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.     

肺腺癌患者列线图预后模型的构建与验证

目的 基于SEER数据库的大样本数据,构建肺腺癌患者生存预后的列线图预测模型.方法 回顾性分析SEER数据库收集的2010—2015年诊断为肺腺癌患者的临床数据.根据影响肺腺癌患者预后的独立因素,采用Lasso Cox回归分析构建列线图模型.C指数和校准曲线评估列线图的判别和校准能力.使用NRI和DCA曲线评估列线图的...     

A novel prognostic nomogram based on microvascular invasion and hematological biomarkers to predict survival outcome for hepatocellular carcinoma patients

PurposeThis study aimed to develop and validate a nomogram for overall survival (OS) prediction in which combine clinical characteristics and hematological biomarkers in patients with hepatocellular carcinoma (HCC).MethodsWe performed a retrospective analysis of 807 HCC patients. All the clinical data of these patients were collected through electronic medical record (EMR). The independent predictive variables were identified by cox regression analysis. We tested the accuracy of the nomograms by discrimination and calibration, and then plotted decision curves to assess the benefits of nomogram-assisted decisions in a clinical context, and compared with the TNM staging systems and microvascular invasion (MVI) on HCC prognosis.ResultsThe primary cohort consisted of 545 patients with clinicopathologically diagnosed with HCC from 2008 to 2013, while 262 patients from 2014 to 2016 in external validation cohort. Variables included in the nomograms were TNM Stage, microvascular invasion (MVI), alpha fetoprotein (AFP), platelet to lymphocyte ratio (PLR) and prothrombin time (PT). The C-index of nomogram was 0.768, which was superior than the C-index of TNM Stage (0.660, P < 0.001) and MVI(0.664, P < 0.001) alone in the primary cohort. In the validation cohort, the models had a C-index of 0.845, and were also statistically higher when compared to C-index values for TNM Stage (0.687, P < 0.001) and MVI(0.684, P < 0.001). Calibration curves showed adequate calibration of predicted and reported OS prediction throughout the range of HCC outcomes. Decision curve analysis demonstrated that the nomogram was clinically useful than the TNM Stage and MVI alone. Moreover, patients were divided into three distinct risk groups for OS by the nomogram: low risk group, middle risk group and a high risk group, respectively.ConclusionThe nomogram presents more accurate and useful prognostic power, which could be used to predict OS for patients with HCC.     

皮肤梭形细胞黑色素瘤患者生存预测模型的构建及验证

背景与目的：梭形细胞黑色素瘤（spindle cell melanoma,SCM）是一种罕见的黑色素瘤类型,有关SCM患者生存预后的研究较少。通过提取公共数据库中的SCM临床信息,构建并验证皮肤SCM患者5和10年癌症特异性生存率（cancer-specific survival,CSS）和总生存率（overall survival,OS）的生存预测模型。方法：从美国国立癌症研究所监测、流行病学和最终结果（Surveillance, Epidemiology, and End Results,SEER）数据库筛选出共1 445例患者,分成建模组（n=1 011）和验证组（n=434）。通过单因素和多因素COX回归分析确定独立预后影响因素,建立列线图预测模型。利用一致性指数（concordance index,C-index）、受试者工作特征（receiver operating characteristic,ROC）曲线和校准曲线评估模型的区分度和准确性,利用决策曲线分析（decision curve analysis,DCA）评估模型的临床实用性。结果：年龄、肿瘤部位、肿瘤厚度、溃疡...     

APRI评分对HBV相关肝细胞癌切除术患者预后的预测价值

目的:评估天冬氨酸转氨酶与血小板计数比值指数（APRI）对HBV相关肝细胞癌（HCC）切除术患者术后总生存率（OS）的预测价值。方法:采用回顾性队列研究方法,收集2012年1月至2016年12月期间在广西医科大学附属肿瘤医院行切除术治疗的1 031例HBV相关HCC患者的术前临床资料。通过Kaplan-Meier生存曲线确定APRI评分的cutoff值。采用Kaplan-Meier法绘制不同APRI组患者的生存曲线,并通过Log-rank检验评估两组人群的生存差异。运用逐步多因素Cox回归筛选患者OS独立影响因素。采用限制性立方条图（RCS)评价患者APRI与死亡风险的相关性。建立列线图模型评估APRI对OS的预测能力并内部验证。结果:RCS显示APRI与死亡风险呈非线性关联（非线性P＜0.001）。多因素Cox回归结果显示:APRI、BCLC分期、AFP、性别和肿瘤大小是OS独立影响因素,高APRI组死亡风险是低APRI组2.1倍。患者OS的列线图显示APRI对OS的预测能力仅次于BCLC分期。在建模组和验证组中预测OS列线图的C-index分别为0.71（95%CI:0.68~0.74）、0.69（95%CI:0.64~0.75）;1和5年OS校正曲线显示列线图具有良好的校准度;临床决策曲线（DCA）显示模型具有良好的临床应用价值。结论:APRI是HBV相关HCC切除术患者OS独立影响因素,基于APRI对患者预后进行分层,有利于进行个体化治疗和随访。     

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 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.     

Individualized model for predicting COVID-19 deterioration in patients with cancer: A multicenter retrospective study

The 2019 novel coronavirus has spread rapidly around the world. Cancer patients seem to be more susceptible to infection and disease deterioration, but the factors affecting the deterioration remain unclear. We aimed to develop an individualized model for prediction of coronavirus disease (COVID-19) deterioration in cancer patients. The clinical data of 276 cancer patients diagnosed with COVID-19 in 33 designated hospitals of Hubei, China from December 21, 2019 to March 18, 2020, were collected and randomly divided into a training and a validation cohort by a ratio of 2:1. Cox stepwise regression analysis was carried out to select prognostic factors. The prediction model was developed in the training cohort. The predictive accuracy of the model was quantified by C-index and time-dependent area under the receiver operating characteristic curve (t-AUC). Internal validation was assessed by the validation cohort. Risk stratification based on the model was carried out. Decision curve analysis (DCA) were used to evaluate the clinical usefulness of the model. We found age, cancer type, computed tomography baseline image features (ground glass opacity and consolidation), laboratory findings (lymphocyte count, serum levels of C-reactive protein, aspartate aminotransferase, direct bilirubin, urea, and d -dimer) were significantly associated with symptomatic deterioration. The C-index of the model was 0.755 in the training cohort and 0.779 in the validation cohort. The t-AUC values were above 0.7 within 8 weeks both in the training and validation cohorts. Patients were divided into two risk groups based on the nomogram: low-risk (total points ≤ 9.98) and high-risk (total points > 9.98) group. The Kaplan-Meier deterioration-free survival of COVID-19 curves presented significant discrimination between the two risk groups in both training and validation cohorts. The model indicated good clinical applicability by DCA curves. This study presents an individualized nomogram model to individually predict the possibility of symptomatic deterioration of COVID-19 in patients with cancer.     

Validation of The Hong Kong Liver Cancer Staging System in Patients with Hepatocellular Carcinoma after Curative Intent Treatment

Backgrounds: Recently Hong Kong Liver Cancer (HKLC) staging system has been proposed for staging of hepatocellular carcinoma (HCC), and has been shown to provide better prognostic ability than the Barcelona Clinic Liver Cancer (BCLC) system. However, the HKLC system lacks external validation, and its applicability remains uncertain. The present study was aimed to evaluate the prognostic performance of HKLC in HCC patients treated with curative intent. Methods: Medical records of HCC patients treated with either resection or radiofrequency ablation (RFA) from 2011 to 2016 were retrospectively reviewed. The overall survival and the prognostic ability of the HKLC and BCLC system were evaluated. Results: 79 HCC patients were included, of which 64.56% had Child A cirrhosis. Chronic viral hepatitis B infection was the leading cause of HCC, followed by chronic viral hepatitis C infection, alcohol and alcohol with HBV or HCV infection. According to the BCLC system, 82.28% were in stage 0-A, and according to the HKLC system, 93.67% were in stage I-IIb. RFA and liver resection were the primary treatment in 56.96% and 43.04%, respectively. The 5-year survival rate of patients in HKLC stage I, IIa and IIb were 81.64%, 61.66%, and 54.42%, respectively (P<0.001). Whereas, the 5-year survival rate of patients in BCLC stage 0, A and B were 60.00%, 75.90%, and 26.65%, respectively (P=0.053). The AUROC curve of the HKLC and BCLC for the entire cohort was 0.77 and 0.64, respectively (P=0.15). Subgroup analysis showed the AUROC curve of the HKLC and BCLC for the patients with viral-associated HCC was 0.79 and 0.68, respectively (P=0.02). Conclusions: Applying the HKLC staging system provides a good discriminative ability for survival prediction in HCC patients treated with curative intent. Comparing with the BCLC system, the HKLC system tends to yield better prognostic accuracy, particularly in viral-associated HCC.     

Prediction of late recurrence after radiofrequency ablation of HBV-related hepatocellular carcinoma with the age-male-albumin-bilirubin-platelets (aMAP) risk score: a multicenter study

BackgroundLong-term survivals of patients with HBV-related hepatocellular carcinoma are limited by the high incidence of tumor recurrence after radiofrequency ablation (RFA), identification of the risk factors and understanding the patterns of recurrence can help to improve the comprehensive management of patients after RFA. Therefore, the purpose of the study is to explore the prognostic value of the age-male-albumin-bilirubin-platelets (aMAP) score in patients with early-stage HBV-related hepatocellular carcinoma (HCC) receiving RFA; investigate the risk factors and patterns of late recurrence (LR); and develop a nomogram to predict recurrence-free survival (RFS).MethodsA retrospective review of HBV-related HCC patients who underwent primary RFA from March 2012 to December 2020 was conducted. The prognostic value of the aMAP score was evaluated in a primary cohort (n=302) and then further validated in an independent validation cohort (n=143). The optimal threshold of aMAP scores was calculated by X-tile 3.6.1 software. A prognostic nomogram was constructed from multivariate analysis and validated in an external validation cohort.ResultsPatients with aMAP scores ≤63.8, 63.8–67.8, and >67.8 were classified into low-, medium-, and high-recurrence risk groups, respectively. The C-index to predict LR was 0.76 (95% CI: 0.700–0.810). The high-risk group was associated with the worst RFS (HR: 5.298; 95% CI, 2.697–10.408; P<0.001) and overall survival (OS) (HR: 2.639; 95% CI, 1.097–6.344; P=0.03) compared with medium- and low-risk groups. The aMAP score, multiple tumors and preoperative HBV DNA level were independent risk factors for LR. The proposed nomogram had excellent performance in predicting LR of HBV-related HCC [C-index: 0.82 (95% CI: 0.772–0.870)].ConclusionsThis study demonstrated that the aMAP score can serve as an objective predictor of LR for HBV-related HCC patients after RFA. The nomogram based on preoperative HBV DNA level, aMAP score, and number of tumors can reliably help clinicians to stratify the recurrence risk of HCC patients after RFA.     

Development and validation of a new clinical staging system to predict survival for esophageal squamous cell carcinoma patients: Application of the nomogram

IntroductionSurvival of patients with the same clinical stage varies widely and effective tools to evaluate the prognosis utilizing clinical staging information is lacking. This study aimed to develop a clinical nomogram for predicting survival of patients with Esophageal Squamous Cell Carcinoma (ESCC).Materials and methodsOn the basis of data extracted from the SEER database (training cohort, n = 3375), we identified and integrated significant prognostic factors for nomogram development and internal validation. The model was then subjected to external validation with a separate dataset obtained from Jinling Hospital of Nanjing Medical University (validation cohort, n = 1187). The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index), Akaike information criterion (AIC) and calibration curves. And risk group stratification was performed basing on the nomogram scores.ResultsOn multivariable analysis of the training cohort, seven independent prognostic factors were identified and included into the nomogram. Calibration curves presented good consistency between the nomogram prediction and actual observation for 1-, 3-, and 5-year OS. The AIC value of the nomogram was lower than that of the 8th edition American Joint Committee on Cancer TNM (AJCC) staging system, whereas the C-index of the nomogram was significantly higher than that of the AJCC staging system. The risk groups stratified by CART allowed significant distinction between survival curves within respective clinical TNM categories.ConclusionsThe risk stratification system presented better discriminative ability for survival prediction than current clinical staging system and might help clinicians in decision making.     

International validation of the Chinese University Prognostic Index for staging of hepatocellular carcinoma:a joint United Kingdom and Hong Kong study

The outcome of hepatocellular carcinoma （HCC） patients significantly differs between western and eastern population centers. Our group previously developed and validated the Chinese University Prognostic Index （CUPI） for the prognostication of HCC among the Asian HCC patient population. In the current study, we aimed to validate the CUPI using an international cohort of patients with HCC and to compare the CUPI to two widely used staging systems, the Barcelona Clinic Liver Cancer （BCLC） classification and the Cancer of the Liver Italian Program （CLIP）. To accomplish this goal, two cohorts of patients were enrolled in the United Kingdom （UK; n = 567; 2006-2011） and Hong Kong （HK; n = 517; 2007-2012）. The baseline clinical data were recorded. The performances of the CUPI, BCLC, and CLIP were compared in terms of a concordance index （C-index） and were evaluated in subgroups of patients according to treatment intent. The results revealed that the median follow-up durations of the UK and HK cohorts were 27.9 and 29.8 months, respectively. The median overall survival of the UK and HK cohorts were 22.9 and 8.6 months, respectively. The CUPI stratified the patients in both cohorts into three risk subgroups corresponding to distinct outcomes. The median overall survival of the CUPI low-, intermediate-, and high-risk subgroups were 3.15, 1.24, and 0.29 years, respectively, in the UK cohort and were 2.07, 0.32, and 0.10 years, respectively, in the HK cohort. For the patients who underwent curative treatment, the prognostic performance did not differ between the three staging systems, and all were suboptimal. For those who underwent palliative treatment, the CUPI displayed the highest C-index, indicating that this staging system was the most informative for both cohorts. In conclusion, the CUPI is applicable to both western and eastern HCC patient populations. The performances of the three staging systems differed according to treatment intent, and the CUPI was demonstrated to be optimal for those     

Prognostic Nomogram for Advanced Hepatocellular Carcinoma Treated with FOLFOX 4

Background: The Oxaliplatin plus 5-Fluorouracil /Leucovorin (FOLFOX4) regimen have been approved by Chinese Food and Drug Administration (CFDA), and covered by health insurance for patients with advanced hepatocellular carcinoma (HCC) in China. However, the efficacy of FOLFOX4 for HCC patients is still under debate. In this study, we aimed to establish a nomogram to identify HCC patients who might benefit from FOLFOX4 chemotherapy base on individual profile. Methods: A total of 184 patients from the EACH study who were treated with FOLFOX4 were included in this analysis. Backward Cox proportional hazards regression combined with clinical experience was used to select variables for construction of the nomogram. The nomogram performance was assessed in terms of discrimination and calibration. The results were validated using bootstrap resampling. Results: Six variables were included in the prognostic models based on their clinical relevance: age, maximum tumor diameter, lymph node status, aspartate aminotransferase (AST), total bilirubin (TBIL) and alpha-fetoprotein (AFP). The calibration curve showed that the predicted survival probabilities closely matched the actual observations. The C-index of the model was 0.75 (95%CI: 0.71-0.80). This value was significantly superior to the one for the following staging systems: BCLC (0.67, P=0.004), CUPI (0.66, P<0.001), AJCC seventh edition (0.63, P=0.002), GRETCH (0.63, P<0.001). Conclusions: The proposed nomogram showed accurate prognostic prediction for 6-month overall survival of patients treated with FOLFOX4 and could be useful for clinicians counseling patients and making treatment decisions.     

Nomogram for Predicting the Overall Survival of Patients With Breast Cancer With Pathologic Nodal Status N3

BackgroundPatients with breast cancer with pathologic N3 (pN3) lymph node status have been proven to have a poor prognosis. This study aimed to establish a nomogram to predict overall survival (OS) in patients with pN3 breast cancer.Materials and MethodsThe eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database were randomly divided into training and validation cohorts. χ² tests and survival curves were performed to define the consistency between these 2 cohorts. Univariate and multivariate logistic regressions were carried out to identify the independent clinicopathologic factors of patients with pN3 breast cancer. A nomogram was developed and validated internally and externally by a calibration curve and compared with the seventh edition American Joint Committee on Cancer TNM staging classification in discrimination ability.ResultsRace, age at diagnosis, marital status, grade, T stage, N stage, breast cancer subtype, surgery, radiotherapy, and chemotherapy were independent predictive factors of OS in pN3 breast cancer. We developed a nomogram to predict 1-, 3-, and 5-year OS and further validated it in both cohorts, demonstrating better prediction capacity in OS than that of the seventh edition American Joint Committee on Cancer TNM staging classification (area under the curve in the receiver operating characteristic curve, 0.745 and 0.611 in the training cohort and 0.768 and 0.624 in the validation cohort, respectively).ConclusionWe have developed and validated the first nomogram for predicting the survival of pN3 breast cancer. This nomogram accurately and reliably predicted the OS of patients with pN3 breast cancer. However, more prognostic factors need to be further explored to improve the nomogram.     

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.     

Nomogram predicted disease free survival for colorectal liver metastasis patients with preoperative chemotherapy followed by hepatic resection

BackgroundHepatic resection is regarded to as a potentially curative option for colorectal cancer liver metastases (CRLM), but it is associated with a high rate of recurrence. The present study intended to establish an effective nomogram to predict disease free survival (DFS) and select candidates of hepatic resection.MethodsThe nomogram was based on a retrospective study on 447 CRLM patients treated with preoperative chemotherapy followed by hepatic resection using a multicentric database between January 1st, 2010 and December 31st, 2017. Results were validated using bootstrap resampling on 117 patients. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. Overall survival, disease free survival, and local recurrence rate for patients with colorectal cancer were measured.ResultsBased on multivariate analysis of the primary cohort, independent factors for DFS included tumor size larger than 5 cm, multiple liver metastases(>1), RAS mutation, primary lymph node metastasis and tumor size increase after preoperative chemotherapy. These five factors were all considered in the nomogram. The C-index of the nomogram for predicting survival was 0.675. With external validation, the C-index of the nomogram for the prediction of the DFS was 0.77, which demonstrated that this model has a good level of discriminative ability. For the 382 patients (66.7%) who developed recurrence, the optimal cutoff point for early recurrence was determined to be 12 months after hepatic resection.ConclusionsThe proposed nomogram demonstrated accurate prognostic prediction of DFS for CRLM patients with preoperative chemotherapy followed by hepatic resection.     

基于列线图构建和验证肝细胞癌伴门静脉癌栓患者肝切除术后的预后评估模型

目的 分析影响肝细胞癌伴门静脉癌栓（PVTT-HCC）患者肝切除术后预后的影响因素,并基于列线图模型构建和验证预后评估模型。方法 本研究为回顾性队列研究,选择2008年1月—2017年11月在本院行肝切除术的PVTT-HCC患者为研究对象,随访截至2021年1月。主要预测结局为1、3、5年总生存率。按照7∶3的比例将患者随机分为训练集和验证集,在训练集中采用Cox比例风险回归分析影响预后的影响,并基于影响因素构建列线图模型。同时在训练集和验证集中采用C-index评价模型的区分度,一致性曲线评估模型的校准度。结果 共231例患者符合纳入排除标准纳入分析,其中训练集162例,验证集69例。Cox比例风险回归模型显示,AFP≥400 μg/L、AST≥40 U/L、ALP≥80 U/L、肿瘤个数>1个及肿瘤包膜不完整是影响预后的危险因素。在训练集中,列线图模型预测1、3、5年总生存率的C-index分别为0.826（95%CI: 0.791~0.861）、0.818（95%CI：0.782~0.854）、0.781（95%CI：0.742~0.820）,在验证集中分别为0.814（95%CI：0.777~0.851）、0.798（95%CI：0.758~0.837）、0.769（95%CI：0.728~0.810）。校正曲线显示列线图模型在训练集和验证集均有较好的校准度。结论 本研究构建的列线图模型可准确预测PVTT-HCC患者的预后。     

前列腺穿刺对根治性前列腺切除术后标本ISUP升级预测列线图模型的建立及其应用

目的:构建一个从前列腺穿刺组织到根治性前列腺切除术（RP）后标本ISUP分级升高(ISUP grade upgrading,IGU)风险的预测列线图模型并进行内部验证。方法:对2019年05月至2020年05月我院泌尿外科收治的166例前列腺癌患者临床和病理学资料进行回顾性分析。采用单因素及多因素Logistic回归分析得到IGU的独立危险因素,后根据这些因素构建列线图预测模型。通过校准图进行模型校准,C-指数评估模型的预测能力,决策曲线分析用于检验临床效用,采用Bootstrap resampling对模型进行诊断效能内部验证。结果:该研究中ISUP升级组有47例（28.3%）患者,未升级组有119例（71.7%）患者。多因素logistic回归分析发现前列腺穿刺活检组织Gleason评分（P=0.001）、前列腺穿刺活检方法（P=0.03）和穿刺阳性针数（P=0.04）是IGU的独立危险因素。IGU列线图模型是基于上述独立因素而构建,模型的ROC曲线下面积为0.802,C-指数为0.798,校准图显示预测曲线与实际曲线有较好的相符度。列线图模型在内部验证中C-指数达到0.772。决策曲线分析表明,RP-ISUP升级风险的区间阈值为3%~67%。结论:该研究构建了一个准确性相对较高的列线图模型,有助于临床医生评估RP术后标本ISUP分级升高（特别是经直肠穿刺活检诊断的低风险前列腺癌）的风险。     

Clinicopathologic features,treatment, survival,and prognostic factors of combined hepatocellular and cholangiocarcinoma: A nomogram development based on SEER database and validation in multicenter study

PurposeThe aim of the study was to comprehensively understand the combined hepatocellular and cholangiocarcinoma (CHC) and develop a nomogram for prognostic prediction of CHC.MethodsData were collected from the Surveillance, Epidemiology and End Results (SEER) database (year 2004–2014). Propensity-score matching (PSM) was used to match the demographic characteristic of the CHC versus hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). A nomogram model was established to predict the prognosis in terms of cancer specific survival (CSS). The established nomogram was externally validated by a multicenter cohort.ResultsA total of 71,756 patients enrolled in our study including 62,877 HCC patients, 566 CHC patients, and 8303 ICC patients. The CHC, HCC, and ICC are not exactly similar in clinical characteristic. After PSM, the CSS of CHC was better than HCC but comparable to ICC. Tumor size, M stage, surgery, chemotherapy, and surgery were independently prognostic factors of CHC and were included in the establishment of novel nomogram.The c-index of the novel nomogram in SEER training set and multicenter validation was 0.779 and 0.780, respectively, which indicated that the model was with better discrimination power. In addition, decision curve analyses proved the favorable potential clinical effect of the predictive model. Lastly, a risk classification based on nomogram also verified the reliability of the model.ConclusionCHC had better survival than HCC but was comparable to ICC. The nomogram was established based on tumor size, M stage, chemotherapy, surgery, and radiotherapy and well validated by external multicenter cohort.     

基于SEER数据库构建1~2枚淋巴结阳性且乳房全切的老年早期乳腺癌患者不同腋窝手术方式的生存预测模型

背景与目的：指南推荐1~2枚前哨淋巴结阳性的保乳并计划行全乳放疗的T1-2期乳腺癌患者可以豁免腋窝淋巴结清扫。探讨1~2枚淋巴结阳性且乳房全切的老年早期乳腺癌患者的预后危险因素,并构建不同腋窝处理手术方式下的生存预测模型。方法：从SEER数据库收集2010—2015年期间65岁及以上、T 1-2 期、1~2枚淋巴结阳性且乳房全切的乳腺癌患者并随机分为验证集和训练集。对训练集进行单因素及多因素COX比例风险回归分析筛选出影响总生存的独立预后因素,利用R软件构建预测患者3年和5年总生存率的列线图,利用一致性指数（C指数）和校正曲线对预测模型进行内部（训练集）和外部（验证集）验证。结果：共纳入4 863例患者,中位随访42个月,训练集（3 647例）和验证集（1 216例）的基线分布符合简单随机分组。将多因素COX回归分析筛选出的年龄、种族、婚姻状态、组织学分级、分子分型、T分期、腋窝手术方式、是否放化疗共9个总生存的独立风险因素（P<0.05）用于构建列线图预测模型。训练集（即内部验证）和验证集（即外部验证）的C指数分别为0.710（95% CI：0.689~0.731）和0.728（95 % CI：0.691~0.765）,两组的校正曲线均靠近45°参考线,表明列线图具有良好的预测能力。结论：本研究构建的列线图预测模型具有良好的预测价值,有利于指导临床对患者进行个体化治疗。