BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepat...BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepatitis C virus(HCV)infections.Accurate prognostication is crucial for optimizing treatment and outcomes.Numerous staging systems exist,including the Barcelona Clinic Liver Cancer(BCLC),Hong Kong Liver Cancer(HKLC),cancer of the liver Italian Program(CLIP),Italian Liver Cancer(ITA.LI.CA),Japan Integrated Staging(JIS),Tokyo Score,and model to estimate survival in ambulatory HCC patients(MESIAH).However,their comparative performance in Vietnamese patients remains underexplored.AIM To compare the prognostic accuracy of seven HCC staging systems in predicting survival and identify the optimal model.METHODS This retrospective cohort study included 987 patients with HCC diagnosed at Nhan dan Gia Dinh Hospital,Vietnam,from January 2016 to December 2023.Patients were staged using BCLC,HKLC,CLIP,ITA.LI.CA,JIS,Tokyo score,and MESIAH.Overall survival was analyzed using Kaplan-Meier methods,and prognostic performance was evaluated via the area under the receiver operating characteristic(ROC)curve,Harrell’s concordance index,and calibration plots.RESULTS The HKLC and BCLC systems demonstrated the highest discriminatory ability,with area under the ROC curves of 0.834 and 0.830,respectively,at 12 months and 0.859 for both systems at 36 months.CLIP and ITA.LI.CA exhibited superior calibration,particularly at 36 months.The JIS system consistently showed the poorest discriminatory performance.Subgroup analyses revealed that HKLC maintained strong performance across different viral etiologies(HBV,HCV,non-B-non-C)and treatment modalities(transarterial chemoembolization,surgery,ablation).CONCLUSION The HKLC and BCLC systems showed superior prognostic performance for Vietnamese patients with HCC,supporting HKLC adoption in clinical practice.展开更多
BACKGROUND The prognosis of gastric cancer(GC)patients is poor,and an accurate prognostic staging system would help assess patients'prognostic status before treatment and determine appropriate treatment strategies...BACKGROUND The prognosis of gastric cancer(GC)patients is poor,and an accurate prognostic staging system would help assess patients'prognostic status before treatment and determine appropriate treatment strategies.AIM To develop positive lymph node ratio(LNR)and machine learning(ML)-based staging systems for GC patients with varying differentiation.METHODS This multicenter retrospective cohort study included 11772 GC patients,with 5612 in the training set(Harbin Medical University Cancer Hospital)and 6160 in the validation set(Surveillance,Epidemiology,and End Results Program database).X-tile software identified optimal cutoff values for the positive LNR,and five ML models were developed using pT and LNR staging.Risk scores were divided into seven stages,constructing new staging systems tailored to different tumor differentiation levels.RESULTS In both the training and validation sets,regardless of the tumor differentiation level,LNR staging demonstrated superior prognostic stratification compared to pN.Extreme Gradient Boosting exhibited better predictive performance than the other four models.Compared to tumor node metastasis staging,the new staging systems,developed for patients with different degrees of differentiation,showed significantly better predictive performance.CONCLUSION The new positive lymph nodes ratio staging and integrated staging systems constructed for GC patients with different differentiation grades exhibited better prognostic stratification capabilities.展开更多
Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predi...Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.展开更多
Epidemiological studies have shown that human leukocyte antigen（HLA） allelic polymorphisms are closely correlated to susceptibility to nasopharyngeal carcinoma（NPC）, and in a previous study, we showed that HLA-B＊...Epidemiological studies have shown that human leukocyte antigen（HLA） allelic polymorphisms are closely correlated to susceptibility to nasopharyngeal carcinoma（NPC）, and in a previous study, we showed that HLA-B＊46 and HLA-A＊02-B＊46 haplotypes were strongly associated with NPC susceptibility. In this retrospective study, we investigated the phenotype of the HLA-A and HLA-B alleles and haplotypes and correlated these data to the clinical and pathological parameters of NPC to understand the role of HLA alleles and haplotypes in NPC prognosis. The cohort comprised 117 NPC patients from a Han population in Xinjiang. The local recurrence-free survival（LRFS）, distant metastasis-free survival（DMFS）, disease-free survival（DFS）, and overall survival（OS） were analyzed. The 5-year DMFS of the HLA-A＊02-B＊46 haplotype carriers and non-carriers was 66.4% and 90.3%, respectively. In addition, age was found to be a prognostic factor for LRFS, DFS, and OS（P=0.032, 0.040, and 0.013, respectively）. We found that the HLA-A＊02-B＊46 haplotype might be a prognostic marker in addition to the traditional TNM staging in patients with NPC.展开更多
Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer,...Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer, such as Gleason score, pathological tumor staging, and prostate-specific antigen(PSA) expression level, are considered insufficient to inform recommendation to guide clinical practice. Thus, identification of a novel biomarker is necessary. TWIST is one of the well-studied targets and is correlated with cancer invasion and metastasis in several human cancers. We have investigated two largest prostate cancer patient cohorts available in GEO database and found that TWIST expression is positive correlated with Gleason score and associated with poorer survival. By using a prostate cancer cohort and a prostate cancer cell line dataset, we have identified three potential downstream targets of TWIST, PPM1 A, SRP72 and TBCB. TWIST's prognostic capacity is lost when the gene is mutated. Further investigation in the prostate cancer cohort revealed that gene expression of SERPINA, STX7, PDIA2, FMP5, GP1 BB, VGLL4,KCNMA1, SHMT2, SAA4 and DIDO1 influence the prognostic significance of TWIST and vice versa. Importantly, eight out of these ten genes are prognostic indicator by itself. In conclusion, our study has further confirmed that TWIST is a prognostic marker in prostate cancer, identified its potential downstream targets and genes that could possibly give additional prognostic value to predict TWIST-mediated prostate cancer progression.展开更多
文摘BACKGROUND Hepatocellular carcinoma(HCC),the sixth most common cancer and fourthleading cause of cancer-related mortality globally,imposes a significant burden in Vietnam due to endemic hepatitis B virus(HBV)and hepatitis C virus(HCV)infections.Accurate prognostication is crucial for optimizing treatment and outcomes.Numerous staging systems exist,including the Barcelona Clinic Liver Cancer(BCLC),Hong Kong Liver Cancer(HKLC),cancer of the liver Italian Program(CLIP),Italian Liver Cancer(ITA.LI.CA),Japan Integrated Staging(JIS),Tokyo Score,and model to estimate survival in ambulatory HCC patients(MESIAH).However,their comparative performance in Vietnamese patients remains underexplored.AIM To compare the prognostic accuracy of seven HCC staging systems in predicting survival and identify the optimal model.METHODS This retrospective cohort study included 987 patients with HCC diagnosed at Nhan dan Gia Dinh Hospital,Vietnam,from January 2016 to December 2023.Patients were staged using BCLC,HKLC,CLIP,ITA.LI.CA,JIS,Tokyo score,and MESIAH.Overall survival was analyzed using Kaplan-Meier methods,and prognostic performance was evaluated via the area under the receiver operating characteristic(ROC)curve,Harrell’s concordance index,and calibration plots.RESULTS The HKLC and BCLC systems demonstrated the highest discriminatory ability,with area under the ROC curves of 0.834 and 0.830,respectively,at 12 months and 0.859 for both systems at 36 months.CLIP and ITA.LI.CA exhibited superior calibration,particularly at 36 months.The JIS system consistently showed the poorest discriminatory performance.Subgroup analyses revealed that HKLC maintained strong performance across different viral etiologies(HBV,HCV,non-B-non-C)and treatment modalities(transarterial chemoembolization,surgery,ablation).CONCLUSION The HKLC and BCLC systems showed superior prognostic performance for Vietnamese patients with HCC,supporting HKLC adoption in clinical practice.
基金Supported by Nn10 Program of Harbin Medical University Cancer Hospital,No.Nn10 PY 2017-03.
文摘BACKGROUND The prognosis of gastric cancer(GC)patients is poor,and an accurate prognostic staging system would help assess patients'prognostic status before treatment and determine appropriate treatment strategies.AIM To develop positive lymph node ratio(LNR)and machine learning(ML)-based staging systems for GC patients with varying differentiation.METHODS This multicenter retrospective cohort study included 11772 GC patients,with 5612 in the training set(Harbin Medical University Cancer Hospital)and 6160 in the validation set(Surveillance,Epidemiology,and End Results Program database).X-tile software identified optimal cutoff values for the positive LNR,and five ML models were developed using pT and LNR staging.Risk scores were divided into seven stages,constructing new staging systems tailored to different tumor differentiation levels.RESULTS In both the training and validation sets,regardless of the tumor differentiation level,LNR staging demonstrated superior prognostic stratification compared to pN.Extreme Gradient Boosting exhibited better predictive performance than the other four models.Compared to tumor node metastasis staging,the new staging systems,developed for patients with different degrees of differentiation,showed significantly better predictive performance.CONCLUSION The new positive lymph nodes ratio staging and integrated staging systems constructed for GC patients with different differentiation grades exhibited better prognostic stratification capabilities.
基金supported by the National Natural Science Foundation of China (Grant nos. 82470209 and 82170141)the Jiaxing Key Discipiline of Medcine-Nephrology (Grant no. 2023-ZC-011)。
文摘Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.
基金supported by grants from the Chinese International Cooperation Project(No.2012DFA31560)Key Laboratory Projects of Xinjiang Uygur Autonomous Region(No.2015KL021)the Achievement Promotion Projects of the Autonomous Region(No.201554142)
文摘Epidemiological studies have shown that human leukocyte antigen（HLA） allelic polymorphisms are closely correlated to susceptibility to nasopharyngeal carcinoma（NPC）, and in a previous study, we showed that HLA-B＊46 and HLA-A＊02-B＊46 haplotypes were strongly associated with NPC susceptibility. In this retrospective study, we investigated the phenotype of the HLA-A and HLA-B alleles and haplotypes and correlated these data to the clinical and pathological parameters of NPC to understand the role of HLA alleles and haplotypes in NPC prognosis. The cohort comprised 117 NPC patients from a Han population in Xinjiang. The local recurrence-free survival（LRFS）, distant metastasis-free survival（DMFS）, disease-free survival（DFS）, and overall survival（OS） were analyzed. The 5-year DMFS of the HLA-A＊02-B＊46 haplotype carriers and non-carriers was 66.4% and 90.3%, respectively. In addition, age was found to be a prognostic factor for LRFS, DFS, and OS（P=0.032, 0.040, and 0.013, respectively）. We found that the HLA-A＊02-B＊46 haplotype might be a prognostic marker in addition to the traditional TNM staging in patients with NPC.
基金supported by the University of Macao Multi-Year Research Grants (MYRG2015-00065FHS)the Macao Science and Technology Development Fund (FDCT 018-2015-A1) to Dr. Hang Fai Kwok research group
文摘Prostate cancer is one of the most common cancers in men worldwide, and the number of diagnosed patients has dramatically increased in recent years. Currently, the clinical parameters used to diagnose prostate cancer, such as Gleason score, pathological tumor staging, and prostate-specific antigen(PSA) expression level, are considered insufficient to inform recommendation to guide clinical practice. Thus, identification of a novel biomarker is necessary. TWIST is one of the well-studied targets and is correlated with cancer invasion and metastasis in several human cancers. We have investigated two largest prostate cancer patient cohorts available in GEO database and found that TWIST expression is positive correlated with Gleason score and associated with poorer survival. By using a prostate cancer cohort and a prostate cancer cell line dataset, we have identified three potential downstream targets of TWIST, PPM1 A, SRP72 and TBCB. TWIST's prognostic capacity is lost when the gene is mutated. Further investigation in the prostate cancer cohort revealed that gene expression of SERPINA, STX7, PDIA2, FMP5, GP1 BB, VGLL4,KCNMA1, SHMT2, SAA4 and DIDO1 influence the prognostic significance of TWIST and vice versa. Importantly, eight out of these ten genes are prognostic indicator by itself. In conclusion, our study has further confirmed that TWIST is a prognostic marker in prostate cancer, identified its potential downstream targets and genes that could possibly give additional prognostic value to predict TWIST-mediated prostate cancer progression.
