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Qiu Y, Chen Y, Shen H, Yan S, Li J, Wu W. Naples Prognostic Score: A Novel Predictor of Survival in Patients with Triple-Negative Breast Cancer. J Inflamm Res 2024; 17:5253-5269. [PMID: 39135978 PMCID: PMC11318610 DOI: 10.2147/jir.s472917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 08/02/2024] [Indexed: 08/15/2024] Open
Abstract
Purpose This study investigated the correlation between the Naples prognostic score (NPS), clinicopathological traits, and the postoperative prognoses of patients with triple-negative breast cancer (TNBC). Based on NPS, a predictive nomogram was developed to estimate the long-term survival probabilities of patients with TNBC post-surgery. Patients and Methods We retrospectively examined the clinical records of 223 women with TNBC treated at Ningbo Medical Center, Lihuili Hospital between January 1, 2016 and December 31, 2020. Blood tests and biochemical analyses were conducted before surgery. The prognostic nutritional index (PNI), controlling nutritional status (CONUT), neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and NPS were determined based on blood-related markers. A Kaplan-Meier survival analysis assessed the association between NPS, PNI, CONUT score, overall survival (OS), and breast cancer-specific survival (BCSS). Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUC) and C index. The patients were randomly divided into the training and the validation group (6:4 ratio). A nomogram prediction model was developed and evaluated using the R Software for Statistical Computing (RMS) package. Results NPS outperformed other scores in predicting inflammation outcomes. Patients with an elevated NPS had a poorer prognosis (P<0.001). Lymph node ratio (LNR), surgical method, postoperative chemotherapy, and NPS independently predicted OS, whereas M stage, LNR, and NPS independently predicted BCSS outcome. The OS and BCSS predicted by the nomogram model aligned well with the actual OS and BCSS. The decision curve analysis showed significant clinical utility for the nomogram model. Conclusion In this study, NPS was an important prognostic indicator for patients with TNBC. The nomogram prognostic model based on NPS outperformed other prognostic scores for predicting patient prognosis. The model demonstrated a clear stratification ability for patient prognosis, which emphasized the potential benefits of early intervention for high-risk patients.
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Affiliation(s)
- Yu Qiu
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
- Health Science Center, Ningbo University, Ningbo, Zhejiang, 315000, People’s Republic of China
| | - Yan Chen
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
- Health Science Center, Ningbo University, Ningbo, Zhejiang, 315000, People’s Republic of China
| | - Haoyang Shen
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
- Health Science Center, Ningbo University, Ningbo, Zhejiang, 315000, People’s Republic of China
| | - Shuixin Yan
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
- Health Science Center, Ningbo University, Ningbo, Zhejiang, 315000, People’s Republic of China
| | - Jiadi Li
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
- Health Science Center, Ningbo University, Ningbo, Zhejiang, 315000, People’s Republic of China
| | - Weizhu Wu
- The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315000, People’s Republic of China
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Wei C, Ai H, Mo D, Wang P, Wei L, Liu Z, Li P, Huang T, Liu M. A nomogram based on inflammation and nutritional biomarkers for predicting the survival of breast cancer patients. Front Endocrinol (Lausanne) 2024; 15:1388861. [PMID: 39170737 PMCID: PMC11335604 DOI: 10.3389/fendo.2024.1388861] [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: 02/20/2024] [Accepted: 07/24/2024] [Indexed: 08/23/2024] Open
Abstract
Background We aim to develop a new prognostic model that incorporates inflammation, nutritional parameters and clinical-pathological features to predict overall survival (OS) and disease free survival (DFS) of breast cancer (BC) patients. Methods The study included clinicopathological and follow-up data from a total of 2857 BC patients between 2013 and 2021. Data were randomly divided into two cohorts: training (n=2001) and validation (n=856) cohorts. A nomogram was established based on the results of a multivariate Cox regression analysis from the training cohorts. The predictive accuracy and discriminative ability of the nomogram were evaluated by the concordance index (C-index) and calibration curve. Furthermore, decision curve analysis (DCA) was performed to assess the clinical value of the nomogram. Results A nomogram was developed for BC, incorporating lymphocyte, platelet count, hemoglobin levels, albumin-to-globulin ratio, prealbumin level and other key variables: subtype and TNM staging. In the prediction of OS and DFS, the concordance index (C-index) of the nomogram is statistically greater than the C-index values obtained using TNM staging alone. Moreover, the time-dependent AUC, exceeding the threshold of 0.7, demonstrated the nomogram's satisfactory discriminative performance over different periods. DCA revealed that the nomogram offered a greater overall net benefit than the TNM staging system. Conclusion The nomogram incorporating inflammation, nutritional and clinicopathological variables exhibited excellent discrimination. This nomogram is a promising instrument for predicting outcomes and defining personalized treatment strategies for patients with BC.
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Affiliation(s)
- Caibiao Wei
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Huaying Ai
- Department of Injection Room, The People’s Hospital of Yingtan, Yingtan, Jiangxi, China
| | - Dan Mo
- Department of Breast, Guangxi Zhuang Autonomous Region Maternal and Child Health Care Hospital, Nanning, China
| | - Peidong Wang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Liling Wei
- Department of Anesthesiology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zhimin Liu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Peizhang Li
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Taijun Huang
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
| | - Miaofeng Liu
- Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China
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Hua X, Xu F, Shi W, Long ZQ, Huang X, Duan FF, Wang SF, Zhang C, Wang MD, Ni WQ, Xia W, Chen JY, Gao YS. Prognostic significance of platelet‑to‑albumin ratio in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy: a retrospective study of 858 cases. BMC Cancer 2024; 24:762. [PMID: 38918690 PMCID: PMC11197365 DOI: 10.1186/s12885-024-12499-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 06/10/2024] [Indexed: 06/27/2024] Open
Abstract
BACKGROUND Despite evidence supporting the high correlation of the novel platelet-to-albumin ratio (PAR) with survival in diverse malignancies, its prognostic relevance in nasopharyngeal carcinoma (NPC) remains underexplored. This study aimed to examine the link between PAR and overall survival (OS) in NPC and to establish a predictive model based on this biomarker. METHODS We retrospectively assembled a cohort consisting of 858 NPC patients who underwent concurrent chemoradiotherapy (CCRT). Utilizing the maximally selected log-rank method, we ascertained the optimal cut-off point for the PAR. Subsequently, univariate and multivariate Cox proportional hazards models were employed to discern factors significantly associated with OS and to construct a predictive nomogram. Further, we subjected the nomogram's predictive accuracy to rigorous independent validation. RESULTS The discriminative optimal PAR threshold was determined to be 4.47, effectively stratifying NPC patients into two prognostically distinct subgroups (hazard ratio [HR] = 0.53; 95% confidence interval [CI]: 0.28-0.98, P = 0.042). A predictive nomogram was formulated using the results from multivariate analysis, which revealed age greater than 45 years, T stage, N stage, and PAR score as independent predictors of OS. The nomogram demonstrated a commendable predictive capability for OS, with a C-index of 0.69 (95% CI: 0.64-0.75), surpassing the performance of the conventional staging system, which had a C-index of 0.56 (95% CI: 0.65-0.74). CONCLUSIONS In the context of NPC patients undergoing CCRT, the novel nutritional-inflammatory biomarker PAR emerges as a promising, cost-efficient, easily accessible, non-invasive, and potentially valuable predictor of prognosis. The predictive efficacy of the nomogram incorporating the PAR score exceeded that of the conventional staging approach, thereby indicating its potential as an enhanced prognostic tool in this clinical setting.
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Affiliation(s)
- Xin Hua
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Fei Xu
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Wei Shi
- Department of Oncology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhi-Qing Long
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Xin Huang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Fang-Fang Duan
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Si-Fen Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Chao Zhang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Meng-Di Wang
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Wei-Qiong Ni
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Wen Xia
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, SunYat-sen University Cancer Center, Guangzhou, China
| | - Jia-Yi Chen
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Yun-Sheng Gao
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China.
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Xue X, Li C, Chen D. A cross-sectional study investigating the relationship between urinary albumin creatinine ratio and abdominal aortic calcification in adults. Front Cardiovasc Med 2024; 11:1352921. [PMID: 38500760 PMCID: PMC10944970 DOI: 10.3389/fcvm.2024.1352921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 02/15/2024] [Indexed: 03/20/2024] Open
Abstract
Introduction The presence of abdominal aortic calcification (AAC) is strongly linked to the development of atherosclerosis and the incidence of morbidity and mortality related to cardiovascular diseases (CVD). Urinary albumin creatinine ratio (UACR) was found related with the increased risk of CVD. The aim of this study is to explore the relationship between the UACR and severe AAC (SAAC). Methods and Results This study included a total of 2,379 individuals aged over 40 years, and their information was obtained from the National Health and Nutrition Examination Survey conducted (NHANES) in 2013-2014. The measurement of AAC was conducted through dual-energy x-ray absorptiometry and assessed using the Kauppila scoring system. SAAC was characterized by a Kauppila score of 6 or higher. Multivariate regression models were used to analyze the relationship between UACR level and SAAC, with covariate adjustment. In the completely adapted model, the top third subgroup exhibits increased likelihood of SAAC (odds ratio 1.50; 95%CI: 0.98, 2.29; p = 0.030) in contrast to the bottom third subgroup. The subgroup analyses revealed a more pronounced correlation among the older participants (p-value for interaction = 0.013). Discussion In the United States, SAAC was more likely to occur in adults who had a higher probability of UACR. The use of UACR has the potential to be a valuable method for forecasting the likelihood of SAAC.
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Affiliation(s)
- Xian Xue
- Nanyang City Center Hospital, Nanyang, China
| | - Chen Li
- Nanyang Second General Hospital, Nanyang, China
| | - Dongping Chen
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Ma G, Tian Y, Zi J, Hu Y, Li H, Zeng Y, Luo H, Xiong J. Systemic inflammation mediates the association between environmental tobacco smoke and depressive symptoms: A cross-sectional study of NHANES 2009-2018. J Affect Disord 2024; 348:152-159. [PMID: 38158048 DOI: 10.1016/j.jad.2023.12.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/04/2023] [Accepted: 12/24/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Depression is associated with both environmental tobacco smoke (ETS) and inflammation. However, whether systemic inflammation mediates the ETS-depression relationship is unclear. METHODS We analyzed 19,612 participants from the 2009-2018 National Health and Nutrition Examination Survey (representing approximately 206,284,711 USA individuals), utilizing data of depressive symptoms (assessed by Patient Health Questionnaire-9), blood cotinine level (an ETS biomarker), dietary inflammatory index (DII, assessed by 24-h dietary recall) and inflammation, represented by immune-inflammation index (SII) and systemic inflammation response index (SIRI). RESULTS Weighted multivariable logistic regression showed that a higher blood cotinine level is significantly associated with a higher depressive symptoms risk (OR = 1.79, 1.35-2.38). After adjusting for covariates, the effect in smokers (OR = 1.220, 95 % CI: 1.140-1.309) is larger than that in non-smokers (OR = 1.150, 95 % CI: 1.009-1.318). Compared to the lowest level, depressive symptoms risks in participants with the highest level of SII, SIRI and DII are 19 % (OR = 1.19, 1.05-1.35), 15 % (OR = 1.15, 1.01-1.31) and 88 % (OR = 1.88, 1.48-2.39) higher, respectively. Weighted linear regression demonstrated positive correlations of SII (β = 0.004, 0.001-0.006), SIRI (β = 0.009, 0.005-0.012) and DII (β = 0.213, 0.187-0.240) with blood cotinine level. Restricted cubic splines model showed a linear dose-response relationship between blood cotinine and depressive symptoms (Pnon-linear = 0.410), with decreasing risk for lower DII. And SII and SIRI respectively mediate 0.21 % and 0.1 % of the association between blood cotinine and depressive symptoms. LIMITATION Cross-sectional design, and lack of medication data for depression. CONCLUSIONS Positive association of ETS (blood cotinine) with depressive symptoms risk is partly mediated by systemic inflammation, and anti-inflammatory diet could be beneficial.
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Affiliation(s)
- Guochen Ma
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Ye Tian
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Jing Zi
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Yifan Hu
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Haoqi Li
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Yaxian Zeng
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Hang Luo
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Jingyuan Xiong
- Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China; Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu 610041, China.
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Wang Z, Bao Y, Xu Z, Sun Y, Yan X, Sheng L, Ouyang G. A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Diffuse Large B Cell Lymphoma. J Inflamm Res 2024; 17:1-13. [PMID: 38193043 PMCID: PMC10771722 DOI: 10.2147/jir.s436392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 12/19/2023] [Indexed: 01/10/2024] Open
Abstract
Purpose This study aimed to examine the predictive ability of inflammatory and nutritional markers and further establish a novel inflammatory nutritional prognostic scoring (INPS) system. Patients and Methods We collected clinicopathological and baseline laboratory data of 352 patients with DLBCL between April 2010 and January 2023 at the First affiliated hospital of Ningbo University. Eligible patients were randomly divided into training and validation cohorts (n = 281 and 71, respectively) in an 8:2 ratio. We used the least absolute shrinkage and selection operator (LASSO) Cox regression model to determine the most important factors among the eight inflammatory-nutritional variables. The impact of INPS on OS was evaluated using the Kaplan-Meier curve and the Log rank test. A prognostic nomogram was developed based on the multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the nomogram. Results Seven inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), prognostic nutritional index (PNI), body mass index (BMI), monocyte-lymphocyte ratio (MLR), prealbumin, C reactive protein, and D-dimer were selected using the LASSO Cox analysis to construct INPS, In the multivariate analysis, IPI-High-intermediate group, IPI-High group, high INPS were independently associated with OS, respectively. The prognostic nomogram for overall survival consisting of the above two indicators showed excellent discrimination. The C-index for the nomogram was 0.94 and 0.95 in the training and validation cohorts. The time-dependent ROC curves showed that the predictive accuracy of the nomogram for OS was better than that of the NCCN-IPI system. Conclusion The INPS based on seven inflammatory-nutritional indexes was a reliable and convenient predictor of outcomes in DLBCL patients.
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Affiliation(s)
- Zanzan Wang
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Yurong Bao
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Zhijuan Xu
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Yongcheng Sun
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Xiao Yan
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Lixia Sheng
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
| | - Guifang Ouyang
- Department of Hematology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of China
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Cho JS, Cho YJ, Shim JK, Jeon Y, Lee S, Choi HW, Kwak YL. Risk stratification model integrating nutritional and inflammatory factors for predicting 1-year mortality after valvular heart surgery: a retrospective cohort study. Int J Surg 2024; 110:287-295. [PMID: 37800574 PMCID: PMC10793763 DOI: 10.1097/js9.0000000000000807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/18/2023] [Indexed: 10/07/2023]
Abstract
INTRODUCTION Existing risk-scoring systems for cardiac surgery include only standard preoperative factors without considering nutritional and inflammatory status or intraoperative factors. The objective of this study was to develop a comprehensive prediction model for mortality incorporating nutritional, inflammatory, and perioperative factors in patients undergoing valvular heart surgery. MATERIALS AND METHODS In this retrospective review of 2046 patients who underwent valvular heart surgery, Cox and LASSO regression analyses were performed to identify independent prognostic factors for 1-year postoperative mortality among various perioperative factors known to affect prognosis, including objective nutritional and inflammatory indices. A novel nomogram model incorporating selected prognostic factors was developed, and its discrimination ability was evaluated using the C-index. The model was validated in internal and external cohorts. RESULTS The 1-year mortality rate after valvular heart surgery was 5.1% (105 of 2046 patients) and was significantly associated with several preoperative objective inflammatory and nutritional indices. Cox and LASSO analyses identified the following five independent prognostic factors for mortality: monocyte-to-lymphocyte ratio (an objective inflammatory index), EuroSCORE II, Controlling Nutritional Status score, cardiopulmonary bypass time, and number of erythrocyte units transfused intraoperatively. The nomogram model incorporating these five factors had a C-index of 0.834 (95% CI: 0.791-0.877), which was higher than that of EuroSCORE II alone (0.744, 95% CI: 0.697-0.791) ( P <0.001). The nomogram achieved good discrimination ability, with C-indices of 0.836 (95% CI: 0.790-0.878) and 0.727 (95% CI: 0.651-0.803) in the internal and external validation cohorts, respectively, and showed well-fitted calibration curves. CONCLUSIONS A nomogram model incorporating five inflammatory, nutritional, and perioperative factors, as well as EuroSCORE II, was a better predictor of 1-year mortality after valvular heart surgery than EuroSCORE II alone, with good discrimination and calibration power for predicting mortality in both internal and external validation cohorts.
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Affiliation(s)
- Jin Sun Cho
- Department of Anaesthesiology and Pain Medicine
- Anaesthesia and Pain Research Institute, Yonsei University College of Medicine
| | - Youn Joung Cho
- Department of Anaesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jae-Kwang Shim
- Department of Anaesthesiology and Pain Medicine
- Anaesthesia and Pain Research Institute, Yonsei University College of Medicine
| | - Yunseok Jeon
- Department of Anaesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seohee Lee
- Department of Anaesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | - Young-Lan Kwak
- Department of Anaesthesiology and Pain Medicine
- Anaesthesia and Pain Research Institute, Yonsei University College of Medicine
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Zhai WY, Duan FF, Lin YB, Lin YB, Zhao ZR, Wang JY, Rao BY, Zheng L, Long H. Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy. J Inflamm Res 2023; 16:3329-3339. [PMID: 37576157 PMCID: PMC10422963 DOI: 10.2147/jir.s418276] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 08/01/2023] [Indexed: 08/15/2023] Open
Abstract
Background We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection. Methods The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR. Results Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response. Conclusion Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.
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Affiliation(s)
- Wen-Yu Zhai
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Fang-Fang Duan
- Department of Medical oncology, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
| | - Yao-Bin Lin
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Yong-Bin Lin
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Ze-Rui Zhao
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Jun-Ye Wang
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Bing-Yu Rao
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Lie Zheng
- Medical Imaging Division, Department of Medical Imaging and Interventional Radiology, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
| | - Hao Long
- Department of Thoracic Surgery, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China
- Lung Cancer Research Center, Sun Yat-Sen University, Guangzhou, People’s Republic of China
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Xu F, Ni W, Hua X, Xu C, Chen J, Cao W, Gao Y. A single center retrospective study assessing the prognostic significance of pre-treatment neutrophil/lymphocyte ratio in locally advanced nasopharyngeal carcinoma. Transl Cancer Res 2023; 12:1672-1683. [PMID: 37588746 PMCID: PMC10425666 DOI: 10.21037/tcr-23-528] [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: 03/25/2023] [Accepted: 06/25/2023] [Indexed: 08/18/2023]
Abstract
Background In light of the growing evidence suggesting the impact of inflammatory parameters on the survival of individuals with cancer, this research assessed the prognostic significance of the neutrophil-to-lymphocyte ratio (NLR) in individuals diagnosed with locally advanced nasopharyngeal carcinoma (NPC) prior to undergoing intensity-modulated radiation therapy (IMRT). Methods A total of 163 individuals diagnosed with locally advanced NPC treated with IMRT at our hospital between January 2012 and December 2017 were included in this research. For each patient, the absolute counts of neutrophils and lymphocytes were recorded, and the NLR was calculated at the first diagnosis. To determine the optimal cut-off values for NLR, receiver operating characteristic (ROC) curve analysis was conducted. The effects of the determined cut-off value on local failure-free survival (LFFS), overall survival (OS), progression-free survival (PFS), and distant failure-free survival (DFFS) were evaluated employing the Cox regression model. Results The median follow-up duration for the individuals in this study was 15 months (ranging from 6 to 79 months). According to the determined NLR cut-off value of 3.27, individuals were classified into two groups (high NLR and low NLR). Individuals in the high-NLR group had remarkably poorer 3-year OS (62.8% vs. 91.7%), PFS (51.4% vs. 82.4%), and DFFS (70.7% vs. 89.6%) compared to the low-NLR group. Furthermore, the outcomes of univariate and multivariate survival analyses revealed that NLR served as an independent predictor of DFFS (HR: 2.81, 95% CI: 1.195-6.608, P=0.018), OS (HR: 3.1, 95% CI: 1.211-7.935, P=0.018), and PFS (HR: 2.21, 95% CI: 1.133-4.292, P=0.02). Conclusions Elevated NLR exhibited a significant correlation with reduced OS, DFFS, and PFS. These findings suggest that NLR holds promise as a cost-effective and reliable marker for the prediction of clinical outcomes among patients with locoregionally advanced nasopharyngeal carcinoma (LANPC). Furthermore, incorporating NLR into clinical decision-making regarding LANPC treatment strategies may contribute to a more targeted approach aimed at reducing the risk of distant failure.
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Affiliation(s)
- Fei Xu
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqiong Ni
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin Hua
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Cheng Xu
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiayi Chen
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiguo Cao
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yunsheng Gao
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Hua X, Long ZQ, Wang SF, Xu F, Wang MD, Chen JY, Zhang YL, Ni WQ, Gao YS. Prognostic significance of the novel nutrition-inflammation marker of lymphocyte-C-reactive protein ratio in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy. Front Nutr 2023; 10:1162280. [PMID: 37545573 PMCID: PMC10399231 DOI: 10.3389/fnut.2023.1162280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 06/27/2023] [Indexed: 08/08/2023] Open
Abstract
Background Recent studies indicate that the novel lymphocyte-C-reactive protein ratio (LCR) is strongly associated with the survival of various tumors, but its prognostic value in nasopharyngeal carcinoma (NPC) is understudied. This study aimed to explore the relationship between LCR and overall survival (OS) in NPC and develop a predictive model. Methods A total of 841 NPC patients who received concurrent chemoradiotherapy (CCRT) between January 2010 and December 2014 were retrospectively enrolled and randomly divided into a training cohort (n = 589) and a validation cohort (n = 252), and 122 patients between January 2015 and March 2015 were included as an additional validation cohort. Univariate and multivariate Cox analyses were performed to identify variables associated with OS and construct a predictive nomogram. The predictive accuracy of the nomogram was evaluated and independently validated. Results The LCR score differentiated NPC patients into two groups with distinct prognoses (HR = 0.53; 95% CI: 0.32-0.89, P = 0.014). Multivariate analysis showed that age, T stage, N stage, EBV-DNA status, and LCR score were independently associated with OS, and a predictive nomogram was developed. The nomogram had a good performance for the prediction of OS [C-index = 0.770 (95% CI: 0.675-0.864)]. and outperformed the traditional staging system [C-index = 0.589 (95% CI: 0.385-0.792)]. The results were internally and additionally validated using independent cohorts. Conclusion The pretreatment LCR could independently predict the overall survival in NPC patients. A novel LCR-based prognostic model of an easy-to-use nomogram was established, and it outperformed the conventional staging system in terms of predictive power. Further external verification remains necessary.
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Affiliation(s)
- Xin Hua
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Zhi-Qing Long
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Si-Fen Wang
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Fei Xu
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Meng-Di Wang
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Jia-Yi Chen
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Yu-Ling Zhang
- Department of Endocrinology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China
| | - Wei-Qiong Ni
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Yun-Sheng Gao
- Department of Radiation Oncology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
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He J, Tong L, Wu P, Wu Y, Shi W, Chen L. Prognostic Significance of Preoperative Lactate Dehydrogenase to Albumin Ratio in Breast Cancer: A Retrospective Study. Int J Gen Med 2023; 16:507-514. [PMID: 36789133 PMCID: PMC9922482 DOI: 10.2147/ijgm.s396871] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/31/2023] [Indexed: 02/10/2023] Open
Abstract
Purpose We explored the relationship between platelet count to lymphocyte count ratio (PLR), monocyte count to lymphocyte count ratio (MLR), lactate dehydrogenase to albumin ratio (LAR), and long-term survival in patients with breast cancer. Patients and Methods We retrospectively analyzed the clinical and follow-up data of 134 patients with breast cancer. The receiver operating characteristic curve (ROC curve) was used to distinguish between the low and high ratio groups. The chi-square test or Fisher's exact test was used to calculate the differences among the investigation factors. The Kaplan-Meier method was used to draw the survival curves. Log rank test was used for univariate analysis, and Cox proportional hazards regression model was used for multivariate analysis. A P value of <0.05 was considered statistically significant. Results The median follow-up time was 45 months. The PFS rates in the low group (LAR≤3.4066) at 18 months, 24 months, and 36 months were 100%, 100%, and 97.6%, and those in the high group (LAR > 3.4066) were 97.7%, 94.3%, and 87.3%, respectively. LAR was associated with Age (P=0.002) and BMI (body mass index) (P=0.002). Univariate analysis showed that Tumor size (P=0.027), Node positivity (P<0.001), TNM (tumor-node-metastasis) stage (P<0.001), PLR (P=0.034), MLR (P=0.038), and LAR (P=0.035) were significantly associated with PFS (progression-free survival) in breast cancer patients. Multivariate analysis showed that Node positivity (P<0.001) and LAR (P=0.035) were associated with PFS, while PLR and MLR were not independent prognostic indicators. Conclusion Preoperative high LAR will be an independent predictor of prognosis in patients with breast cancer.
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Affiliation(s)
- Jing He
- Department of Breast Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Ling Tong
- Human Reproductive Medicine Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Ping Wu
- Department of Clinical Nutrition, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Yibo Wu
- Human Reproductive Medicine Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Weifeng Shi
- Department of Breast Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China
| | - Ling Chen
- Department of Breast Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, People’s Republic of China,Correspondence: Ling Chen; Weifeng Shi, Email ;
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Xia Y, Xia C, Wu L, Li Z, Li H, Zhang J. Systemic Immune Inflammation Index (SII), System Inflammation Response Index (SIRI) and Risk of All-Cause Mortality and Cardiovascular Mortality: A 20-Year Follow-Up Cohort Study of 42,875 US Adults. J Clin Med 2023; 12:jcm12031128. [PMID: 36769776 PMCID: PMC9918056 DOI: 10.3390/jcm12031128] [Citation(s) in RCA: 90] [Impact Index Per Article: 90.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/21/2023] [Accepted: 01/28/2023] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND AND AIM Chronic low-grade inflammation is associated with various health outcomes, including cardiovascular diseases (CVDs) and cancers. Systemic immune inflammation index (SII) and system inflammation response index (SIRI) have lately been explored as novel prognostic markers for all-cause mortality and cardiovascular mortality. However, studies on prediction value in nationwide representative population are scarce, which limit their generalization. To bridge the knowledge gap, this study aims to prospectively assess the association of SII, SIRI with all-cause mortality and cardiovascular mortality in the National Health and Nutrition Examination Survey (NHANES). METHODS From 1999 to 2018, 42,875 adults who were free of pregnancy, CVDs (stroke, acute coronary syndrome), cancers, and had follow-up records and participated in the NHANES were included in this study. SII and SIRI were quantified by calculating the composite inflammation indicators from the blood routine. To explore the characteristics of the population in different SII or SIRI levels, we divided them according to the quartile of SII or SIRI. The associations between SII, SIRI, and all-cause mortality and cardiovascular mortality events were examined using a Cox regression model. To investigate whether there was a reliable relationship between these two indices and mortalities, we performed subgroup analysis based on sex and age. RESULTS A total of 42,875 eligible individuals were enrolled, with a mean age of 44 ± 18 years old. During the follow-up period of up to 20 years, 4250 deaths occurred, including 998 deaths from CVDs. Cox proportional hazards modeling showed that adults with SII levels of >655.56 had higher all-cause mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.18-1.41) and cardiovascular mortality (HR, 1.33; 95% CI, 1.11-1.59) than those with SII levels of <335.36. Adults with SIRI levels of >1.43 had higher risk of all-cause (HR, 1.39; 95% CI, 1.26-1.52) and cardiovascular death (HR, 1.39; 95% CI, 1.14-1.68) than those with SIRI levels of <0.68. In general population older than 60 years, the elevation of SII or SIRI was associated with the risk of all-cause death. CONCLUSION Two novel inflammatory composite indices, SII and SIRI, were closely associated with cardiovascular death and all-cause death, and more attention should be paid to systemic inflammation to provide better preventive strategies.
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Affiliation(s)
- Yiyuan Xia
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Chunlei Xia
- Department of Intensive Medicine, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing 211166, China
| | - Lida Wu
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Zheng Li
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Hui Li
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Junxia Zhang
- Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
- Correspondence: ; Tel.: +86-153-6615-5682
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A Novel Inflammatory and Nutritional Prognostic Scoring System for Nonpathological Complete Response Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy. DISEASE MARKERS 2022; 2022:8044550. [PMID: 36569222 PMCID: PMC9788886 DOI: 10.1155/2022/8044550] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 11/08/2022] [Accepted: 11/22/2022] [Indexed: 12/23/2022]
Abstract
Background It has been demonstrated that inflammatory and nutritional variables are associated with poor breast cancer survival. However, some studies do not include these variables due to missing data. To investigate the predictive potential of the INPS, we constructed a novel inflammatory-nutritional prognostic scoring (INPS) system with machine learning. Methods This retrospective analysis included 249 patients with malignant breast tumors undergoing neoadjuvant chemotherapy (NAC). After comparing seven potent machine learning models, the best model, Xgboost, was applied to construct an INPS system. K-M survival curves and the log-rank test were employed to determine OS and DFS. Univariate and multivariate analyses were carried out with the Cox regression model. Additionally, we compared the predictive power of INPS, inflammatory, and standard nutritional variables using the Z test. Results After comparing seven machine learning models, it was determined that the XGBoost model had the best OS and DFS performance (AUC = 0.865 and 0.771, respectively). For overall survival (OS, cutoff value = 0.3917) and disease-free survival (cutoff value = 0.4896), all patients were divided into two groups by the INPS. Those with low INPS had higher 5-year OS and DFS rates (77.2% vs. 50.0%, P < 0.0001; and 59.6% vs. 32.1%, P < 0.0001, respectively) than patients with high INPS. For OS and DFS, the INPS exhibited the highest AUC compared to the other inflammatory and nutritional variables (AUC = 0.615, P = 0.0003; AUC = 0.596, P = 0.0003, respectively). Conclusion The INPS was an independent predictor of OS and DFS and exhibited better predictive ability than BMI, PNI, and MLR. For patients undergoing NAC for nonpCR breast cancer, INPS was a crucial and comprehensive biomarker. It could also forecast individual survival in breast cancer patients with low HER-2 expression.
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Feng J, Wang L, Yang X, Chen Q, Cheng X. Prognostic prediction by a novel integrative inflammatory and nutritional score based on least absolute shrinkage and selection operator in esophageal squamous cell carcinoma. Front Nutr 2022; 9:966518. [PMID: 36438741 PMCID: PMC9686353 DOI: 10.3389/fnut.2022.966518] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 10/25/2022] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND This study aimed to establish and validate a novel predictive model named integrative inflammatory and nutritional score (IINS) for prognostic prediction in esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS We retrospectively recruited 494 pathologically confirmed ESCC patients with surgery and randomized them into training (n = 346) or validation group (n = 148). The least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) regression analysis was initially used to construct a novel predictive model of IINS. The clinical features and prognostic factors with hazard ratio (HRs) and 95% confidence intervals (CIs) grouped by IINS were analyzed. Nomogram was also established to verify the prognostic value of IINS. RESULTS According to the LASSO Cox PH regression analysis, a novel score of IINS was initially constructed based on 10 inflammatory and nutritional indicators with the optimal cut-off level of 2.35. The areas under the curve (AUCs) of IINS regarding prognostic ability in 1-year, 3-years, and 5-years prediction were 0.814 (95% CI: 0.769-0.854), 0.748 (95% CI: 0.698-0.793), and 0.792 (95% CI: 0.745-0.833) in the training cohort and 0.802 (95% CI: 0.733-0.866), 0.702 (95% CI: 0.621-0.774), and 0.748 (95% CI: 0.670-0.816) in the validation cohort, respectively. IINS had the largest AUCs in the two cohorts compared with other prognostic indicators, indicating a higher predictive ability. A better 5-years cancer-specific survival (CSS) was found in patients with IINS ≤ 2.35 compared with those with IINS > 2.35 in both training cohort (54.3% vs. 11.1%, P < 0.001) and validation cohort (53.7% vs. 18.2%, P < 0.001). The IINS was then confirmed as a useful independent factor (training cohort: HR: 3.000, 95% CI: 2.254-3.992, P < 0.001; validation cohort: HR: 2.609, 95% CI: 1.693-4.020, P < 0.001). Finally, an IINS-based predictive nomogram model was established and validated the CSS prediction (training set: C-index = 0.71 and validation set: C-index = 0.69, respectively). CONCLUSION Preoperative IINS is an independent predictor of CSS in ESCC. The nomogram based on IINS may be used as a potential risk stratification to predict individual CSS and guide treatment in ESCC with radical resection.
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Affiliation(s)
- Jifeng Feng
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
- Department of Thoracic Oncological Surgery, Chinese Academy of Science, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
- Chinese Academy of Science, Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
| | - Liang Wang
- Department of Thoracic Oncological Surgery, Chinese Academy of Science, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
| | - Xun Yang
- Department of Thoracic Oncological Surgery, Chinese Academy of Science, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
| | - Qixun Chen
- Department of Thoracic Oncological Surgery, Chinese Academy of Science, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
| | - Xiangdong Cheng
- Chinese Academy of Science, Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Key Laboratory of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang Province, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Hangzhou, China
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Zhang X, Li N, Cui Y, Wu H, Jiao J, Yu Y, Gu G, Chen G, Zhang H, Yu S. Plasma metabolomics analyses highlight the multifaceted effects of noise exposure and the diagnostic power of dysregulated metabolites for noise-induced hearing loss in steel workers. Front Mol Biosci 2022; 9:907832. [PMID: 36060246 PMCID: PMC9437629 DOI: 10.3389/fmolb.2022.907832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/07/2022] [Indexed: 11/13/2022] Open
Abstract
Noise exposure can lead to various kinds of disorders. Noise-induced hearing loss (NIHL) is one of the leading disorders confusing the noise-exposed workers. It is essential to identify NIHL markers for its early diagnosis and new therapeutic targets for its treatment. In this study, a total of 90 plasma samples from 60 noise-exposed steel factory male workers (the noise group) with (NIHL group, n = 30) and without NIHL (non-NIHL group, n = 30) and 30 male controls without noise exposure (control group) were collected. Untargeted human plasma metabolomic profiles were determined with HPLC-MS/MS. The levels of the metabolites in the samples were normalized to total peak intensity, and the processed data were subjected to multivariate data analysis. The Wilcoxon test and orthogonal partial least square-discriminant analysis (OPLS-DA) were performed. With the threshold of p < 0.05 and the variable importance of projection (VIP) value >1, 469 differential plasma metabolites associated with noise exposure (DMs-NE) were identified, and their associated 58 KEGG pathways were indicated. In total, 33 differential metabolites associated with NIHL (DMs-NIHL) and their associated 12 KEGG pathways were identified. There were six common pathways associated with both noise exposure and NIHL. Through multiple comparisons, seven metabolites were shown to be dysregulated in the NIHL group compared with the other two groups. Through LASSO regression analysis, two risk models were constructed for NIHL status predication which could discriminate NIHL from non-NIHL workers with the area under the curve (AUC) values of 0.840 and 0.872, respectively, indicating their efficiency in NIHL diagnosis. To validate the results of the metabolomics, cochlear gene expression comparisons between susceptible and resistant mice in the GSE8342 dataset from Gene Expression Omnibus (GEO) were performed. The immune response and cell death-related processes were highlighted for their close relations with noise exposure, indicating their critical roles in noise-induced disorders. We concluded that there was a significant difference between the metabolite’s profiles between NIHL cases and non-NIHL individuals. Noise exposure could lead to dysregulations of a variety of biological pathways, especially immune response and cell death-related processes. Our results might provide new clues for noise exposure studies and NIHL diagnosis.
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Affiliation(s)
- Xiuzhi Zhang
- Department of Pathology, Henan Medical College, Zhengzhou, Henan, China
| | - Ningning Li
- Department of Scientific Research and Foreign Affairs, Henan Medical College, Zhengzhou, Henan, China
| | - Yanan Cui
- Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Hui Wu
- Henan Institute for Occupational Health, Zhengzhou, Henan, China
| | - Jie Jiao
- Henan Institute for Occupational Health, Zhengzhou, Henan, China
| | - Yue Yu
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Guizhen Gu
- Henan Institute for Occupational Health, Zhengzhou, Henan, China
| | - Guoshun Chen
- Wugang Institute for Occupational Health, Wugang, Henan, China
| | - Huanling Zhang
- Wugang Institute for Occupational Health, Wugang, Henan, China
| | - Shanfa Yu
- School of Public Health, Henan Medical College, Zhengzhou, Henan, China
- *Correspondence: Shanfa Yu,
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