Association of type 2 diabetes mellitus with incidences of microvascular invasion and survival outcomes in hepatitis B virus-related hepatocellular carcinoma after liver resection: A multicenter study

BackgroundMicrovascular invasion (MVI) adversely affects long-term survival in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). This study aimed to examine the association between preoperative type 2 diabetes mellitus (T2DM) with incidences of MVI and prognosis in HBV-related HCC after liver resection (LR).Material and methodsData of HBV-related HCC patients who underwent LR as an initial therapy from four hospitals in China were retrospectively collected. Clinicopathological factors associated with the incidence of MVI were identified using univariate and multivariate logistic regression analysis. The recurrence-free survival (RFS) and overall survival (OS) curves between different cohorts of patients were generated using the Kaplan-Meier method and compared using the log-rank test.ResultsOf 1473 patients who were included, 219 (14.9%) patients had T2DM. Preoperative T2DM, HBV DNA load, antiviral treatment, AFP level, varices, and tumor encapsulation were identified to be independent predictors of the incidence of MVI. Patients with HBV-related HCC and T2DM had a higher incidence of MVI (65.8%) than those without T2DM (55.4%) (P = 0.004). The RFS and OS were significantly worse in patients with T2DM than those without T2DM (median RFS: 11.1 vs 16.7 months; OS: 26.4 vs 42.6 months, both P < 0.001). Equivalent results were obtained in HCC patients with MVI who had or did not have T2DM (median RFS: 10.0 vs 15.9 months; OS: 24.5 vs 37.9 months, both P < 0.001).ConclusionsPreoperative T2DM was an independent risk factor of incidence of MVI. Patients with HBV-related HCC and T2DM had worse prognosis than those without T2DM after LR.     

Prognostic value and association of sarcopenic obesity and systemic inflammatory indexes in patients with hepatocellular carcinoma following hepatectomy and the establishment of novel predictive nomograms

BackgroundThe specific impacts of sarcopenic obesity (SO) on hepatocellular carcinoma (HCC) and the association between SO and systemic inflammation remain unclear. This study aimed to investigate the prognostic value and association of SO and systemic inflammation with outcomes after hepatectomy for HCC and develop novel nomograms based on SO and inflammatory indexes for survival prediction.MethodsWe retrospectively enrolled 452 patients with HCC who underwent radical hepatectomy between January 2012 and March 2015 in Fujian Provincial Hospital as the training cohort. In addition, 275 patients during the same period were enrolled as the external validation cohort. Patients were classified into different groups according to the presence of sarcopenia and obesity. Different inflammation indexes were evaluated to select the best predictor of overall survival (OS) and recurrence-free survival (RFS). Univariate and multivariate logistic regression were performed to investigate the associations between inflammatory indexes and SO. The inflammatory indexes with the highest predictive values and SO were selected for subgroup analyses to establish a novel classification system: the SOLMR grade. SOLMR grades identified in the multivariate Cox analysis were selected to construct novel nomograms for OS and RFS.ResultsSO (P<0.001) was an independent risk factor for OS and RFS. The lymphocyte‐monocyte ratio (LMR) had the highest areas under the receiver operating characteristic (ROC) curves (AUCs) for OS (P<0.001) and RFS (P<0.001) and was identified as an independent factor of SO (P=0.001). SO and the LMR were selected to establish the SOLMR grade. Multivariate Cox analysis revealed that SOLMR grade was a significant independent predictor of OS (P<0.001) and RFS (P<0.001). Nomograms based on SOLMR grades were generated and accurately predicted 1-, 3- and 5-year OS and RFS in HCC patients. The C-index of the novel nomograms was higher than those of the other conventional staging systems (P<0.001).ConclusionsBoth SO and the LMR were independent risk factors for OS and RFS in HCC patients after hepatectomy. The LMR was an independent factor of SO. The novel nomograms developed from the SOLMR grading system combining SO with the LMR provide good prognostic estimates of the outcomes of HCC patients.     

A novel classification in predicting prognosis and guiding postoperative management after R0 liver resection for patients with hepatocellular carcinoma and microvascular invasion

BackgroundMicrovascular invasion (MVI) is a significant risk factor affecting survival outcomes of patients after R0 liver resection (LR) for hepatocellular carcinoma (HCC). The current classification of MVI is not refined enough to prognosticate long-term survival of these patients, and a new MVI classification is needed.MethodsPatients with HCC who underwent R0 LR at the Eastern Hepatobiliary Surgery Hospital from January 2013 to December 2013 and with resected specimens showing MVI were included in this study with an aim to establish a novel MVI classification. The classification which was developed using multivariate cox regression analysis was externally validated.ResultsThere were 180 patients in the derivation cohort and 131 patients in the external validation cohort. The following factors were used for scoring: α-fetoprotein level (AFP), liver cirrhosis, tumor number, tumor diameter, MVI number, and distance between MVI and HCC. Three classes of patients could be distinguished by using the total score: class A, ≤3 points; class B, 3.5–5 points and class C, >5 points with distinct long-term survival outcomes (median recurrence free survival (mRFS), 22.6, 10.2, and 1.9 months, P < 0.001). The predictive accuracy of this classification was more accurate than the other commonly used classifications for HCC patients with MVI. In addition, the mRFS of class C patients was significantly prolonged (1.9 months vs. 6.2 months, P < 0.001) after adjuvant transcatheter arterial chemoembolization (TACE).ConclusionsA novel MVI classification was established in predicting prognosis of HCC patients with MVI after R0 LR. Adjuvant TACE was useful for class C patients.     

Nomogram for the prediction of lymph node metastasis and survival outcomes in rectal neuroendocrine tumour patients undergoing resection

BackgroundThe current study analysed rectal neuroendocrine tumour (RNET) patients undergoing resection to identify predictive factors and construct nomograms for lymph node metastasis, cancer-specific survival (CSS) and overall survival (OS).MethodsRNET patients registered in the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. Multivariable logistic regression analysis was used to investigate the relationships between clinicopathological factors and lymph node metastasis. A multivariate competing risk model was applied to investigate factors independently associated with CSS. Through the Cox regression model, a multivariable analysis of OS was performed. Nomograms were established based on independent predictive factors. Calibration plots, receiver operating characteristic (ROC) curves and Brier scores were used to evaluate the predictive accuracy of the nomograms.ResultsIn this study, 1,253 RNET patients were included for further analysis. Tumour size ≥12 mm (P<0.001), T3/T4 stage (P<0.001) and M1 stage (P=0.001) were independently associated with lymph node metastasis. The performance of the nomogram was acceptable for predicting lymph node metastasis, with an area under the ROC curve (AUC) of 0.937 [95% confidence interval (CI): 0.874–1.000]. Calibration curves and the Hosmer-Lemeshow test revealed desirable model calibration (P=0.99996). The multivariate competing risk model analysis showed that grade II (P=0.017), tumour size ≥12 mm (P=0.007), AJCC TNM stage II (P=0.002), stage III (P<0.001) and stage IV (P<0.001) were significantly associated with worse CSS. In the competing risk nomogram model, the time-dependent AUC revealed good discriminatory ability of the model (time from 1 to 107 months, AUC >0.900), and the Brier score showed good accuracy of the nomogram, which was greater than that of the AJCC TNM stage. Multivariate Cox analysis showed that age >60 years (P=0.002), median income ≥$65,000 (P=0.013), AJCC TNM stage III (P=0.038) and AJCC TNM stage IV (P<0.001) were independently associated with worse OS. In the nomogram for the prediction of OS, the C-statistic was 0.703 (95% CI: 0.615–0.792), which was significantly better than that of the AJCC TNM stage (0.703 vs. 0.607, P=0.009). A calibration plot for the probability of survival demonstrated good calibration.ConclusionsThe present study is the first to establish nomograms with great discrimination and accuracy for the prediction of lymph node metastases, CSS and OS in RNET patients, which can be used to guide treatment decision-making and surveillance.     

Adjuvant transarterial chemoembolization improves survival outcomes in hepatocellular carcinoma with microvascular invasion: A systematic review and meta-analysis

BackgroundThe benefits of adjuvant transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) remain controversial. We compared the efficacy and safety of adjuvant TACE and hepatic resection (HR) alone for HCC patients with MVI.MethodsThe PubMed, EMBASE, Cochrane Library, VIP, Wan Fang, and Sino Med databases were systematically searched to compare adjuvant TACE and HR alone for the treatment of HCC with MVI from inception to January 1, 2019. The study outcomes, including overall survival (OS) and disease-free survival (DFS), were extracted independently by two authors.Results12 trials involving 2190 patients were evaluated. A meta-analysis of 11 studies suggested that the 1-, 3-, and 5-year overall survival (OS) rates (OR = 0.33, P < 0.001; OR = 0.49, P < 0.001; and OR = 0.59, P < 0.01; respectively), favored adjuvant TACE over HR alone. 11 studies were included in the meta-analysis of DFS, and adjuvant TACE showed better 1-, 3-, and 5-DFS (OR = 0.45, P < 0.001; OR = 0.50, P < 0.001; and OR = 0.58, P < 0.001; respectively) compared to HR alone. Subgroup analysis demonstrated that adjuvant TACE could benefit HCC patients with MVI with tumor diameter >5 cm or multinodular tumors.ConclusionAdjuvant TACE may improve OS and DFS for HCC patients with MVI compared to HR alone and should be recommended for selected HCC patients with MVI. However, these results need to be validated through further high-quality clinical studies.Lay summaryThe benefits of adjuvant TACE in HCC patients with microvascular invasion remain controversial. Twelve studies involving 2190 patients were include in our meta-analysis. Adjuvant TACE may improve OS and DFS for HCC patients with MVI compared to HR alone and should be recommended for selected HCC patients with MVI.     

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.     

Nomograms for survival prediction in patients undergoing liver resection for hepatitis B virus related early stage hepatocellular carcinoma

BackgroundThe long-term outcomes of patients who underwent liver resection (LR) for early-stage hepatitis B virus (HBV)-related hepatocellular carcinomas (HCCs) are difficult to predict. This study aimed to develop two nomograms to predict postoperative disease-free survival (DFS) and overall survival (OS), respectively.MethodsData on a primary cohort of 1328 patients who underwent LR for HBV-related HCCs within Milan criteria at the Eastern Hepatobiliary Surgery Hospital (EHBH) from 2000 to 2006 were used to develop the nomograms by the Cox regression analyses. An internal validation cohort of 442 patients operated from 2006 to 2011 at the EHBH and an external validation cohort of 474 patients operated from 2007 to 2009 at the Zhongshan Hospital were used for validation studies. Discrimination and calibration were measured using concordance index (C-index), calibration plots and Kaplan–Meier curves.ResultsThe independent predictors of DFS or OS which included tumour stage factors, biomarker and HBV–DNA level were respectively incorporated into the two nomograms. In the primary cohort, the C-indexes of the models in predicting DFS and OS were 0.76 (95% confidence interval: 0.75–0.78) and 0.79 (0.77–0.81), respectively. The calibration curves fitted well. Both nomograms accurately stratify patients into four distinct incremental prognostic subgroups. The C-indexes of the nomogram for OS prediction was significantly higher than those of the six conventional staging systems (0.65–0.71, all P < 0.001). These results were verified by the internal and external validations.ConclusionThe proposed nomograms showed good prognostication for patients with early HBV-related HCCs after hepatectomy.     

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.     

External validation of three lymph node ratio-based nomograms predicting survival using an international cohort of patients with resected pancreatic head ductal adenocarcinoma

IntroductionLymph node ratio (LNR) is an important prognostic factor of survival in patients with pancreatic ductal adenocarcinoma (PDAC). This study aimed to validate three LNR-based nomograms using an international cohort.Materials and methodsConsecutive PDAC patients who underwent upfront pancreatoduodenectomy from six centers (Europe/USA) were collected (2000–2017). Patients with metastases, R2 resection, missing LNR data, and who died within 90 postoperative days were excluded. The updated Amsterdam nomogram, the nomogram by Pu et al., and the nomogram by Li et al. were selected. For the validation, calibration, discrimination capacity, and clinical utility were assessed.ResultsAfter exclusion of 176 patients, 1′113 patients were included. Median overall survival (OS) of the cohort was 23 months (95% CI: 21–25).For the three nomograms, Kaplan-Meier curves showed significant OS diminution with increasing scores (p < 0.01). All nomograms showed good calibration (non-significant Hosmer-Lemeshow tests). For the Amsterdam nomogram, area under the ROC curve (AUROC) for 3-year OS was 0.64 and 0.67 for 5-year OS. Sensitivity and specificity for 3-year OS prediction were 65% and 59%. Regarding the nomogram by Pu et al., AUROC for 3- and 5-year OS were 0.66 and 0.70. Sensitivity and specificity for 3-year OS prediction were 68% and 53%. For the Li nomogram, AUROC for 3- and 5-year OS were 0.67 and 0.71, while sensitivity and specificity for 3-year OS prediction were 63% and 60%.ConclusionThe three nomograms were validated using an international cohort. Those nomograms can be used in clinical practice to evaluate survival after pancreatoduodenectomy for PDAC.     

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.     

Hepatectomy for ruptured hepatocellular carcinoma classified as Barcelona Clinic Liver Cancer stage 0/A: The optimal treatment

Background and aimsRuptured hepatocellular carcinoma (rHCC) generally has a very poor prognosis and is currently classified as T4 in the tumor–node–metastasis (TNM) staging system. In this study, we aimed to demonstrate the actual impact of rHCC, as well as the positive effect of hepatectomy in patients with Barcelona Clinic Liver Cancer (BCLC) stage 0/A rHCC.MethodsWe enrolled 86 patients with rHCC after surgery and 526 patients with non-rHCC after surgery or transcatheter arterial chemoembolization (TACE). Survival curves were plotted using the Kaplan–Meier method to compare the postoperative prognosis of patients with rHCC with that of patients with non-rHCC. Univariate and multivariate Cox regression analyses were used to identify the risk factors affecting patient survival.ResultsBCLC stage 0/A rHCC treated with surgery had a worse prognosis than BCLC stage 0/A non-rHCC treated with surgery (overall survival [OS]: hazard ratio [HR] = 3.12 [2.24–4.34], P < 0.001; recurrence-free survival [RFS]: HR = 2.26 [1.65–3.09], P < 0.001). Rupture was an independent prognostic factor in patients with BCLC stage 0/A rHCC (OS: HR = 1.685 [1.416–2.006], P < 0.001; RFS: HR = 1.484 [1.267–1.737], P < 0.001), and patients with BCLC stage 0/A rHCC who underwent surgery had a comparable prognosis to patients with BCLC stage B HCC who underwent surgery or TACE (OS: P = 0.78).ConclusionsPatients classified as having BCLC stage 0/A rHCC can achieve comparable outcomes to patients with BCLC stage B HCC after hepatectomy. However, not all patients with rHCC should be classified as T4 in the TNM staging system.     

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.     

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.     

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.     

Optimal treatment strategy and prognostic analysis for hypopharyngeal squamous-cell carcinoma patients with T3-T4 or node-positive: A population-based study

PurposeTo explore the optimal treatment strategy and relevant prognostic analysis for hypopharyngeal squamous-cell carcinoma patients (HSCC) with T3-T4 or node-positive.Methods and materialsFrom 2004 to 2018, data for 2574 patients from the Surveillance, Epidemiology, and End Results database (SEER) and 66 patients treated at our center from 2013 to 2022 with T3-T4 or N + HSCC were collected. Patients in the SEER cohort were randomly assigned to the training set or validation set at a 7:3 ratio. Variables with statistically significant (P < 0.05) in univariate COX regression analysis or clinical significance were included in the multivariate COX regression model and subsequently used to construct the nomogram.ResultsThe 3-year OS (52.9%vs44.4%, P < 0.01) and 3-year CSS rate (58.7%vs51.5%, P < 0.01) rates in the surgery combined with postoperative adjuvant therapy (S + ADT) group were superior to the radiotherapy combined with chemotherapy (CRT) group. The multivariate Cox regression analysis of the training group showed that age, race, marital status, primary site, T stage, N stage, and treatment modalities were correlated with OS and CSS. Based on those variables, we constructed nomograms for OS and CSS. Both the internal and external validation showed high prediction accuracy of the nomogram.ConclusionAmong patients with T3-T4 or node-positive, S + ADT was associated with superior OS and CSS compared to those treated with primary CRT, while the survival rate in the CRT group was comparable to S + ADT group in T2-T3 disease. The internal and external verification shows that the prognostic model has good discrimination ability and accuracy.     

Individual prediction of lateral neck metastasis risk in patients with unifocal papillary thyroid carcinoma

IntroductionMuch controversy exists over whether to perform lateral neck dissection (LND) on patients with papillary thyroid carcinoma (PTC). This study aimed to build predictive nomograms that could individually estimate lateral neck metastasis (LNM) risk and help determine follow up intensity.Patients and methodsUnifocal PTC patients who underwent LND between April 2012 and August 2014 were identified. Clinical and pathological variables were retrospectively evaluated using univariate and stepwise multivariate logistic regression analysis. Variables that had statistical significance in final multivariate logistic models were chosen to build nomograms, which were further corrected using the bootstrap resampling method.ResultsIn all, 505 PTC patients were eligible for analysis. Among these, 178 patients (35.2%) had lateral neck metastasis. Two nomograms were generated: nomogram (c) and nomogram (c + p). Nomogram (c) incorporated four clinical variables: age, tumor size, tumor site, and extrathyroidal extension (ETE). It had a good discriminative ability, with a C-index of 0.79 (bootstrap-corrected, 0.78). Nomogram (c + p) incorporated two clinical variables and two pathological variables: tumor size, tumor site, extranodal extension (ENE), and number of positive nodes in the central compartment. Nomogram (c + p) showed an excellent discriminative ability, with a C-index of 0.86 (bootstrap-corrected, 0.85).ConclusionTwo predictive nomograms were generated. Nomogram (c) is a clinical model, whereas nomogram (c + p) is a clinicopathological model. Each nomogram incorporates only four variables and can give an accurate estimate of LNM risk in unifocal PTC patients, which may assist clinicians in patient counseling and decision making regarding LND.     

Comprehensive lymphadenectomy and survival prediction in uterine serous cancer patients after surgery: A population-based analysis

ObjectiveEvidence on uterine serous cancer (USC) prognosis has been limited and inconclusive. We aim to explore the survival benefits of comprehensive lymphadenectomy in USC patients after surgery and develop a prognostic nomogram to predict survival.MethodsUSC patients who had undergone hysterectomy between 2010 and 2015 were identified from Surveillance, Epidemiology and End Results (SEER) database. The relationship between the extent of lymphadenectomy and survival, including overall survival (OS) and cancer-specific survival (CSS), was estimated with Kaplan-Meier (K-M) analysis. Univariate and multivariate Cox regression analyses were utilized to determine the independent prognostic factors. A nomogram was then developed, calibrated and internally validated.ResultsA total of 2853 patients were identified. K-M survival analysis revealed that patients with ≥12 pelvic lymph nodes (PLNs) removed had significantly better OS and CSS than those without (both P < 0.001). However, patients with ≥6 para-aortic lymph nodes removed was not associated with similar survival benefits than patients without (P > 0.1). Multivariate analyses for OS and CSS revealed that age, T-stage, N-stage, tumor size, adjuvant therapy and ≥12 PLNs removed were independent prognostic factors (all P < 0.05) and were subsequently incorporated into the nomogram. The Harrell's C-index of the nomogram was significantly higher than that of the FIGO staging system (OS: 0.739 vs 0.671, P < 0.001; CSS: 0.752 vs 0.695, P < 0.001). Furthermore, the nomogram was well calibrated with satisfactory consistency.ConclusionsComprehensive pelvic lymphadenectomy should be recommended to USC patients for its survival benefits. And a nomogram has been developed to predict the survivals of USC patients after surgery.     

Prognostic impact of lymph node harvest for patients with node-negative esophageal squamous cell carcinoma: a large-scale multicenter study

BackgroundWe examined the association between the number of resected lymph nodes and survival to determine the optimal lymphadenectomy for thoracic esophageal squamous cell carcinoma (ESCC) patients with negative lymph node.MethodsWe included 1,836 patients from Chinese three high-volumed hospitals with corresponding clinicopathological characters such as gender, age, tumor location, tumor grade and TNM stage of patients. The median follow-up of included patients was 45.7 months (range, 1.03–117.3 months). X-Tile plot was used to identify the lowest number of lymphadenectomy. The multivariate model’s construction was in use of parameters with clinical significance for survival and a nomogram based on clinical variable with P<0.05 in Cox regression analysis. Both two models were validated using a cohort extracted from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database between 1975 and 2016 (n=951).ResultsMore lymphadenectomy numbers were significantly associated with better survival in patients both in training cohort [hazard ratio (HR) =0.980; 95% confidence interval (CI): 0.971–0.988; P<0.001] and validation cohort (HR =0.980; 95% CI: 0.968–0.991; P=0.001). Cut-off point analysis determined the lowest number of 9 for thoracic ESCC patients in N0 stage through training cohort (C-index: 0.623; sensitivity: 80.7%; 1 − specificity: 72.5%) when compared with 10 in validation cohort (C-index: 0.643; sensitivity: 78.2%; 1 − specificity: 63.0%). The cut-off points of 9 were examined in training cohort and validated in the divided cohort from validation cohort (all P<0.05). Meanwhile, nomograms for both cohorts were constructed and the calibration curves for both cohorts agreed well with the actual observations in terms of predicting 3- and 5-year survival, respectively.ConclusionsLarger number for lymphadenectomy was associated with better survival in thoracic ESCC patients in N0 stage. Nine was what we got as the lowest number for lymphadenectomy in pN0 ESCC patients through this study, and our result should be confirmed further.     

Prognostic impact of preoperative prognostic nutritional index in resected advanced gastric cancer: A multicenter propensity score analysis

BackgroundAdvanced gastric cancer (AGC) causes debilitating malnutrition and leads to deterioration of the immune response. However, the concept of the prognostic nutritional index (PNI) is controversial when applied to patients with AGC. The aim of the present study was to evaluate the effect of the PNI after gastrectomy in patients with AGC.Materials and methodsA multicenter retrospective study was conducted using propensity score matching (PSM) in gastric adenocarcinoma patients who underwent resection via laparoscopic or open surgery between 2014 and 2017. To overcome selection bias, we performed 1:1 matching using 5 covariates.ResultsThe resection margins (P < 0.001) and LNM (P = 0.004) were significantly different between the two groups. In univariate analysis, poor tumor differentiation (P = 0.038) (R1+R2, P = 0.004), vascular and neural invasion (P < 0.001), and a PNI<50 (P < 0.001) were associated with poor recurrence-free survival (RFS). In multivariate analysis, a PNI<50 (hazard ratio (HR), 12.993; P < 0.001) was a risk factor for RFS. Univariate analysis for overall survival (OS) revealed that a PNI<50 (P < 0.001) (R1+R2,P = 0.006) and vascular and neural invasion (P < 0.001) were risk factors. In subsequent multivariate analysis, a PNI<50 (HR, 24.501; P < 0.001) was a significant risk factor for OS. Clinical assessments performed during a 12.34 (±5.050) month follow-up revealed that OS (P < 0.001) and RFS (P < 0.001) were worse in patients with a low PNI (<50) than in matched patients with a high PNI.ConclusionA low PNI is a strong predictor of unfavorable RFS and OS in patients with AGC.     

Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma

ObjectiveTo evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall survival (OS) in patients with early stage hepatocellular carcinoma (HCC) receiving surgical resection.MethodsAll 283 eligible patients were included retrospectively between January 2008 and December 2015, and assigned into the training cohort (n = 198) and the testing cohort (n = 85). We extracted radiomics features via handcrafted radiomics analysis manually and DL analysis of pretrained convolutional neural networks via transfer learning automatically. Support vector machine was adopted as the classifier. A clinical-radiological model for MVI status integrated significant clinical features and the radiological signature generated from the radiological model with the optimal area under the receiver operating characteristics curve (AUC) in the testing cohort. Otherwise, DL-based prognostic models were constructed in prediction of recurrence and mortality via Cox proportional hazard analysis.ResultsThe clinical-radiological model for MVI represented an AUC of 0.909, accuracy of 96.47%, sensitivity of 90.91%, specificity of 97.30%, positive predictive value of 83.33%, and negative predictive value of 98.63% in the testing cohort. The clinical-radiological models for identification of RFS and OS outperformed prediction performance of the clinical model or the DL signature alone. The DL-based integrated model for prognostication showed great predictive value with significant classification and discrimination abilities after validation.ConclusionsThe integrated DL-based radiomics models achieved accurate preoperative prediction of MVI status, and might facilitate predicting tumor recurrence and mortality in order to optimize clinical decisions for patients with early stage HCC.