Simeprevir added to peginterferon and ribavirin lessens time with fatigue,depressive symptoms and functional limitations in patients with chronic hepatitis C compared with peginterferon and ribavirin: results from 1161 patients in the QUEST‐1, QUEST‐2 and PROMISE studies

The value of adding simeprevir (SMV) vs placebo (PBO) to peginterferon and ribavirin (PR) for treatment of chronic hepatitis C virus infection was examined using patient‐reported outcomes (PROs); further, concordance of PROs with virology endpoints and adverse events (AEs) was explored. Patients (n = 768 SMV/PR, n = 393 PBO/PR) rated fatigue (FSS), depressive symptoms (CES‐D) and functional impairment (WPAI: Hepatitis C Productivity, Daily Activity and Absenteeism) at baseline and throughout treatment in three randomised, double‐blind trials comparing the addition of SMV or PBO during initial 12 weeks of PR. PR was administered for 48 weeks (PBO group) and 24/48 weeks (SMV group) using a response‐guided therapy (RGT) approach. Mean PRO scores (except Absenteeism) worsened from baseline to Week 4 to the same extent in both groups but reverted after Week 24 for SMV/PR and only after Week 48 for PBO/PR. Accordingly, there was a significantly lower area under the curve (baseline–Week 60, AUC₆₀) and fewer weeks with clinically important worsening of scores in the SMV/PR group at any time point. Incidences of patients with fatigue and anaemia AEs were similar in both groups, but FSS scores showed that clinically important increases in fatigue lasted a mean of 6.9 weeks longer with PBO/PR (P < 0.001). PRO score subgroup analysis indicated better outcomes for patients who met the criteria for RGT or achieved sustained virological response 12 weeks post‐treatment (SVR12); differences in mean PRO scores associated with fibrosis level were only observed with PBO/PR. Greater efficacy of SMV/PR enabled reduced treatment duration and reduced time with PR‐related AEs without adding to AE severity.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

Mixed Reality Combined with Three‐Dimensional Printing Technology in Total Hip Arthroplasty: An Updated Review with a Preliminary Case Presentation

Three‐dimensional (3D) printing technology, virtual reality, and augmented reality technology have been used to help surgeons to complete complex total hip arthroplasty, while their respective shortcomings limit their further application. With the development of technology, mixed reality (MR) technology has been applied to improve the success rate of complicated hip arthroplasty because of its unique advantages. We presented a case of a 59‐year‐old man with an intertrochanteric fracture in the left femur, who had received a prior left hip fusion. After admission to our hospital, a left total hip arthroplasty was performed on the patient using a combination of MR technology and 3D printing technology. Before surgery, 3D reconstruction of a certain bony landmark exposed in the surgical area was first performed. Then a veneer part was designed according to the bony landmark and connected to a reference registration landmark outside the body through a connecting rod. After that, the series of parts were made into a holistic reference registration instrument using 3D printing technology, and the patient's data for bone and surrounding tissue, along with digital 3D information of the reference registration instrument, were imported into the head‐mounted display (HMD). During the operation, the disinfected reference registration instrument was installed on the selected bony landmark, and then the automatic real‐time registration was realized by HMD through recognizing the registration landmark on the reference registration instrument, whereby the patient's virtual bone and other anatomical structures were quickly and accurately superimposed on the real body of the patient. To the best of our knowledge, this is the first report to use MR combined with 3D printing technology in total hip arthroplasty.     

单纯 Ilizarov 环形外固定技术治疗合并骨筋膜室综合征的胫骨平台骨折

目的探讨单纯 Ilizarov 环形外固定技术治疗合并骨筋膜室综合征的胫骨平台骨折的疗效。方法2013 年 9 月—2017 年 3 月，收治 30 例合并骨筋膜室综合征的胫骨平台骨折患者，采用单纯 Ilizarov 环形外固定技术治疗。男 23 例，女 7 例；年龄 23～43 岁，平均 34.4 岁。致伤原因：交通事故伤 12 例，高处坠落伤 4 例，摔伤 8 例，重物砸伤 6 例。受伤至入院时间 1～12 h，平均 4.8 h。骨折 Schatzker 分型：Ⅱ型 1 例、Ⅲ型 3 例、Ⅳ型 10 例、Ⅴ型 7 例、Ⅵ型 9 例。30 例均因骨筋膜室综合征行切开减压；切开减压至手术时间为 10～15 d，平均 12.5 d。治疗后采用膝关节学会评分系统（KSS）及 Ilizarov 方法研究与应用协会（ASAMI）协议评价膝关节功能。结果手术时间 110～155 min，平均 123.1 min；术中出血量 100～500 mL，平均 245 mL；术后住院时间 3～5 d，平均 3.8 d。患者均获随访，随访时间 20～24 周，平均 22.7 周。除 2 例患者出现针道感染征象外，无其他并发症发生。X 线片复查显示骨折均愈合，愈合时间 10～20 周，平均 14.6 周。末次随访时，膝关节 KSS 临床评分总分为 70～95 分，平均 87.5 分；功能评分总分为 70～90 分，平均 79.0 分。参照 ASAMI 协议评价获优 24 例、良 3 例、可 2 例、差 1 例。结论对于合并骨筋膜室综合征的胫骨平台骨折，单纯 Ilizarov 环形外固定技术治疗后患者关节功能可以基本恢复且并发症少，是一项相对安全、有效的治疗方法。     

TGFβ promotes YAP‐dependent AXL induction in mesenchymal‐type lung cancer cells

The acquisition of chemoresistance remains a major cause of cancer mortality due to the limited accessibility of targeted or immune therapies. However, given that severe alterations of molecular features during epithelial‐to‐mesenchymal transition (EMT) lead to acquired chemoresistance, emerging studies have focused on identifying targetable drivers associated with acquired chemoresistance. Particularly, AXL, a key receptor tyrosine kinase that confers resistance against targets and chemotherapeutics, is highly expressed in mesenchymal cancer cells. However, the underlying mechanism of AXL induction in mesenchymal cancer cells is poorly understood. Our study revealed that the YAP signature, which was highly enriched in mesenchymal‐type lung cancer, was closely correlated to AXL expression in 181 lung cancer cell lines. Moreover, using isogenic lung cancer cell pairs, we also found that doxorubicin treatment induced YAP nuclear translocation in mesenchymal‐type lung cancer cells to induce AXL expression. Additionally, the concurrent activation of TGFβ signaling coordinated YAP‐dependent AXL expression through SMAD4. These data suggest that crosstalk between YAP and the TGFβ/SMAD axis upon treatment with chemotherapeutics might be a promising target to improve chemosensitivity in mesenchymal‐type lung cancer.

Abbreviations

AUC

area under the curve

AXL

AXL receptor tyrosine kinase

BCL2

B‐cell lymphoma 2

CTD2

cancer target discovery and development

CTGF

connective tissue growth factor

DEG

differentially expressed genes

DOXO

doxorubicin

EMT

epithelial–mesenchymal transition

Eto

etoposide

FDA

Food and Drug Administration

ITGB3

integrin beta‐3

MAPK

mitogen‐activated protein kinase

MMP2

matrix metalloproteinase‐2

MMP9

matrix metalloproteinase‐9

mRNA

messenger RNA

NF‐κB

nuclear factor kappa‐light‐chain‐enhancer of activated B cells

SBE

SMAD binding element

SERPINE1

serpin family E member 1

siRNA

small interfering RNA

ssGSEA

single‐sample gene set enrichment analysis

TCGA

The Cancer Genome Atlas

TGFβ

transforming growth factor beta

YAP

Yes‐associated protein

YAP8SA

mutants of inhibitory phosphorylation site at eight serine to Alanine of YAP

ZEB1

zinc finger E‐box binding homeobox 1

ZEB2

zinc finger E‐box‐binding homeobox 2