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Cheng W, Li T, Wang X, Xu T, Zhang Y, Chen J, Wei Z. The neutrophil-to-apolipoprotein A1 ratio is associated with adverse outcomes in patients with acute decompensated heart failure at different glucose metabolic states: a retrospective cohort study. Lipids Health Dis 2024; 23:118. [PMID: 38649986 PMCID: PMC11034163 DOI: 10.1186/s12944-024-02104-1] [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: 01/25/2024] [Accepted: 04/06/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND The present study was performed to assess the association between the neutrophil-to-apolipoprotein A1 ratio (NAR) and outcomes in patients with acute decompensated heart failure (ADHF) at different glucose metabolism states. METHODS We recruited 1233 patients with ADHF who were admitted to Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from December 2014 to October 2019. The endpoints were defined as composites of cardiovascular death, nonfatal myocardial infarction, nonfatal ischemic stroke and exacerbation of chronic heart failure. The restricted cubic spline was used to determine the best cutoff of NAR, and patients were divided into low and high NAR groups. Kaplan-Meier plots and multivariable Cox proportional hazard models were used to investigate the association between NAR and the risk of adverse outcomes. RESULTS During the five-year follow-up period, the composite outcome occurred in 692 participants (56.1%). After adjusting for potential confounding factors, a higher NAR was associated with a higher incidence of composite outcomes in the total cohort (Model 1: HR = 1.42, 95% CI = 1.22-1.65, P<0.001; Model 2: HR = 1.29, 95% CI = 1.10-1.51, P = 0.002; Model 3: HR = 1.20, 95% CI = 1.01-1.42, P = 0.036). At different glucose metabolic states, a high NAR was associated with a high risk of composite outcomes in patients with diabetes mellitus (DM) (Model 1: HR = 1.54, 95% CI = 1.25-1.90, P<0.001; Model 2: HR = 1.40, 95% CI = 1.13-1.74, P = 0.002; Model 3: HR = 1.31, 95% CI = 1.04-1.66, P = 0.022), and the above association was not found in patients with prediabetes mellitus (Pre-DM) or normal glucose regulation (NGR) (both P>0.05). CONCLUSIONS The NAR has predictive value for adverse outcomes of ADHF with DM, which implies that the NAR could be a potential indicator for the management of ADHF.
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Affiliation(s)
- Weimeng Cheng
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Tianyue Li
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Xiaohan Wang
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Tingting Xu
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Ying Zhang
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Jianzhou Chen
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China.
| | - Zhonghai Wei
- Department of Cardiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China.
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Lin Z, Luo C, Yuan Y. The Ratio of Monocyte to Apolipoprotein A1 is an Independent Predictor of Breast Cancer: A Retrospective Study. Cancer Manag Res 2023; 15:423-432. [PMID: 37214188 PMCID: PMC10198180 DOI: 10.2147/cmar.s402770] [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: 01/31/2023] [Accepted: 05/06/2023] [Indexed: 05/24/2023] Open
Abstract
Objective To explore the predictive value of the ratio of monocyte to apolipoprotein A1 (MAR) (a new index related to inflammation and lipid in breast cancer (BC)) and its relationship with clinicopathological staging. Methods The hematological test results of 394 patients with breast diseases, including 276 cases of BC, 118 cases of benign breast disease (BBD), and 219 healthy volunteers (HV), were retrospectively collected. The clinical value of MAR was analyzed with binary logistic regression. Results Using statistical software analysis, the results showed that MAR level (P<0.001) was the largest in the BC group, followed by BBD, and the lowest in the HV group, and it was found to be an indicator to distinguish BC from BBD, also an independent risk factor for BC. The increase in MAR level showed that the risk of BC was 3.733 times higher than that of HV (P<0.001). In addition, there was a notable difference in MAR between early, middle and late stages of BC patients (P=0.047), with the highest MAR level in late stage (0.510±0.078) and the lowest MAR level in early stage (0.392±0.011); the MAR level of those with tumor invasion depth of Phase 4 was the highest (0.484±0.072), and that of Phase 1/2 was the lowest (0.379±0.010), with a statistically significant difference (P<0.001). MAR was positively correlated with tumor invasion depth (P<0.001, r=0.210), that's, the size of MAR increased when there was more deeper tumor invasion. Conclusion MAR is a new indicator for the auxiliary differential diagnosis of benign and malignant breast diseases, and is also an independent risk factor for BC. High-level MAR is closely related to late staging and tumor invasion depth of BC. It can be seen that MAR is a potentially valuable predictor of BC, and this is the first study to explore the clinical value of MAR in BC.
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Affiliation(s)
- Zhongyuan Lin
- Department of Clinical Laboratory, The People’s Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China
| | - Changliang Luo
- Department of Clinical Laboratory, The People’s Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China
| | - Yulin Yuan
- Department of Clinical Laboratory, The People’s Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China
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Zhang X, Wei M, Bo Y, Song J, Yu Y, Zhou X, Tang B. Predictive value of neutrophil-to-apolipoprotein A1 ratio in all-cause and cardiovascular death in elderly non-valvular atrial fibrillation patients. Heliyon 2023; 9:e12918. [PMID: 36820183 PMCID: PMC9938414 DOI: 10.1016/j.heliyon.2023.e12918] [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: 09/28/2022] [Revised: 12/13/2022] [Accepted: 01/09/2023] [Indexed: 01/13/2023] Open
Abstract
Neutrophil-to-apolipoprotein AI ratio's (NAR's) predictive value for the elderly non-valvular atrial fibrillation (NVAF) patients' death has not been fully recognized. We consecutively enrolled 1224 elderly patients with NVAF (≥75 years). With an average follow-up of 733.35 ± 271.39 days, 222 all-cause deaths were identified. Among these, 101 were caused by cardiovascular diseases. Cox regression showed that after correcting for potential confounders, patients in the Q4 group had an increased all-cause (hazard ratio [HR] = 1.90, 95% confidence interval [CI]: 1.20-2.99) and cardiovascular death (HR = 2.59, 95% CI: 1.30-5.15) risk compared to those in the lowest NAR quartile. Kaplan-Meier analysis indicated that all-cause and cardiovascular death were higher in the high NAR than those in the lowest NAR category (log rank, all, P < 0.001). A nonlinear association was observed between death and NAR. NAR may be a promising predictive biomarker for identifying elderly NVAF patients with poor clinical prognoses.
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Affiliation(s)
- Xiaoxue Zhang
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China
| | - Meng Wei
- Department of Outpatient, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China
| | - Yakun Bo
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China
| | - Jie Song
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China
| | - Yaping Yu
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China
| | - Xianhui Zhou
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Corresponding author.Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China.
| | - Baopeng Tang
- Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Xinjiang Key Laboratory of Cardiac Electrophysiology and Remodeling, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China,Corresponding author.Department of Cardiac Pacing and Electrophysiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054 P.R., China.
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He Y, Chen J, Ma Y, Chen H. Apolipoproteins: New players in cancers. Front Pharmacol 2022; 13:1051280. [PMID: 36506554 PMCID: PMC9732396 DOI: 10.3389/fphar.2022.1051280] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/15/2022] [Indexed: 11/26/2022] Open
Abstract
Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.
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Affiliation(s)
- Yingcheng He
- Department of Histology and Embryology, Medical College of Nanchang University, Nanchang, Jiangxi, China,Medical Department, Queen Mary School, Nanchang University, Nanchang, Jiangxi, China
| | - Jianrui Chen
- Department of Histology and Embryology, Medical College of Nanchang University, Nanchang, Jiangxi, China,Medical Department, Queen Mary School, Nanchang University, Nanchang, Jiangxi, China
| | - Yanbing Ma
- Department of Histology and Embryology, Medical College of Nanchang University, Nanchang, Jiangxi, China,Medical Department, Queen Mary School, Nanchang University, Nanchang, Jiangxi, China
| | - Hongping Chen
- Department of Histology and Embryology, Medical College of Nanchang University, Nanchang, Jiangxi, China,Jiangxi Key Laboratory of Experimental Animals, Nanchang University, Nanchang, Jiangxi, China,*Correspondence: Hongping Chen,
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Development and validation of a risk prediction model for overall survival in patients with nasopharyngeal carcinoma: a prospective cohort study in China. Cancer Cell Int 2022; 22:360. [PMCID: PMC9675189 DOI: 10.1186/s12935-022-02776-8] [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: 08/18/2022] [Accepted: 11/02/2022] [Indexed: 11/21/2022] Open
Abstract
Objective Nasopharyngeal carcinoma (NPC) is prevailing in Southern China, characterized by distinct geographical distribution. Aimed to predict the overall survival (OS) of patients with nasopharyngeal carcinoma, this study developed and validated nomograms considering demographic variables, hematological biomarkers, and oncogenic pathogens in China. Methods The clinicopathological and follow-up data of the nasopharyngeal carcinoma patients obtained from a prospective longitudinal cohort study in the Chongqing University Cancer Hospital between Jan 1, 2017 and Dec 31, 2019 (\documentclass[12pt]{minimal}
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\begin{document}$$\mathrm{n}=1635$$\end{document}n=1635). Cox regression model was used to tested the significance of all available variables as prognostic factors of OS. And independent prognostic factors were identified based on multivariable analysis to model nomogram. Concordance index (C-index), area under the receiver operating characteristic (AUC), calibration curve, and decision curve analysis (DCA) were measured to assess the model performance of nomogram. Results Data was randomly divided into a training cohort (1227 observers, about 70% of data) and a validation group (408 observers, about 30% of data). At multivariable analysis, the following were independent predictors of OS in NPC patients and entered into the nomogram: age (hazard ratio [HR]: 1.03), stage (stage IV vs. stage I–II, HR: 4.54), radiotherapy (Yes vs. No, HR: 0.43), EBV (\documentclass[12pt]{minimal}
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\begin{document}$$<1000$$\end{document}<1000, HR: 1.92), LAR (\documentclass[12pt]{minimal}
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\begin{document}$$>6.15$$\end{document}>6.15 vs.\documentclass[12pt]{minimal}
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\begin{document}$$\le 6.15$$\end{document}≤6.15, HR: 2.05), NLR (\documentclass[12pt]{minimal}
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\begin{document}$$>4.84$$\end{document}>4.84 vs. \documentclass[12pt]{minimal}
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\begin{document}$$\le 4.84$$\end{document}≤4.84 HR: 1.54), and PLR (\documentclass[12pt]{minimal}
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\begin{document}$$>206.33$$\end{document}>206.33 vs.\documentclass[12pt]{minimal}
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\begin{document}$$\le 206.33$$\end{document}≤206.33, HR: 1.79). The C-indexes for training cohort at 1-, 3- and 5-year were 0.73, 0.83, 0.80, respectively, in the validation cohort, the C-indexes were 0.74 (95% CI 0.63–0.86), 0.80 (95% CI 0.73–0.87), and 0.77 (95% CI 0.67–0.86), respectively. The calibration curve demonstrated that favorable agreement between the predictions of the nomograms and the actual observations in the training and validation cohorts. In addition, the decision curve analysis proved that the nomogram model had the highest overall net benefit. Conclusion A new prognostic model to predict OS of patients with NPC was developed. This can offer clinicians treatment making and patient counseling. Furthermore, the nomogram was deployed into a website server for use.
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The Prognostic Value of Serum Apolipoprotein A-I Level and Neutrophil-to-Lymphocyte Ratio in Colorectal Cancer Liver Metastasis. JOURNAL OF ONCOLOGY 2022; 2022:9149788. [PMID: 36204177 PMCID: PMC9532097 DOI: 10.1155/2022/9149788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/08/2022] [Indexed: 12/24/2022]
Abstract
Background Colorectal cancer liver metastasis (CRLM) is a high degree of malignancy with rapid disease progression and has a poor prognosis. Both serum apolipoprotein A-I (ApoA-I) and neutrophil-to-lymphocyte ratio (NLR) play key roles in anti-inflammation and antitumor. This study is aimed at evaluating the implication of serum ApoA-I level in combination with NLR in the prognosis of CRLM. Methods We retrospectively analyzed the serum ApoA-I level and NLR in 237 patients with CRLM. Cox regression analyses were used to identify the independent prognostic significance of these indicators. Kaplan-Meier method and Log-rank test were applied to compute overall survival (OS). Both the ApoA-I and NLR were divided into three levels, according to their medians. A risk-stratified prediction model was established to evaluate the prognosis of patients with CRLM. The ROC curve AUC values were applied to evaluate the capability of the model. Results Higher levels of ApoA-I and lower NLR were strongly associated with prolonged OS (Log-rank test, P < 0.05). The patients were then grouped into three queues according to the ApoA-I level and NLR. There was a crucial diversity in the OS (P < 0.001) between the high-risk (ApoA − I ≤ 1.03 g/L and NLR > 3.24), medium-risk (ApoA − I > 1.03 g/L or NLR ≤ 3.24) and low-risk groups (ApoA − I > 1.03 g/L and NLR ≤ 3.24). The AUC value of the prediction model (AUC = 0.623, 95% CI: 0.557-0.639, P = 0.001) was higher than other individual indicators (including ApoA-I, NLR, cT classification, and cN classification). Additionally, the association of the prediction model and cTN classification (AUC = 0.715, 95% CI: 0.606-0.708, P < 0.001) was better than the model and cTN classification alone. Conclusion The combination of ApoA-I level and NLR could be a prognostic indicator for CRLM.
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