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.     

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.     

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...     

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.     

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.     

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...     

Survival after resection of perihilar cholangiocarcinoma—development and external validation of a prognostic nomogram

BackgroundThe objective of this study was to derive and validate a prognostic nomogram to predict disease-specific survival (DSS) after a curative intent resection of perihilar cholangiocarcinoma (PHC).Patients and methodsA nomogram was developed from 173 patients treated at Memorial Sloan Kettering Cancer Center (MSKCC), New York, USA. The nomogram was externally validated in 133 patients treated at the Academic Medical Center (AMC), Amsterdam, The Netherlands. Prognostic accuracy was assessed with concordance estimates and calibration, and compared with the American Joint Committee on Cancer (AJCC) staging system. The nomogram will be available as web-based calculator at mskcc.org/nomograms.ResultsFor all 306 patients, the median overall survival (OS) was 40 months and the median DSS 41 months. Median follow-up for patients alive at last follow-up was 48 months. Lymph node involvement, resection margin status, and tumor differentiation were independent prognostic factors in the derivation cohort (MSKCC). A nomogram with these prognostic factors had a concordance index of 0.73 compared with 0.66 for the AJCC staging system. In the validation cohort (AMC), the concordance index was 0.72, compared with 0.60 for the AJCC staging system. Calibration was good in the derivation cohort; in the validation cohort patients had a better median DSS than predicted by the model.ConclusionsThe proposed nomogram to predict DSS after curative intent resection of PHC had a better prognostic accuracy than the AJCC staging system. Calibration was suboptimal because DSS differed between the two institutions. The nomogram can inform patients and physicians, guide shared decision making for adjuvant therapy, and stratify patients in future randomized, controlled trials.     

Validation and modification of the AJCC 8th TNM staging system for pancreatic ductal adenocarcinoma in a Chinese cohort: A nationwide pancreas data center analysis

ObjectiveTo validate the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for pancreatic ductal adenocarcinoma (PDAC) in a Chinese cohort of radically resected patients and to develop a refined staging system for PDAC.MethodsData were collected from the China Pancreas Data Center (CPDC) for patients with resected PDAC in 2016 and 2017, and cancer-specific survival (CSS) was evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate analyses based on Cox regression were performed to identify prognostic factors. The recursive partitioning analysis (RPA), Kaplan-Meier method, and log-rank test were performed on the training dataset to generate a proposed modification for the 8th TNM staging system utilizing the preoperative carbohydrate antigen (CA)19-9 level. Validation was performed for both staging systems in the validation cohort.ResultsA total of 1,676 PDAC patients were retrieved, and the median CSS was significantly different between the 8th TNM groupings, with no significant difference in survival between stage IB and IIA. The analysis of T and N stages demonstrated a better prognostic value in the N category. Multivariate analysis showed that the preoperative serum CA19-9 level was the strongest prognostic indicator among all the independent risk factors. All patients with CA19-9 >500 U/mL had similar survival, and we proposed a new staging system by combining IB and IIA and stratifying all patients with high CA19-9 into stage III. The modified staging system had a better performance for predicting CSS than the 8th AJCC staging scheme.ConclusionsThe 8th AJCC staging system for PDAC is suitable for a Chinese cohort of resected patients, and the N category has a better prognostic value than the T category. Our modified staging system has superior accuracy in predicting survival than the 8th AJCC TNM staging system.     

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.     

A new prognostic model predicting hepatocellular carcinoma early recurrence in patients with microvascular invasion who received postoperative adjuvant transcatheter arterial chemoembolization

BackgroudIn this study, we aimed to develop a prognostic model to predict HCC early recurrence (within 1-year) in patients with microvascular invasion who received postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE).MethodsA total of 148 HCC patients with MVI who received PA-TACE were included in this study. The modes were verified in an internal validation cohort (n = 112) and an external cohort (n = 36). Univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors relevant to early recurrence. A clinical nomogram prognostic model was established, and nomogram performance was assessed via internal validation and calibration curve statistics.ResultsAfter data dimensionality reduction and element selection, multivariate Cox regression analysis indicated that alpha fetoprotein level, systemic inflammation response index, alanine aminotransferase, tumour diameter and portal vein tumour thrombus were independent prognostic factors of HCC early recurrence in patients with MVI who underwent PA-TACE. Nomogram with independent factors was established and achieved a better concordance index of 0.765 (95% CI: 0.691–0.839) and 0.740 (95% CI: 0.583–0.898) for predicting early recurrence in training cohort and validation cohort, respectively. Time-dependent AUC indicated comparative stability and adequate discriminative ability of the model. The DCA revealed that the nomogram could augment net benefits and exhibited a wider range of threshold probabilities than AJCC T stage.ConclusionsThe nomogram prognostic model showed adequate discriminative ability and high predictive accuracy.     

Preoperative serum fibrinogen as a valuable predictor in the nomogram predicting overall survival of postoperative patients with gallbladder cancer

BackgroundCoagulation and fibrinolysis activation are frequently observed in cancer patients, and the tumors in these cases are thought to be associated with a higher risk of invasion, metastasis and worse long-term outcome. The specific aim of this study was to develop an effective prognostic nomogram to help make individualized estimates for patients with resected gallbladder cancer (GBC).MethodsPatients with resected GBC who were diagnosed between 2006 and 2014 at Xinhua Hospital were selected. Model performance was measured by c-index and calibration curve. The results were further validated using bootstrap and a cohort of 38 patients from a branch hospital who underwent surgery from 2006 to 2014.ResultsBackward stepwise selection and Lasso were applied respectively to select predictors. T stage, N stage, and preoperative serum fibrinogen were included in the final model. Predictions correlated well with observed 1- and 3-year survival. The c-index for predicting survival was 0.74 (95% confidence interval, 0.70–0.78), which was statistically higher than that of the AJCC 7th system and Nevin system (P=0.04, 0.04, respectively). In the validation cohort, the nomogram performed better than the other two staging systems (c-index: 0.71 vs. 0.67 and 0.67).ConclusionsThe validated nomogram is a practical tool for predicting the overall survival (OS) of postoperative GBC patients. Preoperative serum fibrinogen levels were associated with tumor progression and may be an independent predictor for GBC patients.     

Prognostic stratification based on a novel nomogram for left-sided pancreatic adenocarcinoma after surgical resection: a multi-center study

Left-sided pancreatic adenocarcinoma (LPAC) has a poorer prognosis and has some distinct features compared to cancer of pancreatic head. A reliable model to predict the prognosis of LPAC following surgery is needed in clinical practice. Our study included 231 patients with resected LPAC from 3 Chinese pancreatic disease centers. Cox-regression analysis was conducted to identify independent risk factors of LAPC. Then we established a nomogram and performed C-index, receiver operating characteristic curve, calibration plot and decision curve analysis to assess its discrimination and calibration. As a result, CA19-9, surgical margin, tumor differentiation, lymph node metastasis, and postoperative adjuvant chemotherapy were identified as significant prognostic factors. Based on these predictors, a novel nomogram was constructed. The nomogram achieved high C-indexes in the training cohort (0.805) and validation cohort (0.719), which were superior than the AJCC-8 staging system and other nomograms. The area under curve of the nomogram for predicting patients survival at 1-, 2-, and 3-year in training cohort were more than 0.8. Kaplan-Meier survival curve for the subgroups stratified based on the nomogram showed a better separation than the AJCC-8 stage I, II, III, indicating a superior ability of risk stratification for our model. In summary, we constructed a nomogram which showed a better predictive ability for patients’ survival with LPAC after surgical resection than the AJCC staging system and other predictive models. Our model would be helpful to discriminate high-risk LPAC and facilitate clinical decision making.     

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 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.     

Comparison of 4 lymph node staging systems for the prognostic prediction of esophagogastric junction adenocarcinoma with ≤15 retrieved lymph nodes

BackgroundDirectly applying the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) staging system to evaluate the prognosis of patients with esophagogastric junction adenocarcinoma (AEG) might lead to under-staging, when insufficient lymph nodes were retrieved during surgery. The prognostic value of 4 lymph nodes staging systems, 8th AJCC TNM N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and negative lymph nodes (NLN), in AEG patients having ≤15 retrieved lymph nodes were compared.Methods869 AEG patients diagnosed between 2004 and 2012 with ≤15 retrieved lymph nodes were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were conducted to assess the association of cancer-specific survival (CSS) and overall survival (OS) with 8th AJCC TNM N stage, LNR, LODDS, and NLN respectively. Predictive survival ability was assessed and compared using linear trend χ2 score, likelihood ratio (LR) test, Akaike information criterion (AIC), Harrell concordance index (C-index), and Receiver Operative Curve (ROC).ResultsThe N stage, LNR, LODDS, and NLN were all independent prognostic predictors for CSS and OS in multivariate Cox models. Comparatively, LODDS demonstrated higher linear trend χ2 score, LR test score, C-index and integrated area under the curve (iAUC) value, and lower AIC in CSS compared to the other three systems. Moreover, for patients without regional lymph node metastasis, NLN showed higher C-index and lower AIC.ConclusionsLODDS showed better predictive performance than N, LNR, and NLN among patients with node-positive patients while NLN performed better in node-negative patients. A combination of LODDS and NLN has the potential to provide more prognostic information than the current AJCC TNM classification.     

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.     

A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer

BackgroundAccurate assessment of lymph node status in gastric cancer (GC) patients can help to select appropriate treatment strategies for GC, but the diagnostic accuracy of conventional methods needs to be improved. The aim of this study was to investigate the predictive value of preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) on lymph node status in GC patients and to construct a risk prediction model.MethodsThis study retrospectively analyzed the clinicopathological characteristics of 349 patients with GC who underwent radical gastrectomy, among which 250 patients were recruited in the training cohort and 99 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified as independent variables in multivariate logistic regression analysis, which were then incorporated and presented in a nomogram. Receiver operating characteristic (ROC) curves, Calibration curve and decision curve analysis (DCA) curves were used to evaluate the discrimination, prediction accuracy and clinical effectiveness of the modelResultsMultifactorial logistic regression analysis showed that alcohol use (OR =2.203, P=0.036), Depth of invasion (OR =7.756, P<0.001), differentiation (OR =2.252, P=0.018), carcinoembryonic antigen (CEA) (OR =2.443, P=0.017), carbohydrate antigen 19-9 (CA199) (OR =2.715, P=0.008) and HALP (OR =2.276, P=0.032) were independent risk factors for lymph node metastasis (LNM) in GC. We used these factors to construct a nomogram for predicting LNM in GC patients, and the ROC curves showed good discrimination of the model with AUC values of 0.854 (training cohort) and 0.868 (validation cohort), respectively, and the calibration curves showed good predictive ability of the nomogram, in addition to the DCA curves results showed the clinical usefulness of the model.ConclusionsIn conclusion, we established a nomogram for predicting LNM in patients with GC.     

Development and External Validation of a Clinical Nomogram for Individually Predicting Survival of Metaplastic Breast Cancer

BackgroundFew studies have concerned the prognosis of metaplastic breast cancer (MpBC), a rare and diverse malignancy. A prognostic index estimating the MpBC survival would be attractive in clinical practice.Patients and MethodsWe retrospectively analyzed MpBC patients from the Surveillance, Epidemiology, and End Results (SEER) database. Prognostic factors were identified and the final nomogram was developed to predict the 1-, 3-, or 5-year overall survival (OS). Calibration curves were provided to internally validate the performance of the nomogram and discriminative ability was appraised by concordance index (C-index).ResultsA total of 1017 MpBC patients diagnosed between 2010 and 2015 were assigned into 3:1 as training set (n = 763) and SEER validation set (n = 254). An external validation was performed by an individual set of 94 MpBC patients from National Cancer Center in China from 2010 to 2018. The nomogram finally consisted of 7 independent prognostic factors and presented a good accuracy for predicting the OS with the C-index of 0.77 (95% CI: 0.751-0.786). Interestingly, the nomogram based on the western (including 92.5% non-Asian) SEER validation population (C-index of nomogram: 0.76, 95% CI: 0.737-0.796) also has an optimal discrimination in Asian population (C-index of nomogram: 0.70). The calibration plots of the nomogram predictions were also accurate and corresponded closely with the actual survival rates.ConclusionThis novel nomogram was accurate enough to predict the OS by using readily available clinicopathologic factors in MpBC general population, which could provide individualized recommendations for patients and clinical decisions for physicians.     

The effect of the American Joint Committee on Cancer eighth edition on breast cancer staging and prognostication

IntroductionBreast cancer staging has been developed to quantify prognosis and guide treatment. The American Joint Committee on Cancer eighth edition manual (AJCC8) departed from traditional anatomic staging by incorporating biological factors such as grade, hormone and HER2 receptor status into a novel prognostic staging model. The aim of this study was to externally validate AJCC8 prognostic staging.MethodsThis retrospective cohort investigated patients diagnosed between 2010 and 2013 at the McGill University Health Center. Patients were classified using both anatomic and prognostic staging systems according AJCC8. Overall survival analysis using a multivariate Cox-proportional hazard model was performed and model accuracy was evaluated using the Harrell concordance index (C-index) and Akaike Information Criterion (AIC).ResultsThe cohort included 1703 women. Anatomic and prognostic stage assignments displayed discrepancies for 46.2% of patients, where 38.8% were downstaged and 7.5% were upstaged with prognostic staging. Patients with anatomic stages IB, IIA, IIB, IIIA and IIIC had high rates of downstaging (64.6–96.5%), as opposed to anatomic stages IA and IIIB where 93.1% and 75.0% of patients stage remained unchanged, respectively. The prognostic stage displayed increased prognostic accuracy with respect to overall survival, where the C-index was significantly higher compared to anatomic staging (0.810 vs 0.799, p < 0.05). In addition, prognostic staging displayed an improved model fit with a lower AIC (983.9) compared to anatomic staging (995.2).ConclusionPrognostic and anatomic staging differ in their classification of patients, where prognostic staging displays improved accuracy, supporting its use in informing patient prognosis and guiding treatment decisions.     

Prognostic significance of systemic immune-inflammation index-based nomogram for early stage hepatocellular carcinoma after radiofrequency ablation

BackgroundRadiofrequency ablation (RFA) is the recommended treatment for early stage hepatocellular carcinoma (HCC), and the prognostic value of systemic immune-inflammation index (SII) in early stage HCC is not discussed. Therefore, the purpose of the study is to explore the prognostic value of SII based on lymphocyte, neutrophil, and platelet counts in patients with HCC after RFA.MethodsWe retrospectively evaluated the prognostic value of the SII in training and validation cohorts, and then established an effective nomogram for HCC after RFA based on SII. The C-index, and area under the time-dependent receiver operating characteristic curve (t-AUC) were used to evaluate the discrimination and calibration value of the nomogram.ResultsAn optimal cut-off value for the SII of 324.55×10⁹ stratified the patients with HCC into high- and low-SII groups. Univariate and multivariate analyses revealed that SII was an independent predictor for overall survival (OS) and recurrence-free survival (RFS). Moreover, SII was an independent prognostic factor for early-stage HCC with normal alpha-fetoprotein (AFP) levels. The t-AUC of the SII was higher for OS and RFS than for neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR). A high preoperative SII was associated with multiple tumors, larger tumors, and higher levels of AFP. A well-discriminated and calibrated nomogram was constructed to predict the probability of 1-, 2-, 3-, and 5-year RFS with C-indexes of 0.80, which was significantly higher than that obtained with other prognostic clinical indexes.ConclusionsThe SII is an independent prognostic factor affecting the survival outcomes of patients with early-stage HCC. The comprehensive nomogram based on SII presented in this study is a promising model for predicting RFS in HCC patients after RFA.