胃神经内分泌瘤患者预后Nomogram预测模型的构建

[摘要] 目的：基于美国国立癌症研究所（NCI）的监测、流行病学和最终结果（SEER）数据库数据分析影响胃神经内分泌瘤（G-NEN）患者预后的相关因素,并构建Nomogram预测模型用于个体化预测G-NEN患者预后。方法：收集SEER数据库2010 年至2015 年有完整随访资料的2 720 例G-NEN患者的临床数据,基于生存分析确定独立危险因素并构建Nomogram 预测模型,采用一致性指数（C-index）和校准曲线评估模型准确性,采用受试者特征曲线下面积（AUC）比较该模型与第7 版AJCC TNM分期评估法的预测价值。结果：2 720 例G-NEN患者的1、3、5 年生存率分别为88.14%、79.09%、71.86%。多因素COX回归分析显示,性别、年龄、婚姻状况、是否伴发其他肿瘤、组织学类型、肿瘤分级、T分期、M分期及是否手术是影响G-NEN患者生存时间的独立危险因素。新构建的Nomogram预测模型C-index 为0.816,显著高于7 版AJCC TNM分期评估法的0.702（P<0.001）,且1、3、5 年校准曲线显示预测生存率与实际生存率之间具有良好的一致性。新构建的Nomogram 预测模型1、3、5 年AUC分别为0.800、0.811及0.820,显著高于第7 版AJCC TNM分期评估法的0.650、0.688 及0.698（Z=6.600、8.058、9.632,均P<0.0001）。结论：构建的预测G-NEN患者预后的Nomogram模型具有较高的预测价值,能够个体化预测G-NEN患者的生存率,有助于临床治疗决策和临床研究方案的选择。     

联合SCC-Ag水平建立早期宫颈鳞癌的预后预测模型

摘 要：［目的］ 构建一个能够预测早期宫颈鳞癌患者术后生存的模型。［方法］ 纳入1435例在浙江省肿瘤医院行宫颈癌根治术的ⅠA～ⅡA期宫颈鳞状细胞癌患者,收集其临床特征、病理特征、术前血清SCC-Ag水平、术后辅助治疗及随访资料,随机抽取2/3患者组成建模组（n=957）用于列线图的开发,余1/3患者组成验证组（n=478）用于验证模型的性能。在建模组中,根据单因素、多因素COX回归分析结果确定影响患者总生存率的独立危险因素,结合临床意义将这些因素纳入预测模型,预测模型的区分度和准确性通过一致性指数（C-index）和校准曲线确定。进一步通过验证组评估模型的预测性能。［结果］ 在建模组中,单因素、多因素COX回归分析显示,肿块大小（HR=1.895,95%CI：1.140～3.151,P=0.014）、切缘状态（HR=3.709,95%CI：1.089～12.636,P=0.036）、脉管瘤栓（HR=2.330,95%CI：1.375～3.947,P=0.002）、术前血清SCC-Ag水平（HR=1.797,95%CI：1.131～2.858,P=0.013）、术后辅助放疗的有无（HR=0.542,95%CI 0.306～0.958,P=0.035）是早期宫颈癌的独立预后因素。结合这些因素及盆腔淋巴结状态、腹主动脉旁淋巴结状态、间质浸润,建立一个能够预测患者3年、5年OS的列线图。模型在建模组和验证组均显示出良好的区分度,C-index分别为0.71、0.69,优于FIGO分期的0.53、0.61。校准曲线也验证了该列线图预测的生存率与实际的生存率之间的一致性。［结论］本研究构建了一个有助于个体化预测早期宫颈鳞癌患者生存预后的量化模型,对于临床上制定后续的治疗方案具有一定的指导意义。     

基于列线图探索脑内皮黏附分子表达水平在结肠癌预后预测中的作用

目的：探索脑内皮细胞黏附分子（CERCAM）与结肠癌患者预后的关系，利用Cox模型建立具有良好预后判断价值的列线图并予以验证。方法：下载TCGA及GTEx数据库中结肠癌及正常组织中CERCAM表达及患者临床特征数据，收集2013年2月至2019年6月南京市第一医院收治的4例结肠癌患者的癌及癌旁组织样本进行验证，通过差异分析、通路富集分析以及生存分析等方法探索CERCAM的组织定位、功能及预后价值。通过Cox回归筛选出结肠癌的预后危险因素，基于CERCAM及各危险因素构建列线图，分别使用一致性指数、校准曲线、时间依赖性受试者工作特征（ROC）曲线进行验证与评价，根据危险分层绘制生存曲线。结果：结肠肿瘤组织中CERCAM基因的表达水平显著低于正常组织（P<0.001），在结肠癌患者中，CERCAM高表达人群OS（P=0.034）及存活状态（P=0.002）显著劣于低表达组，且CERCAM与癌症信号通路以及PI3K-Akt信号通路的活化有关联。Cox分析显示，CERCAM表达水平（HR=2.23，P=0.015）、T分期（HR=5.64，P=0.015）、M分期（HR=2.62，P=0.022）是结肠癌预后的独立危险因素，血管浸润（HR=2.30，P=0.089）是危险因素，利用上述因素建立列线图，一致性指数提示其区分度好，且训练集与测试集一致；校准曲线、ROC曲线同样显示该列线图的预测能力较好。通过危险分层绘制生存曲线，结果提示高风险组有更低的生存率（P<0.000 1）。结论：CERCAM高表达与结肠癌患者不良预后密切相关，且可能与癌症中蛋白聚糖及PI3K-Akt信号通路有关联，基于CERCAM建立的列线图优于传统预测模型，对结肠癌患者生存预后的评估具有一定临床价值，这种实用的模型有助于患者风险分层及治疗方案的优化。     

预测子宫内膜癌根治术后生存的列线图模型

摘 要： ［目的］ 分析影响子宫内膜癌根治术后生存的相关因素,建立列线图预测模型。［方法］ 选取2013年8月至2015年8月收治的子宫内膜癌患者300例作为建模组,2015年9月至2016年9月收治的52例子宫内膜癌患者作为验证组。采用Kaplan-Meier法计算术后3年及5年生存率,Cox回归模型筛选术后生存率的独立影响因素。基于预后相关独立影响因素建立列线图预测模型。 ［结果］ 术后对300例患者实施5年随访,失访14例,286例患者3年、5年生存率分别为95.45%、86.71%。多因素Cox风险回归分析显示,手术病理分期、组织学分级、肌层浸润深度、淋巴结转移是子宫内膜癌患者术后生存率的独立危险因素（P＜0.05）。基于影响术后生存的危险因素建立列线图预测模型,列线图预测模型预测3年、5年生存率的ROC曲线下面积分别为0.859（95%CI：0.820~0.892）、0.849（95%CI：0.805~0.880）;校准曲线为斜率近似于1的直线。验证组列线图预测3年、5年生存率的ROC曲线下面积分别为0.858（95%CI：0.803~0.903）、0.827（95%CI：0.758~0.876）。Kaplan-Meier生存曲线结果显示,高危组患者5年生存率为78.63%,明显低于低危组患者的92.31%（P＜0.05）。［结论］ 基于子宫内膜癌根治术后生存率的影响因素建立列线图预测模型预测术后3年、5年生存率的区分度与一致性良好,可为子宫内膜癌的术后辅助治疗提供一定参考价值。     

miRNA-203表达水平对结直肠癌患者预后的临床价值

目的:探讨miRNA-203表达水平对结直肠癌患者预后的预测价值。方法:回顾性选择2010年1月至2013年12月来我院接受手术切除治疗的结直肠癌患者120例,所有患者均经病理确认。根据结直肠癌组织中miRNA-203表达水平将患者分为miRNA-203低表达组（n=42）和miRNA-203高表达组（n=78）。分析结直肠癌组织中miRNA-203表达水平与临床病理特征的关系,应用单因素、多因素非条件Cox回归分析影响结直肠癌患者预后的危险因素,并采用Kaplan-Meier法绘制累积生存曲线。结果:结直肠癌患者组织中miRNA-203表达量与年龄、性别、吸烟史、嗜酒史、组织类型、肿瘤位置、肿瘤直径无关（P>0.05）,与分化程度、TNM分期、淋巴结转移、脉管浸润有关（P<0.05）。单因素、多因素Cox回归分析结果显示,分化程度为高分化、TNM分期为IV期、组织中miRNA-203低表达是影响结直肠癌患者无进展生存率和总生存率的危险性因素（P<0.05）。Kaplan-Meier法生存曲线结果显示,miRNA-203高表达组结直肠癌患者无进展生存率和总生存率显著高于低表达组（P<0.05）。结论:miRNA-203表达水平可作为预测结直肠癌患者预后的指标。     

结合p53构建胃癌根治术后患者生存率的列线图预测模型

[目的]结合p53蛋白构建预测胃癌根治术后生存率的列线图模型,验证并评价该模型的预测价值。[方法]收集2016年1月至2017年5月在宁夏医科大学总医院胃肠外科行胃癌手术患者203例的临床病理及生存数据资料,建立数据库,采用Kaplan-Meier单因素分析、Log-rank检验和Cox多因素回归分析,筛选出影响胃癌术后患者总生存期（overall survival,OS）的独立预后因素,通过R软件构建胃癌根治术后1年、3年、5年生存率的列线图模型,计算Cox模型的一致性指数(C指数)、绘制受试者工作特征曲线（receiver operating characteristic curve,ROC曲线）,计算曲线下面积（area under the cure,AUC）及绘制校准曲线验证模型的有效性。将上述患者作为训练组,并收集2017年6月至7月宁夏医科大学总医院胃肠外科51例行胃癌根治手术的患者资料作为验证组进行外部验证。[结果]有203例患者被纳入本研究,通过Kaplan-Meier单因素及Cox多因素回归分析显示,影响胃癌根治术后生存率的独立预后因素分别为年龄、浸润深度、淋巴结转移...     

术前血小板水平与可切除肢端黑色素瘤预后相关性

摘 要：［目的］ 分析术前外周血中淋巴细胞、中性粒细胞、血小板等指标与可切除的肢端黑色素瘤患者预后的关系。［方法］ 回顾性分析2005年1月至2015年1月在中山大学肿瘤医院接受根治性手术切除的223例Ⅰ~Ⅲ期肢端黑色素瘤患者的临床病理特征及术前血常规各项指标。应用Cox比例风险回归模型进行生存分析;采用Kaplan-Meier法绘制生存曲线并对组间差异进行Log-rank检验。［结果］ 单因素分析结果显示年龄、PS评分、溃疡、肿瘤分期、术前LDH及血小板水平是肢端黑色素瘤患者生存的影响因素。多因素分析结果显示溃疡、肿瘤分期、术前LDH及血小板水平是影响患者预后的独立危险因素（P＜0.05）。在Ⅱ期（P=0.006）和Ⅲ期（P=0.028）患者中,不同术前血小板水平者生存率均具有统计学差异。［结论］溃疡、肿瘤分期、术前LDH和血小板水平是可切除的肢端黑色素瘤患者的独立危险因素,术前常规评估血小板水平有助于临床医师判断患者预后并进行个体化治疗。     

2008—2017年江苏省南通市肿瘤医院皮肤癌住院患者生存率分析

摘 要：［目的］ 对2008—2017年在南通市肿瘤医院住院的皮肤癌患者进行生存分析。［方法］ 采用被动随访与主动随访相结合的方法,对皮肤癌住院患者进行生存结局随访,随访截止时间为2020年12月31日。采用Kaplan-Meier法计算观察生存率（OSR）,差异比较使用Log-rank检验,并采用Cox回归进行多因素分析。通过R软件构建列线图生存率预测模型,计算Cox 模型的一致性指数（C-index）并绘制校准曲线验证模型的有效性。 ［结果］ 共纳入328例皮肤癌患者,其中男性168例,女性160例。5年OSR为66.31%。单因素分析显示,TNM分期、治疗方式和肿瘤类型为皮肤癌患者生存率的影响因素（P<0.05）。多因素分析显示,采取其他治疗手段是影响皮肤癌生存率的独立危险因素（P<0.05）。模型的C-index值为0.618,校准曲线显示皮肤癌患者的生存率的预测校准曲线与理想参考线拟合度良好,提示该模型预测准确度较好。［结论］ 南通市肿瘤医院皮肤癌住院患者的5年生存率相对较高,但分型为恶性黑色素瘤的患者预后较差。是否采取手术治疗能够为预测皮肤癌患者的预后提供参考。     

基于阴性淋巴结数目的胃印戒细胞癌预后评估模型的建立与验证

目的 探讨阴性淋巴结数目（NLNC）对胃印戒细胞癌（GSRC）患者预后的影响及构建G S R C 患者的预后预测模型。方法 基于SEER数据库收集GSRC患者2101例，随机分为建模组和验证组，检验临床病理特征与GSRC预后的关系。多因素Cox比例风险回归模型分析影响总生存的独立危险因素并建立预后预测模型。一致性指数（C?index）、校准曲线、净分类指数（NRI）、综合判别指数（IDI）和临床决策曲线（DCA）对列线图进行准确性和临床适用性评估。结果 所有患者按照7:3比例划分，建模组1473例，验证组628例。NLNC>10是GSRC患者预后的保护因素（HR=0.578, 95%CI: 0.504~0.662），根据多因素Cox比例风险回归模型筛选的变量建立Nomogram图，建模组和验证组的C-index分别为0.737（95%CI: 0.720~0.753）和0.724（95%CI: 0.699~0.749），区分度良好，校准曲线显示模型的一致性较高。NRI=17.77%，连续NRI=36.34%，IDI=4.2%，表明该模型较传统模型是正向收益，DCA决策曲线远离基准线表明模型临床适用性好。结论 NLNC增加是GSRC患者预后的有利因素。本研究建立的列线图相对准确，可预测GSRC患者的预后。     

基于SEER数据库低级别胶质瘤预后列线图的构建

目的:通过监测、流行病学及预后（surveillance，epidemiology，and end result,SEER）数据库开发列线图来分析低级别胶质瘤（low-grade glioma,LGG）患者的预后因素并且预测其生存率。方法:通过SEER数据库收集LGG患者5 439例，并统计其人口统计学信息及临床特征。随机抽取其中1 001例作为模型的内部验证集,并收集2010-2017年间就诊于山西省人民医院的LGG患者67例作为外部验证集。采用单因素、多因素Cox回归及Lasso回归分析LGG患者的独立危险因素，并考虑其临床效用性。将这些独立预测因素整合在一起，绘制预测LGG患者1年和3年生存率的列线图。通过内部验证集数据及外部验证集数据绘制ROC曲线和校准曲线图来评估列线图的性能。结果:纳入训练集患者4 438例，内部验证集患者1 001例，外部验证集患者67例。一般情况人群分布无显著统计学差异。通过单因素、多因素Cox回归及Lasso回归分析联合生存分析结果选择独立危险因素，纳入年龄、病理学分型、手术方式、肿瘤大小、婚姻状况、放化疗及发病部位为独立预测因素(P<0.001)。由上述7种因素构建预后预测模型，结果以列线图形式呈现。内部验证集验证列线图的ROC曲线下面积为0.841和0.804；外部验证集验证列线图的ROC曲线下面积为0.703和0.742，表明该模型的区分度与准确度较高。校准曲线显示其具有较好的一致性。结论:本列线图可用于预测LGG患者1年和3年生存率，并且拥有较高的临床价值，可以为LGG的个体化治疗提供参考。     

Development and validation of prognostic nomogram based on log odds of positive lymph nodes for patients with gastric signet ring cell carcinoma

ObjectiveOur aims were to establish novel nomogram models, which directly targeted patients with signet ring cell carcinoma (SRC), for individualized prediction of overall survival (OS) rate and cancer-specific survival (CSS).MethodsWe selected 1,365 SRC patients diagnosed from 2010 to 2015 from Surveillance, Epidemiology and End Results (SEER) database, and then randomly partitioned them into a training cohort and a validation cohort. Independent predicted indicators, which were identified by using univariate testing and multivariate analyses, were used to construct our prognostic nomogram models. Three methods, Harrell concordance index (C-index), receiver operating characteristics (ROC) curve and calibration curve, were used to assess the ability of discrimination and predictive accuracy. Integrated discrimination improvement (IDI), net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess clinical utility of our nomogram models.ResultsSix independent predicted indicators, age, race, log odds of positive lymph nodes (LODDS), T stage, M stage and tumor size, were associated with OS rate. Nevertheless, only five independent predicted indicators were associated with CSS except race. The developed nomograms based on those independent predicted factors showed reliable discrimination. C-index of our nomogram for OS and CSS was 0.760 and 0.763, which were higher than American Joint Committee on Cancer (AJCC) 8th edition tumor-node-metastasis (TNM) staging system (0.734 and 0.741, respectively). C-index of validation cohort for OS was 0.757 and for CSS was 0.773. The calibration curves also performed good consistency. IDI, NRI and DCA showed the nomograms for both OS and CSS had a comparable clinical utility than the TNM staging system.ConclusionsThe novel nomogram models based on LODDS provided satisfying predictive ability of SRC both in OS and CSS than AJCC 8th edition TNM staging system alone.     

A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes to Predict Overall Survival for Non-Metastatic Bladder Cancer Patients after Radical Cystectomy

(1) Purpose: The purpose of this study was to evaluate the prognostic capacity of the pathological N status (pN), lymph node ratio (LNR), and the log odds of positive lymph nodes (LODDS), and to build a prognostic nomogram to predict overall survival (OS) for bladder cancer patients treated by radical cystectomy. (2) Methods: The clinical and pathological characteristics of 10,938 patients with bladder cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017. The predictive capacity was assessed by univariate and multivariate Cox regression analyses, the area under the receiver operating characteristic curve (AUC), and C-index. Calibration curves, decision curve analysis (DCA), and risk-grouping were utilized to evaluate the predictive accuracy and discriminative ability of the nomogram. (3) Results: LODDS was an independent risk factor for bladder cancer (all p < 0.001) and demonstrated the highest values of C-index and AUC. The values of AUCs in the training cohort were 0.747, 0.743, and 0.735 for predicting 1-, 3-, and 5-year OS, respectively. Calibration curves and DCA curves suggested the excellent clinical application value of our nomogram. (4) Conclusions: LODDS is a better predictive indicator for bladder cancer patients compared to pN and LNR. The LODDS-incorporated nomogram has excellent accuracy and promising clinical application value for non-metastatic bladder cancer after radical cystectomy.     

Prognostic nomogram for predicting cancer-specific survival in patients with resected hilar cholangiocarcinoma: a large cohort study

BackgroundThe aim of the study was to establish and validate a novel prognostic nomogram of cancer-specific survival (CSS) in resected hilar cholangiocarcinoma (HCCA) patients.MethodsA training cohort of 536 patients and an internal validation cohort of 270 patients were included in this study. The demographic and clinicopathological variables were extracted from the Surveillance, Epidemiology and End Results (SEER) database. Univariate and multivariate Cox regression analysis were performed in the training cohort, followed by the construction of nomogram for CSS. The performance of the nomogram was assessed by concordance index (C-index) and calibration plots and compared with the American Joint Committee on Cancer (AJCC) staging systems. Decision curve analysis (DCA) was applied to measure the predictive power and clinical value of the nomogram.ResultsThe nomogram incorporating age, tumor size, tumor grade, lymph node ratio (LNR) and T stage parameters was with a C-index of 0.655 in the training cohort, 0.626 in the validation cohort, compared with corresponding 0.631, 0.626 for the AJCC 8th staging system. The calibration curves exhibited excellent agreement between CSS probabilities predicted by nomogram and actual observation in the training cohort and validation cohort. DCA indicated that this nomogram generated substantial clinical value.ConclusionsThe proposed nomogram provided a more accurate prognostic prediction of CSS for individual patients with resected HCCA than the AJCC 8th staging system, which might be served as an effective tool to stratify resected HCCA patients with high risk and facilitate optimizing therapeutic benefit.     

Development and validation of a Surveillance,Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in elderly patients with gastric cancer after surgery

BackgroundElderly gastric cancer (ELGC) remains one of the intensively investigated topics during the last decades. To establish a comprehensive nomogram for effective clinical practice and assessment is of significance. This study is designed to develop a prognostic nomogram for ELGC both in overall survival (OS) and cancer-specific survival (CSS).MethodsThe recruited cases were from the Surveillance, Epidemiology, and End Results (SEER) database and input for the construction of nomogram.ResultsA total of 4,414 individuals were recruited for this study, of which 2,208 were randomly in training group and 2,206 were in validation group. In univariate analysis of OS, significant variables (P<0.05) included age, marital status, grade, American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) stage, bone/brain/liver/lung metastasis and tumor size. In univariate analysis of CSS, significant variables (P<0.05) included age, grade, AJCC TNM stage, bone/brain/liver/lung metastasis and tumor size. In multivariate analysis of OS, sex, age, race, grade, TNM stage, lung metastasis and tumor size were considered as the significant variables and subjected to the establishment of nomogram. In multivariable analysis of CSS, age, grade, TNM, tumor size were considered as the significant variables and input to the establishment of nomogram. Sex, age, race, grade, TNM stage, lung metastasis and tumor size were included for the establishment of nomogram in OS while age, grade, TNM, tumor size were included to the establishment of nomogram in CSS. C-index, decision curve analysis (DCA) and the area under the curve (AUC) showed distinct value of newly established nomogram models. Both OS and CSS nomograms showed higher statistic power over the AJCC stage.ConclusionsThis study established and validated novel nomogram models of OS and CSS for ELGC based on population dataset.     

A novel preoperative MRI-based radiomics nomogram outperforms traditional models for prognostic prediction in pancreatic ductal adenocarcinoma

To develop an efficient prognostic model based on preoperative magnetic resonance imaging (MRI) radiomics for patients with pancreatic ductal adenocarcinoma (PDAC), the preoperative MRI data of PDAC patients in two independent centers (defined as development cohort and validation cohort, respectively) were collected retrospectively, and the radiomics features of tumors were then extracted. Based on the optimal radiomics features which were significantly related to overall survival (OS) and progression-free survival (PFS), the score of radiomics signature (Rad-score) was calculated, and its predictive efficiency was evaluated according to the area under receiver operator characteristic curve (AUC). Subsequently, the clinical-radiomics nomogram which incorporated the Rad-score and clinical parameters was developed, and its discrimination, consistency and application value were tested by calibration curve, concordance index (C-index) and decision curve analysis (DCA). Moreover, the predictive value of the clinical-radiomics nomogram was compared with traditional prognostic models. A total of 196 eligible PDAC patients were enrolled in this study. The AUC value of Rad-score for OS and PFS in development cohort was 0.724 and 0.781, respectively, and the value of Rad-score was negatively correlated with PDAC’s prognosis. Moreover, the developed clinical-radiomics nomogram showed great consistency with the C-index for OS and PFS in development cohort was 0.814 and 0.767, respectively. In addition, the DCA demonstrated that the developed nomogram displayed better clinical predictive usefulness than traditional prognostic models. We concluded that the preoperative MRI-based radiomics signature was significantly related to the poor prognosis of PDAC patients, and the developed clinical-radiomics nomogram showed better predictive ability, it might be used for individualized prognostic assessment of preoperative patients with PDAC.     

四肢纤维肉瘤患者预后诺模图的开发和验证

目的:开发诺模图来预测原发于四肢纤维肉瘤患者的总体生存率(OS)和癌症特异性生存率(CSS)。方法:根据SEER数据库,收集原发于四肢纤维肉瘤病例。采用Cox比例风险回归模型对病例预后进行分析,获得独立的预测因素。这些独立的预测因子被整合在一起,形成了预测5年和10年OS及CSS的诺模图。使用R软件通过一致性指数(C-index指数）、ROC曲线和校准曲线图来评估诺模图的性能。结果:在OS的单因素和多因素分析中,年龄、病理分级、肿瘤大小和手术被确定为独立的危险因素。 在CSS的单变量和多变量分析中,病理分级、肿瘤大小和肿瘤分期被确定为独立的危险因素。 这些特征均整合在诺模图中以预测5年和10年OS和CSS,C指数分别为0.812和0.857。通过5年和10年OS和CSS的概率的C-index指数和AUG曲线显示,诺模图预测和观察结果之间具有很好的一致性。结论:诺模图可以准确地预测四肢纤维肉瘤患者的OS和CSS,并有助于个性化的预后评估和个性化的临床决策。     

Prognosis prediction model for a special entity of gastric cancer,linitis plastica

BackgroundGastric linitis plastica (GLP) is characteristic by its poor prognosis and highly aggressive characteristics compared with other types of gastric cancer (GC). However, the guidelines have not yet been distinguished between GLP and non-GLP.MethodsA total of 342 eligible patients with GLP identified in the Surveillance, Epidemiology, and End Results (SEER) dataset were randomly divided into training set (n=298) and validation set (n=153). A nomogram would be developed with the constructed predicting model based on the training cohort’s data, and the validation cohort would be used to validate the model. Principal component analysis (PCA) was used to evaluate the differences between groups. Cox regression and LASSO (least absolute shrinkage and selection operator) were used to construct the models. Calibration curve, time-dependent receiver operating characteristic (ROC) curve, concordance index (C-index) and decision curve analysis (DCA) were used to evaluate the predicting performance. Restricted mean survival time (RMST) was used to analyze the curative effect of adjuvant therapy.ResultsFor patients in training cohort, univariable and multivariable Cox analyses showed that age, examined lymph nodes (LN.E), positive lymph nodes (LN.P), lesion size, combined resection, and radiotherapy are independent prognostic factors for overall survival (OS), while chemotherapy can not meet the proportional hazards (PHs) assumption; age, race, lesion size, LN.E, LN.P, combined resection and marital status are independent prognostic factors for cancer-specific survival (CSS). The C-index of the nomogram was 0.678 [95% confidence interval (CI), 0.660–0.696] and 0.673 (95% CI, 0.630–0.716) in the training and validation cohort, respectively. Meanwhile, the C-index of the CSS nomogram was 0.671 (95% CI, 0.653–0.699) and 0.650 (95% CI, 0.601–0.691) in the training and validation cohort for CSS, respectively. Furthermore, the nomogram was well calibrated with satisfactory consistency. RMST analysis further determined that chemotherapy and radiotherapy might be beneficial for improving 1- and 3-year OS and CSS, but not the 5-year CSS.ConclusionsWe developed nomograms to help predict individualized prognosis for GLP patients. The new model might help guide treatment strategies for patients with GLP.     

A prognostic nomogram for colorectal cancer liver metastases after percutaneous thermal ablation

Purpose: To assess the efficacy of percutaneous thermal ablation in treating colorectal cancer liver metastases (CRCLM), and to propose a prognostic nomogram for overall survival (OS).

Materials and methods: Seventy-one patients with CRCLM undergoing thermal ablation at our institute from 2009 to 2013 were identified and analysed to formulate a prognostic nomogram. The concordance index (C-index) and calibration curve were calculated to evaluate the predictive accuracy of the nomogram. The nomogram was compared with two current prognostic nomograms for patients with CRCLM who had undergone hepatectomy (Kattan) and selective internal radiation therapy (Fendler). Predictive validity was assessed in the validation cohort of 25 patients who had undergone thermal ablation from 2014 to 2016.

Results: The median OS in the primary cohort was 26.4?months, whereas the 1-, 3- and 5-year OS rates were 72.2%, 37.2% and 17%, respectively. The median progression-free survival was 4.2?months. After univariate and multivariate analysis, a prognostic nomogram was formulated based on four predictors, including the number of tumours, maximum diameter of the tumour, CA19–9 level and ablation margin. The C-index of the nomogram was 0.815. Based on the patients of this study, the C-index was significantly higher than that of the Fendler nomogram (C-index, 0.698) and Kattan nomogram (C-index, 0.514, p?Conclusions: Thermal ablation was an effective therapy for CRCLM. Moreover, the nomogram was effective and simple for CRCLM patients undergoing thermal ablation.     

A novel prognostic nomogram for hepatocellular carcinoma after thermal ablation

It remains impossible to accurately assess the prognosis after thermal ablation in patients with hepatocellular carcinoma (HCC). Our aim was to build a nomogram to predict the survival rate of HCC patients after thermal ablation. We developed and validated a nomogram using data of 959 HCC patients after thermal ablation from two centers. Harrell’s concordance index (C-index), calibration plot and Decision curve analysis (DCA) were used to measure the performance of the nomogram, and we compared it with the Barcelona Clinic Liver Cancer (BCLC) staging system and a previous nomogram. Six variables including age, serum albumin, operation method, risk area, tumor number and early recurrence were selected to construct the nomogram. In the training cohort, internal validation cohort, and external validation cohort, the nomogram all had a higher C-index to predict survival rate than both the BCLC staging system and the previous nomogram (0.736, 0.558 and 0.698, respectively; 0.763, 0.621 and 0.740, respectively; and 0.825, 0.551 and 0.737, respectively). Calibration plots showed a high degree of consistency between prediction and actual observation. Decision curve analysis (DCA) presented that compared with BCLC system and the previous nomogram, our nomogram had the highest net benefit. In all three cohorts, the nomogram could accurately divide patients into three subgroups according to predicted survival risk. A nomogram was developed and validated to predict survival of HCC patients who underwent thermal ablation, which is helpful for prognostic prediction and individual surveillance in clinical practice.     

Development and validation of survival nomograms in colorectal cancer patients with synchronous liver metastases underwent simultaneous surgical treatment of primary and metastatic lesions

Colorectal cancer patients with synchronous liver metastases (CRSLM) can be treated by simultaneous surgery, that is the primary tumor and liver metastasis are removed at the same time. However, criteria for simultaneous surgery are underwent continuously modified and expanded. An appropriate selection of adequate candidates for simultaneous surgery is vital to get best benefits. A retrospective study including CRSLM patients underwent simultaneous surgical treatment was conducted. CRSLM patients from SEER database were screened as development set, while CRSLM patients in Harbin (China) were enrolled as validation set. Overall survival (OS) and cancer-specific survival (CSS) were applied as end-point. Variables were screen by LASSO-Cox regression, then Cox regression was applied to construct 1-, 3- and 5-year OS, and CSS nomograms. Nomograms were compared to TMN stage for survival prediction and evaluated by concordance indexes (C-indexes), Time-dependent receiver operating characteristic (ROC) curves, Decision Curve Analysis (DCA). 1347 and 112 CRSLM patients were included in the development set and validation set respectively. Nine factors were found associated with OS and CSS, i.e., Age, Primary Site, Differentiation grade, Histology type, T stage, N stage, Tumor size, Chemotherapy, CEA. Compared to the TNM stage, OS nomogram in development set and validation set got C-indexes values of 0.701 vs 0.641, 0.670 vs 0.557 respectively. Meanwhile, compared to the TNM stage, CSS nomogram in development set and validation set got C-indexes values of 0.704 vs 0.649, 0.677 vs 0.569 respectively. AUC values of the OS and CSS nomograms were higher than the TNM stage, DCA showed the OS and CSS nomograms got more clinical net benefit than the TNM stage, in both the development set and validation set. Our nomograms for predicting survival might be helpful to identify the right CRSLM patients who can get most benefit from simultaneous surgery.