The incidence of gastrointestinal malignancies has increased over the past decade at an alarming rate.Colorectal and gastric cancers are the third and fifth most commonly diagnosed cancers worldwide but are cited as t...The incidence of gastrointestinal malignancies has increased over the past decade at an alarming rate.Colorectal and gastric cancers are the third and fifth most commonly diagnosed cancers worldwide but are cited as the second and third leading causes of mortality.Early institution of appropriate therapy from timely diagnosis can optimize patient outcomes.Artificial intelligence(AI)-assisted diagnostic,prognostic,and therapeutic tools can assist in expeditious diagnosis,treatment planning/response prediction,and post-surgical prognostication.AI can intercept neoplastic lesions in their primordial stages,accurately flag suspicious and/or inconspicuous lesions with greater accuracy on radiologic,histopathological,and/or endoscopic analyses,and eliminate over-dependence on clinicians.AI-based models have shown to be on par,and sometimes even outperformed experienced gastroenterologists and radiologists.Convolutional neural networks(state-of-the-art deep learning models)are powerful computational models,invaluable to the field of precision oncology.These models not only reliably classify images,but also accurately predict response to chemotherapy,tumor recurrence,metastasis,and survival rates post-treatment.In this systematic review,we analyze the available evidence about the diagnostic,prognostic,and therapeutic utility of artificial intelligence in gastrointestinal oncology.展开更多
BACKGROUND Extramedullary multiple myeloma(MM)(EMM)is a rare and aggressive subentity of MM that can be present at diagnosis or develop anytime during the disease course.There is a paucity of data on the clinical char...BACKGROUND Extramedullary multiple myeloma(MM)(EMM)is a rare and aggressive subentity of MM that can be present at diagnosis or develop anytime during the disease course.There is a paucity of data on the clinical characteristics and overall epidemiology of EMM.Furthermore,there is a scarcity of data on how the interaction of age and gender influences the survival of EMM.AIM To evaluate the clinical characteristics of patients with EMM over the past 2 decades and to identify epidemiologic characteristics that may impact overall prognosis.METHODS A total of 858 patients diagnosed with EMM,between 2000 and 2017,were ultimately enrolled in our study by retrieving the Surveillance,Epidemiology,and End Results database.We analyzed demographics,clinical characteristics,and overall mortality(OM)as well as cancer-specific mortality(CSM)of EMM.Variables with a P value<0.1 in the univariate Cox regression were incorporated into the multivariate Cox model to determine the independent prognostic factors,with a hazard ratio(HR)of greater than 1 representing adverse prognostic factors.RESULTS From a sample of 858 EMM,the male gender(63.25%),age range 60-79 years(51.05%),and non-Hispanic whites(66.78%)were the most represented.Central Nervous System and the vertebral column was the most affected site(33.10%).Crude analysis revealed higher OM in the age group 80+[HR=6.951,95%confidence interval(95%CI):3.299-14.647,P=0],Non-Hispanic Black population(HR=1.339,95%CI:1.02-1.759,P=0.036),Bones not otherwise specified(NOS)(HR=1.74,95%CI:1.043-2.902,P=0.034),and widowed individuals(HR=2.107,95%CI:1.511-2.938,P=0).Skin involvement(HR=0.241,95%CI:0.06-0.974,P=0.046)and a yearly income of$75000+(HR=0.259,95%CI:0.125-0.538,P=0)had the lowest OM in the crude analysis.Crude analysis revealed higher CSM in the age group 80+,Non-Hispanic Black,Bones NOS,and widowed.Multivariate cox proportional hazard regression analyses only revealed higher OM in the age group 80+(HR=9.792,95%CI:4.403-21.774,P=0)and widowed individuals(HR=1.609,95%CI:1.101-2.35,P=0.014).Multivariate cox proportional hazard regression analyses of CSM also revealed higher mortality of the same groups.Eyes,mouth,and ENT involvement had the lowest CSM in the multivariate analysis.There was no interaction between age and gender in the adjusted analysis for OM and CSM.CONCLUSION EMM is a rare entity.To our knowledge,there is a scarcity of data on the clinical characteristics and prognosis factors of patients with extramedullary multiple myeloma.In this retrospective cohort,using a United States-based population,we found that age,marital status,and tumor site were independent prognostic factors.Furthermore,we found that age and gender did not interact to influence the mortality of patients with EMM.展开更多
文摘The incidence of gastrointestinal malignancies has increased over the past decade at an alarming rate.Colorectal and gastric cancers are the third and fifth most commonly diagnosed cancers worldwide but are cited as the second and third leading causes of mortality.Early institution of appropriate therapy from timely diagnosis can optimize patient outcomes.Artificial intelligence(AI)-assisted diagnostic,prognostic,and therapeutic tools can assist in expeditious diagnosis,treatment planning/response prediction,and post-surgical prognostication.AI can intercept neoplastic lesions in their primordial stages,accurately flag suspicious and/or inconspicuous lesions with greater accuracy on radiologic,histopathological,and/or endoscopic analyses,and eliminate over-dependence on clinicians.AI-based models have shown to be on par,and sometimes even outperformed experienced gastroenterologists and radiologists.Convolutional neural networks(state-of-the-art deep learning models)are powerful computational models,invaluable to the field of precision oncology.These models not only reliably classify images,but also accurately predict response to chemotherapy,tumor recurrence,metastasis,and survival rates post-treatment.In this systematic review,we analyze the available evidence about the diagnostic,prognostic,and therapeutic utility of artificial intelligence in gastrointestinal oncology.
文摘BACKGROUND Extramedullary multiple myeloma(MM)(EMM)is a rare and aggressive subentity of MM that can be present at diagnosis or develop anytime during the disease course.There is a paucity of data on the clinical characteristics and overall epidemiology of EMM.Furthermore,there is a scarcity of data on how the interaction of age and gender influences the survival of EMM.AIM To evaluate the clinical characteristics of patients with EMM over the past 2 decades and to identify epidemiologic characteristics that may impact overall prognosis.METHODS A total of 858 patients diagnosed with EMM,between 2000 and 2017,were ultimately enrolled in our study by retrieving the Surveillance,Epidemiology,and End Results database.We analyzed demographics,clinical characteristics,and overall mortality(OM)as well as cancer-specific mortality(CSM)of EMM.Variables with a P value<0.1 in the univariate Cox regression were incorporated into the multivariate Cox model to determine the independent prognostic factors,with a hazard ratio(HR)of greater than 1 representing adverse prognostic factors.RESULTS From a sample of 858 EMM,the male gender(63.25%),age range 60-79 years(51.05%),and non-Hispanic whites(66.78%)were the most represented.Central Nervous System and the vertebral column was the most affected site(33.10%).Crude analysis revealed higher OM in the age group 80+[HR=6.951,95%confidence interval(95%CI):3.299-14.647,P=0],Non-Hispanic Black population(HR=1.339,95%CI:1.02-1.759,P=0.036),Bones not otherwise specified(NOS)(HR=1.74,95%CI:1.043-2.902,P=0.034),and widowed individuals(HR=2.107,95%CI:1.511-2.938,P=0).Skin involvement(HR=0.241,95%CI:0.06-0.974,P=0.046)and a yearly income of$75000+(HR=0.259,95%CI:0.125-0.538,P=0)had the lowest OM in the crude analysis.Crude analysis revealed higher CSM in the age group 80+,Non-Hispanic Black,Bones NOS,and widowed.Multivariate cox proportional hazard regression analyses only revealed higher OM in the age group 80+(HR=9.792,95%CI:4.403-21.774,P=0)and widowed individuals(HR=1.609,95%CI:1.101-2.35,P=0.014).Multivariate cox proportional hazard regression analyses of CSM also revealed higher mortality of the same groups.Eyes,mouth,and ENT involvement had the lowest CSM in the multivariate analysis.There was no interaction between age and gender in the adjusted analysis for OM and CSM.CONCLUSION EMM is a rare entity.To our knowledge,there is a scarcity of data on the clinical characteristics and prognosis factors of patients with extramedullary multiple myeloma.In this retrospective cohort,using a United States-based population,we found that age,marital status,and tumor site were independent prognostic factors.Furthermore,we found that age and gender did not interact to influence the mortality of patients with EMM.
