背景与目的气管支气管转移(endotracheal and endobronchial metastases,EEM)在肺癌中罕见,国外文献报道可发生于手术切除后,但国内目前尚未见相关报道,本研究旨在总结和分析肺癌发生EEM的临床特征。方法回顾2015年1月-2018年12月于北...背景与目的气管支气管转移(endotracheal and endobronchial metastases,EEM)在肺癌中罕见,国外文献报道可发生于手术切除后,但国内目前尚未见相关报道,本研究旨在总结和分析肺癌发生EEM的临床特征。方法回顾2015年1月-2018年12月于北京大学第三医院确诊原发性肺癌并行支气管镜的患者,同时检索截至2020年2月Pub Med检索系统中的病例,采集并比较两组患者的临床、病理、影像、支气管镜和预后等资料。结果我院共有6例肺癌伴EEM入选,发生率为0.62%(6/967),均为初诊为肺癌时即伴有EEM。鳞癌4例,腺癌1例,小细胞肺癌1例。Ⅲb期1例,Ⅳ期5例。中央型肺癌5例,周围型1例。EEM在支气管镜下表现为肺癌原发灶之外的气道黏膜结节或息肉性病变5例、局灶性黏膜异常1例。转移至对侧支气管5例,至同侧支气管和气管各1例。中位总生存期为7.5个月。从Pub Med数据库共检索到13例,其中12例为肺癌术后随诊胸部计算机断层扫描(computed tomography,CT)异常继而确诊为EEM。中央型9例,鳞癌8例,EEM在CT上表现为腔内结节10例,气管壁局限增厚2例,支气管镜下均表现为气道黏膜结节或息肉样病变。转移至气管10例,至对侧支气管5例,至同侧支气管1例。结论EEM是原发性肺癌罕见的转移方式,可发生于初诊时,也可发生于术后,多见于晚期中央型鳞癌,预后差。展开更多
Background:The literature recommends that reduced dosage of CPT-11 should be applied in patients with UGT1 A1 homozygous mutations,but the impact of UGT1 A1 heterozygous mutations on the adverse reactions of CPT-11 is...Background:The literature recommends that reduced dosage of CPT-11 should be applied in patients with UGT1 A1 homozygous mutations,but the impact of UGT1 A1 heterozygous mutations on the adverse reactions of CPT-11 is still not fully clear.Methods:A total of 107 patients with UGT1 A1 heterozygous mutation or wild-type,who were treated with CPT-11 from January 2018 to September 2021 in Peking University Third Hospital,were retrospectively enrolled.The adverse reaction spectra of patients with UGT1 A1*6 and UGT1 A1*28 mutations were analyzed.Adverse reactions were evaluated according to National Cancer Institute Common Terminology Criteria for Adverse Events(NCI-CTCAE) 5.0.The efficacy was evaluated according to Response Evaluation Criteria in Solid Tumors(RECIST) 1.1.The genotypes of UGT1 A1*6 and UGT1 A1*28 were detected by digital fluorescence molecular hybridization.Results:There were 43 patients with UGT1 A1*6 heterozygous mutation,26 patients with UGT1 A1*28 heterozygous mutation,8 patients with UGT1 A1*6 and UGT1 A1*28 double heterozygous mutations,61 patients with heterozygous mutation at any gene locus of UGT1 A1*6 and UGT1 A1*28.Logistic regression analysis showed that the presence or absence of vomiting(P=0.013) and mucositis(P=0.005) was significantly correlated with heterozygous mutation of UGT1 A1*28,and the severity of vomiting(P<0.001) and neutropenia(P=0.021) were significantly correlated with heterozygous mutation of UGT1 A1*6.In colorectal cancer,UGT1 A1*6 was significantly correlated to diarrhea(P=0.005),and the other adverse reactions spectrum was similar to that of the whole patient cohort,and efficacy and prognosis were similar between patients with different genotypes and patients treated with reduced CPT-11 dosage or not.Conclusion:In clinical use,heterozygous mutations of UGT1 A1*6 and UGT1 A1*28 are related to the risk and severity of vomiting,diarrhea,neutropenia and mucositis in patients with Pan-tumor and colorectal cancer post CPT-11 therpy.In colorectal cancer,UGT1 A1*6 is significantly related to diarrhea post CPT-11 use,efficacy and prognosis is not affected by various genotypes or CPT-11 dosage reduction.展开更多
The sole use of single modality data often fails to capture the complex heterogeneity among patients,including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens,for the tre...The sole use of single modality data often fails to capture the complex heterogeneity among patients,including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens,for the treatment of HER2-positive gastric cancer(GC).This modality deficit has not been fully considered in many studies.Furthermore,the application of artificial intelligence in predicting the treatment response,particularly in complex diseases such as GC,is still in its infancy.Therefore,this study aimed to use a comprehensive analytic approach to accurately predict treatment responses to anti-HER2 therapy or anti-HER2 combined immunotherapy in patients with HER2-positive GC.We collected multi-modal data,comprising radiology,pathology,and clinical information from a cohort of 429 patients:310 treated with anti-HER2 therapy and 119 treated with a combination of anti-HER2 and anti-PD-1/PD-L1 inhibitors immunotherapy.We introduced a deep learning model,called the Multi-Modal model(MuMo),that integrates these data to make precise treatment response predictions.MuMo achieved an area under the curve score of 0.821 for anti-HER2 therapy and 0.914 for combined immunotherapy.Moreover,patients classified as low-risk by MuMo exhibited significantly prolonged progression-free survival and overall survival(log-rank test,P<0.05).These findings not only highlight the significance of multi-modal data analysis in enhancing treatment evaluation and personalized medicine for HER2-positive gastric cancer,but also the potential and clinical value of our model.展开更多
文摘Background:The literature recommends that reduced dosage of CPT-11 should be applied in patients with UGT1 A1 homozygous mutations,but the impact of UGT1 A1 heterozygous mutations on the adverse reactions of CPT-11 is still not fully clear.Methods:A total of 107 patients with UGT1 A1 heterozygous mutation or wild-type,who were treated with CPT-11 from January 2018 to September 2021 in Peking University Third Hospital,were retrospectively enrolled.The adverse reaction spectra of patients with UGT1 A1*6 and UGT1 A1*28 mutations were analyzed.Adverse reactions were evaluated according to National Cancer Institute Common Terminology Criteria for Adverse Events(NCI-CTCAE) 5.0.The efficacy was evaluated according to Response Evaluation Criteria in Solid Tumors(RECIST) 1.1.The genotypes of UGT1 A1*6 and UGT1 A1*28 were detected by digital fluorescence molecular hybridization.Results:There were 43 patients with UGT1 A1*6 heterozygous mutation,26 patients with UGT1 A1*28 heterozygous mutation,8 patients with UGT1 A1*6 and UGT1 A1*28 double heterozygous mutations,61 patients with heterozygous mutation at any gene locus of UGT1 A1*6 and UGT1 A1*28.Logistic regression analysis showed that the presence or absence of vomiting(P=0.013) and mucositis(P=0.005) was significantly correlated with heterozygous mutation of UGT1 A1*28,and the severity of vomiting(P<0.001) and neutropenia(P=0.021) were significantly correlated with heterozygous mutation of UGT1 A1*6.In colorectal cancer,UGT1 A1*6 was significantly correlated to diarrhea(P=0.005),and the other adverse reactions spectrum was similar to that of the whole patient cohort,and efficacy and prognosis were similar between patients with different genotypes and patients treated with reduced CPT-11 dosage or not.Conclusion:In clinical use,heterozygous mutations of UGT1 A1*6 and UGT1 A1*28 are related to the risk and severity of vomiting,diarrhea,neutropenia and mucositis in patients with Pan-tumor and colorectal cancer post CPT-11 therpy.In colorectal cancer,UGT1 A1*6 is significantly related to diarrhea post CPT-11 use,efficacy and prognosis is not affected by various genotypes or CPT-11 dosage reduction.
基金supported by the National Natural Science Foundation of China(91959205 to L.S.,U22A20327 to L.S.,82203881 to Y.C.,82272627 to XT.Z.,7232018 to Y.S.,12090022 to B.D.,11831002 to B.D.,81801778 to L.Z.)Beijing Natural Science Foundation(7222021 to Y.C.,Z200015 to XT.Z.)+1 种基金Beijing Hospitals Authority Youth Programme(QML20231115 to Y.C.)Clinical Medicine Plus X-Young Scholars Project of Peking University(PKU2023LCXQ041 to Y.C.and L.Z.).
文摘The sole use of single modality data often fails to capture the complex heterogeneity among patients,including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens,for the treatment of HER2-positive gastric cancer(GC).This modality deficit has not been fully considered in many studies.Furthermore,the application of artificial intelligence in predicting the treatment response,particularly in complex diseases such as GC,is still in its infancy.Therefore,this study aimed to use a comprehensive analytic approach to accurately predict treatment responses to anti-HER2 therapy or anti-HER2 combined immunotherapy in patients with HER2-positive GC.We collected multi-modal data,comprising radiology,pathology,and clinical information from a cohort of 429 patients:310 treated with anti-HER2 therapy and 119 treated with a combination of anti-HER2 and anti-PD-1/PD-L1 inhibitors immunotherapy.We introduced a deep learning model,called the Multi-Modal model(MuMo),that integrates these data to make precise treatment response predictions.MuMo achieved an area under the curve score of 0.821 for anti-HER2 therapy and 0.914 for combined immunotherapy.Moreover,patients classified as low-risk by MuMo exhibited significantly prolonged progression-free survival and overall survival(log-rank test,P<0.05).These findings not only highlight the significance of multi-modal data analysis in enhancing treatment evaluation and personalized medicine for HER2-positive gastric cancer,but also the potential and clinical value of our model.
