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Ji P, He J. Prognostic value of pretreatment systemic immune-inflammation index in patients with endometrial cancer: a meta-analysis. Biomark Med 2024; 18:345-356. [PMID: 38623927 PMCID: PMC11218804 DOI: 10.2217/bmm-2023-0629] [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: 10/07/2023] [Accepted: 03/06/2024] [Indexed: 04/17/2024] Open
Abstract
Background: The present work focused on evaluating the systemic immune-inflammation index (SII) for its role in predicting endometrial cancer (EC) patient prognosis by meta-analysis. Methods: SII's role in predicting the prognosis of EC patients was analyzed by calculating combined hazard ratios (HRs) and 95% CIs. Results: As revealed by combined analysis, an increased SII predicted poor overall survival (HR = 2.01; 95% CI = 1.58-2.57; p < 0.001) as well as inferior progression-free survival (HR = 1.87; 95% CI = 1.36-2.58; p < 0.001) of EC. Conclusion: An increased SII score significantly predicted poor overall survival and progression-free survival in subjects with EC. The SII is suitable for predicting short- and long-term prognoses of patients with EC.
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Affiliation(s)
- Pengtian Ji
- Department of Oncological Radiotherapy, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, The Fifth School of Clinical Medicine of Zhejiang Chinese Medical University, Huzhou, Zhejiang, 313000, China
| | - Junjun He
- Clinical Laboratory, Huzhou Traditional Chinese Medicine Hospital Affiliated to Zhejiang Chinese Medical University, Huzhou, Zhejiang, China
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Zhang J, Wang D, Peng L, Shi X, Shi Y, Zhang G. Preoperative evaluation and a nomogram prediction model for pelvic lymph node metastasis in endometrial cancer. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024; 50:108230. [PMID: 38430704 DOI: 10.1016/j.ejso.2024.108230] [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: 11/27/2023] [Revised: 02/19/2024] [Accepted: 02/24/2024] [Indexed: 03/05/2024]
Abstract
OBJECTIVE The primary objective of this study is to explore the preoperative risk factors of pelvic lymph node metastasis (PLNM) in endometrial cancer patients, and construct a nomogram prediction model. MATERIALS AND METHODS We retrospectively collected various preoperative clinical characteristics of patients and analyzed their relationship with PLNM. Logistic regression analysis was used to screen for independent risk factors for PLNM of endometrial cancer. A nomogram prediction model was constructed, the receiver operating characteristic (ROC), calibration curve and decision curve analysis (DCA) were constructed and used to assess discrimination, calibration, and net benefit. RESULTS Out of the 276 patients, 74 (26.81%) with postoperative pathological confirmation of PLNM. Multivariate logistic regressive analysis demonstrated that preoperative depth of myometrial invasion (DIM) ≥50% determined by Magnetic Resonance Imaging (MRI) (p = 0.003), carbohydrate antigen 125 (CA125) (p = 0.030), carbohydrate antigen 19-9 (CA 19-9) (p = 0.044), and platelet/lymphocyte ratio (PLR) (p = 0.025) could serve as independent risk factors for PLNM. A risk factors-based nomogram prediction model was constructed, which showed good discrimination (AUC = 0.841, p < 0.001) and good efficacy (C-index = 0.842) and good calibration (mean absolute error = 0.046). DCA showed that the model can provide clinical benefits. CONCLUSIONS Preoperative DIM ≥50% determined by MRI, serum CA 19-9, CA125 and PLR could be utilized to predict PLNM in endometrial cancer patients. This nomogram prediction model can provide preoperative help for evaluation and identification of patients with endometrial cancer, and provide a theoretical basis for clinical intervention.
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Affiliation(s)
- Jie Zhang
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Dengfeng Wang
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Liping Peng
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Xunwei Shi
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Shi
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China
| | - Guonan Zhang
- Department of Gynecologic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
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Ren Z, Chen B, Hong C, Yuan J, Deng J, Chen Y, Ye J, Li Y. The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis. Front Oncol 2023; 13:1289050. [PMID: 38173835 PMCID: PMC10761539 DOI: 10.3389/fonc.2023.1289050] [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: 09/05/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Background The early identification of lymph node metastasis status in endometrial cancer (EC) is a serious challenge in clinical practice. Some investigators have introduced machine learning into the early identification of lymph node metastasis in EC patients. However, the predictive value of machine learning is controversial due to the diversity of models and modeling variables. To this end, we carried out this systematic review and meta-analysis to systematically discuss the value of machine learning for the early identification of lymph node metastasis in EC patients. Methods A systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science until March 12, 2023. PROBAST was used to assess the risk of bias in the included studies. In the process of meta-analysis, subgroup analysis was performed according to modeling variables (clinical features, radiomic features, and radiomic features combined with clinical features) and different types of models in various variables. Results This systematic review included 50 primary studies with a total of 103,752 EC patients, 12,579 of whom had positive lymph node metastasis. Meta-analysis showed that among the machine learning models constructed by the three categories of modeling variables, the best model was constructed by combining radiomic features with clinical features, with a pooled c-index of 0.907 (95%CI: 0.886-0.928) in the training set and 0.823 (95%CI: 0.757-0.890) in the validation set, and good sensitivity and specificity. The c-index of the machine learning model constructed based on clinical features alone was not inferior to that based on radiomic features only. In addition, logistic regression was found to be the main modeling method and has ideal predictive performance with different categories of modeling variables. Conclusion Although the model based on radiomic features combined with clinical features has the best predictive efficiency, there is no recognized specification for the application of radiomics at present. In addition, the logistic regression constructed by clinical features shows good sensitivity and specificity. In this context, large-sample studies covering different races are warranted to develop predictive nomograms based on clinical features, which can be widely applied in clinical practice. Systematic review registration https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420774.
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Affiliation(s)
- Zhonglian Ren
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Banghong Chen
- Data Science R&D Center of Yanchang Technology, Chengdu, China
| | - Changying Hong
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Jiaying Yuan
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Junying Deng
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Yan Chen
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Jionglin Ye
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
| | - Yanqin Li
- Department of Obstetrics and Gynecology, Chengdu Shuangliu Distract Maternal and Child Health Hospital, Chengdu, China
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Song YJ, Kim HG, Yoon HJ, Choi KU, Suh DS, Kim KH. Preoperative Haematologic Markers for the Differentiation of Endometrial Cancer from Benign Endometrial Lesions in Postmenopausal Patients with Endometrial Masses. Cancer Manag Res 2023; 15:1111-1121. [PMID: 37822733 PMCID: PMC10563776 DOI: 10.2147/cmar.s430013] [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: 08/09/2023] [Accepted: 10/03/2023] [Indexed: 10/13/2023] Open
Abstract
Purpose The diagnostic value of preoperative hematological changes in endometrial cancer (EC) remains unclear. This study aimed to assess the role of preoperative hematologic parameters in differentiating EC from benign endometrial lesions in postmenopausal women with endometrial masses. Methods Preoperative laboratory variables were retrospectively reviewed in patients with malignant or benign endometrial lesions, and the significance of intergroup differences was assessed. Receiver operating characteristic curves were used to analyze the optimal cut-off values for each variable. Logistic regression analysis was used to identify the variables predicting the presence of endometrial malignancy. Results Preoperative laboratory variables of 176 patients (84 EC and 92 benign lesions) with endometrial masses were analyzed. Significant differences were observed between malignant and benign lesions in terms of WBC count, ANC, MCV, MPV, PDW, CA125, NLR, PMR, LMR, and SII (P < 0.05). Multivariate analyses showed that a high WBC count, high ANC, low MCV, low MPV, low PDW, high CA125, high NLR, high PMR, high LMR, and high SII independently predicted the presence of endometrial malignancy. Conclusion The combination markers, MPV+PDW+NLR, had good discriminatory power for the presence of malignancy (AUC 0.797). Our results suggest that hematologic markers could be useful for the differentiation of malignant and benign endometrial lesions.
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Affiliation(s)
- Yong Jung Song
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan, South Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, South Korea
| | - Hwi Gon Kim
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan, South Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, South Korea
| | - Hyung Joon Yoon
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan, South Korea
| | - Kyung Un Choi
- Department of Pathology, Pusan National University School of Medicine, Busan, South Korea
| | - Dong Soo Suh
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan, South Korea
| | - Ki Hyung Kim
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan, South Korea
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Kose C, Korpe B, Korkmaz V, Ustun YE. The role of systemic immune inflammation index in predicting treatment success in tuboovarian abscesses. Arch Gynecol Obstet 2023; 308:1313-1319. [PMID: 37354237 DOI: 10.1007/s00404-023-07107-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 06/11/2023] [Indexed: 06/26/2023]
Abstract
PURPOSE The aim of this study was to determine the predictability of the systemic immune inflammation index (SII) on the response to medical treatment in tubo-ovarian abscess (TOA). METHODS 296 patients with TOA in a tertiary center were enrolled in the study. Patients were divided into two groups: Group1 (n = 165) included patients in whom medical treatment was successful, and Group2 (n = 131) included patients in whom surgery was required. Demographic, sonographic and laboratory findings were compared between groups. SII was calculated using peripheral blood parameters [SII = (platelets ∗ neutrophils)/lymphocytes]. RESULTS Age, BMI, gravida, parity, smoking and menopausal status, CRP levels of patients were similar in both groups (p > 0.05). Mass size (4.398 ± 0.306 vs 7.683 ± 0.689, p < 0.001), white blood cell (WBC) (8685.08 ± 3981.98 vs 9994.35 ± 4468.024, p = 0.008), Hb (12.18 ± 1.65 vs 11.68 ± 1.65, p = 0.010), platelet to lymphocyte ratio (PLR) (151.26 ± 74.83 vs 230.77 ± 140.25, p < 0.001), neutrophil to lymphocyte ratio (NLR) (4.21 ± 3.27 vs 6.07 ± 6.6, p = 0.003), monocyte to lymphocyte ratio (MLR) (0.300 ± 0.177 vs 0.346 ± 0.203, p = 0.041) and SII (1014.18 ± 781.71 vs 2094.088 ± 2117.58, p < 0.001) were statistically higher in group 2. ROC Analysis was used to determine the predictability of the variables and PLR (AUC = 0.718, p < 0.001), NLR (AUC = 0.593, p = 0.593), MLR (AUC = 0.576, p = 0.024), SII (AUC = 0.723, p < 0.001) and size of mass (AUC = 0.670, p < 0.001) were found to be significant. The SII, size of mass and bilateral involvement of adnexa were found to be the strongest prognostic factors for surgical intervention (OR:1.004 (1.002-1.005), OR:1.018 (1.010-1.027), OR:3.397 (1.338-8.627); p < 0.001, p < 0.001, p = 0.010 resspectively). CONCLUSION SII, size of mass and bilaterality can be used to predict medical treatment success in patients with TOA.
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Affiliation(s)
- Caner Kose
- Ankara Etlik Zubeyde Hanım Women's Health Training and Research Hospital, 06010, Ankara, Turkey.
| | - Busra Korpe
- Ankara Etlik Zubeyde Hanım Women's Health Training and Research Hospital, 06010, Ankara, Turkey
| | - Vakkas Korkmaz
- Department of Gynecologic Oncology, Ankara Etlik Zubeyde Hanım Women's Health Training and Research Hospital, Ankara, Turkey
| | - Yaprak Engin Ustun
- Ankara Etlik Zubeyde Hanım Women's Health Training and Research Hospital, 06010, Ankara, Turkey
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Ren S, Zang C, Yuan F, Yan X, Zhang Y, Yuan S, Sun Z, Lang B. Correlation between burst suppression and postoperative delirium in elderly patients: a prospective study. Aging Clin Exp Res 2023; 35:1873-1879. [PMID: 37479909 DOI: 10.1007/s40520-023-02460-5] [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: 10/20/2022] [Accepted: 05/29/2023] [Indexed: 07/23/2023]
Abstract
OBJECTIVE To explore the correlation between intraoperative burst suppression (BS) and postoperative delirium (POD) in elderly patients, and provide more ideas for reducing POD in clinical. METHODS Ninety patients, aged over 60 years, who underwent lumbar internal fixation surgery in our hospital were selected. General information of patients was obtained and informed consent was signed during preoperative visits. Patients were divided into burst suppression (BS) group and non-burst suppression (NBS) group by intraoperative electroencephalogram monitoring. Intraoperative systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and heart rate (HR) were recorded, and the variation and minimum value were obtained by calculating. Hemoglobin (HGB), C-reactive protein (CRP), system immune inflammatory index (SII) at 24 and 72 h after surgery, the incidence of postoperative adverse reactions, postoperative hospital stay, and total cost were recorded after operation. POD assessment was performed using CAM within 7 days after surgery or until discharge. SPSS25.0 was used for statistical analysis. RESULTS Compared with the NBS group, the number of elderly patients with high frailty level in BS group was more (P = 0.048). There is correlation between BS and POD (OR: 4.954, 95%CI 1.034-23.736, P = 0.045), and most of the POD patients in BS group behave as hyperactive type. CONCLUSION The occurrence of intraoperative BS is associated with POD, and elderly patients with frailty are more likely to have intraoperative BS. BS can be used as a predictor of POD.
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Affiliation(s)
- Shengjie Ren
- School of Anesthesiology, Weifang Medical University, Weifang, 261053, China
- Department of Anesthesiology, Weifang Second People's Hospital, Weifang, 261041, China
| | - Chuanbo Zang
- School of Anesthesiology, Weifang Medical University, Weifang, 261053, China
| | - Fang Yuan
- Department of Anesthesiology, Zibo Central Hospital, Zibo, 255020, China
| | - Xuemei Yan
- Department of Anesthesiology, Weifang People's Hospital, Weifang, 261041, China
| | - Yanan Zhang
- School of Anesthesiology, Weifang Medical University, Weifang, 261053, China
| | - Shu Yuan
- School of Anesthesiology, Weifang Medical University, Weifang, 261053, China
| | - Zenggang Sun
- School of Anesthesiology, Weifang Medical University, Weifang, 261053, China
| | - Bao Lang
- Department of Anesthesiology, Weifang People's Hospital, Weifang, 261041, China.
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Decker K, Murata S, Baig N, Hasan S, Halaris A. Utilizing the Systemic Immune-Inflammation Index and Blood-Based Biomarkers in Association with Treatment Responsiveness amongst Patients with Treatment-Resistant Bipolar Depression. J Pers Med 2023; 13:1245. [PMID: 37623494 PMCID: PMC10455950 DOI: 10.3390/jpm13081245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 07/28/2023] [Accepted: 08/03/2023] [Indexed: 08/26/2023] Open
Abstract
(1) Background: Inflammation is associated with depressive illness and treatment resistance. This study assessed a novel inflammatory index, the Systemic Immune-Inflammation Index (SII), in patients diagnosed with treatment-resistant bipolar depression (TRBDD) before and after treatment with escitalopram (ESC) and celecoxib (CBX) add-on or ESC and placebo (PBO), and compared them to healthy control (HC) subjects. (2) Methods: This is a secondary biological analysis from a double-blind randomized placebo-controlled trial of CBX augmentation in TRBDD. Our subsample with available complete blood count (CBC) data included 52 TRBDD subjects, randomized into an ESC + CBX, (n = 29), an ESC + PBO arm (n = 23), and an HC group (n = 32). SII was calculated from the CBC with differential (SII = platelets x neutrophils/lymphocytes) at baseline and end of treatment (8 weeks). Blood inflammation biomarkers, growth factors, and kynurenine metabolites were determined at both timepoints. Depressive symptom severity was the primary outcome, using the HAMD-17 rating scale score to quantitate treatment response and remission rates. (3) Results: Baseline SII did not discriminate TRBDD from HC, nor was it associated with HAMD-17 score at any timepoint, although it was significantly associated with lower baseline VEGF (p = 0.011) and higher week 8 levels of IL1-β (p = 0.03) and CRP (p = 0.048). Post-treatment HAMD-17 was not independently predicted using baseline SII unless an interaction with age was present (p = 0.003 was included), even after relevant adjustments. A similar effect was seen with baseline neutrophils. (4) Conclusions: While SII was not an independent predictor of treatment outcome, elevated baseline SII was a predictor of poor treatment response amongst older patients with TRBDD.
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Affiliation(s)
- Kyle Decker
- Department of Psychiatry and Behavioral Neurosciences, Loyola University Chicago Stritch School of Medicine, Loyola University Medical Center, Maywood, IL 60153, USA; (K.D.); (N.B.); (A.H.)
- Stritch School of Medicine, Loyola University, Maywood, IL 60153, USA
| | - Stephen Murata
- Pine Rest Christian Mental Health Services, Michigan State University, Grand Rapids, MI 49548, USA
| | - Nausheen Baig
- Department of Psychiatry and Behavioral Neurosciences, Loyola University Chicago Stritch School of Medicine, Loyola University Medical Center, Maywood, IL 60153, USA; (K.D.); (N.B.); (A.H.)
- Stritch School of Medicine, Loyola University, Maywood, IL 60153, USA
| | - Sakibur Hasan
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, USA;
| | - Angelos Halaris
- Department of Psychiatry and Behavioral Neurosciences, Loyola University Chicago Stritch School of Medicine, Loyola University Medical Center, Maywood, IL 60153, USA; (K.D.); (N.B.); (A.H.)
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Ma J, Li K. Systemic immune-inflammation index is associated with coronary heart disease: a cross-sectional study of NHANES 2009-2018. Front Cardiovasc Med 2023; 10:1199433. [PMID: 37485261 PMCID: PMC10361751 DOI: 10.3389/fcvm.2023.1199433] [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: 04/06/2023] [Accepted: 06/07/2023] [Indexed: 07/25/2023] Open
Abstract
Background Inflammation has been linked to the development of coronary heart disease (CHD). The systemic immune inflammation index (SII) is a useful biomarker of systemic inflammation. Our study aimed to explore the correlation between SII and CHD. Methods We conducted a multivariate logistic regression analysis, smoothing curve fitting, and segmented model comparison on 15,905 participants with a CHD prevalence of 3.31% and a mean age of 46.97 years. Results Adjusting for gender, age, and race, we found a negative association between SII and CHD [odds ratio (OR) 0.66; 95% confidence interval (CI) 0.48, 0.90]. There was an inverse trend where increasing SII was associated with decreasing odds of CHD (p for trend = 0.0017). After further adjustment, the association was strengthened, with a similar trend (p for trend = 0.0639). Smoothing curve fitting demonstrated a gender-specific association between SII and CHD. Conclusions Our findings suggest that higher SII values may be associated with a higher incidence of CHD, which varies by gender. SII may be a cost-effective and convenient method to detect CHD. Further studies are needed to confirm the causality of these findings in a larger prospective cohort.
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Feng X, Li XC, Yang X, Cheng Y, Dong YY, Wang JY, Zhou JY, Wang JL. Metabolic syndrome score as an indicator in a predictive nomogram for lymph node metastasis in endometrial cancer. BMC Cancer 2023; 23:622. [PMID: 37403054 DOI: 10.1186/s12885-023-11053-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/09/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND Lymph node metastasis (LNM) is an important factor affecting endometrial cancer (EC) prognosis. Current controversy exists as to how to accurately assess the risk of lymphatic metastasis. Metabolic syndrome has been considered a risk factor for endometrial cancer, yet its effect on LNM remains elusive. We developed a nomogram integrating metabolic syndrome indicators with other crucial variables to predict lymph node metastasis in endometrial cancer. METHODS This study is based on patients diagnosed with EC in Peking University People's Hospital between January 2004 and December 2020. A total of 1076 patients diagnosed with EC and who underwent staging surgery were divided into training and validation cohorts according to the ratio of 2:1. Univariate and multivariate logistic regression analyses were used to determine the significant predictive factors. RESULTS The prediction nomogram included MSR, positive peritoneal cytology, lymph vascular space invasion, endometrioid histological type, tumor size > = 2 cm, myometrial invasion > = 50%, cervical stromal invasion, and tumor grade. In the training group, the area under the curve (AUC) of the nomogram and Mayo criteria were 0.85 (95% CI: 0.81-0.90) and 0.77 (95% CI: 0.77-0.83), respectively (P < 0.01). In the validation group (N = 359), the AUC was 0.87 (95% CI: 0.82-0.93) and 0.80 (95% CI: 0.74-0.87) for the nomogram and the Mayo criteria, respectively (P = 0.01). Calibration plots revealed the satisfactory performance of the nomogram. Decision curve analysis showed a positive net benefit of this nomogram, which indicated clinical value. CONCLUSION This model may promote risk stratification and individualized treatment, thus improving the prognosis.
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Affiliation(s)
- Xuan Feng
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Xing Chen Li
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Xiao Yang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Yuan Cheng
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Yang Yang Dong
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Jing Yuan Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China
| | - Jing Yi Zhou
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China.
| | - Jian Liu Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, 100044, China.
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Yang C, Li ZQ, Wang J. Association between systemic immune-inflammation index (SII) and survival outcome in patients with primary glioblastoma. Medicine (Baltimore) 2023; 102:e33050. [PMID: 36800573 PMCID: PMC9936030 DOI: 10.1097/md.0000000000033050] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/19/2023] Open
Abstract
The purpose was to evaluate the prognostic value of systemic immune-inflammation index (SII) in glioblastoma patients. A total of 100 patients were retrospectively analyzed. We performed Kaplan-Meier and Cox regression analyses to determine the prognostic significance of SII. A nomogram was constructed by incorporating independent prognostic variables. The predictive accuracies of nomograms were evaluated by Harrell concordance index (c-index) and receiver operating characteristic curve analysis; the clinical benefit was evaluated by decision curve analysis. A high SII (>510.8 × 109 cells/L) (hazard ratio = 1.672, P = .034) and neutrophil count (>3.9 × 109 cells/L) (hazard ratio = 1.923, P = .009) were independently related with poor outcome in glioblastoma patients based on Cox analysis. The nomogram incorporating SII showed a good predictive accuracy (c-index = 0.866). Preoperative SII and neutrophil count are potential prognostic biomarkers for overall survival in glioblastoma patients and the nomogram model that integrated the SII may be used to facilitate a comprehensive preoperative survival evaluation.
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Affiliation(s)
- Chao Yang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhi-Qiang Li
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jie Wang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
- * Correspondence: Jie Wang, Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430072, China (e-mail: )
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Chen Y, Yu J, Shi L, Han S, Chen J, Sheng Z, Deng M, Jin X, Zhang Z. Systemic Inflammation Markers Associated with Bone Mineral Density in perimenopausal and Postmenopausal Women. J Inflamm Res 2023; 16:297-309. [PMID: 36713047 PMCID: PMC9879040 DOI: 10.2147/jir.s385220] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 12/24/2022] [Indexed: 01/23/2023] Open
Abstract
Objective The aim of this research was to determine whether systemic inflammatory indicators, including aggregate index of systemic inflammation (AISI), neutrophils lymphocyte to platelet ratio (NLPR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), are related to bone mineral density (BMD) in perimenopausal and postmenopausal women. Methods One hundred and eighty-one perimenopausal and 390 postmenopausal women were enrolled in this cross-sectional study. Continuous variables by analysis of variance and Kruskal Wallis test for comparing the clinical characteristics. Linear regression analysis was conducted to investigate the associations between inflammatory indicators with BMD. The comparison between the subgroups was performed using the nonparametric test and the T-test. Results AISI, NLPR, SII, and SIRI quartile values were inversely associated with BMD in menopausal women (P = 0.021; P = 0.047; P < 0.001; P < 0.001, respectively). After adjusting for confounding factors, four inflammatory indicators remained significantly associated with BMD (all P for trend <0.001). Analysis according to menopausal status demonstrated that AISI, SII, and SIRI were significantly correlated with mean femoral neck BMD in postmenopausal women (P for trend = 0.015, 0.004, and 0.001), but not significantly associated with BMD in perimenopausal women (P for trend = 0.248, 0.054, and 0.352) after adjustment for covariates. Conclusion The quartile values of AISI, SII, and SIRI were inversely associated with BMD in postmenopausal women, following adjustment for individual variables, hormone profiles and glucolipid metabolism profiles. AISI, SII, and SIRI have potential to be important tools for screening and prevention of bone loss in menopausal women in future clinical practice.
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Affiliation(s)
- Yijie Chen
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China
| | - Jingjing Yu
- School of Public Health, Hangzhou Normal University, Hangzhou, People’s Republic of China
| | - Lan Shi
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China
| | - Shuyang Han
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China
| | - Jun Chen
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China
| | - Zhumei Sheng
- Department of the Reproductive Endocrinology Division, Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, People’s Republic of China
| | - Miao Deng
- Department of the Reproductive Endocrinology Division, Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, People’s Republic of China
| | - Xuejing Jin
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China,Department of the Reproductive Endocrinology Division, Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, People’s Republic of China
| | - Zhifen Zhang
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China,Department of the Reproductive Endocrinology Division, Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital), Hangzhou, People’s Republic of China,Correspondence: Zhifen Zhang; Xuejing Jin, The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, 548 Binwen Road, Binjiang District, Hangzhou, Zhejiang, 310053, People’s Republic of China, Email ;
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Huang G, Gao H, Chen Y, Lin W, Shen J, Xu S, Liu D, Wu Z, Lin X, Jiang T, Dong B, Sun P. Platelet-to-Lymphocyte Ratio (PLR) as the Prognostic Factor for Recurrence/Residual Disease in HSIL Patients After LEEP. J Inflamm Res 2023; 16:1923-1936. [PMID: 37152868 PMCID: PMC10162391 DOI: 10.2147/jir.s406082] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 04/19/2023] [Indexed: 05/09/2023] Open
Abstract
Purpose The platelet-to-lymphocyte ratio (PLR) is considered correlated with cancer prognosis including cervical cancer, in addition to high-risk papillomavirus (HR-HPV) infection, of which the predictive value in prognosis of high-grade squamous intraepithelial lesions (HSILs) remains unknown. Here, the prognostic predictive value of PLR in HSIL after loop electrosurgical excision procedure (LEEP) was evaluated. Patients and Methods This study included 335 nonpregnant participants with histopathologically confirmed HSIL and 3- and 5-year follow-ups from the Fujian Cervical Lesions Screening Cohorts (FCLSCs) between September 2016 and September 2018. PLR and other variables were evaluated to identify the factors related to the recurrence/residual cervical intraepithelial neoplasia (CIN)-free survival (RFS), namely, the time from LEEP at baseline to first detection of recurrence/residual CIN or end of follow-up, by logistic and Cox regression. Results In the Kaplan‒Meier analysis, HR-HPV infection (p=0.049/0.012), higher PLR (p=0.031/0.038), and gland invasion (p=0.047) had a higher risk for recurrence/residual CIN at the 3-/5-year follow-up. The univariate logistic and Cox regression analyses showed significant differences and a higher cumulative risk in patients with HR-HPV infection (OR=3.917, p=0.026; HR=3.996, p=0.020) and higher PLR (OR=2.295, p=0.041; HR=2.161, p=0.030) at the 5-year follow-up. The findings by multivariate Cox regression analysis were similar, indicating a poor prognosis for patients with HR-HPV infection (HR=3.901, p=0.023) and higher PLR (HR=2.082, p=0.038) at the 5-year follow-up. The calibration plot showed a better model fit for RFS at the 3-year follow-up. Conclusion Preoperative PLR level and HR-HPV infection could be available markers for predicting recurrence/residual disease of HSIL after LEEP. Clinically, combining PLR with HR-HPV tests may provide novel evaluation method and reference for management in post-treatment patients with cervical precancerous lesions.
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Affiliation(s)
- Guanxiang Huang
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Hangjing Gao
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Yanlin Chen
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Wenyu Lin
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Jun Shen
- Fujian Provincial Cervical Disease Diagnosis and Treatment Health Center, Fujian Maternity and Child Health Hospital, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, 350001, People’s Republic of China
| | - Shuxia Xu
- Department of Pathology, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, 350001, People’s Republic of China
| | - Dabin Liu
- Department of Gynecology, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, 350001, People’s Republic of China
| | - Zhihui Wu
- Department of Clinical Laboratory, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, 350001, People’s Republic of China
| | - Xite Lin
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Tingting Jiang
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Binhua Dong
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
| | - Pengming Sun
- Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Key Laboratory of Women and Children’s Critical Diseases Research, Fujian Maternity and Child Health Hospital (Fujian Women and Children’s Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Fujian Clinical Research Center for Gynecological Oncology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou, Fujian, 350001, People’s Republic of China
- Correspondence: Pengming Sun; Binhua Dong, Laboratory of Gynecologic Oncology, Department of Gynecology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China, Tel +86-591-87558732; +86-13599071900, Fax +86-591-87551247, Email ; ; ;
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Yaradilmiş RM, Güneylioğlu MM, Öztürk B, Göktuğ A, Aydın O, Güngör A, Bodur İ, Kaya Ö, Örün UA, Karacan CD, Tuygun N. A Novel Marker for Predicting Fulminant Myocarditis: Systemic Immune-Inflammation Index. Pediatr Cardiol 2023; 44:647-655. [PMID: 35984471 PMCID: PMC9389492 DOI: 10.1007/s00246-022-02988-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/08/2022] [Indexed: 11/25/2022]
Abstract
In myocarditis, the search for effective and appropriate prognostic biomarkers can help clinicians identify high-risk patients in a timely manner and make better medical decisions in clinical practice. The prognostic value of systemic immune-inflammatory index (SII), an innovate biomarker of inflammation, in fulminant myocarditis in children has not been assessed. This study aims to (1) determine the effect of SII and other inflammatory markers on the prognosis of patients with myocarditis, and (2) characterize other factors affecting adverse outcomes in myocarditis. All patients aged between 1 months and 18 years who admitted to Pediatric Emergency Department between January 1, 2015 and October 1, 2021 and were diagnosed with myocarditis were retrospectively analyzed. 106 Eligible subjects were enrolled (67% male, 12.5 years (IQR 6-16). Fulminant myocarditis developed in 16 (15%) of the patients. The median SII was 1927 (1147.75-3610.25) in the fulminant myocarditis group and 351 (251.75-531.25) in the non-fulminant group (p < 0.001). In estimation of fulminant myocarditis, AUC was 0.87 for WBC [95% confidence interval (CI) 0.72-1.00, p = 0.002], 0.94 for ANC (95% CI 0.85-1.00), p = 0.000), 0.92 for SII (95% CI 0.82-1.00, p = 0.000). Spearman's correlation analysis showed a significant negative correlation between SII and LVEF (r = 0.576, p < 0.001). The highest AUC values were associated with ANC, SII, and WBC levels to predict fulminant myocarditis. SII, a readily available biomarker from routine blood parameters, allows early recognition of negative outcomes and can independently predict the prognosis of myocarditis in children.
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Affiliation(s)
- Raziye Merve Yaradilmiş
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080, Ankara, Turkey.
| | - Muhammed Mustafa Güneylioğlu
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Betül Öztürk
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Aytaç Göktuğ
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Orkun Aydın
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Ali Güngör
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - İlknur Bodur
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Özkan Kaya
- Department of Pediatric Cardiology, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Utku Arman Örün
- Department of Pediatric Cardiology, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Can Demir Karacan
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
| | - Nilden Tuygun
- Department of Pediatric Emergency Care, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Plevne M Babur C No 41, Gunesevler, 06080 Ankara, Turkey
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Bai G, Zhou Y, Rong Q, Qiao S, Mao H, Liu P. Development of Nomogram Models Based on Peripheral Blood Score and Clinicopathological Parameters to Predict Preoperative Advanced Stage and Prognosis for Epithelial Ovarian Cancer Patients. J Inflamm Res 2023; 16:1227-1241. [PMID: 37006810 PMCID: PMC10064492 DOI: 10.2147/jir.s401451] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/02/2023] [Indexed: 04/04/2023] Open
Abstract
Purpose Nutritional and inflammatory states are crucial in cancer development. The purpose of this study is to construct a scoring system grounded on peripheral blood parameters associated with nutrition and inflammation and explore its value in stage, overall survival (OS), and progression-free survival (PFS) prediction for epithelial ovarian cancer (EOC) patients. Patients and Methods Four hundred and fifty-three EOC patients were retrospectively identified and their clinical data and relevant peripheral blood parameters were collected. The ratio of neutrophil to lymphocyte, lymphocyte to monocyte, fibrinogen to lymphocyte, total cholesterol to lymphocyte and albumin level were calculated and dichotomized. A scoring system named peripheral blood score (PBS) was constructed. Univariate and multivariate Logistic or Cox regression analyses were used to select independent factors; these factors were then used to develop nomogram models of advanced stage and OS, PFS, respectively. The internal validation and DCA analysis were performed to evaluate models. Results Lower PBS indicated a better prognosis and higher PBS indicated inferior. High PBS is associated with advanced stage, high CA125, serous histological type, poor differentiation, and accompanied ascites. The logistic regression showed age, CA125, and PBS were independent factors for the FIGO III-IV stage. The nomogram models for advanced FIGO stage based on these factors showed good efficiency. FIGO stage, residual disease, and PBS were independent factors affecting OS and PFS, the nomogram models composed of these factors had good performance. DCA curves revealed the models augmented net benefits. Conclusion PBS can be a noninvasive biomarker for EOC patients' prognosis. The related nomogram models could be powerful, cost-effective tools to provide information of advanced stage, OS, and PFS for EOC patients.
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Affiliation(s)
- Gaigai Bai
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
| | - Yue Zhou
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
| | - Qing Rong
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
| | - Sijing Qiao
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
| | - Hongluan Mao
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Correspondence: Hongluan Mao; Peishu Liu, Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, People’s Republic of China, Tel +86-18560081988; +86-18560082027, Email ;
| | - Peishu Liu
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
- Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People’s Republic of China
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Yang C, Hu BW, Tang F, Zhang Q, Quan W, Wang J, Wang ZF, Li YR, Li ZQ. Prognostic Value of Systemic Immune-Inflammation Index (SII) in Patients with Glioblastoma: A Comprehensive Study Based on Meta-Analysis and Retrospective Single-Center Analysis. J Clin Med 2022; 11:jcm11247514. [PMID: 36556130 PMCID: PMC9787672 DOI: 10.3390/jcm11247514] [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: 11/19/2022] [Revised: 12/14/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022] Open
Abstract
Inflammation is related to cancer. The systemic immune-inflammation index (SII) has been linked to the prognosis of many types of cancer. The present study aimed to determine the prognostic value of the SII in glioblastoma (GBM) patients based on meta-analysis and single-center retrospective analysis. Relevant publications published before 1 October 2022 were identified by searching PubMed, EMBASE, Cochrane Library databases, and Web of Science. Moreover, 208 GBM patients from Zhongnan Hospital were incorporated. Kaplan−Meier and Cox regression analyses determined the prognostic significance of inflammatory markers. By combining these indicators, we developed scoring systems. Nomograms were also built by incorporating independent variables. The accuracies of nomograms were evaluated by Harrell’s concordance index (c-index) and the calibration curve. According to meta-analysis, an elevated SII predicted the worst overall survival (OS) (Hazard ratio [HR] = 1.87, p < 0.001). Furthermore, a higher SII (>510.8) (HR = 1.782, p = 0.007) also predicted a poorer outcome in a retrospective cohort. The scoring systems of SII-NLR (neutrophil-to-lymphocyte ratio) showed the best predictive power for OS. The nomogram without MGMT (c-index = 0.843) exhibited a similar accuracy to that with MGMT (c-index = 0.848). A pre-treatment SII is independently associated with OS in GBM. A nomogram integrating the SII-NLR score may facilitate a comprehensive survival evaluation independent of molecular tests in GBM.
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Affiliation(s)
- Chao Yang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Bo-Wen Hu
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Feng Tang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Qing Zhang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Wei Quan
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Jie Wang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Ze-Fen Wang
- Department of Physiology, School of Basic Medical Sciences, Wuhan University, Wuhan 430071, China
| | - Yi-Rong Li
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Correspondence: (Y.-R.L.); (Z.-Q.L.); Tel.: +86-027-6781-3052 (Y.-R.L.); +86-18907123005 (Z.-Q.L.)
| | - Zhi-Qiang Li
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Correspondence: (Y.-R.L.); (Z.-Q.L.); Tel.: +86-027-6781-3052 (Y.-R.L.); +86-18907123005 (Z.-Q.L.)
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Li Z, Zhang H, Baraghtha S, Mu J, Matniyaz Y, Jiang X, Wang K, Wang D, Xue YX. Short- and Mid-Term Survival Prediction in Patients with Acute Type A Aortic Dissection Undergoing Surgical Repair: Based on the Systemic Immune-Inflammation Index. J Inflamm Res 2022; 15:5785-5799. [PMID: 36238764 PMCID: PMC9553311 DOI: 10.2147/jir.s382573] [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: 07/15/2022] [Accepted: 09/27/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose The postoperative survival of patients with acute type A aortic dissection (aTAAD) remains unsatisfactory. The current study developed an easy-to-use survival prediction model and calculator. Methods A total of 496 patients with aTAAD undergoing surgical repair were included in this study. The systemic immune-inflammation index (SII) and other clinical features were collected and subjected to logistic and Cox regression analyses. The survival prediction model was based on Cox regression analyses and exhibited as a nomogram. For convenience of use, the nomogram was further developed into calculator software. Results We demonstrated that a higher preoperative SII was associated with in-hospital death (OR: 4.116, p < 0.001) and a higher postoperative overall survival rate (HR: 2.467, p < 0.001) in aTAAD patients undergoing surgical repair. A survival prediction model and calculator based on SII and four other clinical features were developed. The overall C-index of the model was 0.743. The areas under the curves (AUCs) of the 1- and 3-month and 1- and 3-year survival probabilities were 0.73, 0.71, 0.71 and 0.72, respectively. The model also showed good calibration and clinical utility. Conclusion Preoperative SII is significantly associated with postoperative survival. Based on SII and other clinical features, we created the first easy-to-use prediction model and calculator for predicting the postoperative survival rate in aTAAD patients, which showed good prediction performance.
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Affiliation(s)
- Zeshi Li
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Graduate School of Peking Union Medical College, Nanjing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - He Zhang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Graduate School of Peking Union Medical College, Nanjing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Sulaiman Baraghtha
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China,International School, University of Mannheim, Mannheim, Baden-Württemberg, Federal Republic of Germany
| | - Jiabao Mu
- School of Data Science, University of Science and Technology of China, Hefei, Anhui, People’s Republic of China
| | - Yusanjan Matniyaz
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China
| | - Xinyi Jiang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Graduate School of Peking Union Medical College, Nanjing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Kuo Wang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of XuZhou Medical University, Nanjing, People’s Republic of China
| | - Dongjin Wang
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Graduate School of Peking Union Medical College, Nanjing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, People’s Republic of China,Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of XuZhou Medical University, Nanjing, People’s Republic of China
| | - Yun Xing Xue
- Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, People’s Republic of China,Correspondence: Yun Xing Xue; Dongjin Wang, Email ;
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Preoperative Prediction Value of Pelvic Lymph Node Metastasis of Endometrial Cancer: Combining of ADC Value and Radiomics Features of the Primary Lesion and Clinical Parameters. JOURNAL OF ONCOLOGY 2022; 2022:3335048. [PMID: 35813867 PMCID: PMC9262528 DOI: 10.1155/2022/3335048] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/08/2022] [Indexed: 01/17/2023]
Abstract
Objective To investigate the value of apparent diffusion coefficient (ADC) value of endometrial cancer (EC) primary lesion and magnetic resonance imaging (MRI) three-dimensional (3D) radiomics features combined with clinical parameters for preoperative prediction of pelvic lymph node metastasis (PLNM). Methods A total of 136 patients with EC confirmed by postoperative pathology were retrospectively reviewed and analyzed. Patients were randomly divided into training set (n = 95) and test set (n = 41) at a ratio of 7 : 3. Radiomics features based on T2WI, DWI, and contrast-enhanced T1WI (CE-T1WI) sequence were extracted and screened, and then radiomics score (Rads-score) was calculated. Clinical parameters and ADC value of EC primary lesion were measured and collected, and their correlation with PLNM was analyzed. Receiver operating characteristic (ROC) curve was plotted to assess the diagnostic efficacy of the model. A nomogram for PLNM was created based on the multivariate logistic regression model. Results The ADC value of the EC primary lesion showed inverse correlation with PLNM, while CA125 and Rads-score were positively associated with PLNM. A predictive model was proposed based on ADC value, Rads-score, CA125, and MR-reported pelvic lymph node status (PLNS) for PLNM in EC. The area under the curve (AUC) of the model is 0.940; the sensitivity and specificity (87.1% and 90.6%) of the model were significantly higher than that of the MRI morphological signs. Conclusion A combination of ADC value, MRI 3D radiomics features of the EC primary lesion, and clinical parameters generated a prediction model for PLNM in EC and had a good diagnostic performance; it was a useful supplement to MR-reported PLNS based on MRI morphological signs.
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