The Nomograms for Predicting Cancer-specific Survival in Patients With Ovarian Cancer After Surgery

Cox Regression ◽

Clear Cell Adenocarcinoma ◽

Regional Lymph Nodes ◽

Mixed Cell ◽

Cox Regression Analysis ◽

High Risk Factors ◽

Adenocarcinoma Of The Ovary ◽

Good Calibration

Abstract Objectives: Clear cell adenocarcinoma of the ovary (CCAO) and mixed cell adenocarcinoma of the ovary (MACO) were one of the gynecological malignancies.Methods: Univariate and multivariate cox regression analysis were used to determine prognostic factors. Drawing nomograms, the receiver operating characteristic (ROC) curve and the calibration curve was applied to evaluate the agreement of the nomogram. The survival analysis was constructed to the high-risk factors.Results: The nomogram was constructed and had a better discrimination. The calibration curves indicated that the nomograms had good calibration capabilities.4 or more regional lymph nodes removed by surgery was beneficial to the patient's prognosis. Conclusions: Our study analyzed the prognosis of CCAO or MACO patients, and constructed a predictive nomogram with good accuracy.

Effects of marital status on overall and cancer-specific survival in laryngeal cancer patients: a population-based study

Scientific Reports ◽

10.1038/s41598-020-80698-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhao Ding ◽

Deshun Yu ◽

Hefeng Li ◽

Yueming Ding

Keyword(s):

Marital Status ◽

Cancer Patients ◽

Laryngeal Cancer ◽

Cox Regression ◽

Group Analysis ◽

Population Based ◽

Cox Regression Analysis ◽

Prognostic Effect ◽

The Difference

AbstractMarital status has long been recognized as an important prognostic factor for many cancers, however its’ prognostic effect for patients with laryngeal cancer has not been fully examined. We retrospectively analyzed 8834 laryngeal cancer patients in the Surveillance Epidemiology and End Results database from 2004 to 2010. Patients were divided into four groups: married, widowed, single, and divorced/separated. The difference in overall survival (OS) and cancer-specific survival (CSS) of the various marital subgroups were calculated using the Kaplan–Meier curve. Multivariate Cox regression analysis screened for independent prognostic factors. Propensity score matching (PSM) was also conducted to minimize selection bias. We included 8834 eligible patients (4817 married, 894 widowed, 1732 single and 1391 divorced/separated) with laryngeal cancer. The 5-year OS and CSS of married, widowed, single, and separated/divorced patients were examined. Univariate and multivariate analyses found marital status to be an independent predictor of survival. Subgroup survival analysis showed that the OS and CSS rates in widowed patients were always the lowest in the various American Joint Committee on Cancer stages, irrespective of sex. Widowed patients demonstrated worse OS and CSS in the 1:1 matched group analysis. Among patients with laryngeal cancer, widowed patients represented the highest-risk group, with the lowest OS and CSS.

Trends of incidence and prognosis of primary adenocarcinoma of the bladder

Therapeutic Advances in Urology ◽

10.1177/17562872211018006 ◽

2021 ◽

Vol 13 ◽

pp. 175628722110180

Author(s):

Haowen Lu ◽

Weidong Zhu ◽

Weipu Mao ◽

Feng Zu ◽

Yali Wang ◽

...

Keyword(s):

Prediction Model ◽

Marital Status ◽

Cox Regression ◽

Tnm Staging ◽

Primary Site ◽

Primary Adenocarcinoma ◽

Training Cohort ◽

Cox Regression Analysis ◽

Ajcc Stage

Background: Primary adenocarcinoma of the bladder (ACB) is a rare malignant tumor of the bladder with limited understanding of its incidence and prognosis. Methods: Patients diagnosed with ACB between 2004 and 2015 were obtained from the SEER database. The incidence changes of ACB patients between 1975 and 2016 were detected by Joinpoint software. Nomograms were constructed based on the results of multivariate Cox regression analysis to predict overall survival (OS) and cancer-specific survival (CSS) in patients with ACB, and the constructed nomograms were validated. Results: The incidence of ACB was trending down from 1991 to 2016. A total of 1039 patients were included in the study and randomly assigned to the training cohort (727) and validation cohort (312). In the training cohort, multivariate Cox regression showed that age, marital status, primary site, histology type, grade, AJCC stage, T stage, SEER stage, surgery, radiotherapy, and chemotherapy were independent prognostic factors for OS, whereas these were age, marital status, primary site, histology type, grade, AJCC stage, T/N stage, SEER stage, surgery, and radiotherapy for CSS. Based on the above Cox regression results, we constructed prognostic nomograms for OS and CSS in ACB patients. The C-index of the nomogram OS was 0.773 and the C-index of CSS was 0.785, which was significantly better than the C-index of the TNM staging prediction model. The area under the curve (AUC) and net benefit of the prediction model were higher than those of the TNM staging system. In addition, the calibration curves were very close to the ideal curve, suggesting appreciable reliability of the nomograms. Conclusion: The incidence of ACB patients showed a decreasing trend in the past 25 years. We constructed a clinically useful prognostic nomogram for calculating OS and CSS of ACB patients, which can provide a personalized risk assessment for ACB patient survival.

Diagnostic and prognostic significance of miR-451a in patients with atherosclerosis

Vascular ◽

10.1177/17085381211058571 ◽

2021 ◽

pp. 170853812110585

Author(s):

Baizhi Wang ◽

Xingliang Duan ◽

Qing Xu ◽

Yani Li

Keyword(s):

Cox Regression ◽

Prognostic Biomarker ◽

Prognostic Significance ◽

High Sensitivity ◽

Roc Curves ◽

Cox Regression Analysis ◽

Chi Squared ◽

Cardiovascular Endpoint ◽

Inflammatory Vascular Disease

Objectives Atherosclerosis (AS) is a chronic inflammatory vascular disease. This study aimed to detect the expression level of miR-451a and investigate the diagnostic and prognostic values of miR-451a for AS patients. Methods The relative expression of miR-451a was assessed by qRT-PCR. Comparison of groups was analyzed with the t-test and chi-squared test. Pearson analysis was used to validate the correlation of miR-451 with CRP and CIMT. The receiver operating characteristic (ROC) curves, K-M analysis, and Cox regression analysis were conducted to explore the roles of miR-451a in diagnosing AS patients and predicting outcomes of AS patients. Results The expression of miR-451a was significantly decreased in the serum of AS patients. The results of Pearson analysis showed the expression of miR-451a was negatively correlated with CRP and CIMT. The data of ROC proposed miR-451a could differentiate AS patients from healthy individuals with high sensitivity and specificity. K-M analysis and Cox regression showed miR-451a might be an independent biomarker of suffering cardiovascular endpoint diseases in AS patients. The expression of miR-451a was obviously inhibited in AS patients with cardiovascular endpoint events. Conclusion Deregulation of miR-451a might be associated with the development of AS. MiR-451a might be used as a promising diagnostic and prognostic biomarker for clinical treatment of AS patients.

Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.632803 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shaojie Chen ◽

Feifei Huang ◽

Shangxiang Chen ◽

Yinting Chen ◽

Jiajia Li ◽

...

Keyword(s):

Pancreatic Cancer ◽

Overall Survival ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Cox Regression ◽

Time Dependent ◽

Concordance Index ◽

Cox Regression Analysis ◽

Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

Overall Survival Rate Analysis For Risk Factors In Women With Neuroendocrine Carcinoma of The Cervix Using Surveillance, Epidemiology, And End Results (SEER) Database

10.21203/rs.3.rs-1131793/v1 ◽

2021 ◽

Author(s):

Ziran Yin ◽

Xiumin Huang

Keyword(s):

Overall Survival ◽

Lymph Nodes ◽

Neuroendocrine Carcinoma ◽

Cox Regression ◽

Analysis Data ◽

Seer Database ◽

Regional Lymph Nodes ◽

Data Set ◽

Cox Models ◽

Cox Regression Analysis

Abstract Background: Neuroendocrine carcinoma of the cervix is rare and aggressive disease, of which prognosis information and the effectiveness of the therapies is unclear.Methods: A retrospective study using data from the SEER database for the first diagnosed Neuroendocrine carcinoma of the cervix patients was conducted. We performed univariate and multivariate Cox models to screen for independent prognostic factors for overall survival. Subgroup analysis and sensitive analysis were performed for further study, then again univariate and multivariate analyses of Cox regression analysis were performed based on the sensitivity analysis data set.Results: A total of 250 Neuroendocrine carcinoma of the cervix cases was included, tumor subtype, age, marriage, race, number of regional lymph nodes, number of positive lymph nodes, radiotherapy, surgery, and FIGO stage were all factors affecting OS, and multivariate analysis identified FIGO staging (HR, 2.4; 95% CI, 1.505-3.828, P < 0.001) and surgery (HR, 0.467; 95% CI, 0.358-0.609, P < 0.001) treatment as independent indicators. With respect to the factors associated with treatments, we found that patients who underwent surgery (yes vs. no vs. unknown) or radiation (yes vs. no) experienced prolonged survival, both P < 0.001Conclusions: Our investigation shows that for patients with NECC surgery seems to be the effective treatment. Chemotherapy cannot improve the prognosis of NECC patients, and the effectiveness of radiation should be further verified.

A risk stratification model based on four novel biomarkers predicts prognosis for patients with renal cell carcinoma

World Journal of Surgical Oncology ◽

10.1186/s12957-020-02046-9 ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Shigehisa Kubota ◽

Tetsuya Yoshida ◽

Susumu Kageyama ◽

Takahiro Isono ◽

Takeshi Yuasa ◽

...

Keyword(s):

Prognostic Model ◽

Cox Regression ◽

Treatment Strategies ◽

Immunohistochemical Analysis ◽

Clinical Prognosis ◽

Cox Regression Analysis ◽

Model Based ◽

Novel Biomarkers ◽

Metastatic Rcc

Abstract Background Accurate prediction of the prognosis of RCC using a single biomarker is challenging due to the genetic heterogeneity of the disease. However, it is essential to develop an accurate system to allow better patient selection for optimal treatment strategies. ARL4C, ECT2, SOD2, and STEAP3 are novel molecular biomarkers identified in earlier studies as survival-related genes by comprehensive analyses of 43 primary RCC tissues and RCC cell lines. Methods To develop a prognostic model based on these multiple biomarkers, the expression of four biomarkers ARL4C, ECT2, SOD2, and STEAP3 in primary RCC tissue were semi-quantitatively investigated by immunohistochemical analysis in an independent cohort of 97 patients who underwent nephrectomy, and the clinical significance of these biomarkers were analyzed by survival analysis using Kaplan-Meier curves. The prognostic model was constructed by calculation of the contribution score to prognosis of each biomarker on Cox regression analysis, and its prognostic performance was validated. Results Patients whose tumors had high expression of the individual biomarkers had shorter cancer-specific survival (CSS) from the time of primary nephrectomy. The prognostic model based on four biomarkers segregated the patients into a high- and low-risk scored group according to defined cut-off value. This approach was more robust in predicting CSS compared to each single biomarker alone in the total of 97 patients with RCC. Especially in the 36 metastatic RCC patients, our prognostic model could more accurately predict early events within 2 years of diagnosis of metastasis. In addition, high risk-scored patients with particular strong SOD2 expression had a much worse prognosis in 25 patients with metastatic RCC who were treated with molecular targeting agents. Conclusions Our findings indicate that a prognostic model based on four novel biomarkers provides valuable data for prediction of clinical prognosis and useful information for considering the follow-up conditions and therapeutic strategies for patients with primary and metastatic RCC.

Survival predictors of metastatic angiosarcomas: a surveillance, epidemiology, and end results program population-based retrospective study

BMC Cancer ◽

10.1186/s12885-020-07300-7 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Shihong Ren ◽

Yucheng Wang ◽

Zhan Wang ◽

Jinxiang Shao ◽

Zhaoming Ye

Keyword(s):

Tumor Size ◽

Cox Regression ◽

Radiation Treatment ◽

Tumor Grade ◽

Population Based ◽

Cox Regression Analysis ◽

Metastatic Sites ◽

Survival Predictors ◽

End Results

Abstract Background Angiosarcomas (AS) have poor prognosis and often metastasize to distant sites. The potential predictors of metastatic angiosarcomas (MAS) have not been extensively investigated. The main objective of this study was to identify survival predictors of MAS. Methods Surveillance, Epidemiology, and End Results (SEER) datasets were used to identify patients with MAS from 2010 to 2016. Risk predictors were determined with the aid of Kaplan-Meier and Cox regression model analyses. Results A total of 284 MAS patients met the study entry criteria. Among these, 121 patients (42.6%) were diagnosed with metastasis in bone, 26 in brain (9.2%), 86 in liver (30.3%) and 171 in lung (60.2%). Overall, 96 patients (33.8%) had two or more metastatic sites. The 1- and 3-year overall survival (OS) rates were 20.8 and 3.8% while 1- and 3-year cancer-specific survival (CSS) rates were 22.0 and 5.2%, respectively. Cox regression analysis revealed chemotherapy, radiation treatment (RT) and tumor size ≤10 cm as independent favorable predictors of OS. In terms of CSS, tumor grade IV, tumor size > 10 cm and absence of chemotherapy were independent adverse predictors. Surgery did not prolong survival outcomes (both OS and CSS) in the current cohort. Conclusion MAS is associated with extremely poor survival. Chemotherapy, RT, and tumor size are independent predictors of OS. Chemotherapy and tumor size are independent prognostic factors of CSS. Chemotherapy is therefore recommended as the preferred treatment option for MAS patients.

Oncological outcomes of neoadjuvant chemotherapy in patients with locally advanced upper tract urothelial carcinoma: A multicenter study.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.6_suppl.429 ◽

2018 ◽

Vol 36 (6_suppl) ◽

pp. 429-429

Author(s):

Shingo Hatakeyama ◽

Yuka Kubota ◽

Hayato Yamamoto ◽

Takahiro Yoneyama ◽

Yasuhiro Hashimoto ◽

...

Keyword(s):

Regression Analysis ◽

Neoadjuvant Chemotherapy ◽

Urothelial Carcinoma ◽

Lymphovascular Invasion ◽

Cox Regression ◽

Locally Advanced ◽

Upper Tract Urothelial Carcinoma ◽

Cox Regression Analysis ◽

Oncological Outcomes

429 Background: The clinical impact of neoadjuvant chemotherapy (NAC) on oncological outcomes in patients with locally advanced upper tract urothelial carcinoma (UTUC) remains unclear. We investigated the oncological outcomes of platinum-based NAC for locally advanced UTUC. Methods: A total of 426 patients who underwent radical nephroureterectomy at five medical centers between January 1995 and April 2017 were examined retrospectively. Of the 426 patients, 234 were treated for a high-risk disease (stages cT3–4 or locally advanced [cN+] disease) with or without NAC. NAC regimens were selected based on eligibility of cisplatin. We retrospectively evaluated post-therapy pathological downstaging, lymphovascular invasion, and prognosis stratified by NAC use. Multivariate Cox regression analysis was performed for independent factors for prognosis. Results: Of 234 patients, 101 received NAC (NAC group) and 133 did not (Control [Ctrl] group). The regimens in the NAC group included gemcitabine and carboplatin (75%), and gemcitabine and cisplatin (21%). Pathological downstagings of the primary tumor and lymphovascular invasion were significantly improved in the NAC than in the Ctrl groups. NAC for locally advanced UTUC significantly prolonged recurrence-free and cancer-specific survival. Multivariate Cox regression analysis using an inverse probability of treatment weighted (IPTW) method showed that NAC was selected as an independent predictor for prolonged recurrence-free and cancer-specific survival. However, the influence of NAC on overall survival was not statistically significant. Conclusions: Platinum-based NAC for locally advanced UTUC potentially improves oncological outcomes. Further prospective studies are needed to clarify the clinical benefit of NAC for locally advanced UTUC.

Systematic Analysis of the Relationship Between Ovarian Cancer Prognosis and Alternative Splicing

10.21203/rs.3.rs-488874/v1 ◽

2021 ◽

Author(s):

Di Zhang ◽

Dan Zou ◽

Yue Deng ◽

Lihua Yang

Keyword(s):

Regression Analysis ◽

Cox Regression ◽

Risk Groups ◽

Time Dependent ◽

Survival Curves ◽

Cox Regression Analysis ◽

Prognostic Analysis ◽

Independent Analysis ◽

The Relationship

Abstract Background: Ovarian cancer(OC) is the gynecological tumor with the highest mortality rate, effective biomarkers are of great significance in improving its prognosis. In recent years, there have been many studies on alternative splicing (AS) events, and the role of AS events in tumor has become a focus of attention.Methods: Data were downloaded from the TCGA database and Univariate Cox regression analysis was performed to determine AS events associated with OC prognosis. Eight prognostic models of OC were constructed in R package, and the accuracy of the models were evaluated by the time-dependent receiver operating characteristic (ROC) curves. Eight types of survival curves were drawn to evaluate the differences between the high and low risk groups. Independent prognostic factors of OC were analyzed by single factor independent analysis and multi-factor independent prognostic analysis. Again, Univariate Cox regression analysis was used to analyze the relationship between splicing factors(SF) and AS events, and Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis were performed on OS-related SFs to understand the pathways.Results: Univariate Cox regression analysis showed that among the 15,278 genes, there were 31,286 overall survival (OS) related AS events, among which 1524 AS events were significantly correlated with OS. The area under the time-dependent receiver operating characteristic curve (AUC) of AT and ME were the largest and the RI was the smallest ,which were 0.757 and 0.68 respectively. The constructed models have good value for the prognosis assessment of OC patients. Among the eight survival curves, AP was the most significant difference between the high and low risk groups, with a P value of 1.61e−1.The results of single factor independent analysis and multi-factor independent prognostic analysis showed that risk score calculated by the model and age could be used as independent risk factors. According to univariate COX regression analysis ,109 SFs were correlated with AS events and adjusted in two ways: positive and negative.Conclusions: SFs and AS events can directly or indirectly affect the prognosis of OC patients. It is very important to find effective prognostic markers to improve the survival rate of OC.

A Novel Predictive Model Associated With Osteosarcoma Metastasis

10.21203/rs.3.rs-597836/v1 ◽

2021 ◽

Author(s):

Han Zhang ◽

Guanhong Chen ◽

Xiajie Lyu ◽

Tao Li ◽

Rong Chun ◽

...

Keyword(s):

Cox Regression ◽

High Reliability ◽

Characteristic Curve ◽

Predictive Ability ◽

Lasso Regression ◽

Cox Regression Analysis ◽

Metastasis Model ◽

Non Coding Rnas ◽

Novel Model

Abstract Background: Long non-coding RNAs (lncRNAs) have diverse roles in modulating gene expression on both transcriptional and translational aspects, whereas its role in the metastasis of osteosarcoma (OS) is unclear.Method: Expression and clinical data were downloaded from TARGET datasets. The OS metastasis model was established by seven lncRNAs screened by univariate cox regression, lasso regression and multivariate cox regression analysis. The area under receiver operating characteristic curve (AUC) values were used to evaluate the models.Results: The predictive ability of this model is extraordinary (1 year: AUC = 0.92, 95% Cl = 0.83–1.01; 3 years: AUC = 0.87, 95% Cl = 0.79–0.96; 5 years: AUC = 0.86, 95% Cl = 0.76–0.96). Patients in high group had poor survival compared to low group (p < 0.0001). “NOTCH_SIGNALING”, and “WNT_BETA_CATENIN_SIGNALING” were enriched via the GSEA analysis and dendritic cells resting were associated with the AL512422.1, AL357507.1 and AC006033.2 (p < 0.05).Conclusion: We constructed a novel model with high reliability and accuracy to predict the metastasis of OS patients based on seven prognosis-related lncRNAs.