scholarly journals Risk Factors for the Morbidity and Prognosis of Lung Metastases in Newly Diagnosed Ovarian Carcinoma: A Large Population-based Study

2021 ◽  
Author(s):  
Shuning Ding ◽  
Kaibo Guo ◽  
Linqin Wu ◽  
Dongxu Li ◽  
Peipei Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ovarian Carcinoma ◽  
Cox Regression ◽  
Lung Metastases ◽  
Population Based ◽  
Ca 125 ◽  
Newly Diagnosed ◽  
Cox Regression Analysis

Abstract Background: To evaluate the risk factors for the morbidity and prognosis of lung metastases (LM) in patients with newly diagnosed ovarian carcinoma (OC). Methods: Based on the Surveillance, Epidemiology, and End Results (SEER) dataset, OC patients from 2010 and 2016 were retrospectively analyzed. Risk factors for the morbidity of LM in OC patients and their survival were assessed by logistic regression analysis and Kaplan-Meier and Gray method, respectively. Cox regression analysis was performed to identify risk factors for the prognosis of OC patients with LM, and their prognostic potentials were further validated by two established nomograms.Results: There are 27,123 eligible OC patients were enrolled in the study, with the morbidity of LM at 5.61% (1,521/27,123). Logistic regression models illustrated that T3 stage [odds ratio (OR)=2.74, 95%CI=2.09-3.66, P<0.01], advanced N stage (OR=1.86, 95%CI=1.62-2.14, P<0.01), and the prevalence of bone metastasis (OR=3.78, 95%CI=2.79-5.11, P<0.01), brain metastasis (OR=4.67, 95%CI=2.50-8.63, P<0.01) and liver metastasis (OR=3.60, 95%CI=3.14-4.12, P<0.01) were all significantly correlated with the morbidity of LM in OC patients. Median survival for OC patients with LM was 11 months (interquartile range, 3 to 25 months). Cox regression analyses illustrated over 80 years of age [hazard ratio (HR)=2.52, 95%CI=2.33-2.72, P<0.01] and positive expression of cancer antigen 125 (CA-125, HR=1.63, 95%CI=1.47-1.82, P<0.01) were significantly correlated with the high mortality of LM, while chemotherapy (HR=0.62, 95%CI=0.59-0.65, P<0.01) was significantly correlated with the low mortality. Two nomograms were established to examine the concordance index (C-index), calibration curves, the area under the curve (AUC), decision curve analyses (DCAs) and clinical impact curves (CICs), which validated the prognostic potentials of identified risk factors in OC patients with LM. Conclusion: The population-based cohort study provides references for guiding clinical screening and individualized treatment of OC patients with LM.

scholarly journals Role of Disease Modifying Treatment in the Risk of Alloimmunization in Transfused Patients with Myelodysplastic Syndromes: A Population-Based Study

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4253-4253
Author(s):  
Hanne Rozema ◽  
Robby Kibbelaar ◽  
Nic Veeger ◽  
Mels Hoogendoorn ◽  
Eric van Roon
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Cox Regression ◽  
Population Based ◽  
Incidence Rates ◽  
Blood Products ◽  
Cox Regression Analysis ◽  
In The Beginning ◽  
Observation Period

The majority of patients with myelodysplastic syndromes (MDS) require regular red blood cell (RBC) transfusions. Alloimmunization (AI) against blood products is an adverse event, causing time-consuming RBC compatibility testing. The reported incidence of AI in MDS patients varies greatly. Even though different studies on AI in MDS patients have been performed, there are still knowledge gaps. Current literature has not yet fully identified the risk factors and dynamics of AI in individual patients, nor has the influence of disease modifying treatment (DMT) been explored. Therefore, we performed this study to evaluate the effect of DMT on AI. An observational, population-based study, using the HemoBase registry, was performed including all newly diagnosed MDS patients between 2005 and 2017 in Friesland, a province of the Netherlands. All available information about treatment and transfusions, including transfusion dates, types, and treatment regimens, was collected from the electronic health records and laboratory systems. Follow-up occurred through March 2019. For our patient cohort, blood products were matched for AB0 and RhD, and transfused per the 'type and screen' policy (i.e. electronic matching of blood group phenotype between patient and donor). After a positive antibody screening, antibody identification and Rh/K phenotyping was performed and subsequent blood products were (cross)matched accordingly. The observation period was counted from first transfusion until last transfusion or first AI event. Univariate analyses and cumulative frequency distributions were performed to study possible risk factors and dynamics of AI. DMT was defined as hypomethylating agents, lenalidomide, chemotherapy and monoclonal antibodies. The effect of DMT as a temporary risk period on the risk of AI was estimated with incidence rates, relative risks (RR) and hazard ratios (HR) using a cox regression analysis. Follow-up was limited to 24 months for the cox regression analysis to avoid possible bias by survival differences. Statistical analyses were performed using IBM SPSS 24 and SAS 9.4. Out of 292 MDS patients, 236 patients received transfusions and were included in this study, covering 463 years of follow-up. AI occurred in 24 patients (10%). AI occurred mostly in the beginning of the observation period: Eighteen patients (75%) were alloimmunized after receiving 20 units of RBCs, whereas 22 patients (92%) showed AI after 45 units of RBCs (Figure 1). We found no significant risk factors for AI in MDS patients at baseline. DMT was given to 67 patients (28%) during the observation period. Patients on DMT received more RBC transfusions than patients that did not receive DMT (median of 33 (range: 3-154) and 11 (range: 0-322) RBC units respectively, p<0,001). Four AI events (6%) occurred in patients on DMT and 20 AI events (12%) occurred in patients not on DMT. Cox regression analysis of the first 24 months of follow-up showed an HR of 0.30 (95% CI: 0.07-1.31; p=0.11). The incidence rates per 100 person-years were 3.19 and 5.92 respectively. The corresponding RR was 0.54 (95% CI: 0.16-1.48; p=0.26). Based on our results, we conclude that the incidence of AI in an unselected, real world MDS population receiving RBC transfusions is 10% and predominantly occurred in the beginning of follow-up. Risk factors for AI at baseline could not be identified. Our data showed that patients on DMT received significantly more RBC transfusions but were less susceptible to AI. Therefore, extensive matching of blood products may not be necessary for patients on DMT. Larger studies are needed to confirm the protective effect of DMT on AI. Disclosures Rozema: Celgene: Other: Financial support for visiting MDS Foundation conference.

scholarly journals Risk Factors for Leukemic Transformation Among 1,306 Patients with Primary Myelofibrosis: Mutations Predict Early Events

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3044-3044
Author(s):  
Rangit Reddy Vallapureddy ◽  
Mythri Mudireddy ◽  
Natasha Szuber ◽  
Domenico Penna ◽  
Maura Nicolosi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
High Risk ◽  
Cox Regression ◽  
Primary Myelofibrosis ◽  
Idh1 Mutation ◽  
Severe Anemia ◽  
Cox Regression Analysis ◽  
Version 2.0

Abstract Background: Current prognostic models in primary myelofibrosis (PMF) target overall survival (OS) and utilize MIPSS70 (mutation-enhanced international prognostic scoring system for transplant-age patients), MIPSS70+ version 2.0 (karyotype-enhanced MIPSS70) and GIPSS (genetically-inspired prognostic scoring system, which is based on mutations and karyotype) (JCO 2018;36:310; JCO doi: 10.1200/JCO.2018.78.9867; Leukemia. 2018;doi:10.1038/s41375-018-0107). In the current study, we used logistic regression statistics to identify risk factors for leukemic transformation (LT) within 5 years of diagnosis/referral (i.e. early events) and also performed Cox regression analysis of overall leukemia-free survival (LFS). Methods : Study patients were recruited from the Mayo Clinic, Rochester, MN, USA. Diagnoses of LT and chronic phase PMF were confirmed by both clinical and bone marrow examinations, in line with the 2016 World Health Organization criteria (Blood. 2016;127:2391); specifically, LT required presence of ≥20% blasts in the peripheral blood (PB) or bone marrow (BM) (Blood 2016;127:2391). Statistical analyses considered clinical and laboratory data collected at the time of initial PMF diagnosis or Mayo Clinic referral point. Logistic regression statistics was used to identify predictors of LT at 5 years from initial diagnosis/referral; in the particular method, patients with documented LT within 5 years were "uncensored" while those followed up for at least 5 years, without developing LT, were "censored"; the analysis excluded patients without LT and not followed for at least 5 years. In addition, Cox regression analysis was performed to identify risk factors for overall LFS. The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 1,306 patients with PMF (median age 65 years; 63% males) were included in the current study; MIPSS70+ version 2.0 risk distribution was 20% very high risk, 41% high risk, 19% intermediate risk, 16% low risk and 4% very low risk. 149 (11%) patients were documented to experience LT, and compared to the remaining patients (n=1157), they were more likely to be males (p=0.02) and mutated for ASXL1 (p=0.01), SRSF2 (0.001) and IDH1 (0.02) and present with higher risk MIPSS70+ version 2.0 (p=0.02). Multivariable logistic regression identified the following as predictors of LT in the first 5 years of disease: IDH1 mutation (odds ratio; OR 78.4), very high risk (VHR) karyotype (OR 57.6), ASXL1 mutation (OR 15.1), age >70 years (OR 13.3), SRSF2 mutation (OR 8.5), male sex (OR 6.9), PB blasts ≥3% (OR 5.4), presence of moderate or severe anemia, adjusted for sex (OR 3.6) and constitutional symptoms (OR 3.1). On Cox regression analysis, the following were associated with inferior LFS: IDH1 mutation (HR 4.3), PB blasts ≥3% (HR 3.3), SRSF2 mutation (HR 3.0), age >70 years (HR 2.1), ASXL1 mutation (HR 2.0) and presence of moderate or severe anemia, adjusted for sex (HR 1.9). Subsequently, HR-based risk point allocation resulted in highly discriminating LT predictive model with HR (95% CI) of 39.4 (10.8-114) for high risk and 4.1 (2.4-7.3) for intermediate risk (Figure 1). Conclusions: The current study identifies IDH1 mutation as a main predictor of LT in PMF. Our study also implicates SRSF2 and ASXL1 mutations and VHR karyotype as other genetic markers of early LT. Other independent contributors of early LT and inferior LFS, overall, included PB blasts ≥3%, moderate to severe anemia and older age. We provide LT prediction model, based on these variables, with leukemia risk ranging from 8% to 57%. Disclosures No relevant conflicts of interest to declare.

scholarly journals Cardiac-Related Lesions in Newly Diagnosed Patients with Acute Leukemia

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3381-3381
Author(s):  
Wei Xiao ◽  
Linlu Ma ◽  
Yufeng Shang ◽  
Yuxin Tan ◽  
Fuling Zhou
Keyword(s):  
Risk Factors ◽  
Coronary Heart Disease ◽  
Regression Analysis ◽  
Heart Disease ◽  
Acute Leukemia ◽  
Cox Regression ◽  
Newly Diagnosed ◽  
Cox Regression Analysis ◽  
Heart Damage ◽  
Normally Distributed

Abstract Background: More and more cases of leukemia with heart injury have been reported, mostly due to tumor cell infiltration, endothelial injury and high viscosity of leukemia cells in circulating blood. To evaluate whether the newly diagnosed acute leukemia patients have suffered heart-related injuries, and determine the possible related factors, we carried out this study. Methods: From January 2015 to August 2019, we retrospectively selected 408 patients from the Department of Hematology and Cardiology, Zhongnan Hospital of Wuhan University. There were 200 newly diagnosed acute leukemia patients (including 15 acute hyperleukocytic leukemia patients), 105 patients without cancer and no known heart disease, and 103 cases of confirmed coronary heart disease. We collected the basic information of patients, echocardiographic data and myocardial enzyme results. We also followed up all newly diagnosed acute leukemia patients for prognostic analysis. All data were logarithmically transformed to make the data normally distributed. Normally distributed samples were compared using independent sample t-tests, Mann-Whitney U rank sum test was used for non-normally distributed samples and qualitative data was using chi-square test. The log-rank test was used to perform univariate analysis through Kaplan-Meier curves, and meaningful values were screened for multivariate COX regression analysis. The statistical analysis was performed with the SPSS software. Results: Compared with the control group, patients with newly diagnosed acute leukemia had already experienced some heart-related injuries. The average values of myocardial enzyme indexes such as CKMB,LDH,hs-cTnI,BNP and echocardiography indexes such as LV,EDV,ESV,SV,EF were all significantly different. But the degree of heart damage was lower than that of the coronary heart disease group. Compared with hyperleukocytic leukemia, non-hyperleukocytic leukemia had suffered more serious heart damage, especially myocardial enzyme indexes such as HBDH and LDH were significantly increased. Analyze the relationship between age, gender, cardiovascular risk factors (hypertension, diabetes and smoking history), myocardial enzyme indexes, echocardiography indexes and survival, to screen for risk factors related to the prognosis of the disease. Variables with statistically significant effect measurement values include age (p&lt;0.001), LDH (p=0.018), and EF (p=0.053). In addition, the meaningful variables in the previous single-factor analysis were subjected to multi-factor COX regression analysis, and age (HR = 1.515, 95 %CI, 0.994-2.311, P = 0.001), EF (HR = 0.526, 95% CI, 0.361-0.766, P=0.05) were independent factors related to the prognosis of patients. Classification based on the clinical diagnosis of echocardiography in newly diagnosed acute leukemia patients, significant differences in myocardial enzymes and related indicators of echocardiography were included for ROC plots. The 3 indicators with the highest results for the area under the curve (AUC) from ROC plots were LV, EDV and HBDH, AUC were 0.721,0.619 and 0.615, respectively. This result revealed that the best predictor of leukemia myocardial damage was LV. It showed the predict ability of LV (AUC = 0.721, 95%CI = 0.643-0.799, P &lt;0.001; sensitivity = 42.4%; specificity = 91.8%). Conclusions： According to our research, we have confirmed that the cardiac function of newly diagnosed acute leukemia patients is significantly different from that of patients without leukemia, and these differences will have an impact on the prognosis of patients. Among them, the best predictor of leukemia heart damage is LV, and EF is an independent risk factor for the prognosis of leukemia patients. In addition, newly diagnosed acute leukemia patients are more likely to have an increase in left ventricular diameter and a significant decrease in ejection fraction. Further research is needed to explore the specific mechanism in the future. Disclosures No relevant conflicts of interest to declare.

Effect of cumulative dexamethasone dose during concomitant chemoradiation on lymphopenia in patients with newly diagnosed glioblastoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14533-e14533
Author(s):  
Stephen Ahn ◽  
Jae-Sung Park ◽  
Jin Ho Song ◽  
Sin-Soo Jeun ◽  
Yong-Kil Hong
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Cox Regression ◽  
Performance Status ◽  
Multivariate Logistic Regression Analysis ◽  
Newly Diagnosed ◽  
Cox Regression Analysis ◽  
Female Sex ◽  
Concomitant Chemoradiation ◽  
Independent Risk Factors

e14533 Background: Lymphopenia frequently occurs after concomitant chemoradiation (CCRT) in patients with glioblastoma (GBM) and is associated with worse overall survival (OS). A few studies have tried to identify risk factors for lymphopenia; however, the results were not clear. We aimed to identify potential risk factors for lymphopenia, focusing on the use of dexamethasone to control cerebral edema in patients with GBM. Methods: The electronic medical records of 180 patients with newly diagnosed GBM treated at our institution between 2009 and 2017 were retrospectively examined. Acute lymphopenia was defined as TLC (total lymphocyte count) less than 1,000 cells/mm3 at 4 weeks after completion of CCRT. Multivariate logistic regression analysis was used to identify independent risk factors for lymphopenia, and Cox regression analysis was used to identify independent risk factors for OS. Results: Of the 125 eligible patients, 40 patients (32.0%) developed acute lymphopenia. Female sex and median daily dexamethasone dose > 2mg after initiation of CCRT were independent risk factors for acute lymphopenia on multivariate analysis. Acute lymphopenia, extent of surgical resection, and performance status were associated with OS; however, dexamethasone use itself was not an independent risk factor for poor OS. Conclusions: Female sex, median daily dexamethasone dose > 2 mg after initiation of CCRT until four weeks after completion of CCRT may be associated with acute lymphopenia. However, dexamethasone use itself did not affect OS in patients newly diagnosed with GBM. These results should be validated by further prospective studies controlling for other confounding factors.

scholarly journals A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110279
Author(s):  
Qinping Guo ◽  
Yinquan Wang ◽  
Jie An ◽  
Siben Wang ◽  
Xiushan Dong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Cox Regression ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Signet Ring ◽  
Ring Cell ◽  
Independent Risk Factors

Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.

scholarly journals Alternative splicing acts as an independent prognosticator in ovarian carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yan Ouyang ◽  
Kaide Xia ◽  
Xue Yang ◽  
Shichao Zhang ◽  
Li Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Alternative Splicing ◽  
Ovarian Carcinoma ◽  
Cancer Patients ◽  
Cox Regression ◽  
Excision Repair ◽  
Splicing Factors ◽  
Prognostic Signature ◽  
Cox Regression Analysis

AbstractAlternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

NLRP3 is a Novel Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma and Skin Cutaneous Melanoma

2021 ◽  
Author(s):  
Chenxi Yuan ◽  
Qingwei Wang ◽  
Xueting Dai ◽  
Yipeng Song ◽  
Jinming Yu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
The Impact ◽  
Nlrp3 Expression

Abstract Background: Lung adenocarcinoma (LUAD) and skin cutaneous melanoma (SKCM) are common tumors around the world. However, the prognosis in advanced patients is poor. Because NLRP3 was not extensively studied in cancers, so that we aimed to identify the impact of NLRP3 on LUAD and SKCM through bioinformatics analyses. Methods: TCGA and TIMER database were utilized in this study. We compared the expression of NLRP3 in different cancers and evaluated its influence on survival of LUAD and SKCM patients. The correlations between clinical information and NLRP3 expression were analyzed using logistic regression. Clinicopathologic characteristics associated with overall survival in were analyzed by Cox regression. In addition, we explored the correlation between NLRP3 and immune infiltrates. GSEA and co-expressed gene with NLRP3 were also done in this study. Results: NLRP3 expressed disparately in tumor tissues and normal tissues. Cox regression analysis indicated that up-regulated NLRP3 was an independent prognostic factor for good prognosis in LUAD and SKCM. Logistic regression analysis showed increased NLRP3 expression was significantly correlated with favorable clinicopathologic parameters such as no lymph node invasion and no distant metastasis. Specifically, a positive correlation between increased NLRP3 expression and immune infiltrating level of various immune cells was observed. Conclusion: Together with all these findings, increased NLRP3 expression correlates with favorable prognosis and increased proportion of immune cells in LUAD and SKCM. These conclusions indicate that NLRP3 can serve as a potential biomarker for evaluating prognosis and immune infiltration level.

scholarly journals Expression of LOX Suggests Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Expression Level ◽  
Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p &lt; 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

scholarly journals Effect of Positive Hepatitis B Surface Antigen on The Risk of Synchronous Liver Metastasis: A Retrospective Study of 868 Consecutive Patients of Newly Diagnosed Gastric Cancer

2020 ◽  
Author(s):  
Tingya Wang ◽  
Haijun Zhang
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Retrospective Study ◽  
Liver Metastasis ◽  
Hepatitis B ◽  
Surface Antigen ◽  
Hepatitis B Surface Antigen ◽  
Newly Diagnosed

Abstract Background. The study aimed to explore the influence of hepatitis B virus (HBV) infection on the risk of synchronous gastric cancer liver metastasis (synGCLM).Methods. This was a retrospective study which enrolled 868 patients with newly diagnosed gastric cancer (GC). The study compared the prevalence of synGCLM between hepatitis B surface antigen (HBsAg)-positive (HBsAg+) and -negative (HBsAg-) patients. Logistic regression analysis was utilized to analyze the risk factors for synGCLM. Among patients with and without synGCLM, aspartate aminotransferase to platelet ratio index (APRI), liver fibrosis-4 index (FIB-4) and hepatitis B e antigen (HBeAg) status were further analyzed. Results. The prevalence of synGCLM in the HBsAg+ patients was higher than that in the HBsAg- patients, which was statistically significant (P = 0.025). Multivariate logistic regression analysis demonstrated that HBsAg, the elevated level of carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), γ-glutamyltransferase (GGT) and alkaline phosphatase (ALP) were risk factors for synGCLM. Among the HBsAg+ patients, both ARPI and FIB-4 were significantly higher in the patients with synGCLM (synGCLM+) than those without synGCLM (synGCLM-) (ARPI: P = 0.045; FIB-4: P = 0.047); HBeAg positivity was detected in 20.0% of synGCLM+ patients compared to 6.0% of synGCLM- patients, but the difference was of no significance (P = 0.190). Conclusions. HBV infection significantly increases the risk of synGCLM, and elevated ARPI and FIB-4 may be pro-metastatic especially among the HBsAg+ GC patients.

scholarly journals Incidence, Survival, and Associated Factors Estimation in Osteosarcoma Patients with Lung Metastasis: A Single-center Experience of 11 Years in Tianjin, China

2021 ◽  
Author(s):  
Chao Zhang ◽  
Haixiao Wu ◽  
Guijun Xu ◽  
Wenjuan Ma ◽  
Lisha Qi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Lung Metastasis ◽  
Associated Factors ◽  
Cox Regression ◽  
Cancer Center ◽  
Single Center ◽  
Cox Regression Analysis

Abstract Background: Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods: From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. Prognostic factors of patients with osteosarcoma were identified by the Cox proportional hazard regression analysis. Risk factor of lung metastasis in osteosarcoma were investigated by the logistic regression model. Results: A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteo-sarcoma patients was 70.0%. Surgery, bone and lung metastasis were the significant prognostic factors in multivariable Cox regression analysis. Twenty-one (10.3%) patients showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) lung metastases during the later course. T3 stage (OR=11.415, 95%CI 1.362-95.677, P=0.025) and synchronous bone metastasis (OR=6.437, 95%CI 1.69-24.51, P=0.006) were risk factors of synchronous lung metastasis occurrence. Good necrosis (≥90%, OR=0.097, 95%CI 0.028-0.332, P=0.000) and elevated Ki-67 (≥50%, OR=4.529, 95%CI 1.241-16.524, P=0.022) were proved to be significantly associated with metachronous lung metastasis occurrence. Conclusion: The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management.

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