zhang
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yanjie Yang
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ying Xia
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Wentao Li
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Yunhe Liu
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China
| | - Qian Cui
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Dong Wang
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China; Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jian Zhao
- Department of Oncology-Pathology, Karolinska Institutet, BioClinicum, Karolinska University Hospital Solna, Stockholm, Sweden.
| | - Jianchun Yu
- Department of Oncology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin, China.
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Zhang Q, Gong X, Sun L, Miao L, Zhou Y. The Predictive Value of Pretreatment Lactate Dehydrogenase and Derived Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Patients Treated With PD-1/PD-L1 Inhibitors: A Meta-Analysis. Front Oncol 2022; 12:791496. [PMID: 35924149 PMCID: PMC9340347 DOI: 10.3389/fonc.2022.791496] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 06/09/2022] [Indexed: 12/24/2022] Open
Abstract
Background The Lung Immune Prognostic Index (LIPI) combines the lactate dehydrogenase (LDH) level and the derived neutrophil-to-lymphocyte ratio (dNLR). A lot of studies have shown that LDH and dNLR are associated with the prognosis of advanced non-small cell lung cancer (NSCLC) in patients treated with programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitors. However, previous results were inconsistent, and the conclusions remain unclear. This meta-analysis aimed to investigate the predictive value of pretreatment LDH and dNLR for NSCLC progression in patients treated with PD-1/PD-L1 inhibitors. Methods PubMed, Embase, and the Cochrane Library were searched by two researchers independently for related literature before March 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) were extracted to assess the predictive value of LDH and dNLR. STATA 15. 0 was used to perform the meta-analysis. Results A total of 3,429 patients from 26 studies were included in this meta-analysis. The results revealed that high pretreatment LDH was related to poor OS (HR = 1.19, 95%CI = 1.11–1.24, p < 0.001), but not closely related to poor PFS (HR = 1.02, 95%CI = 1.00–1.04, p = 0.023 < 0.05). The pooled results for dNLR suggested that high pretreatment dNLR was related to poor OS (HR = 1.55, 95%CI = 1.33–1.80, p < 0.001) and PFS (HR = 1.33, 95%CI = 1.16–1.54, p < 0.001). Conclusion Both pretreatment LDH and dNLR have the potential to serve as peripheral blood biomarkers for patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors. However, more studies on LDH are needed to evaluate its predictive value for PFS in patients with NSCLC.
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Affiliation(s)
- Qianning Zhang
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University Nanjing Drum Tower Hospital, Nanjing, China
| | - Xiaoling Gong
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University Nanjing Drum Tower Hospital, Nanjing, China
| | - Lei Sun
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University Nanjing Drum Tower Hospital, Nanjing, China
| | - Liyun Miao
- Department of Respiratory and Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- *Correspondence: Liyun Miao, ; Yujie Zhou,
| | - Yujie Zhou
- Department of Respiratory and Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
- *Correspondence: Liyun Miao, ; Yujie Zhou,
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Issa M, Klamer BG, Mladkova N, Laliotis GI, Karivedu V, Bhateja P, Byington C, Dibs K, Pan X, Chakravarti A, Grecula J, Jhawar SR, Mitchell D, Baliga S, Old M, Carrau RL, Rocco JW, Blakaj DM, Bonomi M. Update of a prognostic survival model in head and neck squamous cell carcinoma patients treated with immune checkpoint inhibitors using an expansion cohort. BMC Cancer 2022; 22:767. [PMID: 35836204 PMCID: PMC9284772 DOI: 10.1186/s12885-022-09809-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/14/2022] [Indexed: 11/15/2022] Open
Abstract
Background Immune checkpoint inhibitors (ICI) treatment in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) offers new therapeutic venues. We have previously developed a predictive survival model in this patient population based on clinical parameters, and the purpose of this study was to expand the study cohort and internally validate the model. Methods A single institutional retrospective analysis of R/M HNSCC patients treated with ICI. Clinical parameters collected included p-16 status, hemoglobin (Hb), albumin (Alb), lactate dehydrogenase (LDH), neutrophil, lymphocyte and platelet counts. Cox proportional hazard regression was used to assess the impact of patient characteristics and clinical variables on survival. A nomogram was created using the rms package to generate individualized survival prediction. Results 201 patients were included, 47 females (23%), 154 males (77%). Median age was 61 years (IQR: 55-68). P-16 negative (66%). Median OS was 12 months (95% CI: 9.4, 14.9). Updated OS model included age, sex, absolute neutrophil count, absolute lymphocyte count, albumin, hemoglobin, LDH, and p-16 status. We stratified patients into three risk groups based on this model at the 0.33 and 0.66 quantiles. Median OS in the optimal risk group reached 23.7 months (CI: 18.5, NR), 13.8 months (CI: 11.1, 20.3) in the average risk group, and 2.3 months (CI: 1.7, 4.4) in the high-risk group. Following internal validation, the discriminatory power of the model reached a c-index of 0.72 and calibration slope of 0.79. Conclusions Our updated nomogram could assist in the precise selection of patients for which ICI could be beneficial and cost-effective.
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Affiliation(s)
- Majd Issa
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA.
| | - Brett G Klamer
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Nikol Mladkova
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Georgios I Laliotis
- Sidney Kimmel Comprehensive Cancer Center and Department of Oncology, Johns Hopkins University, Baltimore, MD, 21231, USA
| | - Vidhya Karivedu
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Priyanka Bhateja
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Chase Byington
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Khaled Dibs
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Xueliang Pan
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Arnab Chakravarti
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - John Grecula
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Sachin R Jhawar
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Darrion Mitchell
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Sujith Baliga
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Matthew Old
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Ricardo L Carrau
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - James W Rocco
- Department of Otolaryngology - Head and Neck Surgery, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Dukagjin M Blakaj
- Division of Radiation Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Marcelo Bonomi
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
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Liu N, Mao J, Tao P, Chi H, Jia W, Dong C. The relationship between NLR/PLR/LMR levels and survival prognosis in patients with non-small cell lung carcinoma treated with immune checkpoint inhibitors. Medicine (Baltimore) 2022; 101:e28617. [PMID: 35060536 PMCID: PMC8772656 DOI: 10.1097/md.0000000000028617] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 12/29/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND The relationship between neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) and the dire prognosis of non-small cell lung carcinoma patients who received immune checkpoint inhibitors (ICIs) are not known yet. METHODS We screened the articles that meet the criteria from the database. The relationship between NLR/PLR/LMR levels and the survival and prognosis of non-small cell lung cancer patients treated with ICIs was analyzed. Summarize hazard ratio (HR) with 95% confidence interval (CI) to study progression-free survival (PFS) and overall survival (OS). RESULTS Thirty-four studies involving 3124 patients were enrolled in the final analysis. In short, high pre-treatment NLR was related to poor OS (HR = 2.13, 95% CI:1.74-2.61, P < .001, I2 = 83.3%, P < .001) and PFS (HR = 1.77, 95% CI:1.44-2.17, P < .001, I2 = 79.5%, P < .001). Simultaneously, high pre-treatment PLR was related to poor OS (HR = 1.49, 95% CI:1.17-1.91, P < .001, I2 = 57.6%, P = .003) and PFS (HR = 1.62, 95% CI:1.38-1.89, P < .001, I2 = 47.1%, P = .036). In all subgroup analysis, most subgroups showed that low LMR was related to poor OS (HR = 0.45, 95% CI: 0.34-0.59, P < .001) and PFS (HR = 0.60, 95% CI: 0.47-0.77, P < 0.001, I2 = 0.0%, P < .001). CONCLUSION High pre-treatment NLR and pre-treatment PLR in non-small cell lung carcinoma patients treated with ICIs are associated with low survival rates. Low pre-treatment and post-treatment LMR are also related to unsatisfactory survival outcomes. However, the significance of post-treatment NLR and post-treatment PLR deserve further prospective research to prove.
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Xia L, Guo L, Kang J, Yang Y, Yao Y, Xia W, Sun R, Zhang S, Li W, Gao Y, Chen H, Li Z, Yang J, Lu S, Wang Y. Predictable Roles of Peripheral IgM Memory B Cells for the Responses to Anti-PD-1 Monotherapy Against Advanced Non-Small Cell Lung Cancer. Front Immunol 2021; 12:759217. [PMID: 34899709 PMCID: PMC8652218 DOI: 10.3389/fimmu.2021.759217] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 11/08/2021] [Indexed: 01/21/2023] Open
Abstract
Tumor-infiltrating B cells and tertiary lymphoid structures have been identified to predict the responses to immune checkpoint inhibitors (ICIs) in cancer immunotherapy. Considering the feasibility of sample collection, whether peripheral B cell signatures are associated with the responses to ICI therapy remains unclear. Herein, we have defined peripheral B cell signatures in advanced non-small cell lung cancer (NSCLC) patients receiving anti-PD-1 monotherapy and investigated their associations with clinical efficacy. It was found that the percentages of B cells before the treatment (baseline) were significantly higher (P = 0.004) in responder (R, n = 17) than those in non-responder (NonR, n = 33) NSCLC patients in a discovery cohort. Moreover, the percentages of baseline IgM+ memory B cells were higher (P < 0.001) in R group than those in NonR group, and associated with a longer progression free survival (PFS) (P = 0.003). By logistic regression analysis peripheral baseline IgM+ memory B cells were identified as an independent prognostic factor (P = 0.002) for the prediction of the responses to anti-PD-1 monotherapy with the AUC value of 0.791, which was further validated in another anti-PD-1 monotherapy cohort (P = 0.011, n = 70) whereas no significance was observed in patients receiving anti-PD-L1 monotherapy (P = 0.135, n = 30). Therefore, our data suggest the roles of peripheral IgM+ memory B cells in predicting the responses to anti-PD-1 treatment in Chinese advanced NSCLC patients.
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Affiliation(s)
- Liliang Xia
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.,Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Limin Guo
- Department of Genetic Engineering, School of Life Sciences and Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jin Kang
- Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, School of Medicine, Guangzhou, China
| | - Yi Yang
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yaxian Yao
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Weimin Xia
- Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruiming Sun
- Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shun Zhang
- Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenfeng Li
- Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, School of Medicine, Guangzhou, China
| | - Yuer Gao
- Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, School of Medicine, Guangzhou, China
| | - Hongyan Chen
- Department of Genetic Engineering, School of Life Sciences and Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Ziming Li
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jinji Yang
- Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, School of Medicine, Guangzhou, China
| | - Shun Lu
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Wang
- Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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11
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Sun L, Cen W, Tang W, Long Y, Yang X, Ji X, Yang J, Zhang R, Wang F, Shao J, Du Z. Smoking status combined with tumor mutational burden as a prognosis predictor for combination immune checkpoint inhibitor therapy in non-small cell lung cancer. Cancer Med 2021; 10:6610-6617. [PMID: 34469045 PMCID: PMC8495280 DOI: 10.1002/cam4.4197] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/08/2021] [Accepted: 07/16/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND This study aimed to explore the prognostic value of tumor mutational burden (TMB) combined with smoking status in advanced non-small cell lung cancer (NSCLC) patients who received immune checkpoint inhibitor therapy (anti PD-1/PD-L1 therapy) combined with chemotherapy or anti-angiogenesis therapy. METHODS We conducted a retrospective analysis of NSCLC patients who underwent next-generation sequencing test (either 295-gene panel NGS or 1021-gene panel NGS) from September 2017 to November 2020. The relationship between TMB and smoking status was investigated. Kaplan-Meier survival analysis was used to compare progression-free survival (PFS) of the NSCLC patients who received combination immunotherapy grouped by TMB value and smoking status. RESULTS We enrolled 323 cases and 388 cases of NSCLC patients in the 295-gene panel cohort and 1021-gene panel cohort, respectively. Positive correlation between TMB and smoking status was found in lung adenocarcinoma, but not in lung squamous cell carcinoma. Participants with both high TMB and smoking status who received immune checkpoint therapy combined with chemotherapy or anti-angiogenesis therapy had longer PFS than other participants (p < 0.05). CONCLUSIONS The combination of TMB with smoking status might be a potential predictor for the efficacy of combination immunotherapy in advanced NSCLC.
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Affiliation(s)
- Li‐Yue Sun
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Wen‐Jian Cen
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Wen‐Ting Tang
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Ya‐Kang Long
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Xin‐Hua Yang
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Xiao‐Meng Ji
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Jiao‐Jiao Yang
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Ren‐Jing Zhang
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Fang Wang
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Jian‐Yong Shao
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
| | - Zi‐Ming Du
- State Key Laboratory of Oncology in South ChinaGuangzhouChina
- Collaborative Innovation Center for Cancer MedicineGuangzhouChina
- Department of Molecular DiagnosticsSun Yat‐sen University Cancer CenterGuangzhouChina
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12
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Yang T, Hao L, Yang X, Luo C, Wang G, Lin Cai C, Qi S, Li Z. Prognostic value of derived neutrophil-to-lymphocyte ratio (dNLR) in patients with non-small cell lung cancer receiving immune checkpoint inhibitors: a meta-analysis. BMJ Open 2021; 11:e049123. [PMID: 34475167 PMCID: PMC8413941 DOI: 10.1136/bmjopen-2021-049123] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVES Derived neutrophil-to-lymphocytes ratio (dNLR) has recently been reported as a novel potential biomarker associated with prognosis of non-small cell lung cancer (NSCLC). However, evidence for the prognostic utility of dNLR in patients with NSCLC treated with immune checkpoint inhibitors (ICIs) remains inconsistent. The objective of this work was to evaluate the association between pretreatment dNLR and prognosis of patients with NSCLC treated with ICIs. DESIGN This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DATA SOURCES PubMed, EMBASE, Web of Science and the Cochrane Library were searched for eligible studies up to 16 October 2020. ELIGIBILITY CRITERIA: (1) Human subjects receiving ICIs therapy and who had been diagnosed with NSCLC; (2) the baseline values of dNLR were obtained; (3) the objective of the study was to investigate the relationships between dNLR and overall survival (OS) or progression-free survival (PFS) in NSCLC and (4) HR and 95% CI were displayed in the original article or could be extracted from Kaplan-Meier curves. DATA EXTRACTION AND SYNTHESIS Two investigators extracted data independently. Data synthesis was performed via systematic review and meta-analysis of eligible cohort studies. Meta-analysis was performed with Cochran's Q test and I2 statistics. Publication bias of studies was assessed by Begg's test and Egger's test. We used V.12.0 of the Stata statistical software. RESULTS This analysis included eight studies (2456 cases) on the prognostic utility of dNLR in ICI therapy for NSCLC. The results indicate that higher dNLR significantly predicted poor OS (HR=1.65, 95% CI 1.46 to 1.88; p<0.001) and PFS (HR=1.38, 95% CI 1.23 to 1.55; p<0.001). Subgroup analyses of OS-related studies indicated that there were similar results in stratifications by ethnicity, sample size, type of HR and dNLR cut-off value. As for PFS-related studies, subgroup analyses showed no significant difference in Asian populations. Publication biases were not detected using Begg's test and Egger's linear regression test. CONCLUSIONS This meta-analysis indicated that elevated pretreatment dNLR may be a negative prognostic predictor for patients with NSCLC treated with ICIs. More large-sample and higher-quality studies are warranted to support our findings. PROSPERO REGISTRATION NUMBER CRD42021214034.
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Affiliation(s)
- Tao Yang
- Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, China
- Beijing Shijitan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Lizheng Hao
- Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, China
| | - Xinyu Yang
- Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, China
| | - Changyong Luo
- Beijing University of Chinese Medicine, Beijing, China
| | - Guomi Wang
- Beijing University of Chinese Medicine, Beijing, China
| | | | - Shuo Qi
- Department of Thyroid, Sun Simiao hospital, Beijing University of Chinese Medicine, Tongchuan, China
| | - Zhong Li
- Department of Hematology and Oncology, Beijing University of Chinese Medicine Affiliated Dongzhimen Hospital, Beijing, China
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13
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Zeng H, Huang WW, Liu YJ, Huang Q, Zhao SM, Li YL, Tian PW, Li WM. Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer. Front Oncol 2021; 11:685047. [PMID: 34458139 PMCID: PMC8397581 DOI: 10.3389/fonc.2021.685047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 07/26/2021] [Indexed: 02/05/2023] Open
Abstract
Background Immune checkpoint inhibitors (ICIs) plus chemotherapy improved the prognosis of patients with non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers are lacking. We explored factors associated with prognosis and developed a predictive model. Methods We retrospectively analyzed 130 consecutive stage IIIA–IVB NSCLC patients treated with ICIs combined with chemotherapy. Cox univariate and multivariate proportional hazards regression analyses were used to identify prognostic factors associated with progression-free survival (PFS). A nomogram was developed based on key factors in the training cohort (n = 86) and evaluated in the validation cohort (n = 44). According to the nomogram-based total point scores, we divided patients into low- and high-risk groups. Results In the training cohort, bone metastases (p = 0.017) and an increased derived neutrophil-to-lymphocyte ratio (p = 0.018) were significantly associated with poor PFS, while smoking (p = 0.007) and programmed death-ligand 1 (PD-L1) ≥50% (p = 0.001) were associated with improved PFS. A nomogram based on these factors was developed to predict PFS at 3, 6, and 12 months. The C-index of the nomogram to predict PFS was 0.725 (95% CI: 0.711–0.739) in the training cohort and 0.688 (95% CI: 0.665–0.711) in the validation cohort. The area under the curve (AUC) exhibited an acceptable discriminative ability, and calibration curves demonstrated a consistency between the actual results and predictions. In the training cohort, the median PFS (mPFS) was 12.3 and 5.7 months in the low- and high-risk groups, respectively (p < 0.001). In the validation cohort, the mPFS was 12.6 and 6.2 months in the low- and high-risk groups, respectively (p = 0.021). Conclusions A predictive nomogram was developed to help clinicians assess prognosis early for advanced NSCLC patients who received ICI plus chemotherapy.
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Affiliation(s)
- Hao Zeng
- Department of Respiratory and Critical Care Medicine, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Wei-Wei Huang
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yu-Jie Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China
| | - Qin Huang
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, China
| | - Sheng-Min Zhao
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ya-Lun Li
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, China
| | - Pan-Wen Tian
- Department of Respiratory and Critical Care Medicine, Lung Cancer Treatment Center, West China Hospital, Sichuan University, Chengdu, China
| | - Wei-Min Li
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
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Liao ZX, Kempson IM, Hsieh CC, Tseng SJ, Yang PC. Potential therapeutics using tumor-secreted lactate in nonsmall cell lung cancer. Drug Discov Today 2021; 26:2508-2514. [PMID: 34325010 DOI: 10.1016/j.drudis.2021.07.014] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/03/2021] [Accepted: 07/19/2021] [Indexed: 01/13/2023]
Abstract
Targeted-therapy failure in treating nonsmall cell lung cancer (NSCLC) frequently occurs because of the emergence of drug resistance and genetic mutations. The same mutations also result in aerobic glycolysis, which further antagonizes outcomes by localized increases in lactate, an immune suppressor. Recent evidence indicates that enzymatic lowering of lactate can promote an oncolytic immune microenvironment within the tumour. Here, we review factors relating to lactate expression in NSCLC and the utility of lactate oxidase (LOX) for governing therapeutic delivery, its role in lactate oxidation and turnover, and relationships between lactate depletion and immune cell populations. The lactate-rich characteristic of NSCLC provides an exploitable property to potentially improve NSCLC outcomes and design new therapeutic strategies to integrate with conventional therapies.
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Affiliation(s)
- Zi-Xian Liao
- Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
| | - Ivan M Kempson
- Future Industries Institute, University of South Australia, Mawson Lakes, SA 5095, Australia
| | - Chia-Chen Hsieh
- Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan
| | - S-Ja Tseng
- Graduate Institute of Oncology, National Taiwan University College of Medicine, Taipei 10051, Taiwan; National Taiwan University YongLin Scholar, YongLin Institute of Health, National Taiwan University, Taipei 10051, Taiwan.
| | - Pan-Chyr Yang
- Graduate Institute of Oncology, National Taiwan University College of Medicine, Taipei 10051, Taiwan; Department of Internal Medicine, National Taiwan University College of Medicine, Taipei 10051, Taiwan; Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.
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15
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Cai JS, Dou XM, Li JB, Yang MZ, Xie CL, Hou X, Yang HX. Nomogram to Predict Cancer Specific Survival in Patients with Pathological Stage IA Non-small Cell Lung Cancer. Semin Thorac Cardiovasc Surg 2021; 34:1040-1048. [PMID: 34216749 DOI: 10.1053/j.semtcvs.2021.06.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 12/18/2022]
Abstract
We identified the prognostic factors of resected stage IA non-small cell lung cancer (NSCLC) and developed a nomogram, with purpose of defining the high-risk population who may need closer follow-up or more intensive care. Eligible stage IA NSCLC cases from the Surveillance, Epidemiology, and End Results (SEER) database and the Sun Yat-sen University Cancer Center (SYSUCC) were included. Stage IB NSCLCs were also included for evaluating the risk stratification efficacy. Cancer specific survival (CSS) was compared between groups. Statistically significant factors from multivariate analysis were entered into the nomogram. The performance of the nomogram was evaluated by concordance index (C-index) and calibration plots. A total of 23,112 NSCLC cases (SEER stage IA training cohort, N=7,777; SEER stage IA validation cohort, N=7,776; SEER stage IB cohort, N=7,559) from the SEER database were included. 1,304 NSCLC cases (SYSUCC stage IA validation cohort, N=684; SYSUCC stage IB cohort, N=620) from the SYSUCC were also included. Younger age, female, lobectomy, well differentiated, smaller size and more examined lymph nodes were identified as favorable prognostic factors. A nomogram was established. The C-index was 0.68 (95%CI, 0.67-0.69), 0.66 (95% CI, 0.64-0.68) and 0.66 (95% CI, 0.61-0.71) for the SEER training cohort, SEER validation cohort and SYSUCC validation cohort. A risk classification system was constructed to stratify stage IA NSCLC into low-risk subgroup and high-risk subgroup. The CSS curves of these two subgroups showed statistically significant distinctions. This nomogram delivered a prognostic prediction for stage IA NSCLC and may aid individual clinical practice.
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Affiliation(s)
- Jing-Sheng Cai
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China
| | - Xiao-Meng Dou
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China
| | - Ji-Bin Li
- State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; Department of Epidemiology and Biostatistics, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, P.R. China
| | - Mu-Zi Yang
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China
| | - Chu-Long Xie
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China
| | - Xue Hou
- State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China.
| | - Hao-Xian Yang
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China.
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