Time-dependent Receiver Operating Characteristic Curve Research Articles

Construction of a CCL20-centered circadian-signature based prognostic model in cervical cancer

BackgroundRather low vaccination rates for Human papillomavirus (HPV) and pre-existing cervical cancer patients with limited therapeutic strategies ask for more precise prognostic model development. On the other side, the clinical significance of circadian clock signatures in cervical cancer lacks investigation.MethodsSubtypes classification based upon eight circadian clock core genes were implemented in TCGA-CESC through k-means clustering methods. Afterwards, KEGG, GO and GSEA analysis were conducted upon differentially expressed genes (DEGs) between high and low-risk groups, and tumor microenvironment (TME) investigation by CIBERSORT and ESTIMATE. Furthermore, a prognostic model was developed by cox and lasso regression methods, and verified in GSE44001 by time-dependent receiver-operating characteristic curve (ROC) analysis. Lastly, FISH and IHC were used for validation of CCL20 expression in patients’ specimens and U14 subcutaneous tumor models were built for TME composition.ResultsWe successfully classified cervical patients into high-risk and low-risk groups based upon circadian-oscillation-signatures. Afterwards, we built a prognostic risk model composed of GJB2, CCL20 and KRT24 with excellent predictive value on patients’ overall survival (OS). We then proposed metabolism unbalance, especially for glycolysis, and immune related pathways to be major enriched signatures between the high-risk and low-risk groups. Then, we proposed an ‘immune-desert’-like suppressive myeloid cells infiltration pattern in high-risk group TME and verified its resistance to immunotherapies. Finally, CCL20 was proved positively correlated with real-world patients’ stages and induced significant less CD8+ T cells and more M2 macrophages infiltration in mouse model.ConclusionsWe unraveled a prognostic risk model based upon circadian oscillation and verified its solidity. Specifically, we unveiled distinct TME immune signatures in high-risk groups.

A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer.

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO-Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients' response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.

Prognostic significance of TMEM131L in glioma and establishment of oxidative stress prognostic model.

Gliomas are the most aggressive of all brain tumors. In this study, it was found that there is a significant expression of transmembrane-like 131 (TMEM131L) in glioma tissues. The relevance of TMEM131L in the diagnosis and clinical prognosis of GBM and LGG was verified by additional clinical correlation and survival analysis. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve reflected the diagnostic effect of TMEM131L on the clinicopathologic features of glioma. As a unique molecular marker for the poor prognosis of overall survival (OS), PFI, and DSS in patients with GCB and LGG, TMEM131L might be employed, according to time-dependent ROC curves and Kaplan-Meier survival analysis at 1, 3, and 5 years. The potential methylation sites of TMEM131L were selected by correlation analysis between TMEM131L and DNA methylation sites. Meanwhile, TMEM131L was significantly correlated with matrix, immunity, and estimated scores of GBM and LGG. The CIBERSORT analysis revealed a significant correlation between immune checkpoint and infiltration of 22 different kinds of immune cells. Coexpression genes of TMEM131L associated with oxidative stress phenotype were screened by the LASSO logistic regression analysis. Nomogram and calibration curves further confirmed that the prognostic model composed of SYT1, CREB3L3, ITPR1, RASGRF2, PDX1, and RASGRF1 has good stability and potential application value for poor prognosis in patients with glioma.

Nomogram Based on Preoperative Absolute Lymphocyte Count to Predict Local Recurrence in Patients with Non-Small Cell Lung Cancer After Microwave Ablation.

This study aims to investigate the prognostic value of preoperative absolute lymphocyte count (preALC) for non-small cell lung cancer (NSCLC) after microwave ablation (MWA) and build a combined nomograph with clinical features to predict the local recurrence. A total of 118 NSCLC patients who underwent microwave ablation were enrolled in this study. The median local recurrence-free survival (LRFS) was 35.5 months. Independent prognostic factors obtained by multivariate analysis were included in the prediction model. The prognostic value of the model was assessed by the area under the time-dependent receiver operating characteristic curve (T-AUC). Histological subtype and preALC were independent risk factors for local relapse-free survival. According to the time-dependent receiver operating characteristic curve (T-ROC), the optimal cut-off value of preALC was 1.965×109/L, the sensitivity was 0.837, and the specificity was 0.594. The area under the T-ROC curve (AUC) of preALC was 0.703. To establish a nomogram to predict the local recurrence rate of NSCLC after MWA based on the prognostic factors revealed by Cox regression. Preoperative lymphocyte count reduction is associated with poor prognosis of NSCLC. The nomogram model combined with preALC can provide a good individualized prediction of local recurrence after microwave ablation.

Impact of surgical resection for gastrointestinal stromal tumor (GIST) patients with initially diagnosed synchronous hepatic metastases on long-term survival outcomes.

The effect of surgical resection on the long-term outcome of GIST patients with initially diagnosed synchronous hepatic metastases in the targeted therapy era is still uncertain. The main aims of this study were to investigate the role of surgery in the treatment of these patients and establish clinical predictive models for assessing prognosis. We identified these patients from the Surveillance, Epidemiology and End Results (SEER) database between 2010 and 2018. The selection bias in comparisons was minimized by performing propensity score matching (PSM). The risk factors associated with long-term survival outcomes were identified by a Cox proportional hazards model and thus used to establish the nomograms. Nomograms were validated by concordance indexes (C-indexes), time-dependent receiver operator characteristic (ROC) curves, calibration plots, and decision curve analyses (DCA). Of these 523 eligible patients, there were 187 (35.8%) and 336 (64.2%) patients in the surgical and nonsurgical groups, respectively. Multivariate analysis revealed that surgical resection was an independent prognostic factor for OS (hazard ratio [HR] 0.62; 95% confidence interval [CI] 0.44-0.88, p=0.0068) and CSS (HR 0.51; 95% CI 0.33 - 0.77, p=0.0016). After PSM, it was found that surgical resection still showed significantly improved OS (5-year 54.9% vs 38.8%, p=0.028) and CSS (5-year 65.8% vs 50.3%, p=0.077). In addition, the C-indexes of the nomograms for OS and CSS prediction were 0.692 and 0.705, respectively, and the nomograms showed good consistency. This study revealed that surgical resection has a favorable impact on the long-term outcome of patients with synchronous GIST liver metastases, and the nomograms showed remarkable prediction performance for OS and CSS.

Prognostic significance of the Naples prognostic score in colorectal cancer patients undergoing curative resection: a propensity score matching analysis

BackgroundSystemic inflammation is recognized as a hallmark of cancer that contributes to tumor development and progression in various malignancies. The Naples prognostic score (NPS) was established as a prognostic indicator for colorectal cancer (CRC). This study aims to examine the predictive value of the NPS for survival in CRC patients undergoing curative resection by a propensity score matching (PSM) analysis.MethodsA total of 533 CRC patients were enrolled in this study. Overall survival (OS) and disease-free survival (DFS) were compared between high-NPS and low-NPS groups. A time-dependent receiver operator characteristic (ROC) curve analysis was conducted to calculate the area under curve (AUC) of the NPS for OS. A multivariable Cox-proportional hazards regression analysis and PSM analysis were used to identify independent prognostic factors for OS and DFS. We compared the predictive value of the NPS to that of the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), Onodera prognostic nutritional index (PNI), and controlling nutritional status score (CONUT) for OS.ResultsHigh-NPS was significantly associated with worse OS and DFS. After PSM, 123 patients were included in each group. A multivariate analysis revealed that Age ≥ 68, ASA-PS ≥ 3, high NPS and undifferentiated tumor type were independently associated with OS, while high NPS, advanced T and N stage were independently associated with DFS after PSM. The NPS had the greatest AUC for OS in comparison to the NLR, LMR, PNI and CONUT.ConclusionsWe successfully validated the prognostic utility of the NPS for CRC patients after curative resection.

Associations of levels of peripheral blood leukocyte and subtypes with type 2 diabetes: A longitudinal study of Chinese government employees.

Available evidence suggests that type 2 diabetes (T2D) may be associated with inflammation and that leukocytes are a topical clinical, biological indicator of inflammation. This study investigates the associations between peripheral blood leukocyte and subtypes levels with T2D. A total of 5,475 individuals were included in the baseline examination from January 2018 to April 2020, with incidence data updated to April 30, 2021, and follow-up to 5,362 individuals. T2D was defined according to the Chinese guidelines for preventing and treating type 2 diabetes. Physiological and biochemical indicators, including leukocyte and subtypes, were obtained from the physical examination results of the tertiary care hospitals relied on at the cohort sites. Covariates such as demographic characteristics and lifestyle were collected by questionnaire. Binary logistic regression and Cox proportional hazard models were used to explore the correlations. Receiver Operating Characteristic (ROC) curves and time-dependent ROC curves were used to estimate the predictive diagnosis of T2D across the subtype of leukocytes. The mean follow-up time was 12 months, and the cumulative incidence density of T2D was 4.0/1000 person-years. Cross-sectional results at baseline showed that the levels of peripheral blood leukocyte and its subtypes were higher in the T2D group than in the non-T2D group. Total leukocyte count and subtypes levels were grouped by quintile. After adjusting for age, sex, family history of diabetes, lifestyle score, and triglyceride levels, all were compared with the lowest quintile of each group. Logistic regression model results showed that the corrected OR for those with the highest quintile level of leukocyte was 2.01 (95% CI: 1.02-3.98). The longitudinal analysis showed that the adjusted HR was 8.43 (95%CI: 1.06-66.92) for those with the highest quintile level of leukocytes at baseline after controlling for the effects of the above covariates. For those with the highest quintile level of neutrophils at baseline, the adjusted HR was 5.05 (95%CI: 1.01-25.29). The leukocyte and subtypes had predictive values for T2D. Patients with T2D have a higher level of peripheral blood leukocyte and subtypes than those without the disease. Elevated leukocyte and neutrophil counts may link to a higher risk of T2D.

Development and validation of nomograms for predicting survival in differentiated thyroid cancer patients with or without radioiodine therapy.

This study aimed to establish and validate the nomograms for predicting overall survival (OS) probabilities in differentiated thyroid cancer (DTC) patients who received and did not receive radioiodine therapy (RAI), respectively. In this study, 11, 099 patients diagnosed with DTC in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2016 were selected. Whether they have RAI, they are divided into RAI (n=6427) and non-RAI (n=4672) groups. They were randomly assigned to either a training cohort (RAI: n=4498, non-RAI: n=3263) or a validation cohort (RAI: n=1929, non-RAI: n=1399) using R software to divide the patients in a 7-to-3 ratio randomly. Variables were selected using a backward stepwise method in a Cox regression model to determine the independent prognostic factors, which were then utilized to build two nomograms to predict the 5-, 8-, and 10-year OS probabilities in DTC patients with or without RAI. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the performance of our models. The multivariate analyses demonstrated that birth of the year, race, histological type, tumor size, grade, TNM stage, lymph node dissections, surgery, and chemotherapy were risk factors for OS. Compared to the AJCC stage, the C-index (RAI: training group: 0.911 vs. 0.810, validation group: 0.873 vs. 0.761; non-RAI: training group: 0.903 vs. 0.846, validation group: 0.892 vs. 0.808). The AUC values for the training cohort (RAI: 0.940, 0.933, and 0.942; non-RAI: 0.891, 0.884, and 0.852 for the 5-, 8-, and 10-year OS, respectively) and validation cohort (RAI: 0.855, 0.825, and 0.900, non-RAI: 0.867, 0.896, and 0.899), and the calibration plots of both two models all exhibited better performance. Additionally, the NRI and IDI further showed that they exhibited good 5-, 8-, and 10-year net benefits. We have established the prediction models of DTC patients with or without RAI respectively through various variables. The nomogram may be more targeted to guide clinical decisions in the future.

Clinical features and prognostic factors in patients diagnosed with lymphovascular invasion of testicular germ-cell tumors: Analysis based on the SEER database.

Lymphovascular invasion (LVI) is a high-risk factor for testicular germ-cell tumors (TGCT), but a prognostic model for TGCT-LVI patients is lacking. This study aimed to develop a nomogram for predicting the overall survival (OS) of TGCT-LVI patients. A complete cohort of 3288 eligible TGCG-LVI patients (training cohort, 2300 cases; validation cohort, 988 cases) were obtained from the Surveillance, Epidemiology, and End Results database. Variables screened by multivariate Cox regression analysis were used to construct a nomogram, which was subsequently evaluated using the consistency index (C-index), time-dependent receiver operating characteristic curve (ROC), and calibration plots. The advantages and disadvantages of the American Joint Committee on Cancer (AJCC) staging system and the nomogram were assessed by integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Decision-analysis curve (DCA) was used to measure the net clinical benefit of the nomogram versus the AJCC staging system. Finally, Kaplan-Meier curves were used to evaluate the ability to identify different risk groups between the traditional AJCC staging system and the new risk-stratification system built on the nomogram. Nine variables were screened by multivariate Cox regression analysis to construct the nomogram. The C-index (training cohort, 0.821; validation cohort, 0.819) and time-dependent ROC of 3-, 5-, and 9-year OS between the two cohorts suggested that the nomogram had good discriminatory ability. Calibration curves showed good consistency of the nomogram. The NRI values of 3-, 5-, and 9-year OS were 0.308, 0.274, and 0.295, respectively, and the corresponding values for the validation cohort were 0.093, 0.093, and 0.099, respectively (P<0.01). Additionally, the nomogram had more net clinical benefit as shown by the DCA curves, and the new risk-stratification system provided better differentiation than the AJCC staging system. A prognostic nomogram and new risk-stratification system were developed and validated to assist clinicians in assessing TGCT-LVI patients.

A semi-parametric approach for time-dependent ROC curves with nonignorable missing biomarker

ABSTRACT The main purpose of this paper is to survey the statistical inference for covariate-specific time-dependent receiver operating characteristic (ROC) curves with nonignorable missing continuous biomarker values. To construct time-dependent ROC curves, we consider a joint model which assumes that the failure time depends on the continuous biomarker and the covariates through a Cox proportional hazards model and that the continuous biomarker depends on the covariates through a semiparametric location model. Assuming a purely parametric model on the propensity score, we utilize instrumental variables to deal with the identifiable issue and estimate the unknown parameters of the propensity score by a simple and efficient method. In addition, when the propensity score is estimated, we develop HT and AIPW approaches to estimate our interested quantities. In the presence of nonignorable missing biomarker, our AIPW estimators of the interested quantities are still doubly robust when the true propensity score is a special parametric logistic model. At last, simulation studies are conducted to assess the performance of our proposed approaches, and a real data analysis is also carried out to illustrate its application.

Development of a prognostic scoring system for hepatic vena cava Budd-Chiari syndrome with hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a serious complication of hepatic vena cava Budd-Chiari syndrome (HVC-BCS) that significantly reduces the survival time of patients. Our study aimed to analyze the prognostic factors influencing the survival of HVC-BCS patients with HCC and to develop a prognostic scoring system. MethodsThe clinical and follow-up data of 64 HVC-BCS patients with HCC who received invasive treatment at the First Affiliated Hospital of Zhengzhou University between January 2015 and December 2019 were retrospectively analyzed. Kaplan-Meier curves and log-rank tests were used to analyze the survival curve of patients and the difference in prognoses between the groups. Univariate and multivariate Cox regression analyses were performed to analyze the influence of biochemical, tumor, and etiological characteristics on the total survival time of patients, and a new prognostic scoring system was developed according to the regression coefficients of the independent predictors in the statistical model. The prediction efficiency was evaluated using the time-dependent receiver operating characteristics curve and concordance index. ResultsMultivariate analysis showed that serum albumin level < 34 g/L [hazard ratio (HR) = 4.207, 95% confidence interval (CI): 1.816-8.932, P = 0.001], maximum tumor diameter > 7 cm (HR = 8.623, 95% CI: 3.771-19.715, P < 0.001), and inferior vena cava stenosis (HR = 3.612, 95% CI: 1.646-7.928, P = 0.001) were independent predictors of survival. A prognostic scoring system was developed according to the above-mentioned independent predictors, and patients were classified into grades A, B, C and D. Significant differences in survival were found among the four groups. ConclusionsThis study successfully developed a prognostic scoring system for HVC-BCS patients with HCC, which is helpful for clinical evaluation of patient prognosis.

Fc fragment of IgG binding protein is correlated with immune infiltration levels in hepatocellular carcinoma.

The Fc fragment of IgG binding protein (FCGBP) has been confirmed to play an important role in various cancers. However, the specific role of FCGBP in hepatocellular carcinoma (HCC) remains undefined. Thus, in this study, the enrichment analyses (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis) of FCGBP in HCC and extensive bioinformatic analyses using data of clinicopathologic characteristics, genetic expression and alterations, and immune cell infiltration were perfomed. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of FCGBP in both HCC tissues and cell lines. The subsequent results confirmed thatFCGBP overexpression positively correlated with poor prognosis in patients with HCC. Additionally, FCGBP expression could effectively distinguish tumor tissues from normal tissues, which was verified by qRT-PCR. The result was further confirmed by using HCC cell lines. The time-dependent survival receiver operator characteristic curve exhibited the strong ability of FCGBP to predict survival in patients with HCC. Additionally, we revealed the strong relationship between FCGBP expression and a number of classic regulatory targets and classical oncogenic signaling pathways of tumors. Finally, FCGBP was involved in the regulation of immune infiltration in HCC. Therefore, FCGBP has potential value in the diagnosis, treatment, and prognosis of HCC and may be a potential biomarker or therapeutic target.

Nomograms for predicting overall survival and cancer-specific survival in patients with head and neck non-Hodgkin lymphoma: A population-based study.

This study aimed to develop comprehensive nomograms for patients with head and neck non-Hodgkin lymphoma (H&NNHL) to determine their overall survival (OS) and cancer-specific survival (CSS). In this study, 602 H&NNHL patients were analyzed from the Surveillance, Epidemiology, and End Results database. The R software was used to randomly divide the patients into the training cohort (n = 421) and the validation cohort (n = 181) in a 7-to-3 ratio. To develop nomograms for projecting OS and CSS, multivariable Cox regression was used to acquire independent predictive factors. We have constructed nomograms to predict the 3-, 5-, and 8-year OS and CSS probabilities of H&NNHL patients. The consistency index of the nomograms for OS (CSS) was 0.74 (0.778) and 0.734 (0.775), in the training and validation cohort respectively, and was higher than that of the Ann Arbor staging system. Calibration plotting showed that our models have good calibration ability. Moreover, assessments of the area under the time-dependent receiver operating characteristics curve, net reclassification improvement, integrated discrimination improvement and decision curve analysis demonstrated that our nomograms performed better and were more clinically useful than the Ann Arbor staging system. This is the first research to establish comprehensive nomograms for predicting OS and CSS in patients with H&NNHL at 3-, 5-, and 8-year. The validation of the models demonstrated good performance. It can provide clinicians with reference information for determining customized clinical treatment options and providing personalized prognoses. Indexes such as the concordance index, the area under the time-dependent receiver operating characteristics curve, calibration curves, the net reclassification improvement, the integrated discrimination improvement, and decision-curve analysis were used to compare new survival models to the classical Ann Arbor staging system.

A novel pyroptosis scoring model was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma.

The phenotype of pyroptosis has been extensively studied in a variety of tumors, but the relationship between pyroptosis and esophageal squamous cell carcinoma (ESCC) remains unclear. Here, 22 pyroptosis genes were downloaded from the website of Gene Set Enrichment Analysis (GSEA), 79 esophageal squamous cell carcinoma samples and GSE53625 containing 179 pairs of esophageal squamous cell carcinoma samples were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. Then, pyroptosis subtypes of esophageal squamous cell carcinoma were obtained by cluster analysis according to the expression difference of pyroptosis genes, and a pyroptosis scoring model was constructed by the pyroptosis-related genes screened from different pyroptosis subtypes. Time-dependent receiver operator characteristic (timeROC) curves and the area under the curve (AUC) values were used to evaluate the prognostic predictive accuracy of the pyroptosis scoring model. Kaplan-Meier method with log-rank test were conducted to analyze the impact of the pyroptosis scoring model on overall survival (OS) of patients with esophageal squamous cell carcinoma. Nomogram models and calibration curves were used to further confirm the effect of the pyroptosis scoring model on prognosis. Meanwhile, CIBERSORTx and ESTIMATE algorithm were applied to calculate the influence of the pyroptosis scoring model on esophageal squamous cell carcinoma immune microenvironment. Our findings revealed that the pyroptosis scoring model established by the pyroptosis-related genes was associated with the prognosis and immune microenvironment of esophageal squamous cell carcinoma, which can be used as a biomarker to predict the prognosis and act as a potential target for the treatment of esophageal squamous cell carcinoma.

Assessment of the prognostic value of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in perihilar cholangiocarcinoma patients following curative resection: A multicenter study of 333 patients.

Tumor-associated chronic inflammation has been determined to play a crucial role in tumor progression, angiogenesis and immunosuppression. The objective of this study was to assess the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in perihilar cholangiocarcinoma (pCCA) patients following curative resection. Consecutive pCCA patients following curative resection at 3 Chinese hospitals between 2014 and 2018 were included. The NLR was defined as the ratio of neutrophil count to lymphocyte count. PLR was defined as the ratio of platelet count to lymphocyte count. The optimal cutoff values of preoperative NLR and PLR were determined according to receiver operating characteristic (ROC) curves for the prediction of 1-year overall survival (OS), and all patients were divided into high- and low-risk groups. Kaplan-Meier curves and Cox regression models were used to investigate the relationship between values of NLR and PLR and values of OS and recurrence-free survival (RFS) in pCCA patients. The usefulness of NLR and PLR in predicting OS and RFS was evaluated by time-dependent ROC curves. A total of 333 patients were included. According to the ROC curve for the prediction of 1-year OS, the optimal cutoff values of preoperative NLR and PLR were 1.68 and 113.1, respectively, and all patients were divided into high- and low-risk groups. The 5-year survival rates in the low-NLR (<1.68) and low-PLR groups (<113.1) were 30.1% and 29.4%, respectively, which were significantly higher than the rates of 14.9% and 3.3% in the high-NLR group (≥1.68) and high-PLR group (≥113.1), respectively. In multivariate analysis, high NLR and high PLR were independently associated with poor OS and RFS for pCCA patients. The time-dependent ROC curve revealed that both NLR and PLR were ideally useful in predicting OS and RFS for pCCA patients. This study found that both NLR and PLR could be used to effectively predict long-term survival in patients with pCCA who underwent curative resection.

PS-BPP02-7: DEFINING THE OPTIMAL CUT-OFF POINTS OF BLOOD PRESSURE COMPONENTS TO PREDICT THE PROGRESSION OF CHRONIC KIDNEY DISEASE IN TOYOOKA CITY

Objective: Early control of blood pressure is critical to delaying the progression of chronic kidney disease (CKD) and preventing future cardiovascular events and mortality. The primary objective of the study is to assess the optimal cut-off points of blood pressure components for predicting the worsening of proteinuria or renal function. Design and method: Retrospective longitudinal data from 2013–2017 specific health surveys among participants of National Health Insurance in Toyooka City were analyzed (n = 5,169 at baseline). Association of blood pressure at baseline and worsening of dip-stick proteinuria or estimated glomerular filtration rate (eGFR) during follow-up were determined with Cox proportional hazard analysis. The optimal cut-off points were determined with time-dependent receiver operating characteristic curves (ROC). Results: Survival analysis revealed that worsening of proteinuria during follow-up was significantly associated with baseline systolic and diastolic blood pressure levels independently of age, gender, or HbA1c levels. Time-dependent ROC curves for detecting worsening of proteinuria during follow-up revealed that the optimal cut-off points of systolic and diastolic blood pressure were 126 mmHg (sensitivity 0.62, specificity 0.45) and 81 mmHg (sensitivity 0.38, specificity 0.70), respectively. When the whole population was categorized with the systolic blood pressure levels of &lt; 126, 126–139, or &gt; = 140 mmHg, the age, gender, and HbA1c-adjusted risks for worsening proteinuria in the highest and intermediate systolic blood pressure groups were 1.5-fold (p = 0.002) and 1.3-fold (p = 0.014) higher than that in the lowest group, respectively. In addition, the risks for more than a 15%-decrease in eGFR during follow-up in the highest and intermediate groups were 2.0-fold (p &lt; 0.001) and 1.6-fold (p = 0.009) higher than that in the lowest group, respectively. When the whole population was categorized with the diastolic blood pressure levels of &lt; 81, 81–89, or &gt; = 90 mmHg, the risks for worsening proteinuria in the highest and intermediate diastolic blood pressure groups were 1.5-fold (p = 0.004) and 1.2-fold (p = 0.056) higher than that in the lowest group, respectively. Furthermore, the time-dependent ROC curve for detecting more than a 15%-decrease in eGFR during follow-up revealed that the optimal cut-off point of pulse pressure was 52 mmHg (sensitivity 0.48, specificity 0.58). In subjects with a baseline pulse pressure of &gt; = 52 mmHg, the adjusted odds ratio for detecting more than a 15%-decrease in eGFR during follow-up was 1.5-fold higher than in those with a baseline pulse pressure of &lt; 52 mmHg (p = 0.005). Conclusions: Data from specific health surveys revealed regional blood pressure-related risks associated with worsening of CKD among participants of National Health Insurance.

Competitive Risk Model Nomogram to Predict Prognosis in Patients Aged Over 65 Years with nonmetastatic Cervical Cancer: A SEER Population-Based Study.

Objective: The prognostic factors for elderly patients with cervical cancer differ from those of younger patients. Competitive risk events could cause biases in the Cox proportional hazards (PH) model. This study aimed to construct a competitive risk model (CRM) nomogram for patients aged > 65 years with nonmetastatic cervical cancer. Methods: We retrospectively analyzed data extracted from the Surveillance, Epidemiology, and End Results (SEER) database and a total of 1856 patients from 18 cancer registries across the United States diagnosed between 2010 and 2015 were included. Kaplan-Meier analysis and log-rank tests were used to compare intergroup survival. Univariate and multivariate Cox proportional regression analyses were performed to identify independent prognostic factors. The cumulative incidence function (CIF) and Fine and Gray's test were used to determine the impact of competitive risk events on prognosis. The CRM nomogram was internally and externally validated using time-dependent receiver operator characteristic (ROC) curve (time-AUC), Brier scores, Harrell's concordance index (C-index), calibration curve, and decision curve analysis (DCA). Results: Analyses revealed that histology, age, the International Federation of Gynaecologists and Obstetricians (FIGO) stage, number of in situ malignancies, chemotherapy, radiotherapy (RT), and surgery were independent prognostic factors. The CRM nomogram accurately predicted 1-year, 3-year, and 5-year disease-specific survival (DSS). The C-indexes and Brier scores of the CRM nomogram were 0.641 and 0.094, respectively, at the 1-year cut-off in the training set. The time-AUC of the CRM nomogram at the 1-year, 3-year, and 5-year intervals in the training set were 77.6%, 77.3%, and 74.5%, respectively. The calibration curve demonstrated a favorable concordance. DCA suggested that the nomogram had a good net benefit. Therefore, the Cox model underestimated the weight of risk factors compared to CRM. Conclusions: This study presents the CRM nomogram to predict DSS in patients aged > 65 years with nonmetastatic cervical cancer. It can help clinicians implement more accurate personalized diagnostic and treatment modalities for elderly patients with cervical cancer.

Combination of Two T1 Substaging Systems (T1a/b/c and T1m/e) Better Predicts Tumor Outcomes in Patients with T1 High Grade Bladder Cancer.

T1 substaging is a predictive factor for non-muscle-invasive bladder cancer, and two types of T1 substaging systems (T1a/b/c and T1m/e) are currently in use. However, the predictive ability of both systems is poor, and there is debate over which system is better. To confirm whether combination of two T1 substaging systems can improve the predictive ability of T1 substaging for tumor outcomes. Patients with primary pT1 high-grade bladder cancer from three centers were included. All tumors were assessed with T1a/b/c and T1m/e substaging. A new variable named COMB was developed in which patients were stratified into T1a/b&T1m, T1a/b&T1e, T1c&T1m or T1c&T1e subgroups. A time-dependent receiver operating characteristic curve (ROC) analysis was used to test whether the accuracy of prediction could be improved with COMB. A total of 239 patients with primary pT1HG were analyzed. No tumor was T1c&T1m, and therefore, only three types of combinations were evaluated: T1a/b&T1m (62 patients), T1a/b&T1e (124 patients) and T1c&T1e (53 patients). Regardless of all patients or those treated with Re-TURBt and adequate BCG, patients with T1a/b&T1m have the best prognosis, and those with T1c&T1e have the poorest prognosis. The time-dependent ROC showed that, for both recurrence and progression, COMB had a higher AUC than T1a/b/c and T1m/e, regardless of population. Compared with either system alone, the combination of two T1 substaging systems improves the predictive ability of T1 substaging for tumor outcomes.

A novel risk classifier for predicting the overall survival of patients with thymic epithelial tumors based on the eighth edition of the TNM staging system: A population-based study.

Thymic epithelial tumors (TETs) are rare tumors that originated from thymic epithelial cells, with limited studies investigating their prognostic factors. This study aimed to investigate the prognostic factors of TETs and develop a new risk classifier to predict their overall survival (OS). This retrospective study consisted of 1224 TETs patients registered in the Surveillance, Epidemiology, and End Results (SEER) database, and 75 patients from the First Affiliated Hospital of Xi'an Jiaotong University. The univariate and multivariate Cox regression analyses were adopted to select the best prognostic variables. A nomogram was developed to predict the OS of these patients. The discriminative and calibrated abilities of the nomogram were assessed using the receiver operating characteristics curve (ROC) and calibration curve. Decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI) were adopted to assess its net clinical benefit and reclassification ability. The multivariate analysis revealed that age, sex, histologic type, TNM staging, tumor grade, surgery, radiation, and tumor size were independent prognostic factors of TETs, and a nomogram was developed to predict the OS of these patients based on these variables. The time-dependent ROC curves displayed that the nomogram yielded excellent performance in predicting the 12-, 36- and 60-month OS of these patients. Calibration curves presented satisfying consistencies between the actual and predicted OS. DCA illustrated that the nomogram will bring significant net clinical benefits to these patients compared to the classic TNM staging system. The estimated NRI and IDI showed that the nomogram could significantly increase the predictive ability of 12-, 36- and 60-month OS compared to the classic TNM staging system. Consistent findings were discovered in the internal and external validationcohorts. The constructed nomogram is a reliable risk classifier to achieve personalized survival probability prediction of TETs, and could bring significant net clinical benefits to these patients.

The Senescence-Related Signature Predicts Prognosis and Characterization of Tumor Microenvironment Infiltration in Pancreatic Cancer.

Senescence is thought to be an imperative effect on the development of cancer. However, few studies pay an attention to the senescence-associated genes in pancreatic cancer (PC). The prognostic value of senescence-related genes (SRGs) and their involvement in tumor microenvironment (TME) in the PC remain obscure. The aim of this research was to investigate the prognostic role of senescence-associated genes and their affection in TME in PC. The transcriptome and clinical information of PC patients were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Two SRG-mediated molecular clusters were comprehensively identified. In total, data from the 285 PC patients were randomly used to develop a senescence-associated gene signature in the training set and verified in the validation set. Immune microenvironment analysis pertained to senescence-related genes was performed. A SRG_score including five senescence-associated genes was established to separate PC patients into two risk groups. High-risk patients had worse overall survival than low-risk patients. The result of the multivariate Cox regression analysis identified the risk score and stage as independent prognostic factors for PC patients. Receiver operating characteristic curve (ROC) analysis confirmed the credible predictive ability of the nomogram. The area under time-dependent ROC curve (AUC) reached 0.746 at 1 year, 0.781 at 3 years, and 0.868 at 5 years in the training set and 0.653 at 1 year, 0.755 at 3 years, and 0.785 at 5 years in the validation set. Moreover, the SRG_score was associated with TME, tumor mutation burden (TMB), and chemotherapeutic drug sensitivity. This study found that the novel SRG_score could be an independent prognostic target for PC patients. Senescence-associated genes had a vital impact on the immune microenvironment and the treatment of PC patients.