The pathologic relevance of metabolic criteria in patients with biopsy-proven nonalcoholic fatty liver disease and metabolic dysfunction associated fatty liver disease:A multicenter cross-sectional study in China

Background:This study aimed to assess the association between metabolic syndrome(Met S)and severity of nonalcoholic fatty liver disease(NAFLD),and to discuss the pathological relevance of the diagnostic criteria in metabolic(dysfunction)associated fatty liver disease(MAFLD).Methods:This was a multicenter,cross-sectional study.Patients with NAFLD confirmed by liver biopsy were enrolled between July 2016 and December 2018 from 14 centers across the mainland of China.Anthropometric and metabolic parameters were collected to assess the pathological relevance.Results:Of 246 enrolled patients with NAFLD,150(61.0%)had the comorbidity of Met S.With the increase of metabolic components,the proportions of nonalcoholic steatohepatitis(NASH)and significant fibrosis were notably increased.The comorbid three metabolic components significantly increased the proportion of NASH,and further increase of metabolic components did not increase the proportion of NASH.However,the increase of metabolic components was parallel to the increase of the proportion of liver fibrosis.Among the 246 patients,239(97.2%)met the diagnostic criteria of MAFLD.Although non-MAFLD patients had less NASH,they present with similar proportion of significant fibrosis and cirrhosis.In the diagnostic criteria of MAFLD,BMI≥23 kg/m2 was related to NASH(Mantel-Haenszel Common Estimate OR:2.975;95%CI:1.037–8.538;P=0.043),and T2 DM was related to significant fibrosis(Mantel-Haenszel Common Estimate OR:2.531;95%CI:1.388–4.613;P=0.002).The homeostasis model assessment of insulin resistance(HOMA-IR)≥2.5 was the most significant factor for NASH(OR:4.100;95%CI:1.772–9.487;P=0.001)and significant factor for liver fibrosis(OR:2.947;95%CI:1.398–6.210;P=0.004)after the adjustments of the BMI and diabetes.Conclusions:Metabolic dysregulations are important risk factors in NAFLD progression.The insulin resistance status may play a predominant role in the progression in MAFLD patients.

Hepatopulmonary metastases from papillary thyroid microcarcinoma:A case report

BACKGROUND Papillary thyroid carcinoma(PTC)is the most common endocrine malignancy.Papillary thyroid microcarcinoma(PTMC)accounts for the majority of PTC cases.However,concurrent pulmonary and hepatic metastases of PTMC are rarely seen.Here,we present a patient with coexisting liver and lung metastases from PTMC.CASE SUMMARY We describe a 26-year-old woman with PTMC with multiple concurrent metastases.After 3 d of unexplained fever,she was admitted to our hospital.Her thyroid functional tests were abnormal.Her positron emission tomography(PET)/magnetic resonance imaging(MRI)examination showed increased fluorodeoxyglucose(FDG)metabolism and space-occupying lesions in the left lobe of the thyroid.Additionally,PET/MRI images revealed multiple nodules in the lung and liver with increased FDG metabolism.Chest computer tomography(CT)showed multiple pulmonary metastases.Abdominal ultrasound and liver MRI showed multiple space-occupying lesions in the liver.The patient underwent total thyroidectomy and central lymph node dissection.Postoperative pathological analysis showed a papillary microcarcinoma multiplex in the left lobe of the thyroid.A diagnosis of hepatopulmonary metastases from papillary thyroid microcarcinoma was made.The patient was given iodine-131 treatment one year after the surgery.She recovered well after the operation,and the incision healed well.After discharge,she was treated with oral levothyroxine sodium tablets,and symptomatic and supportive treatments were also given to promote radioactive excretion and prevent bone marrow suppression by iodine-131 treatment.CONCLUSION Since patients with thyroid cancer concurrent with hepatopulmonary metastases have rarely been reported,our case will highlight the clinical and pathological profiles of these patients.

Trastuzumab,not lapatinib,has therapeutic effects on Chinese patients with HER2-positive cholangiocarcinoma

As a relatively uncommon orphan tumor with high mortality,biliary tract cancer(BTC)presents an aggressive course and heterogeneous clinical features[1].BTC patients present with advanced manifestations[2].Unfortunately,there has been little progress in the management of BTC.Most patients have inoperable lesions and must receive palliative therapy.Gemcitabine-based chemotherapy has been the only widely accepted first-line treatment for advanced BTC[3].Nevertheless,BTCs are often refractory to chemotherapeutic regimens,leading to a poor clinical outcome in these patients.Recently,with the rapid development of next generation sequencing(NGS)technologies,some actionable mutations such as those in IDH1,FGFR2,BRAF,HER2 genes,and unique molecular subsets in BTCs have been identified[4],and related targeted therapy against actionable mutations has been introduced into clinical practice as a promising therapeutic strategy[5].

LEARN algorithm:a novel option for predicting non-alcoholic steatohepatitis

Background:There is an unmet need for accurate non-invasive methods to diagnose non-alcoholic steatohepatitis(NASH).Since impedance-based measurements of body composition are simple,repeatable and have a strong association with non-alcoholic fatty liver disease(NAFLD)severity,we aimed to develop a novel and fully automatic machine learning algorithm,consisting of a deep neural network based on impedance-based measurements of body composition to identify NASH[the bioeLectrical impEdance Analysis foR Nash(LEARN)algorithm].Methods:A total of 1,259 consecutive subjects with suspected NAFLD were screened from six medical centers across China,of which 766 patients with biopsy-proven NAFLD were included in final analysis.These patients were randomly subdivided into the training and validation groups,in a ratio of 4:1.The LEARN algorithm was developed in the training group to identify NASH,and subsequently,tested in the validation group.Results:The LEARN algorithm utilizing impedance-based measurements of body composition along with age,sex,pre-existing hypertension and diabetes,was able to predict the likelihood of having NASH.This algorithm showed good discriminatory ability for identifying NASH in both the training and validation groups[area under the receiver operating characteristics(AUROC):0.81,95%CI:0.77-0.84 and AUROC:0.80,95%CI:0.73-0.87,respectively].This algorithm also performed better than serum cytokeratin-18 neoepitope M30(CK-18 M30)level or other non-invasive NASH scores(including HAIR,ION,NICE)for identifying NASH(P value<0.001).Additionally,the LEARN algorithm performed well in identifying NASH in different patient subgroups,as well as in subjects with partial missing body composition data.Conclusions:The LEARN algorithm,utilizing simple easily obtained measures,provides a fully automated,simple,non-invasive method for identifying NASH.

From NAFLD to MAFLD:a“redefining”moment for fatty liver disease

The term non-alcoholic fatty liver disease(NAFLD)was coined in 1980 to characterize a disease similar to alcoholic fatty liver disease that developed in patients without a history of excessive alcohol intake.[1]Morphologically,NAFLD is characterized by excess fatty infiltration of the liver in the absence of known causes of liver disease(eg,alcohol,autoimmune liver disease,viral hepatitis,etc).The clinical manifestations of NAFLD(both hepatic and extrahepatic)depend on the outcome of complex interactions between its primary drivers including poor lifestyle habits and diet,a dysfunctional microbiota,genetic predisposition,and environmental cues that result in metabolic dysfunction and liver disease.However,bringing all patients with their markedly different clinical courses under the NAFLD umbrella belies its complexity and implies a homogeneous disease state that then negatively impacts clinical management and a deeper understanding of pathogenesis.With advances in current knowledge on the spectrum of fatty liver diseases,it is apparent that the fourdecade-old outdated term NAFLD can no longer serve to usefully describe a highly heterogeneous disease.The disease as we understand it today not only impacts patients who consume alcohol and those who do not,but also potentially impacts all patients with any form of liver disease,by acting as a disease modifier.[2]

Metabolic Disorders Combined with Noninvasive Tests to Screen Advanced Fibrosis in Nonalcoholic Fatty Liver Disease

Background and Aims:Nonalcoholic fatty liver disease(NAFLD)is associated with metabolic disorders.This study aimed to explore the role of metabolic disorders in screening advanced fibrosis in NAFLD patients.Methods:A total of 246 histologically-proven NAFLD patients were enrolled across 14 centers.We compared the severity of fibrosis in patients with different components of metabolic disorders.Based on standard noninvasive tests and metabolic disorders,we developed new algorithms to identify advanced fibrosis.Results:Metabolic syndrome(MetS)was frequent in NAFLD patients(133/246,54%).Patients with MetS had a higher proportion of significant fibrosis(p=0.014)and higher LSM values(9.2 kPa,vs.7.4 kPa,p=0.002)than those without MetS.Patients with more metabolic disorders had higher fibrosis stages(p=0.017).Reduced highdensity lipoprotein cholesterol(odds ratio[OR]:2.241,95%confidence interval[CI]:1.004–5.002,p=0.049)and raised fasting glucose(OR:4.500,95%CI:2.083–9.725,p<0.001)were significantly associated with advanced fibrosis.Using these two metabolic disorders as a screening tool,a sensitivity,specificity and accuracy of 92%,81%and 83%was achieved,respectively.With the new algorithms combining metabolic disorders with noninvasive measurements,the number of patients requiring liver biopsy was reduced,especially in combination with the Fibrosis-4 score and metabolic disorders(36%to 17%,p<0.001).In addition,this stepwise algorithm could achieve a high accuracy(85%)and high negative predictive value(93%).Conclusions:Metabolic disorders should be taken into consideration in the diagnosis of advanced fibrosis.With further validation and investigation,new algorithms could be recommended in primary care units to spare patients from unnecessary referral and liver biopsies.