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A novel nomogram individually predicting disease-specific survival after D2 gastrectomy for advanced gastric cancer

Cancer Communications 2018年第1期38卷 254-262页

作者： Wei Wang Zhe Sun Jing-Yu Deng Xiao-Long Qi Xing-Yu Feng Cheng Fang Xing-Hua Ma Zhen-Ning Wang Han Liang Hui-Mian Xu Zhi-Wei Zhou Department of Gastric Surgery Sun Yat-sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 Dongfeng East RoadGuangzhou 510060GuangdongP.R.China Department of Surgical Oncology The First Affiliated Hospital of China Medical UniversityShenyang 110000LiaoningP.R.China Department of Gastric Cancer Surgery Tianjin Medical University Cancer HospitalTianjin 300000P.R.China Department of General Surgery Nanfang HospitalSouthern Medical UniversityGuangzhou 510515GuangdongP.R.China Department of Gastroenterology Surgery Guangdong General HospitalGuangzhou 510030GuangdongP.R.China Department of Preventive Medicine School of Public HealthSun Yat-sen UniversityGuangzhou 510275GuangdongP.R.China

Background:Few studies have shown nomograms that may predict disease-specific survival(DSS)probability after curative D2 gastrectomy for advanced gastric cancer(AGC),particularly among Chinese *** study sought to develop an elaborative nomogram that predicts long-term DSS for AGC in Chinese ***:A retrospective study was conducted on 6753 AGC patients undergoing D2 gastrectomy between January 1,2000 and December 31,2012 from three large medical hospitals in *** assigned patients from Sun Yat-sen University Cancer Center to the training set,and patients from the First Affiliated Hospital of China Medical University and Tianjin Medical University Cancer Hospital to two separate external validation sets.A multivariate survival analysis was performed using Cox proportional hazards regression model in a training set,and a nomogram was ***’s C-index was used to evaluate discrimination and calibration plots were used to validate similarities between survival probabilities predicted by the nomogram model and actual survival rates in two validation ***:The multivariate Cox regression model identified age,tumor size,location,Lauren classification,lymphatic/venous invasion,depth of invasion,and metastatic lymph node ratio as covariates associated with *** the training set,the nomogram exhibited superior discrimination power compared with the 8th American Joint Com-mittee on Cancer TNM classification(Harrell’s C-index,0.82 vs.0.74;Psurvival predictions that corresponded closely with actual survival ***:The established nomogram was able to predict 3-,5-,and 10-year DSS probabilities for AGC *** revealed that this nomogram exhibited excellent discrimination and calibrat

关键词： Advanced gastric cancer disease-specific survival Prognostic nomogram

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E-cadherin expression pattern in primary colorectal carcinomas and their metastases reflects disease outcome

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World Journal of Gastroenterology 2006年第27期12卷 4304-4309页

作者： Adam Elzagheid Annika lgars Riyad Bendardaf Hanan Lamlum Raija Ristamaki Yrjo Collan Kari Syrjanen Seppo Pyrhonen Department of Oncology and Radiotherapy Turku University HospitalSavitehtaankatu 1 PB 52FIN-20521 TurkuFinland Department of Pathology University of TurkuKiinamyllynkatu 10FIN-20520 TurkuFinland

AIM： To investigate the changes that occur in E-cadherin expression during the process of metastasis in colorectal cancer.METHODS： E-cadherin expression was detected by immunohistochemistry and two indices of expression were calculated which reflected the level of expression and the locations （membrane and cytoplasm）. Univariate and multivariate survival analyses were used to assess the value of these two E-cadherin indices as predictors of both disease-free （DFS） and disease-specific （DSS） survival. RESULTS： E-cadherin membrane index （MI）, but not cytoplasmic index （CI）, was significantly higher in primary tumors than their metastases （P = 0.0001）. Furthermore, both primary tumor MI and CI were higher among the patients who developed subsequent metastasis （P = 0.022 and P = 0.007, respectively）. Interestingly, both indices were higher in liver metastase compared to other anatomic sites （MI, P = 0.034 and CI, P = 0.022）. The CI of the primary tumors was a significant predictor of DFS （P = 0.042, univariate analysis）, with a strong inverse correlation between CI and DFS （P = 0.006, multivariate analysis）. Finally, the MI of primary tumor proved to be a significant independent predictor of DSS, with higher indices being associated with a more favorable outcome （P = 0.016）. CONCLUSION： Examination of E-cadherin expression and distribution in colorectal tumors can be extremely valuable in predicting disease recurrence. The observation that aberrant cytoplasmic expression of E-cadherin can predict disease recurrence is obviously of great importance for both patients and clinicians, and significantly affects decisions concerning the therapy and management of the patients.

关键词： Colorectal carcinoma E-Cadherin membrane Cytoplasmic immunohistochemistry Prognosis diseasefree survival disease-specific survival

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Revalidation of a prognostic score model based on complete blood count for nasopharyngeal carcinoma through a prospective study

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Chinese Journal of Cancer Research 2016年第5期28卷 467-477页

作者： Xiaohui Li Hui Chang Yalan Tao Xiaohui Wang Jin Gao Wenwen Zhang Chen Chen Yunfei Xia Department of Radiation Oncology Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center of Cancer Medicine Guangzhou 510060 China Department of Oncology the 421 Hospital of Chinese People's Liberation Army Guangzhou 510318 China Department of Radiation Oncology Anhui Provincial Hospital Affiliated to Anhui Medical University Hefei 230001 China

Objective： In our previous work, we incorporated complete blood count （CBC） into TNM stage to develop a new prognostic score model, which was validated to improve prediction efficiency of TNM stage for nasopharyngeal carcinoma （NPC）. The purpose of this study was to revalidate the accuracy of the model, and its superiority to TNM stage, through data from a prospective ***： CBC of 249 eligible patients from the 863 Program No. 2006AA02Z4B4 was evaluated. Prognostic index （PI） of each patient was calculated according to the score model. Then they were divided by the PI into three categories： the low-, intermediate-and high-risk patients. The 5-year disease-specific survival （DSS） of the three categories was compared by a log-rank test. The model and TNM stage （Tth edition） were compared on efficiency for predicting the 5-year DSS, through comparison of the area under curve （AUC） of their receiver-operating characteristic ***： The 5-year DSS of the low-, intermediate- and high-risk patients were 96.0%, 79.1% and 62.2%, respectively. The low- and intermediate-risk patients had better DSS than the high-risk patients （P〈0.001 and P〈0.005, respectively）. And there was a trend of better DSS in the low-risk patients, compared with the intermediate-risk patients （P=0.049）. The AUC of the model was larger than that of TNM stage （0.726 vs. 0.661, P：0.023）. Conclusions： A CBC-based prognostic score model was revalidated to be accurate and superior to TNM stage on predicting 5-year DSS of NPC.

关键词： Complete blood count score model revalidadon disease-specific survival nasopharyngeal carcinoma

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Nuclear β-catenin expression as a prognostic factor in advanced colorectal carcinoma

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World Journal of Gastroenterology 2008年第24期14卷 3866-3871页

作者： Adam Elzagheid Abdelbaset Buhmeida Eija Korkeila Yrj Collan Kari Syrjnen Seppo Pyrhnen Department of Pathology Faculty of Medicine Al-Arab Medical University Department of Oncology and Radiotherapy Turku University Hospital Department of pathology University of Turku

AIM： To investigate the changing pattern of β-catenin expression and its prognostic value in advanced colorectal cancer （CRC）. METHODS： Archival tumor samples were analyzed for β-catenin using immunohistochemistry （IHC） in 95 patients with advanced CRC. RESULTS： Membranous β-catenin expression was found in the normal colorectal epithelium. Almost 100% of CRC cases showed membranous and cytoplasmic expression, and 55 （58%） cases showed nuclear expression. In univariate （Kaplan-Meier） survival analysis, only the nuclear index （NI） was a significant predictor of disease free survival （DFS）（P = 0.023; n = 35）, with a NI above the median associated with longer DFS （34.2 too） than those with a NI below the median （15.5 too）（P = 0.045, ANOVA）. The other indices were not significant predictors of DFS, and none of the three tested indices （for membranous, cytoplasmic, or nuclear expression） predicted diseasespecific survival （DSS）. However, when dichotomized as positive or negative nuclear expression, the former was a significant predictor of more favorable DFS （P = 0.041） and DSS （P = 0.046）. CONCLUSION： Nuclear β-catenin expression provides additional information in predicting patient outcome in advanced CRC.

关键词： Colorectal carcinoma β-catenin membranestaining Cytoplasmic staining, Nuclear staining Immunohistochemistry Prognosis disease-freesurvival disease-specific survival

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Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients

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World Journal of Gastrointestinal Oncology 2024年第8期16卷 3507-3520页

作者： Wen Liu Hong-Yu Wu Jia-Xi Lin Shu-Ting Qu Yi-Jie Gu Jin-Zhou Zhu Chun-Fang Xu Department of Gastroenterology Changzhou Hospital of Traditional Chinese MedicineChangzhou 213000Jiangsu ProvinceChina Department of Gastroenterology The First Affiliated Hospital of Soochow UniversitySuzhou 215006Jiangsu ProvinceChina Department of Gastroenterology Suzhou Ninth Hospital Affiliated to Soochow UniversitySuzhou 215200Jiangsu ProvinceChina

BACKGROUND Lymph node ratio(LNR)was demonstrated to play a crucial role in the prognosis of many ***,research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm(NEN)patients was *** To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic *** A total of 286 patients from the Surveillance,Epidemiology,and End Results database were divided into the training set and validation set at a ratio of 8:2.92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test *** regression analysis was used to explore the relationship between LNR and disease-specific survival(DSS)of gastric NEN *** survival forest(RSF)algorithm and Cox proportional hazards(CoxPH)analysis were applied to develop models to predict DSS respectively,and compared with the 8th edition American Joint Committee on Cancer(AJCC)tumornode-metastasis(TNM)*** Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of *** RSF model exhibited the best performance in predicting DSS,with the C-index in the test set being 0.769[95%confidence interval(CI):0.691-0.846]outperforming the CoxPH model(0.744,95%CI:0.665-0.822)and the 8th edition AJCC TNM staging(0.723,95%CI:0.613-0.833).The calibration curves and decision curve analysis(DCA)demonstrated the RSF model had good calibration and clinical ***,the RSF model could perform risk stratification and individual prognosis prediction *** A higher LNR indicated a lower DSS in postoperative gastric NEN *** RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set,showing potential in clinical practice.

关键词： Gastric neuroendocrine neoplasm Lymph node ratio disease-specific survival Random survival forest Predictive model

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Estimating prognosis of gastric neuroendocrine neoplasms using machine learning:A step towards precision medicine

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World Journal of Gastrointestinal Oncology 2024年第12期16卷 4548-4552页

作者： Hong-Niu Wang Jia-Hao An Liang Zong Graduate School of Medicine Changzhi Medical CollegeChangzhi 046000Shanxi ProvinceChina Department of Gastrointestinal Surgery Changzhi People’s HospitalChangzhi 046000Shanxi ProvinceChina

survival rates following radical surgery for gastric neuroendocrine neoplasms(g-NENs)are low,with high recurrence *** fact impacts patient prognosis and complicates postoperative *** prognostic models,including the Cox proportional hazards(CoxPH)model,have shown limited predictive power for postoperative survival in gastrointestinal neuroectodermal tumor *** learning methods offer a unique opportunity to analyze complex relationships within datasets,providing tools and methodologies to assess large volumes of high-dimensional,multimodal data generated by biological *** methods show promise in predicting outcomes across various medical *** the context of g-NENs,utilizing machine learning to predict survival outcomes holds potential for personalized postoperative management *** editorial reviews a study exploring the advantages and effectiveness of the random survival forest(RSF)model,using the lymph node ratio(LNR),in predicting disease-specific survival(DSS)in postoperative g-NEN patients stratified into low-risk and high-risk *** findings demonstrate that the RSF model,incorporating LNR,outperformed the CoxPH model in predicting DSS and constitutes an important step towards precision medicine.

关键词： Machine learning Artificial intelligence Gastric neuroendocrine neoplasm Random survival forest model disease-specific survival

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