Prognostic value of site-specific metastases in pancreatic adenocarcinoma: A Surveillance Epidemiology and End Results database analysis

To evaluate the prognostic value of site-specific metastases among patients with metastatic pancreatic carcinoma registered within the Surveillance, Epidemiology and End Results (SEER) database.METHODSSEER database (2010-2013) has been queried through SEER*Stat program to determine the presentation, treatment outcomes and prognostic outcomes of metastatic pancreatic adenocarcinoma according to the site of metastasis. In this study, metastatic pancreatic adenocarcinoma patients were classified according to the site of metastases (liver, lung, bone, brain and distant lymph nodes). We utilized chi-square test to compare the clinicopathological characteristics among different sites of metastases. We used Kaplan-Meier analysis and log-rank testing for survival comparisons. We employed Cox proportional model to perform multivariate analyses of the patient population; and accordingly hazard ratios with corresponding 95%CI were generated. Statistical significance was considered if a two-tailed P value < 0.05 was achieved.RESULTSA total of 13233 patients with stage IV pancreatic cancer and known sites of distant metastases were identified in the period from 2010-2013 and they were included into the current analysis. Patients with isolated distant nodal involvement or lung metastases have better overall and pancreatic cancer-specific survival compared to patients with isolated liver metastases (for overall survival: lung vs liver metastases: P < 0.0001; distant nodal vs liver metastases: P < 0.0001) (for pancreatic cancer-specific survival: lung vs liver metastases: P < 0.0001; distant nodal vs liver metastases: P < 0.0001). Multivariate analysis revealed that age < 65 years, white race, being married, female gender; surgery to the primary tumor and surgery to the metastatic disease were associated with better overall survival and pancreatic cancer-specific survival.CONCLUSIONPancreatic adenocarcinoma patients with isolated liver metastases have worse outcomes compared to patients with isolated lung or distant nodal metastases. Further research is needed to identify the highly selected subset of patients who may benefit from local treatment of the primary tumor and/or metastatic disease.

Prognostic impact of tumor deposits on overall survival in colorectal cancer:Based on Surveillance, Epidemiology, and End Results database

BACKGROUND In colorectal cancer, tumor deposits(TDs) are considered to be a prognostic factor in the current staging system, and are only considered in the absence of lymph node metastases(LNMs). However, this definition and the subsequent prognostic value based on it is controversial, with various hypotheses. TDs may play an independent role when it comes to survival and addition of TDs to LNM count may predict the prognosis of patients more accurately.AIM To assess the prognostic impact of TDs and evaluate the effect of their addition to the LNM count.METHODS The patients are derived from the Surveillance, Epidemiology, and End Results database. A prognostic analysis regarding impact of TDs on overall survival(OS) was performed using Cox regression model, and other covariates associating with OS were adjusted. The effect of addition of TDs to LNM count on N restaging was also evaluated. The subgroup analysis was performed to explore the different profile of risk factors between patients with and without TDs.RESULTS Overall, 103755 patients were enrolled with 14131(13.6%) TD-positive and 89624(86.4%) TD-negative tumors. TD-positive patients had worse prognosis compared with TD-negative patients, with 3-year OS rates of 47.3%(95%CI, 46.5%-48.1%) and 77.5%(95%CI, 77.2%-77.8%, P < 0.0001), respectively. On multivariable analysis, TDs were associated poorer OS(hazard ratio, 1.35;95%CI, 1.31-1.38;P < 0.0001). Among TD-positive patients, the number of TDs had a linear negative effect on disease-free survival and OS. After reclassifying patients by adding TDs to the LNM count, 885 of 19 965(4.4%) N1 patients were restaged as p N2, with worse outcomes than patients restaged as p N1(3-year OS rate: 78.5%, 95%CI, 77.9%-79.1% vs 63.2%, 95%CI, 60.1%-66.5%, respectively;P < 0.0001).CONCLUSION TDs are an independent prognostic factor for OS in colorectal cancer. The addition of TDs to LNM count improved the prognostic accuracy of tumor, node and metastasis staging.

Risk stratification in gastric cancer lung metastasis: Utilizing an overall survival nomogram and comparing it with previous staging

BACKGROUND Gastric cancer(GC)is prevalent and aggressive,especially when patients have distant lung metastases,which often places patients into advanced stages.By identifying prognostic variables for lung metastasis in GC patients,it may be po-ssible to construct a good prediction model for both overall survival(OS)and the cumulative incidence prediction(CIP)plot of the tumour.AIM To investigate the predictors of GC with lung metastasis(GCLM)to produce nomograms for OS and generate CIP by using cancer-specific survival(CSS)data.METHODS Data from January 2000 to December 2020 involving 1652 patients with GCLM were obtained from the Surveillance,epidemiology,and end results program database.The major observational endpoint was OS;hence,patients were se-parated into training and validation groups.Correlation analysis determined va-rious connections.Univariate and multivariate Cox analyses validated the independent predictive factors.Nomogram distinction and calibration were performed with the time-dependent area under the curve(AUC)and calibration curves.To evaluate the accuracy and clinical usefulness of the nomograms,decision curve analysis(DCA)was performed.The clinical utility of the novel prognostic model was compared to that of the 7th edition of the American Joint Committee on Cancer(AJCC)staging system by utilizing Net Reclassification Improvement(NRI)and Integrated Discrimination Improvement(IDI).Finally,the OS prognostic model and Cox-AJCC risk stratification model modified for the AJCC system were compared.RESULTS For the purpose of creating the OS nomogram,a CIP plot based on CSS was generated.Cox multivariate regression analysis identified eleven significant prognostic factors(P<0.05)related to liver metastasis,bone metastasis,primary site,surgery,regional surgery,treatment sequence,chemotherapy,radiotherapy,positive lymph node count,N staging,and time from diagnosis to treatment.It was clear from the DCA(net benefit>0),time-de-pendent ROC curve(training/validation set AUC>0.7),and calibration curve(reliability slope closer to 45 degrees)results that the OS nomogram demonstrated a high level of predictive efficiency.The OS prediction model(New Model AUC=0.83)also performed much better than the old Cox-AJCC model(AUC difference between the new model and the old model greater than 0)in terms of risk stratification(P<0.0001)and verification using the IDI and NRI.CONCLUSION The OS nomogram for GCLM successfully predicts 1-and 3-year OS.Moreover,this approach can help to ap-propriately classify patients into high-risk and low-risk groups,thereby guiding treatment.

Epidemiology and outcome of individuals with intraductal papillary neoplasms of the bile duct

BACKGROUND Intraductal papillary neoplasm of the bile duct(IPNB)is a rare distinct subtype of precursor lesions of biliary carcinoma.IPNB is considered to originate from luminal biliary epithelial cells,typically displays mucin-hypersecretion or a papillary growth pattern,and results in cystic dilatation[1].IPNB develops anywhere in the intrahepatic and extrahepatic biliary tracts,and can occur in various pathological stages from low-grade dysplasia to invasive carcinoma.IPNBs have similar phenotypic changes in the occurrence and development of all subtypes,and the prognosis is significantly better than that of traditional(nonpapillary)cholangiocarcinoma.AIM To evaluate the clinicopathological features of IPNB to provide evidence-based guidance for treatment.METHODS Invasive IPNB,invasive intraductal papillary mucinous neoplasm of the pancreas(IPMN),and traditional cholangiocarcinoma data for affected individuals from 1975 to 2016 were obtained from the Surveillance,Epidemiology,and End Results(SEER)database.Annual percentage changes(APCs)in the incidence and incidence-based(IB)mortality were calculated.We identified the independent predictors of overall survival(OS)and cancer-specific survival(CSS)in indivi duals with invasive IPNB.RESULTS The incidence and IB mortality of invasive IPNB showed sustained decreases,with an APC of-4.5%(95%CI:-5.1%to-3.8%)and-3.3%(95%CI:-4.1%to-2.6%)(P<0.001),respectively.Similar decreases in incidence and IB mortality were seen for invasive IPMN but not for traditional cholangiocarcinoma.Both OS and CSS for invasive IPNB were better than for invasive IPMN and traditional cholangiocarcinoma.A total of 1635 individuals with invasive IPNB were included in our prognosis analysis.The most common tumor sites were the pancreaticobiliary ampulla(47.9%)and perihilar tract(36.7%),but the mucin-related subtype of invasive IPNB was the main type,intrahepatically(approximately 90%).In the univariate and multivariate Cox regression analysis,age,tumor site,grade and stage,subtype,surgery,and chemotherapy were associated with OS and CSS(P<0.05).CONCLUSION Incidence and IB mortality of invasive IPNB trended steadily downward.The heterogeneity of IPNB comprises site and the tumor’s mucin-producing status.

Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma

Objective To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram.Methods Data from elderly individuals(age≥65 years)histologically diagnosed with brain glioma were sourced from the Surveillance,Epidemiology,and End Results(SEER)database.The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio.Additionally,data obtained from Tangdu Hospital constituted an external validation cohort for the study.The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator(LASSO)and multivariate Cox regression analysis,enabling the construction of a nomogram.Model performance was evaluated using C-index,ROC curves,calibration plot and decision curve analysis(DCA).Results A cohort of 20483 elderly glioma patients was selected from the SEER database.Five prognostic factors(age,marital status,histological type,stage,and treatment)were found to significantly impact overall survival(OS)and cancer-specific survival(CSS),with tumor location emerging as a sixth variable independently linked to CSS.Subsequently,nomogram models were developed to predict the probabilities of survival at 6,12,and 24 months.The assessment findings from the validation queue indicate a that the model exhibited strong performance.Conclusion Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients.They can potentially assist in risk stratification and clinical decision-making.

基于SEER数据库的乳腺髓样癌预后分析及预测模型构建

目的 分析典型乳腺髓样癌(TMBC)与不典型乳腺髓样癌(AMCB)的临床病理特征和预后差异,构建乳腺髓样癌(MBC)预后预测模型。方法 收集美国国家癌症研究所监测、流行病学及结局项目(SEER)数据库中2004年1月至2017年12月经病理学诊断为TMBC(2 017例)和AMCB(157例)的患者。比较两组患者临床病理特征,采用Kaplan-Meier法比较两组的总生存期(OS)和乳腺癌特异生存期(BCSS),并进行亚组分析。采用Cox回归分析影响MBC患者OS的危险因素;构建基于危险因素的OS预测模型,绘制ROC曲线、校正曲线和决策曲线评估模型的预测效能。结果 两组患者临床病理特征比较,差异均无统计学意义(均P>0.05),Kaplan-Meier生存曲线表明两组患者OS和BCSS比较,差异均无统计学意义(均P>0.05)。亚组分析显示,肿瘤直径>5 cm的亚组中AMCB患者OS较差。Cox单因素分析表明年龄、婚姻状况、原发侧、美国癌症联合委员会(AJCC)分期、淋巴结状态、孕激素受体、放化疗、肿瘤大小是MBC预后的危险因素,Cox多因素分析表明年龄、婚姻状况、AJCC分期、淋巴结状态、化疗、肿瘤大小是独立危险因素。基于独立危险因素构建预测MBC 1、3、5年OS的预后模型。ROC曲线、校正曲线和决策曲线均显示该模型有良好的预测效能。结论 TMBC与AMCB的临床病理特征和预后相似,构建MBC预后预测模型可有效预测MBC患者预后。

以SEER为基础的列线图构建和胰腺癌病人生存预测

目的:基于监测、流行病学和最终结果(surveillance,epidemiology,and end results,SEER)数据库,分析影响胰腺癌预后的独立因素并构建预测模型。方法:本研究从SEER数据库获取2010-2015年美国7801例胰腺癌病人的临床资料,以7∶3的比例随机分为建模组、验证组。对建模组临床变量进行多因素COX回归分析获得影响生存的独立因素,构建列线图。通过受试者操作特性(receiver operating characteristic,ROC)曲线和校准曲线验证模型的准确性。结果:年龄、原发部位、病理分级、T分期、N分期、M分期、手术方式、放疗、化疗与胰腺癌的预后相关,总生存的3年、5年ROC曲线下面积(area under cure,AUC)分别为0.90、0.91,癌症特异性生存分别为0.91、0.91。校准曲线显示观察值与预测值之间具有良好的一致性。经筛选得到的临床变量确实对胰腺癌预后有影响。结论:所构建的模型具有较好的预测准确性,有助于胰腺癌病人的临床决策和个性化治疗。

基于SEER数据库构建直肠癌术后患者的生存预测列线图及其验证

目的 分析直肠癌术后患者总生存期(OS)的影响因素并构建其风险预测列线图模型。方法 从SEER数据库中筛选2010—2015年经病理诊断为直肠癌并行手术治疗的患者14201例,按照7∶3的比例随机分为训练集9941例和验证集4260例;另收集兰州大学第二医院2017年1月1日—2021年12月31日与SEER数据库提取标准一致的直肠癌术后患者376例作为外部验证集。通过单因素及多因素COX回归分析并确定影响直肠癌术后患者OS的独立危险因素,据此构建列线图预测模型。通过C指数、受试者操作特征曲线下面积(AUC)评价该模型的区分能力,校准曲线评价该模型的预测值与实际值之间的接近程度。结果 多因素COX回归分析显示,直肠癌术后患者预后相关独立危险因素有13个,包括一般人口学(性别、年龄、婚姻状态)、肿瘤特征学[肿瘤原发部位、肿瘤分期、T分期、N分期、神经侵犯、癌胚抗原(CEA)水平、远处转移(肝转移、肺转移、骨转移)]及化疗(P<0.05)。基于这些独立危险因素构建了直肠癌术后患者生存预测的列线图模型,通过训练集及验证集C指数、AUC及校准曲线显示该预测模型的预测值与实际值具有较好的一致性。结论 基于SEER数据库构建的直肠癌术后患者生存预测的列线图效果良好,且将直肠癌肿瘤原发部位划分后发现发生在直肠的肿瘤较直肠乙状结肠交界处的肿瘤预后更差。

基于SEER数据库构建肝细胞癌患者预后预测新模式

目的研究肝细胞癌患者总生存期的影响因素,构建新的预测模式,为患者的个体化和精准化治疗方案提供理论支持和参考。方法在SEER数据库中获取2011—2015年被诊断为肝细胞癌的患者数据,运用单因素和多因素Cox回归分析筛选预后因素并构建预测模型。采集兰州大学第二医院280例肝细胞癌患者样本数据,作为外部验证队列。应用一致性指数、受试者操作特征曲线、校准曲线、决策曲线评估模型效能并与传统TNM分期进行对比,计算分数对患者进行危险分层并绘制小提琴图。结果回归分析提示年龄、性别、N分期、M分期、甲胎蛋白表达情况、手术情况、放射治疗、化学治疗是影响肝细胞癌患者总生存期的独立预后因素。训练组的一致性指数为0.739(95%CI:[0.730,0.748]),1、3、5年患者总生存期受试者操作特征曲线下面积分别为0.806、0.811、0.812;内部验证组的一致性指数为0.732(95%CI:[0.718,0.746]),1、3、5年患者总生存期受试者操作特征曲线下面积分别为0.787、0.803、0.810;外部验证组的一致性指数为0.719(95%CI:[0.684,0.753]),1、3、5年患者总生存期受试者操作特征曲线下面积分别为0.794、0.841、0.899;传统TNM模型的一致性指数为0.704(95%CI:[0.691,0.714]),1、3、5年患者总生存期受试者操作特征曲线下面积分别为0.716、0.687、0.677。决策曲线显示列线图较传统TNM分期预测效能更好。结论本研究构建的列线图能够用于预测肝细胞癌患者的总生存期,且效果优于传统TNM分期,基于新的预测模型的危险分层系统在区分患者生存期时更精确,对肝细胞癌患者的个体化治疗具有临床参考价值。

Overall survival associated with surgery,radiotherapy,and chemotherapy in metastatic vulvar cancer:A retrospective cohort study based on the SEER database

Background:Large cancer registries help analyze the prognosis of rare malignancies,such as advanced vulvar cancer.This study aimed to compare the overall survival(OS)rates of patients with metastatic vulvar cancer who had undergone chemoradiotherapy and radiotherapy alone and identify prognostic factors using data from the Surveillance,Epidemiology,and End Results(SEER)registry.Methods:In this retrospective cohort study,we used the SEER database to identify patients with metastatic vulvar cancer diagnosed between 2000 and 2019.Propensity score matching was performed to balance the covariates.Kaplan–Meier curves and Cox models were used to analyze OS.Results:A total of 685 patients were included and divided into chemoradiotherapy and radiotherapy groups,and 400 patients were included after propensity score matching.The chemoradiotherapy group had higher OS in the matched cohort(hazard ratio[HR]=0.7367;95%confidence interval[CI]:0.5906–0.9190;P=0.0049)than the radiotherapy group,which was similar to that in the pre-matched cohort(P<0.0001).Patients who had undergone surgery+radiotherapy with or without chemotherapy showed higher OS rates than those who had received radiotherapy with or without chemotherapy for patients aged<75 years and local tumor excision/destruction or surgical removal of the primary site was the recommended surgical choice(P<0.05).Chemoradiotherapy is sufficient for patients 75 years of age.Conclusions:Patients with metastatic vulvar cancer should undergo surgery if they can tolerate it.Adjuvant chemoradiotherapy should be encouraged because this treatment modality was associated with higher OS than radiotherapy alone.

Data mining in clinical big data:the frequently used databases,steps,and methodological models

Many high quality studies have emerged from public databases,such as Surveillance,Epidemiology,and End Results(SEER),National Health and Nutrition Examination Survey(NHANES),The Cancer Genome Atlas(TCGA),and Medical Information Mart for Intensive Care(MIMIC);however,these data are often characterized by a high degree of dimensional heterogeneity,timeliness,scarcity,irregularity,and other characteristics,resulting in the value of these data not being fully utilized.Data-mining technology has been a frontier field in medical research,as it demonstrates excellent performance in evaluating patient risks and assisting clinical decision-making in building disease-prediction models.Therefore,data mining has unique advantages in clinical big-data research,especially in large-scale medical public databases.This article introduced the main medical public database and described the steps,tasks,and models of data mining in simple language.Additionally,we described data-mining methods along with their practical applications.The goal of this work was to aid clinical researchers in gaining a clear and intuitive understanding of the application of data-mining technology on clinical big-data in order to promote the production of research results that are beneficial to doctors and patients.

Survival benefits and disparities in radiation therapy for elderly patients with pancreatic ductal adenocarcinoma

BACKGROUND Older patients represent a unique subgroup of the cancer patient population,for which the role of cancer therapy requires special consideration.However,the outcomes of radiation therapy(RT)in elderly patients with pancreatic ductal adenocarcinoma(PDAC)are not well-defined in the literature.AIM To explore the use and effectiveness of RT in the treatment of elderly patients with PDAC in clinical practice.METHODS Data from patients with PDAC aged≥65 years between 2004 and 2018 were collected from the Surveillance,Epidemiology,and End Results database.Multivariate logistic regression analysis was performed to determine factors associated with RT administration.Overall survival(OS)and cancer-specific survival(CSS)were evaluated using the Kaplan–Meier method with the log-rank test.Univariate and multivariate analyses with the Cox proportional hazards model were used to identify prognostic factors for OS.Propensity score matching(PSM)was applied to balance the baseline characteristics between the RT and non-RT groups.Subgroup analyses were performed based on clinical characteristics.RESULTS A total of 12245 patients met the inclusion criteria,of whom 2551(20.8%)were treated with RT and 9694(79.2%)were not.The odds of receiving RT increased with younger age,diagnosis in an earlier period,primary site in the head,localized disease,greater tumor size,and receiving chemotherapy(all P<0.05).Before PSM,the RT group had better outcomes than did the non-RT group[median OS,14.0 vs 6.0 mo;hazard ratio(HR)for OS:0.862,95%confidence interval(CI):0.819–0.908,P<0.001;and HR for CSS:0.867,95%CI:0.823–0.914,P<0.001].After PSM,the survival benefit associated with RT remained comparable(median OS:14.0 vs 11.0 mo;HR for OS:0.818,95%CI:0.768–0.872,P<0.001;and HR for CSS:0.816,95%CI:0.765–0.871,P<0.001).Subgroup analysis revealed that the survival benefits(OS and CSS)of RT were more significant in patients aged 65 to 80 years,in regional and distant stages,with no surgery,and receiving chemotherapy.CONCLUSION RT improved the outcome of elderly patients with PDAC,particularly those aged 65 to 80 years,in regional and distant stages,with no surgery,and who received chemotherapy.Further prospective studies are warranted to validate our results.

Risk factors,prognostic predictors,and nomograms for pancreatic cancer patients with initially diagnosed synchronous liver metastasis

BACKGROUND Liver metastasis(LM)remains a major cause of cancer-related death in patients with pancreatic cancer(PC)and is associated with a poor prognosis.Therefore,identifying the risk and prognostic factors in PC patients with LM(PCLM)is essential as it may aid in providing timely medical interventions to improve the prognosis of these patients.However,there are limited data on risk and prognostic factors in PCLM patients.AIM To investigate the risk and prognostic factors of PCLM and develop corresponding diagnostic and prognostic nomograms.METHODS Patients with primary PC diagnosed between 2010 and 2015 were reviewed from the Surveillance,Epidemiology,and Results Database.Risk factors were identified using multivariate logistic regression analysis to develop the diagnostic mode.The least absolute shrinkage and selection operator Cox regression model was used to determine the prognostic factors needed to develop the prognostic model.The performance of the two nomogram models was evaluated using receiver operating characteristic(ROC)curves,calibration plots,decision curve analysis(DCA),and risk subgroup classification.The Kaplan-Meier method with a logrank test was used for survival analysis.RESULTS We enrolled 33459 patients with PC in this study.Of them,11458(34.2%)patients had LM at initial diagnosis.Age at diagnosis,primary site,lymph node metastasis,pathological type,tumor size,and pathological grade were identified as independent risk factors for LM in patients with PC.Age>70 years,adenocarcinoma,poor or anaplastic differentiation,lung metastases,no surgery,and no chemotherapy were the independently associated risk factors for poor prognosis in patients with PCLM.The C-index of diagnostic and prognostic nomograms were 0.731 and 0.753,respectively.The two nomograms could accurately predict the occurrence and prognosis of patients with PCLM based on the observed analysis results of ROC curves,calibration plots,and DCA curves.The prognostic nomogram could stratify patients into prognostic groups and perform well in internal validation.CONCLUSION Our study identified the risk and prognostic factors in patients with PCLM and developed corresponding diagnostic and prognostic nomograms to help clinicians in subsequent clinical evaluation and intervention.External validation is required to confirm these results.

Comparison of clinicopathological characteristics and survival outcomes between gallbladder mucinous adenocarcinoma and gallbladder adenocarcinoma:A propensity score-matched study

BACKGROUND Gallbladder mucinous adenocarcinoma(GBMAC)is a rare subtype of gallbladder adenocarcinoma(GBAC),with limited knowledge of its survival outcomes from small case series and single-center retrospective analysis.AIM To compare the clinicopathological characteristics of GBMAC with typical GBAC and its prognostic factors to gain insights into this field.METHODS This study was conducted using data from the Surveillance,Epidemiology,and End Results database,including cases of GBMAC and typical GBAC diagnosed from 2010 to 2017.The Pearson chi-square test or Fisher exact test was used to examine the differences in clinicopathological features between these two cohorts.In addition,propensity score matching(PSM)analysis was performed to balance the selection biases.Univariate and multivariate Cox hazards regression analyses were performed to determine independent prognostic factors for cancer-speci
c survival(CSS)and overall survival(OS).The Kaplan–Meier curves and log-rank tests were used to assess the OS and CSS of GBMAC and typical GBAC patients.RESULTS The clinicopathological and demographic characteristics of GBMAC were different from typical GBAC.They included a larger proportion of patients with unmarried status,advanced American Joint Committee on Cancer(AJCC)stage,higher T stage,higher N1 stage rate and lower N0 and N2 stage rates(P<0.05).Multivariate analyses demonstrated that surgery[OS:Hazard ratio(HR)=2.27,P=0.0037;CSS:HR=2.05,P=0.0151],chemotherapy(OS:HR=6.41,P<0.001;CSS:HR=5.24,P<0.001)and advanced AJCC stage(OS:Stage IV:HR=28.99,P=0.0046;CSS:Stage III:HR=12.31,P=0.015;stage IV:HR=32.69,P=0.0015)were independent prognostic indicators for OS and CSS of GBMAC patients.Furthermore,after PSM analysis,there was no significant difference between GBMAC and matched typical GBAC patients regarding OS(P=0.82)and CSS(P=0.69).CONCLUSION The biological behaviors of GBMAC are aggressive and significantly different from that of typical GBAC.However,they show similar survival prognoses.Surgery,chemotherapy,and lower AJCC stage were associated with better survival outcomes.Further research is needed in the future to verify these results.

乳头状肾细胞癌预后预测模型的构建与验证:一项基于SEER数据库的回顾性研究

目的:建立一个用于评估乳头状肾细胞癌(papillary renal cell carcinoma,PRCC)预后的列线图。方法:获取SEER(Surveillance,Epidemiology,and End Results)数据库的6 028例PRCC患者的临床数据,并将其随机分为训练队列(n=4 220)和验证队列(n=1 808)。使用Cox比例风险回归分析来筛选与PRCC预后相关的临床病理特征。基于Cox模型,构建一个列线图预测PRCC患者的预后,用受试者操作特征曲线及C指数检测模型的区分度,用校准图来评估列线图的预测准确性。结果:从SEER数据库中检索到6 028例PRCC患者的数据。Cox比例风险回归分析结果显示,诊断时的年龄、级别、肿瘤淋巴结转移分期(TNM,AJCC,第7版)、手术治疗、肿瘤数量和婚姻状况是重要的独立预后变量。将所有变量合并以建立列线图。在训练和验证队列中,列线图模型的C指数分别为0.807(95%CI=0.779~0.834)和0.800(95%CI=0.759~0.841),而AJCC TNM分期的C指数分别为0.686(95%CI=0.667~0.706)和0.668(95%CI=0.638~0.697),表明与AJCC TNM分期系统相比,列线图在训练和验证队列中都表现出了良好的总生存率(overall survival,OS)预测能力。校准曲线显示列线图的生存率预测与实际生存率之间高度一致。结论:本研究构建的列线图显示出良好的预测性能,有助于临床评估PRCC患者OS,从而为患者制定个体化的治疗策略提供依据。

Epidemiologic characteristics and risk factors associated with overall survival for patients with mucinous colorectal cancer:A population-based study

BACKGROUND Mucinous adenocarcinoma(MC)has attracted much attention as a distinct histologic subtype of colorectal cancer in recent years.However,data about its epidemiologic and prognostic characteristics are limited.Therefore,patient data extracted from the National Cancer Institute’s Surveillance,Epidemiology,and End Results Program were collected to analyze the epidemiologic and clinicopathological characteristics of MC.AIM To determine the epidemiologic and clinicopathological characteristics of MC.METHODS The incidence trend of MC was calculated through the Joinpoint Regression Program.Cox regression analyses were performed to identify prognostic factors associated with overall survival(OS).A nomogram was established to predict the survival probability of individual patients with MC.RESULTS We found that rates of MC decreased from 4.50/100000 in 2000 to 1.54/100000 in 2018.Rates of MCs in patients aged≤50 years decreased 2.27%/year during 2000-2018.The incidence of appendiceal MCs increased from 0.14/100000 in 2000 to 0.24/100000 in 2018,while the incidence in other anatomic subsites continued to decrease.On multivariable Cox analyses,age,race,tumor site,T stage,N stage,M stage,surgery,and chemotherapy were associated with OS.A nomogram was developed based on these factors,and the area under the curve for 1-year,3-year,and 5-year OS in the training cohort was 0.778,0.778,and 0.768,respectively.CONCLUSION Our results demonstrated that MC incidence decreased in almost all anatomic subgroups except for the appendix.A nomogram predicting the survival probability of patients with MCs showed good performance.

基于SEER数据库的原发性肝癌患者预后危险因素研究

目的:探讨原发性肝癌患者预后的危险因素,为该病患者的临床诊疗和预后判断提供科学依据。方法:以2018年监测、流行病学和结果(Surveillance,Epidemiology,and End Results,SEER)数据库原发性肝癌患者作为研究对象,收集人口学资料、临床指标和预后随访信息,运用单因素和多因素logistic回归分析影响患者术后生存的危险因素。采用一致性指数评价模型的预测能力,构建受试者工作特征曲线分析预测模型的效能。采用绘制森林图的方法对不同分期下肝癌患者的治疗方式进行分析。结果:该研究共收集2018年原发性肝癌患者1750例。单因素logistic回归结果表明,肿瘤分期、淋巴结转移、远处转移、婚姻状况、放化疗及手术是影响原发性肝癌患者生存的危险因素(P<0.05);多因素logistic回归分析结果表明,肿瘤分期[T2/T3相对于T1,OR=5.142/3.390,95%CI=(3.654~7.236)(/2.327~4.939),P<0.001]、远处转移(OR=4.810,95%CI=3.384~6.839,P<0.001)、婚姻状况(OR=0.729,95%CI=0.575~0.925,P=0.009)、放疗(OR=0.361,95%CI=0.260~0.503,P<0.001)、化疗(OR=0.512,95%CI=0.381~0.687,P=0.001)以及手术(OR=0.245,95%CI=0.105~0.574,P=0.028)是影响肝癌患者生存的危险因素。将logistic回归中有意义的变量如肿瘤分期、远处转移、婚姻状况、放化疗和手术情况进行预测模型的构建,研究显示该模型一致性指数为0.786(95%CI=0.762~0.810),曲线下面积(area under the curve,AUC)为0.790(95%CI=0.764~0.812)。仅放疗这种干预方式在任何肿瘤分期的患者中都展现出了优势(P=0.003、P=0.013、P=0.003)。在未发生淋巴结转移的患者中无论哪种干预方式都会降低肝癌患者的病死率(P<0.001,P=0.001,P<0.001,P=0.004),但是在发生淋巴结转移的患者中,是否进行干预对肝癌患者的生存没有影响(P>0.05)。在未发生远处转移的患者中,仅进行放疗、化疗或化疗+放疗干预方式的患者与未进行干预的患者相比生存率更高(P<0.001,P=0.001,P<0.001,P=0.004),在发生远处转移的患者中,仅进行放疗的干预方式展现出优势(P=0.002)。结论:肿瘤分期、远处转移、婚姻状况、放化疗和手术情况是影响原发性肝癌预后的危险因素。

基于SEER数据库构建原发性纵隔生殖细胞瘤患者生存预测的列线图

背景与目的原发性纵隔生殖细胞瘤(primary mediastinal germ cell tumor,PMGCT)是一种相对罕见且偶尔会具有高度侵袭性的纵隔肿瘤。目前对PMGCT的疾病特异性生存期(disease special survival,DSS)的相关研究报道较少,大数据分析亦相对较少,DSS预后模型也较为少见。本研究旨在探讨影响PMGCT DSS的预后相关因素,并构建简便、有效、可对PMGCT患者DSS预后情况进行预测的列线图。方法回顾性分析从监测、流行病学和最终结果(Surveillance,Epidemiology,and End Results,SEER)数据库提取的1975年-2019年共347例PMGCT患者的临床病理资料。采用Kaplan-Meier法及Log-rank检验估计DSS。执行Cox比例风险回归模型筛选影响预后的独立危险因素,构建个体化列线图预测PMGCT患者的3年、5年、8年DSS。通过受试者工作特征(receiver operating characteristic,ROC)曲线、校正曲线及决策曲线分析(decision curve analysis,DCA)评估模型的预测精度。结果PMGCT患者的3年、5年、8年生存率分别为84.6%、83.6%、83.3%。单因素Cox回归分析显示组织学分型、手术与否、年龄、肿瘤大小、肿瘤转移情况及肿瘤分期6项因素可影响PMGCT的预后(P<0.05),多因素Cox回归分析显示组织学分型、手术与否、年龄、肿瘤大小是PMGCT患者预后的独立危险因素(P<0.05),利用这些独立危险因素构建了列线图模型。ROC的曲线下面积(area under the curve,AUC)为0.824,3年、5年、8年生存时间的校正曲线以及DCA曲线,三者结果提示本研究的列线图评估预测结果与真实结果之间有良好的一致性。结论PMGCT中组织学分型为精原细胞瘤的患者比非精原细胞瘤患者预后更佳,年龄>40岁、肿瘤大小≥15 cm且未进行过手术治疗的患者预后不佳。列线图模型可以对PMGCT患者的DSS进行准确直观的预测。

Analysis of cancer-specific survival in patients with metastatic colorectal cancer: A evidence-based medicine study

BACKGROUND Metastatic colorectal cancer(mCRC)is a common malignancy whose treatment has been a clinical challenge.Cancer-specific survival(CSS)plays a crucial role in assessing patient prognosis and treatment outcomes.However,there is still li-mited research on the factors affecting CSS in mCRC patients and their corre-lation.AIM To predict CSS,we developed a new nomogram model and risk grading system to classify risk levels in patients with mCRC.METHODS Data were extracted from the United States Surveillance,Epidemiology,and End Results database from 2018 to 2023.All eligible patients were randomly divided into a training cohort and a validation cohort.The Cox proportional hazards model was used to investigate the independent risk factors for CSS.A new nomogram model was developed to predict CSS and was evaluated through internal and external validation.RESULTS A multivariate Cox proportional risk model was used to identify independent risk factors for CSS.Then,new CSS columns were developed based on these factors.The consistency index(C-index)of the histogram was 0.718(95%CI:0.712-0.725),and that of the validation cohort was 0.722(95%CI:0.711-0.732),indicating good discrimination ability and better performance than tumor-node-metastasis staging(C-index:0.712-0.732).For the training set,0.533,95%CI:0.525-0.540;for the verification set,0.524,95%CI:0.513-0.535.The calibration map and clinical decision curve showed good agreement and good potential clinical validity.The risk grading system divided all patients into three groups,and the Kaplan-Meier curve showed good stratification and differentiation of CSS between different groups.The median CSS times in the low-risk,medium-risk,and high-risk groups were 36 months(95%CI:34.987-37.013),18 months(95%CI:17.273-18.727),and 5 months(95%CI:4.503-5.497),respectively.CONCLUSION Our study developed a new nomogram model to predict CSS in patients with synchronous mCRC.In addition,the risk-grading system helps to accurately assess patient prognosis and guide treatment.

乳腺癌共发甲状腺癌的危险因素及预后分析

目的分析乳腺癌(BC)共发甲状腺癌(TC)的危险因素,探讨预后影响因素。方法在2020年监测、流行病学和结果(SEER)数据库搜集BC共发TC患者(共发组)以及单纯BC患者(单纯组)的信息,比较2组临床资料和生存信息。回顾性分析某医院住院的BC共发TC患者(共发组A)以及单纯BC患者(单纯组A)的临床资料,比较2组临床资料以及生存信息。结果①SEER数据库分析,共发组482例、单纯组500例,单因素分析显示首次确诊年龄和孕激素受体(PR)是BC共发TC的危险因素(P均<0.05),多因素分析显示首次确诊年龄(OR=1.800,95%CI:1.387~2.337,P<0.001)、PR(OR=1.364,95%CI:1.023~1.818,P=0.034)是BC共发TC的独立危险因素。剔除随访资料不完整者后的单因素分析显示肿瘤直径和PR是BC共发TC的预后因素(P<0.05),多因素分析显示肿瘤直径是BC共发TC的独立预后因素(OR=4.328,95%CI:1.410~13.288,P=0.010);单因素分析显示首次确诊年龄和肿瘤直径是单纯BC的预后因素(P均<0.05),多因素分析显示首次确诊年龄(OR=2.443,95%CI:1.014~5.889,P=0.047)、肿瘤直径(OR=2.030,95%CI:1.039~3.969,P=0.038)是单纯BC的独立预后因素。②某医院住院患者分析,共发组A 40例(50%),单纯组A 40例(50%)。单因素分析显示月经情况、PR、增殖指数Ki-67、TT_(3)是BC共发TC的危险因素(P<0.05);多因素分析显示月经情况(OR=0.175,95%CI:0.052~0.591,P=0.005)、PR(OR=5.686,95%CI:1.677~19.282,P=0.005)、Ki-67(OR=3.966,95%CI:1.133~13.875,P=0.031)是BC共发TC的独立危险因素。对80例患者进行随访,共发组A死亡6例,生存27例,失访7例;单纯组A死亡2例,生存29例,失访9例。2组患者Cox回归分析结果均无统计学意义(P均>0.05)。结论首次确诊年龄、月经情况、PR、Ki-67是BC共发TC的危险因素。肿瘤直径是BC共发TC的独立预后因素。首次确诊年龄和肿瘤直径是单纯BC的独立预后因素。