Prediction of Lymph Node Metastasis in T1 Colorectal Cancer Using Artificial Intelligence with Hematoxylin and Eosin-Stained Whole-Slide-Images of Endoscopic and Surgical Resection Specimens

According to the current guidelines, additional surgery is performed for endoscopically resected specimens of early colorectal cancer (CRC) with a high risk of lymph node metastasis (LNM). However, the rate of LNM is 2.1-25.0% in cases treated endoscopically followed by surgery, indicating a high rate of unnecessary surgeries. Therefore, this study aimed to develop an artificial intelligence (AI) model using H&E-stained whole slide images (WSIs) without handcrafted features employing surgically and endoscopically resected specimens to predict LNM in T1 CRC. To validate with an independent cohort, we developed a model with four versions comprising various combinations of training and test sets using H&E-stained WSIs from endoscopically (400 patients) and surgically resected specimens (881 patients): Version 1, Train and Test: surgical specimens; Version 2, Train and Test: endoscopic and surgically resected specimens; Version 3, Train: endoscopic and surgical specimens and Test: surgical specimens; Version 4, Train: endoscopic and surgical specimens and Test: endoscopic specimens. The area under the curve (AUC) of the receiver operating characteristic curve was used to determine the accuracy of the AI model for predicting LNM with a 5-fold cross-validation in the training set. Our AI model with H&E-stained WSIs and without annotations showed good performance power with the validation of an independent cohort in a single center. The AUC of our model was 0.758-0.830 in the training set and 0.781-0.824 in the test set, higher than that of previous AI studies with only WSI. Moreover, the AI model with Version 4, which showed the highest sensitivity (92.9%), reduced unnecessary additional surgery by 14.2% more than using the current guidelines (68.3% vs. 82.5%). This revealed the feasibility of using an AI model with only H&E-stained WSIs to predict LNM in T1 CRC.

Transcriptional Changes in Radiation-Induced Lung Injury: A Comparative Analysis of Two Radiation Doses for Preclinical Research

In a recent stereotactic body radiation therapy animal model, radiation pneumonitis and radiation pulmonary fibrosis were observed at around 2 and 6 weeks, respectively. However, the molecular signature of this model remains unclear. This study aimed to examine the molecular characteristics at these two stages using RNA-seq analysis. Transcriptomic profiling revealed distinct transcriptional patterns for each stage. Inflammatory response and immune cell activation were involved in both stages. Cell cycle processes and response to type II interferons were observed during the inflammation stage. Extracellular matrix organization and immunoglobulin production were noted during the fibrosis stage. To investigate the impact of a 10 Gy difference on fibrosis progression, doses of 45, 55, and 65 Gy were tested. A dose of 65 Gy was selected and compared with 75 Gy. The 65 Gy dose induced inflammation and fibrosis as well as the 75 Gy dose, but with reduced lung damage, fewer inflammatory cells, and decreased collagen deposition, particularly during the inflammation stage. Transcriptomic analysis revealed significant overlap, but differences were observed and clarified in Gene Ontology and KEGG pathway analysis, potentially influenced by changes in interferon-gamma-mediated lipid metabolism. This suggests the suitability of 65 Gy for future preclinical basic and pharmaceutical research connected with radiation-induced lung injury.

Intercellular cross-talk through lineage-specific gap junction of cancer-associated fibroblasts related to stromal fibrosis and prognosis

Stromal fibrosis in cancer is usually associated with poor prognosis and chemotherapy resistance. It is thought to be caused by fibroblasts; however, the exact mechanism is not yet well understood. The study aimed to identify lineage-specific cancer-associated fibroblast (CAF) subgroup and their associations with extracellular matrix remodeling and clinical significances in various tumor types using single-cell and bulk RNA sequencing data. Through unsupervised clustering, six subclusters of CAFs were identified, including a cluster with exclusively high gap junction protein beta-2 (GJB2) expression. This cluster was named GJB2-positive CAF. It was found to be a unique subgroup of terminally differentiated CAFs associated with collagen gene expression and extracellular matrix remodeling. GJB2-positive CAFs showed higher communication frequency with vascular endothelial cells and cancer cells than GJB2-negative CAFs. Moreover, GJB2 was poorly expressed in normal tissues, indicating that its expression is dependent on interaction with other cells, including vascular endothelial cells and cancer cells. Finally, the study investigated the clinical significance of GJB2 signature score for GJB2-positive CAFs in cancer and found a correlation with poor prognosis. These results suggest that GJB2-positive CAF is a unique fibroblast subtype involved in extracellular matrix remodeling, with significant clinical implications in cancer.

Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer

BACKGROUND

When endoscopically resected specimens of early colorectal cancer (CRC) show high-risk features, surgery should be performed based on current guidelines because of the high-risk of lymph node metastasis (LNM). The aim of this study was to determine the utility of an artificial intelligence (AI) with deep learning (DL) of hematoxylin and eosin (H&E)-stained endoscopic resection specimens without manual-pixel-level annotation for predicting LNM in T1 CRC. In addition, we assessed AI performance for patients with only submucosal (SM) invasion depth of 1000 to 2000 μm known to be difficult to predict LNM in clinical practice.

METHODS

H&E-stained whole slide images (WSIs) were scanned for endoscopic resection specimens of 400 patients who underwent endoscopic treatment for newly diagnosed T1 CRC with additional surgery. The area under the curve (AUC) of the receiver operating characteristic curve was used to determine the accuracy of AI for predicting LNM with a fivefold cross-validation in the training set and in a held-out test set.

RESULTS

We developed an AI model using a two-step attention-based DL approach without clinical features (AUC, 0.764). Incorporating clinical features into the model did not improve its prediction accuracy for LNM. Our model reduced unnecessary additional surgery by 15.1% more than using the current guidelines (67.4% vs. 82.5%). In patients with SM invasion depth of 1000 to 2000 μm, the AI avoided 16.1% of unnecessary additional surgery than using the JSCCR guidelines.

CONCLUSIONS

Our study is the first to show that AI trained with DL of H&E-stained WSIs has the potential to predict LNM in T1 CRC using only endoscopically resected specimens with conventional histologic risk factors.

Deep learning-based virtual cytokeratin staining of gastric carcinomas to measure tumor-stroma ratio

The tumor-stroma ratio (TSR) determined by pathologists is subject to intra- and inter-observer variability. We aimed to develop a computational quantification method of TSR using deep learning-based virtual cytokeratin staining algorithms. Patients with 373 advanced (stage III [n = 171] and IV [n = 202]) gastric cancers were analyzed for TSR. Moderate agreement was observed, with a kappa value of 0.623, between deep learning metrics (dTSR) and visual measurement by pathologists (vTSR) and the area under the curve of receiver operating characteristic of 0.907. Moreover, dTSR was significantly associated with the overall survival of the patients (P = 0.0024). In conclusion, we developed a virtual cytokeratin staining and deep learning-based TSR measurement, which may aid in the diagnosis of TSR in gastric cancer.

Clinical Outcomes and Adverse Events of Gastric Endoscopic Submucosal Dissection of the Mid to Upper Stomach under General Anesthesia and Monitored Anesthetic Care

Background/Aims

Endoscopic submucosal dissection (ESD) of gastric tumors in the mid-to-upper stomach is a technically challenging procedure. This study compared the therapeutic outcomes and adverse events of ESD of tumors in the mid-to-upper stomach performed under general anesthesia (GA) or monitored anesthesia care (MAC).

Methods

Between 2012 and 2018, 674 patients underwent ESD for gastric tumors in the midbody, high body, fundus, or cardia (100 patients received GA; 574 received MAC). The outcomes of the propensity score (PS)-matched (1:1) patients receiving either GA or MAC were analyzed.

Results

The PS matching identified 94 patients who received GA and 94 patients who received MAC. Both groups showed high rates ofen bloc resection (GA, 95.7%; MAC, 97.9%; p=0.68) and complete resection (GA, 81.9%; MAC, 84.0%; p=0.14). There were no significant differences between the rates of adverse events (GA, 16.0%; MAC, 8.5%; p=0.18) in the anesthetic groups. Logistic regression analysis indicated that the method of anesthesia did not affect the rates of complete resection or adverse events.

Conclusions

ESD of tumors in the mid-to-upper stomach at our high-volume center had good outcomes, regardless of the method of anesthesia. Our results demonstrate no differences between the efficacies and safety of ESD performed under MAC and GA.

Predicting Successes and Failures of Clinical Trials With Outer Product-Based Convolutional Neural Network

Despite several improvements in the drug development pipeline over the past decade, drug failures due to unexpected adverse effects have rapidly increased at all stages of clinical trials. To improve the success rate of clinical trials, it is necessary to identify potential loser drug candidates that may fail at clinical trials. Therefore, we need to develop reliable models for predicting the outcomes of clinical trials of drug candidates, which have the potential to guide the drug discovery process. In this study, we propose an outer product–based convolutional neural network (OPCNN) model which integrates effectively chemical features of drugs and target-based features. The validation results via 10-fold cross-validations on the dataset used for a data-driven approach PrOCTOR proved that our OPCNN model performs quite well in terms of accuracy, F1-score, Matthews correlation coefficient (MCC), precision, recall, area under the curve (AUC) of the receiver operating characteristic, and area under the precision–recall curve (AUPRC). In particular, the proposed OPCNN model showed the best performance in terms of MCC, which is widely used in biomedicine as a performance metric and is a more reliable statistical measure. Through 10-fold cross-validation experiments, the accuracy of the OPCNN model is as high as 0.9758, F1 score is as high as 0.9868, the MCC reaches 0.8451, the precision is as high as 0.9889, the recall is as high as 0.9893, the AUC is as high as 0.9824, and the AUPRC is as high as 0.9979. The results proved that our OPCNN model shows significantly good prediction performance on outcomes of clinical trials and it can be quite helpful in early drug discovery.

Tumor Margin Contains Prognostic Information: Radiomic Margin Characteristics Analysis in Lung Adenocarcinoma Patients

Simple Summary

The tumor microenvironment is a dynamic area, with continuous interaction between tumor cells and their surrounding environment. We aimed to investigate the relationship between tumor radiomic margin characteristics and prognosis in patients with lung cancer. When compared to the model with clinical variables only (C-index = 0.738), the model incorporating clinical variables and radiomic margin characteristics (C-index = 0.753) demonstrated a higher C-index for predicting overall survival. In the model integrating both clinical variables and radiomic margin characteristics, convexity, Laplace of Gaussian (LoG) kurtosis 3, and roundness factor were independent predictive factors of overall survival. Our study showed that radiomic margin characteristics helped predict overall survival in patients with lung adenocarcinomas, thus implying that the tumor margin contains prognostic information.

Abstract

We aimed to investigate the relationship between tumor radiomic margin characteristics and prognosis in patients with lung cancer. We enrolled 334 patients who underwent complete resection for lung adenocarcinoma. A quantitative computed tomography analysis was performed, and 76 radiomic margin characteristics were extracted. The radiomic margin characteristics were correlated with overall survival. The selected clinical variables and radiomic margin characteristics were used to calculate a prognostic model with subsequent internal and external validation. Nearly all of the radiomic margin characteristics showed excellent reproducibility. The least absolute shrinkage and selection operator (LASSO) method was used to select eight radiomic margin characteristics. When compared to the model with clinical variables only (C-index = 0.738), the model incorporating clinical variables and radiomic margin characteristics (C-index = 0.753) demonstrated a higher C-index for predicting overall survival. In the model integrating both clinical variables and radiomic margin characteristics, convexity, a Laplace of Gaussian (LoG) kurtosis of 3, and the roundness factor were each independently predictive of overall survival. In addition, radiomic margin characteristics were also correlated with the micropapillary subtype, and the sphericity value was able to predict the presence of the micropapillary subtype. In conclusion, our study showed that radiomic margin characteristics helped predict overall survival in patients with lung adenocarcinomas, thus implying that the tumor margin contains prognostic information.

Eradication of Helicobacter pylori infection decreases risk for dyslipidemia: A cohort study

BACKGROUND

Previous studies have suggested a relationship between Helicobacter pylori infection and dyslipidemia; however, large-scale longitudinal studies have not elucidated this association. This study assessed the longitudinal effects of H. pylori infection and eradication on lipid profiles in a large cohort.

METHODS

This cohort study included 2,626 adults without dyslipidemia at baseline, who participated in a repeated, regular health-screening examination, which included upper gastrointestinal endoscopy, between January 2009 and December 2018. The primary outcome was incident dyslipidemia at follow-up.

RESULTS

During the 10,324 person-years of follow-up, participants with persistent H. pylori infection had a higher incidence rate (130.5 per 1,000 person-years) of dyslipidemia than those whose infections had been successfully controlled (98.1 per 1,000 person-years). In a multivariable model adjusted for age, sex, waist circumference, smoking status, alcohol intake, and education level, the H. pylori eradication group was associated with a lower risk of dyslipidemia than the persistent group (HR, 0.85; 95% CI, 0.77-0.95; p = 0.004). The association persisted after further adjustment for baseline levels of low-density and high-density lipoprotein cholesterol (HR, 0.87; 95% CI, 0.79-0.97; p = 0.014).

CONCLUSIONS

H. pylori infection may play a pathophysiologic role in the development of dyslipidemia, whereas H. pylori eradication might decrease the risk of dyslipidemia.

Prediction of drug-target binding affinity using similarity-based convolutional neural network

Identifying novel drug–target interactions (DTIs) plays an important role in drug discovery. Most of the computational methods developed for predicting DTIs use binary classification, whose goal is to determine whether or not a drug–target (DT) pair interacts. However, it is more meaningful but also more challenging to predict the binding affinity that describes the strength of the interaction between a DT pair. If the binding affinity is not sufficiently large, such drug may not be useful. Therefore, the methods for predicting DT binding affinities are very valuable. The increase in novel public affinity data available in the DT-related databases enables advanced deep learning techniques to be used to predict binding affinities. In this paper, we propose a similarity-based model that applies 2-dimensional (2D) convolutional neural network (CNN) to the outer products between column vectors of two similarity matrices for the drugs and targets to predict DT binding affinities. To our best knowledge, this is the first application of 2D CNN in similarity-based DT binding affinity prediction. The validation results on multiple public datasets show that the proposed model is an effective approach for DT binding affinity prediction and can be quite helpful in drug development process.

Deep learning method for comet segmentation and comet assay image analysis

Comet assay is a widely used method, especially in the field of genotoxicity, to quantify and measure DNA damage visually at the level of individual cells with high sensitivity and efficiency. Generally, computer programs are used to analyze comet assay output images following two main steps. First, each comet region must be located and segmented, and next, it is scored using common metrics (e.g., tail length and tail moment). Currently, most studies on comet assay image analysis have adopted hand-crafted features rather than the recent and effective deep learning (DL) methods. In this paper, however, we propose a DL-based baseline method, called DeepComet, for comet segmentation. Furthermore, we created a trainable and testable comet assay image dataset that contains 1037 comet assay images with 8271 manually annotated comet objects. From the comet segmentation test results with the proposed dataset, the DeepComet achieves high average precision (AP), which is an essential metric in image segmentation and detection tasks. A comparative analysis was performed between the DeepComet and the state-of-the-arts automatic comet segmentation programs on the dataset. Besides, we found that the DeepComet records high correlations with a commercial comet analysis tool, which suggests that the DeepComet is suitable for practical application.

Clinical T category for lung cancer staging: A pragmatic approach for real-world practice

BACKGROUND

To determine which components should be measured and which window settings are appropriate for computerized tomography (CT) size measurements of lung adenocarcinoma (ADC) and to explore interobserver agreement and accuracy according to the eighth edition of TNM staging.

METHODS

A total of 165 patients with surgically resected lung ADC earlier than stage 3A were included in this study. One radiologist and two pulmonologists independently measured the total and solid sizes of components of tumors on different window settings and assessed solidity. CT measurements were compared with pathologic size measurements.

RESULTS

In categorizing solidity, 25% of the cases showed discordant results among observers. Measuring the total size of a lung adenocarcinoma predicted pathologic invasive components to a degree similar to measuring the solid component. Lung windows were more accurate (intraclass correlation [ICC] = 0.65-0.81) than mediastinal windows (ICC = 0.20-0.72) at predicting pathologic invasive components, especially in a part-solid nodule. Interobserver agreements for measurement of solid components were good with little significant difference (lung windows, ICC = 0.89; mediastinal windows, ICC = 0.91). A high level of interobserver agreement was seen between the radiologist and pulmonologists and between residents (from the division of pulmonology and critical care) versus a fellow (from the division of pulmonology and critical care) on different windows.

CONCLUSIONS

A considerable percentage (25%) of discrepancies was encountered in categorizing the solidity of lesions, which may decrease the accuracy of measurements. Lung window settings may be superior to mediastinal windows for measuring lung ADCs, with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components.

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: Lung window settings are better for evaluating part-solid lung adenocarcinoma (ADC), with comparable interobserver agreement and moderate accuracy for predicting pathologic invasive components. The considerable percentage (25%) of discrepancies in categorizing solidity of the lesions may also have decreased the accuracy of measurements.

WHAT THIS STUDY ADDS

For accurate measurement and categorization of lung ADC, robust quantitative analysis is needed rather than a simple visual assessment.

Outcomes of Inhaled Amikacin and Clofazimine-Containing Regimens for Treatment of Refractory Mycobacterium avium Complex Pulmonary Disease

Limited data are available regarding optimal treatment for refractory Mycobacterium avium complex-pulmonary disease (MAC-PD). We evaluated outcomes of inhaled amikacin (AMK) with clofazimine (CFZ) regimens as an add-on salvage therapy for refractory MAC-PD. We retrospectively analyzed 52 patients with refractory MAC-PD, characterized by persistently positive sputum cultures despite >6 months of treatment. Thirty-five (67%) patients had M. intracellulare-PD, and 17 (33%) patients had M. avium-PD. Twenty-seven (52%) patients received the salvage therapy for ≥12 months, whereas 25 (48%) patients were treated for <12 months due to adverse effects or other reasons. Seventeen (33%) patients had culture conversion: 10 (10/27) in the ≥12-month treatment group and seven (7/25) in the <12-month treatment group (p = 0.488). Microbiological cure, defined as maintenance of culture negativity, was achieved in 12 (23%) patients; six (6/12) with accompanying symptomatic improvement were considered to have reached cure. Clinical cure, defined as symptomatic improvement with <3 consecutive negative cultures, was achieved in three (6%) patients. Overall, 15 (29%) patients achieved favorable outcomes, including microbiological cure, cure, and clinical cure. Inhaled AMK with CFZ may provide favorable outcomes in some patients with refractory MAC-PD. However, given the adverse effects, more effective strategies are needed to maintain these therapeutic regimens.

Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics

Background

Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth.

Methods

We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume‐based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected.

Results

Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface‐to‐volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface‐to‐volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness.

Conclusions

This study demonstrated the potential of margin‐related radiomic features to predict tumor DT in lung ADCs.

Key points

Significant findings of the study

We found a relationship between margin‐related radiomic features and tumor doubling time.

What this study adds

Margin‐related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies.

Parallel comparison and combining effect of radiomic and emerging genomic data for prognostic stratification of non-small cell lung carcinoma patients

BACKGROUND

A single institution retrospective analysis of 124 non-small cell lung carcinoma (NSCLC) patients was performed to identify whether disease-free survival (DFS) achieves incremental values when radiomic and genomic data are combined with clinical information.

METHODS

Using the least absolute shrinkage and selection operator (LASSO) Cox regression method, radiomic and genetic features were reduced in number for selection of the most useful prognostic feature. We created four models using only baseline clinical data, clinical data with selected genetic features, clinical data with selected radiomic features, and clinical data with selected genetic and radiomic features together. Multivariate Cox proportional hazards analysis was performed to determine predictors of DFS. Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for DFS prediction by four constructed models at the five-year time point.

RESULTS

On precontrast scan, improved discrimination performance was obtained in a merging of selected radiomics and genetics (AUC = 0.8638), compared with clinical data only (AUC = 0.7990), selected genetic features (AUC = 0.8497), and selected radiomic features (AUC = 0.8355). On post-contrast scan, discrimination performance was improved (AUC = 0.8672) compared with the clinical variables (AUC = 0.7913), and selected genetic features (AUC = 0.8376) and selected radiomic features (AUC = 0.8399) were considered.

CONCLUSIONS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating clinicopathologic model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for disease-free survival (DFS). The discriminative performance for DFS was better when combining radiomic and genetic features compared to clinical data only, selected genetic features, and selected radiomic features.

WHAT THIS STUDY ADDS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating a clinicopathological model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

Development and Validation of a Novel Warfarin Dosing Algorithm for Korean Patients With VKORC1 1173C

BACKGROUND

Differences in the performance of suggested warfarin dosing algorithms among different ethnicities and genotypes have been reported; this necessitates the development of an algorithm with enhanced performance for specific population groups. Previous warfarin dosing algorithms underestimated warfarin doses in VKORC1 1173C carriers. We aimed to develop and validate a new warfarin dosing algorithm for Korean patients with VKORC1 1173C.

METHODS

A total of 109 patients carrying VKORC1 1173CT (N=105) or 1173CC (N=4) were included in this study. Multiple regression analysis was performed to deduce a new dosing algorithm. Following literature searches for genotype-guided warfarin dosing algorithms, 21 algorithms were selected and evaluated using the correlation coefficient (ρ) of actual dose and estimated dose, mean error, and root mean square error.

RESULTS

The developed algorithm is as follows: maintenance dose (mg/week)=exp [3.223-0.009×(age)+0.577×(body surface area [BSA])+0.178×(sex)-0.481×(CYP2C9 genotype)+0.227×(VKORC1 genotype)]. Integrated variables explained 44% of the variance in the maintenance dose. The predicted and actual doses showed moderate correlation (ρ=0.641) with the best performance with a mean error of -1.30 mg/week. The proportion of underestimated groups was 17%, which was lower than with the other algorithms.

CONCLUSIONS

This is the first study to develop and validate a warfarin dosing algorithm based on data from VKORC1 1173C carriers; it showed superior predictive performance compared with previously published algorithms.

Clinical Significance of Systemic Inflammation Markers in Newly Diagnosed, Previously Untreated Hepatocellular Carcinoma

This study aimed to investigate the clinical significance of systemic inflammation markers (SIMs)-including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR)-in patients with newly diagnosed, previously untreated hepatocellular carcinoma (HCC). The present study was performed using prospectively collected registry data of newly diagnosed, previously untreated HCC from a single institution. The training set included 6619 patients from 2005 to 2013 and the validation set included 2084 patients from 2014 to 2016. The SIMs as continuous variables significantly affected the overall survival (OS), and the optimal cut-off value of NLR, PLR, and LMR was 3.0, 100.0, and 3.0, respectively. There were significant correlations between SIMs and the albumin-bilirubin grade/Child-Turcotte-Pugh class (indicative of liver function status) and the staging system/portal vein invasion (indicative of the tumor burden). The OS curves were well stratified according to the prognostic model of SIMs and validated using the bootstrap method (1000 times, C-index 0.6367, 95% confidence interval (CI) 0.6274-0.6459) and validation cohort (C-index 0.6810, 95% CI 0.6570-0.7049). SIMs showed significant prognostic ability for OS, independent of liver function and tumor extent, although these factors were significantly correlated with SIMs in patients with newly diagnosed, previously untreated HCC.

Dysregulated miRNA in a cancer-prone environment: A study of gastric non-neoplastic mucosa

Understanding cancer-prone environments is important to efficiently detect and prevent cancers. The associations between miRNA and cancer-prone environments are still largely unknown in gastric cancer (GC). Six miRNAs that are differentially expressed during gastric carcinogenesis were selected, and quantitative real-time PCR was performed in an independent training set (fresh non-tumor and tumor samples from 18 GC patients) and validation sets (set 1 with formalin-fixed paraffin-embedded non-tumor and tumor samples from 19 solitary GC and set 2 with 37 multiple GC patients). The results were compared with those of 37 gastric mucosa from 20 healthy volunteers. The expression levels of miR-26a, miR-375, and miR-1260 in gastric mucosa from healthy volunteers were statistically higher than that of non-tumorous gastric mucosa located 3 cm apart from the GC in the training set (miR-26a, P < 0.0001; miR-375, P = 0.0049; miR-1260, P = 0.0172), validation set 1 (miR-26a and miR-375, P < 0.0001; miR-1260, P = 0.0008), and validation set 2 (miR-26a, miR-375, and miR-1260, P < 0.0001). And a combination of miR-26a and miR-1260 showed the highest area under the curve value of 0.89. miRNAs are differentially expressed in non-neoplastic gastric mucosa and can be used as a biomarker to predict cancer-prone environments.

Deciphering the tumor microenvironment through radiomics in non-small cell lung cancer: Correlation with immune profiles

Growing evidence suggests that the efficacy of immunotherapy in non-small cell lung cancers (NSCLCs) is associated with the immune microenvironment within the tumor. We aimed to explore radiologic phenotyping using a radiomics approach to assess the immune microenvironment in NSCLC. Two independent NSCLC cohorts (training and test sets) were included. Single-sample gene set enrichment analysis was used to determine the tumor microenvironment, where type 1 helper T (Th1) cells, type 2 helper T (Th2) cells, and cytotoxic T cells were the targets for prediction with computed tomographic (CT) radiomic features. Multiple algorithms were in the modeling followed by final model selection. The training dataset comprised 89 NSCLCs and the test set included 60 cases of lung squamous cell carcinoma and adenocarcinoma. A total of 239 CT radiomic features were used. A linear discriminant analysis model was selected for the final model of Th2 cell group prediction. The area under the curve value of the final model on the test set was 0.684. Predictors of the linear discriminant analysis model were skewness (total and outer pixels), kurtosis, variance (subsampled from delta [subtraction inner pixels from outer pixels]), and informational measure of correlation. The performances of radiomics on test set of Th1 and cytotoxic T cell were not accurate enough to be predictable. A radiomics approach can be used to interrogate an entire tumor in a noninvasive manner and provide added diagnostic value to identify the immune microenvironment of NSCLC, in particular, Th2 cell signatures.

Impact of Angiotensin Receptor Blockers, Beta Blockers, Calcium Channel Blockers and Thiazide Diuretics on Survival of Ovarian Cancer Patients

Purpose

We investigated the impact of four types of antihypertensive medications, angiotensin receptor blockers (ARBs), beta blockers (BBs; both selective and non-selective), calcium channel blockers (CCBs), and thiazide diuretics (TDs) on survival outcomes in epithelial ovarian cancer (EOC).

Materials and Methods

A single-institutional retrospective chart review of 878 patients with EOC was performed. Survival was compared according to use of the four antihypertensive medications during primary treatment. Propensity score matching (ratio 1:3) was performed to control possible associated covariates, such as age, International Federation of Gynecology and Obstetrics stage, residual status after primary debulking surgery, and co-morbidity.

Results

Among 878 patients, 56 patients (6.4%) were ARB users, 62 (7.1%) were BB users, 107 (12.2%) were CCBs users and 32 (3.6%) used TDs. Median progression-free survival (PFS) for ARB, BB, and CCB users was 37.8, 27.2, and 23.6 months compared with 33.6 months for non-users. ARB was associated with 35% decreased risk of disease progression (hazard ratio [HR], 0.65; 95% confidence interval [CI], 0.42 to 0.99; p=0.046) in multivariate analysis. After propensity score matching, median PFS for ARB users was 37.8 months and ARB use remained to be associated with lower recurrence rate in univariate (p=0.035) and multivariate analysis (HR, 0.60; 95% CI, 0.39 to 0.93; p=0.022).

Conclusion

In this study, ARBs use during primary treatment is associated with lower recurrence in EOC patients. However, CCBs, BBs, and TDs did not show beneficial impact.

Spontaneous mutations in the single TTN gene represent high tumor mutation burden

Tumor mutation burden (TMB) is an emerging biomarker, whose calculation requires targeted sequencing of many genes. We investigated if the measurement of mutation counts within a single gene is representative of TMB. Whole-exome sequencing (WES) data from the pan-cancer cohort (n = 10,224) of TCGA, and targeted sequencing (tNGS) and TTN gene sequencing from 24 colorectal cancer samples (AMC cohort) were analyzed. TTN was identified as the most frequently mutated gene within the pan-cancer cohort, and its mutation number best correlated with TMB assessed by WES (rho = 0.917, p < 2.2e-16). Colorectal cancer was one of good candidates for the application of this diagnostic model of TTN-TMB, and the correlation coefficients were 0.936 and 0.92 for TMB by WES and TMB by tNGS, respectively. Higher than expected TTN mutation frequencies observed in other FLAGS (FrequentLy mutAted GeneS) are associated with late replication time. Diagnostic accuracy for high TMB group did not differ between TTN-TMB and TMB assessed by tNGS. Classification modeling by machine learning using TTN-TMB for MSI-H diagnosis was constructed, and the diagnostic accuracy was 0.873 by area under the curve in external validation. TTN mutation was enriched in samples possessing high immunostimulatory signatures. We suggest that the mutation load within TTN represents high TMB status.

Comparison of CA 125 alone and risk of ovarian malignancy algorithm (ROMA) in patients with adnexal mass: A multicenter study

BACKGROUND

This multicenter study aimed to evaluate the performance of CA 125 and risk of ovarian malignancy algorithm (ROMA) in differentiating epithelial ovarian cancer (EOC) from benign adnexal mass. We consecutively enrolled 782 patients referred to tertiary hospitals with adnexal mass requiring surgical treatment. A total 322 of patients with benign adnexal disease and 327 patients with EOC were included in the analysis. Using reference cut-off values in premenopausal women, ROMA had better specificity (0.926 vs. 0.787, P < 0.001) and accuracy (0.875 vs. 0.777, P < 0.001) than CA 125 alone and comparable sensitivity (0.707 vs. 0.747, P = 0.549). Using optimum cut-off values in premenopausal women, CA 125 and ROMA had comparable specificity (0.922 vs. 0.947, P < 0.001) and accuracy (0.871 vs. 0.868, P = 0.879); however, sensitivity for CA 125 was inferior to that of ROMA (0.707 vs. 0.613, P = 0.039). In postmenopausal women, sensitivity, specificity, and accuracy were comparable between CA 125 alone and ROMA using either reference cut-off values or optimum cut-off values.ROMA showed better diagnostic performance in differentiating EOC from benign adnexal tumors among premenopausal women. However, in postmenopausal women, ROMA did not show any benefit over CA 125 alone.

Natural course and prognostic factors of chronic urticaria in Korean children: A single center experience

BACKGROUND

Chronic urticaria (CU) has an adverse effect on academic achievement and psychosocial development in children.

OBJECTIVE

We aimed to investigate the natural course of CU and to identify relevant factors associated with a poor CU prognosis in Korean children.

METHODS

We retrospectively analyzed 253 children with episodes of wheals or angioedema at least 3 times a week that persisted for at least 6 weeks. Clinical data and laboratory results were obtained from medical records and parental telephone interviews. Kaplan-Meier survival analysis and log rank tests were performed to assess the median time to remission of CU and prognostic factors.

RESULTS

Median age at onset was 5.0 years (interquartile range, 2.5-9.1) and median follow-up period was 7.6 months (interquartile range, 3.9-19.7). Of 253 patients, 68.8% had chronic inducible urticaria and 31.2% had chronic spontaneous urticaria. Physical urticaria was the only cause of chronic inducible urticaria, and the most common physical urticaria was dermographism. Median duration to remission of CU was 10.2 months (95% confidence intervals, 8.0-12.5 months). Kaplan-Meier analysis revealed that 33.4%, 53.0%, and 71.2% of children were in remission at 6, 12, and 24 months, respectively, after the onset of CU. The presence of allergic sensitization was significantly associated with a poor CU prognosis in univariable and multivariable analyses (P=0.010 and P=0.014, respectively).

CONCLUSION

Half of children with CU were in remission 10.2 months after onset. Allergic sensitization was a risk factor associated with longer duration CU.

Prevalence of and risk factors for pulmonary complications after curative resection in otherwise healthy elderly patients with early stage lung cancer

BACKGROUND AND OBJECTIVE

The prevalence of lung cancer has been increasing in healthy elderly patients with preserved pulmonary function and without underlying lung diseases. We aimed to determine the prevalence of and risk factors for postoperative pulmonary complications (PPCs) in healthy elderly patients with non-small cell lung cancer (NSCLC) to select optimal candidates for surgical resection in this subpopulation.

METHODS

We included 488 patients older than 70 years with normal spirometry results who underwent curative resection for NSCLC (stage IA-IIB) between 2012 and 2016.

RESULTS

The median (interquartile range) age of our cohort was 73 (71-76) years. Fifty-two patients (10.7%) had PPCs. Severe PPCs like acute respiratory distress syndrome, pneumonia, and respiratory failure had prevalences of 3.7, 3.7, and 1.4%, respectively. Compared to patients without PPCs, those with PPCs were more likely to be male and current smokers; have a lower body mass index (BMI), higher American Society of Anesthesiologists (ASA) classification, more interstitial lung abnormalities (ILAs), and higher emphysema index on computed tomography (CT); and have undergone pneumonectomy or bilobectomy (all p < 0.05). On multivariate analysis, ASA classification ≥3, lower BMI, ILA, and extent of resection were independently associated with PPC risk. The short-term all-cause mortality was significantly higher in patients with PPCs.

CONCLUSIONS

Curative resection for NSCLC in healthy elderly patients appeared feasible with 10% PPCs. ASA classification ≥3, lower BMI, presence of ILA on CT, and larger extent of resection are predictors of PPC development, which guide treatment decision-making in these patients.

Creatinine- and cystatin C-based estimated glomerular filtration rate slopes for the prediction of kidney outcome: a comparative retrospective study

BACKGROUND

Many studies have evaluated the usefulness of creatinine- (eGFRcr) and cystatin C-based estimated glomerular filtration rate (eGFRcys) at specific time points in predicting renal outcome. This study compared the performance of both eGFR changing slopes in identifying patients at high risk of end-stage renal disease (ESRD).

METHODS

From 2012 to 2017, patients with more than three simultaneous measurements of serum creatinine and cystatin C for 1 year were identified. Rapid progression was defined as eGFR slope < - 5 mL/min/1.73 m²/year. The primary outcome was progression to ESRD.

RESULTS

Overall, 1323 patients were included. The baseline eGFRcr and eGFRcys were 39 (27-48) and 38 (27-50) mL/min/1.73 m², respectively. Over 2.9 years (range, 2.0-3.8 years) of follow-up, 134 subjects (10%) progressed to ESRD. Both the eGFRcr and eGFRcys slopes were associated with a higher risk of ESRD, independently of baseline eGFR (hazard ratio [HR] = 0.986 [0.982-0.991] and HR = 0.988 [0.983-0.993], respectively; all p <  0.001). The creatinine- and cystatin C-based rapid progressions were associated with increased risk of ESRD (HR = 2.22 [1.57-3.13], HR = 2.03 [1.44-2.86], respectively; all p <  0.001). In the subgroup analyses, the rapid progression group, defined on the basis of creatinine levels (n = 503), showed no association between the eGFRcys slope and ESRD risk (p = 0.31), whereas the eGFRcr slope contributed to further discriminating higher ESRD risk in the subjects with rapid progression based on eGFRcys slopes (n = 463; p = 0.003).

CONCLUSIONS

Both eGFR slopes were associated with future ESRD risk. The eGFRcr slope was comparable with the eGFRcys slope in predicting kidney outcome.

Pathway genes and metabolites in thiopurine therapy in Korean children with acute lymphoblastic leukaemia

AIMS

We aimed to investigate the impact of various genetic polymorphisms affecting thiopurine metabolism pathways and toxicity in paediatric acute lymphoblastic leukaemia patients for the first time in Korea.

METHODS

From May 2006 to September 2016, 139 paediatric acute lymphoblastic leukaemia patients treated with combination chemotherapy including 6-mercaptopurine were included in the study. One hundred and twenty-three variants in 43 genes, including TMPT and NUDT15, were screened using targeted genotyping, such as a MassARRAY system, direct sequencing and polymerase chain reaction-restriction fragment length polymorphism methods. Among the polymorphisms screened, 103 polymorphisms of 43 genes were included for further analyses.

RESULTS

The genetic polymorphisms in the ABCC4, AHCY, ATIC, FAM8A6P, GART, GNG2, GSTA1, MTHFD1, MTHFR, NUDT15, PACSIN2, TYMS and XDH genes, and an intronic polymorphism between HIVEP2 and AIG1, and TPMT genotype were associated with thiopurine metabolism (P < 0.05). Genetic polymorphisms in the ABCC4, ADK, ATIC, GART, GMPS, GSTP1, IMPDH1, ITPA, KCNMA1, MOCOS, MTRR, NUDT15, SLC19A1, SLC28A3, SLC29A1, SLCO1B1, TYMP and XDH genes were associated with thiopurine-related toxicities; neutropenia, hepatotoxicity and treatment interruption (P < 0.05).

CONCLUSIONS

Findings of this study may provide basic knowledge for personalized medicine for thiopurinxe treatment in paediatric acute lymphoblastic leukaemia patients.

Simple functional assessment at hospital discharge can predict long-term outcomes of ICU survivors

Recent studies showed that physical and/or neuropsychiatric impairments significantly affect long-term mortality of ICU survivors. We conducted this study to investigate that simplified measurement of physical function and level of consciousness at hospital discharge by attending nurses could predict long-term outcomes after hospital discharge. A retrospective analysis of prospectively and retrospectively collected data of 246 patients who received medical ICU treatment was conducted. We grouped patients according to physical function and level of consciousness measured by the simplified method at hospital discharge as follow; group A included patients with alert mental and capable of walking or moving by wheel chairs; group B included those with alert mental and bed-ridden status; and Group C included those with confused mental and bed-ridden status. The two-year survival rate after hospital discharge was compared. Of 246 patients, 157 patients were included in the analysis and there were 103 survivors after two-year follow up. Compared to non-survivors, survivors were more likely to be younger (P = 0.026) and have higher body mass index (P = 0.019) and no malignant disease (P = 0.001). There were no statistically significant differences in treatment modalities including medication, use of medical devices, and physical therapy between the survivors and non-survivors. The analysis showed significant differences in survival between the groups classified by physical function (P < 0.001) and level of consciousness (P < 0.01). Multivariate analysis showed that survival rate was significantly lower among the patients in group C than in those in group B or group A (P < 0.001). Simplified method to assess physical function and level of consciousness at hospital discharge can predict long-term outcomes of medical ICU survivors.

Non-contrast liver MRI as an alternative to gadoxetic acid-enhanced MRI for liver metastasis from colorectal cancer

BACKGROUND

Liver magnetic resonance imaging (MRI) provides reliable diagnostic performance for detecting liver metastasis but is costly and time-consuming.

PURPOSE

To compare the diagnostic performance of non-contrast liver MRI to whole MRI using gadoxetic acid for detecting liver metastasis in patients with colorectal cancer (CRC).

MATERIAL AND METHODS

We included 175 patients with histologically confirmed 401 liver metastases and 73 benign liver lesions. A non-contrast MRI (T1-weighted, T2-weighted, and diffusion-weighted images) with or without multidetector computed tomography (MDCT) and a whole MRI (gadoxetic acid-enhanced and non-contrast MRI) were analyzed independently by two observers to detect liver metastasis using receiver operating characteristic analysis.

RESULTS

We found no significant differences in Az value (range = 0.914-0.997), sensitivity (range = 95.2-99.6%), specificity (range = 77.3-100%), or positive (range = 92.9-100%) or negative predictive value (range = 87.5-95.7%) between the non-contrast MRI with or without MDCT and the whole MRI for both observers for all lesions as well as lesions ≤1.0 cm and lesions >1.0 cm in size ( P = 0.203-1.000). Combined MDCT and non-contrast MRI led to similar numbers of false-positive diagnosis to the whole MRI (eight for Observers 1 and 4 vs. 3 for Observer 2).

CONCLUSION

Non-contrast liver MRI may serve as an alternative to gadoxetic acid-enhanced MRI for detecting and characterizing liver metastasis from CRC, at least in patients with relatively high risk of liver metastasis who underwent MDCT. Non-contrast liver MRI could be beneficial especially for patients with lesions that are already documented as benign but require additional follow-up MRIs.

Detection of chromosome structural variation by targeted next-generation sequencing and a deep learning application

Molecular testing is increasingly important in cancer diagnosis. Targeted next generation sequencing (NGS) is widely accepted method but structural variation (SV) detection by targeted NGS remains challenging. In the brain tumor, identification of molecular alterations, including 1p/19q co-deletion, is essential for accurate glial tumor classification. Hence, we used targeted NGS to detect 1p/19q co-deletion using a newly developed deep learning (DL) model in 61 tumors, including 19 oligodendroglial tumors. An ensemble 1-dimentional convolution neural network was developed and used to detect the 1p/19q co-deletion. External validation was performed using 427 low-grade glial tumors from The Cancer Genome Atlas (TCGA). Manual review of the copy number plot from the targeted NGS identified the 1p/19q co-deletion in all 19 oligodendroglial tumors. Our DL model also perfectly detected the 1p/19q co-deletion (area under the curve, AUC = 1) in the testing set, and yielded reproducible results (AUC = 0.9652) in the validation set (n = 427), although the validation data were generated on a completely different platform (SNP Array 6.0 platform). In conclusion, targeted NGS using a cancer gene panel is a promising approach for classifying glial tumors, and DL can be successfully integrated for the SV detection in NGS data.

Infliximab Trough Levels Are Associated With Mucosal Healing During Maintenance Treatment With Infliximab in Paediatric Crohn's Disease

BACKGROUND AND AIMS

Mucosal healing is an important treatment goal in Crohn's disease. We investigated the association between serum infliximab trough levels and mucosal healing, and the infliximab cut-off levels required for mucosal healing in paediatric patients.

METHODS

In this multicentre, retrospective, cross-sectional study, medical records and electronic data of paediatric patients with luminal Crohn's disease, who had received infliximab for ≥1 year, were examined. Ileocolonoscopy was performed on the same day as the infliximab infusion, and serum samples for trough levels were collected immediately before infusion. Mucosal healing was defined as a Simple Endoscopic Score for Crohn's Disease of 0. Univariate, multivariate logistic regression, and receiver operating characteristic curve analyses were performed.

RESULTS

Overall, 105 patients [median age 14.8 years] were included, with mucosal healing observed in 48.6%. Median serum infliximab trough levels were higher in patients with mucosal healing [4.5 µg/mL] than without [3.3 µg/mL, p = 0.002]. In the final multivariate model, infliximab trough level ≥4.2 µg/mL [p = 0.002] and ≥1-year duration from diagnosis to infliximab treatment [p = 0.003] were positively and negatively associated with mucosal healing, respectively. The infliximab trough level for achieving mucosal healing with a specificity of 80% was ≥5 µg/mL.

CONCLUSIONS

Associations between serum infliximab trough concentrations and mucosal healing were observed in paediatric patients. Identification of the infliximab trough level that positively associates with mucosal healing in most paediatric patients with Crohn's disease [≥5 µg/mL] may guide treatment decisions to optimise therapeutic response in the era of treat-to-target.

Risk of high-grade malignancy in parotid gland tumors as classified by the Milan System for Reporting Salivary Gland Cytopathology

BACKGROUND

The Milan System for Reporting Salivary Gland Cytopathology (Milan System) has previously shown its diagnostic utility by categorizing the seven cytology findings in salivary gland lesions. However, there has been lack of study about the risk of high-grade malignancy in the cytology diagnosis based on the Milan System. Thus, we tried to identify the diagnostic ability of the Milan System for high-grade malignancy and to suggest an improved diagnostic approach for preoperative estimation of high-grade malignancy using the Milan System.

METHODS

A total of 413 patients with parotid gland tumors, who had undergone surgical resection from 2011 to 2015 were included in the present study retrospectively. Cytopathology was reclassified according to the Milan System by two independent reviewers. The outcomes were risk of malignancy and risk of high-grade malignancy. The diagnostic performance of the Milan System category [Malignant] for detecting high-grade malignancy was calculated.

RESULTS

The risk of malignancy was 83.3% and 100% in the Milan System categories [Suspicious for Malignancy] and [Malignant], respectively. Meanwhile, the risk of high-grade malignancy was 16.7% and 55.9% in these two categories. Disease-free survival of patients with high-grade malignancy was significantly worse than those with low- and intermediate-grade malignancy. Union combining the Milan System category [Malignant] with the presence of nodal metastasis suggested high-grade malignancy with an acceptable diagnostic sensitivity (0.889-0.963) and negative predictive value (0.900-0.966).

CONCLUSIONS

The Milan System category [Malignant] with the presence of nodal metastasis suggested parotid gland tumors as high-grade malignancy in a pretreatment setting.

Impact of sarcopenia on the risk of advanced colorectal neoplasia

BACKGROUND AND AIM

Sarcopenia is a pathological condition characterized by the progressive loss of muscle mass and increased amount of visceral fat. Recent evidence has revealed that sarcopenia is associated with certain diseases. However, the impact of sarcopenia on colorectal neoplasia has not been documented clearly. We studied the association between sarcopenia and advanced colorectal neoplasia in a large screening population.

METHODS

This cross-sectional study included 14 024 asymptomatic adults who underwent first-time screening colonoscopy. Sarcopenia (class II) was defined as an appendicular skeletal muscle mass (ASM)/bodyweight (%) value more than two standard deviations below the mean for healthy young adults. ASM was estimated using bioelectrical impedance analysis.

RESULTS

In a multivariable model adjusted for age, sex, obesity (body mass index ≥ 25), smoking status, alcohol intake, regular exercise, and family history of colorectal cancer, the odds ratio (OR) for advanced colorectal neoplasia on comparing participants with sarcopenia (class II) to those without sarcopenia (class I + II) was 1.52 (95% confidence interval [CI], 1.23-1.86). Further adjustment for metabolic parameters attenuated this association, but the association was still significant (OR, 1.34; 95% CI, 1.07-1.68). Furthermore, the multivariable (traditional risk factors)-adjusted OR associated with a 1% decrease on the introduction of ASM/weight% as a continuous variable in regression models was 1.04 (95% CI, 1.01-1.07) for advanced colorectal neoplasia.

CONCLUSIONS

Our findings indicate that sarcopenia is significantly and progressively associated with the risk of advanced colorectal neoplasia. This association might be explained by metabolic factors that could be potential mediators of the effect of sarcopenia.

Hepatic neuroendocrine tumors: gadoxetic acid-enhanced magnetic resonance imaging findings with an emphasis on differentiation between primary and secondary tumors

PURPOSE

To describe the findings of magnetic resonance (MR) imaging of hepatic neuroendocrine tumors (hNET) and to identify the features that differentiate secondary from primary tumors.

METHODS

This retrospective study was approved by the institutional review board, and the requirement for informed consent was waived. Between August 2008 and December 2014, 50 patients with pathologically proven hNETs who underwent gadoxetic acid-enhanced MR imaging with diffusion-weighted images were included. The patients were divided into two groups according to whether they had primary (n = 17) or secondary (n = 33) hNETs. Qualitative values based on a consensus between two observers [morphologic findings, signal intensity, and enhancement pattern (poor or indeterminate; hepatocellular carcinoma-like or cholangiocarcinoma-like)], and quantitative values (apparent diffusion coefficient) were evaluated as predictors of secondary hNETs using multivariable logistic regression and receiver operating characteristic (ROC) analysis.

RESULTS

In multivariate analysis, the presence of multiple lesions (p = 0.011), a tumor size less than 6.3 cm (p = 0.001), and a hepatocellular carcinoma-like enhancement pattern (p = 0.031) were significant independent factors for differentiating secondary from primary hNETs, and achieved a sensitivity of 91%, a specificity of 82%, and an accuracy of 88%, with a value of the area under the ROC curve of 0.931.

CONCLUSION

Using these specific MR imaging criteria, secondary hNETs could be differentiated from primary hNETs with a high degree of accuracy in patients with histopathologically proven hNETs.

Early Infliximab Yields Superior Long-Term Effects on Linear Growth in Pediatric Crohn's Disease Patients

Background/Aims

Information regarding the efficacy of early infliximab treatment in pediatric patients with Crohn’s disease (CD) is limited. We aimed to evaluate the impact of early combined immunosuppression on linear growth in pediatric patients with CD by performing step-up comparisons.

Methods

This retrospective study included pediatric patients with moderate-to-severe CD, who received a combination therapy with infliximab and azathioprine for at least 3 years and sustained corticosteroid-free remission without loss of response. The z-scores of the growth indicators obtained at the time of diagnosis and annually for 3 years thereafter were compared between the two groups.

Results

The early combined immunosuppression group displayed significantly increased linear growth 3 years after diagnosis (p=0.026). A significant difference was also observed in the linear growth 3 years after diagnosis between subgroups of Tanner stages 1–2 (p=0.016).

Conclusions

The early introduction of biologics should be considered to improve linear growth in pediatric patients with CD.

Optimal cutoff of pretreatment neutrophil-to-lymphocyte ratio in head and neck cancer patients: a meta-analysis and validation study

BACKGROUND

The prognostic role of neutrophil-to-lymphocyte ratio (NLR) has been proposed in head and neck squamous cell carcinoma (HNSCC). However, it is currently unclear which cutoff values of NLR could consistently and independently differentiate HNSCC patients to better and worse prognosis groups.

METHODS

We performed a meta-analysis of prognostic significance of pretreatment NLR values, using data extracted from 24 relevant articles. Main outcomes were overall survival (OS) and disease-free survival (DFS) in HNSCC patients. Pooled hazard ratio (HR) and 95% confidence intervals (95%CI) were calculated using the random effect model for outcomes. Impacts of NLR cutoff values across the studies were assessed with a meta-regression analysis. Results were validated using an independent data set of patients (n = 540).

RESULTS

Pretreatment high NLR values above the cutoff were significantly associated with shorter OS (HR = 1.96, 95%CI = 1.66-2.31) and DFS (HR = 1.90, 95%CI = 1.41-2.54). Of note, NLR cutoffs ranging from 1.9 to 6.0 did not affect HR of OS or DFS in meta-regression analyses. In an independent cohort, any NLR cutoff between 2 and 6 produced significant HR of OS, similarly. Instead of binary cutoffs, three subgroups of NLR (< 2, 2 to 6, and ≥ 6) showed significant differences of OS in survival analyses.

CONCLUSIONS

Meta-analyses confirmed that pretreatment NLR values above the cutoff were associated with shorter survival in HNSCC patients. However, the binary cutoffs of NLR values were variable across studies. Rather, pretreatment NLR values below 2 and above 6 using a three-tier classification (< 2, 2 to 6, and ≥ 6) could consistently imply better and worse prognosis in HNSCC patients, which could be readily translated to clinics.

The impact of unplanned reoperations in head and neck cancer surgery on survival

OBJECTIVES

Unplanned reoperation causes physical and psychological stress in patients and it costs more in terms of medical, economic and social resource. The purpose of the study was to evaluate the incidence, risk factors and clinical significance of unplanned reoperation (any unscheduled surgery within 30 days from the initial surgery) in patients who had undergone head and neck cancer (HNC) surgery.

MATERIALS AND METHODS

A total of 574 consecutive patients who had received surgery for HNC with or without flap reconstruction from 2010 to 2015 were analyzed. Clinical and biochemical characteristics, cause of unplanned reoperation, cancer subsites, and previous treatment history were compared between unplanned reoperation group (n = 60) and control group (n = 514). Multivariable analyses were performed to identify risk factors for unplanned reoperation. Clinical significance was evaluated by multivariable survival analyses using Cox proportional hazard model.

RESULTS

Overall rate of unplanned reoperation was 10.5%. Flap complication (40.0%) was the most common cause, followed by infection (16.7%), necrosis (11.7%), and bleeding (8.3%). Higher N (N2) classification, long operation time and previous treatment before surgery were identified as risk factors for unplanned reoperation. Based on multivariable survival analyses, recurrence-free survival was significantly decreased in unplanned reoperation group (Hazard ratio = 1.85, 95% confidence interval [1.23-2.80]), but not overall survival.

CONCLUSION

Unplanned reoperation significantly decreased recurrence-free survival in patients with HNC surgery. Thus, careful surgical/ perioperative management is needed to reduce unplanned reoperation in HNC patients with advanced nodal disease, long operation time or previous treatment history.

Deciphering Clinicoradiologic Phenotype for Thymidylate Synthase Expression Status in Patients with Advanced Lung Adenocarcinoma Using a Radiomics Approach

We aimed to identify predictive clinicoradiologic characteristics of thymidylate synthase (TS) expression status in advanced non-squamous non-small cell lung cancer patients. We reviewed clinicoradiologic features of 169 patients stratified into TS-negative (n = 84) and TS-positive (n = 85) groups, including quantitative CT radiomic features of both primary lung and metastatic lesions from initial CT and PET. Clinical factors including age and smoking history were significantly associated with TS as well as radiomic features. The predictive performance for dichotomizing TS expression status was slightly higher when imaging features of primary lung lesions were added compared to the model based solely on the clinical features, but without statistical significance (10-fold cross-validated AUC = 0.619 and 0.581, respectively; P = 0.425). The predictive performance of clinicoradiologic parameters slightly increased with primary lung lesions only compared to the inclusion of metastatic lesions, but without statistical significance (10-fold cross-validated AUC = 0.619 and 0.554, respectively; P = 0.203). Overall survival was prolonged in the TS-negative group compared to the TS-positive group (P = 0.001). TS-negativity is a potential prognostic biomarker, and our study presents that although CT radiomic features have potential for predicting TS expression status, clinical significance is uncertain. The addition of radiomic features to clinical factors did not show significant improvement in predicting TS-negativity.

Prediction and clinical implications of portal vein/superior mesenteric vein invasion in patients with resected pancreatic head cancer: the significance of preoperative CT parameters

AIM

To determine the preoperative computed tomography (CT) parameters that predict portal vein/superior mesenteric vein (PV-SMV) invasion in patients with pancreatic head cancer, and to assess whether PV-SMV invasion affects patient survival.

MATERIALS AND METHODS

Sixty patients with PV-SMV invasion, and 60 randomly selected patients without it, who had undergone preoperative CT and subsequent surgery for pancreatic head cancer were enrolled. The following CT parameters were evaluated using multivariate logistic regression and receiver operating characteristic analyses to predict vessel invasion (tumour size and margin, length of involved vessel, distance from the tumour to the vessel, vessel irregularity, the teardrop sign, and tumour-vein interface [TVI]). The Cox proportional hazard model was used to evaluate the effects of PV-SMV invasion on survival.

RESULTS

In multivariate analysis, tumour size (odds ratio [OR]=1.99) and TVI (OR=3.79 [≤90°], 20.66 [>90°, ≤180°], and 47.24 [>180°]) were independent CT predictors of PV-SMV invasion (p<0.05); they achieved a sensitivity of 87%, a specificity of 75%, and an accuracy of 81%; however, PV-SMV invasion did not affect patient survival after surgery (p=0.374).

CONCLUSION

In patients with pancreatic head cancer, preoperative CT parameters can predict PV-SMV invasion with high accuracy. PV-SMV invasion did not affect treatment outcome after surgery.

Hepatobiliary MRI as novel selection criteria in liver transplantation for hepatocellular carcinoma

BACKGROUND & AIMS

Hepatobiliary magnetic resonance imaging (MRI) provides additional information beyond the size and number of tumours, and may have prognostic implications. We examined whether pretransplant radiological features on MRI could be used to stratify the risk of tumour recurrence after liver transplantation (LT) for hepatocellular carcinoma (HCC).

METHODS

A total of 100 patients who had received a liver transplant and who had undergone preoperative gadoxetic acid-enhanced MRI, including the hepatobiliary phase (HBP), were reviewed for tumour size, number, and morphological type (e.g. nodular, nodular with perinodular extension, or confluent multinodular), satellite nodules, non-smooth tumour margins, peritumoural enhancement in arterial phase, peritumoural hypointensity on HBP, and apparent diffusion coefficients. The primary endpoint was time to recurrence.

RESULTS

In a multivariable adjusted model, the presence of satellite nodules [hazard ratio (HR) 3.07; 95% confidence interval (CI) 1.14-8.24] and peritumoural hypointensity on HBP (HR 4.53; 95% CI 1.52-13.4) were identified as independent factors associated with tumour recurrence. Having either of these radiological findings was associated with a higher tumour recurrence rate (72.5% vs. 15.4% at three years, p <0.001). When patients were stratified according to the Milan criteria, the presence of these two high-risk radiological findings was associated with a higher tumour recurrence rate in both patients transplanted within the Milan criteria (66.7% vs. 11.6% at three years, p <0.001, n = 68) and those who were transplanted outside the Milan criteria (75.5% vs. 28.6% at three years, p <0.001, n = 32).

CONCLUSIONS

Radiological features on preoperative hepatobiliary MRI can stratify the risk of tumour recurrence in patients who were transplanted either within or outside the Milan criteria. Therefore, hepatobiliary MRI can be a useful way to select potential candidates for LT.

LAY SUMMARY

High-risk radiological findings on preoperative hepatobiliary magnetic resonance imaging (either one of the following features: satellite nodule and peritumoural hypointensity on hepatobiliary phase) were associated with a higher tumour recurrence rate in patients transplanted either within or outside the Milan criteria.

Identification of atopic dermatitis phenotypes with good responses to probiotics (Lactobacillus plantarum CJLP133) in children

The therapeutic effect of probiotics in atopic dermatitis (AD) remains controversial and varies according to the individual patient. We aimed to identify a population of AD patients with a good clinical response to probiotic treatment. We recruited 76 children with a median age of 7.1 years who suffered from moderate to severe AD. After a 2-week washout period, all patients were given Lactobacillus plantarum CJLP133 at a dosage of 1×10¹⁰ colony-forming units once a day for 12 weeks. We measured eosinophil counts in the peripheral blood, the proportion of CD4⁺CD25⁺Foxp3⁺ regulatory T (Treg) cells in CD4⁺ T cells, serum total immunoglobulin E (IgE) levels, and specific IgE against common allergens before the start of the treatment (T1) and at discontinuation (T2). Responders were defined as patients with at least a 30% reduction in the SCORing of AD (SCORAD) index after treatment. There were 36 responders and 40 non-responders after probiotic treatment. The median SCORAD was reduced from 29.5 (range 20.6-46.3) at T1 to 16.4 (range 6.3-30.8) at T2 in the responder group (P<0.001). In multivariable logistic regression analysis, a good clinical response was significantly associated with high total IgE levels (aOR 5.1, 95% CI 1.1-23.6), increased expression of transforming growth factor (TGF)-β (aOR 4.6, 95% CI 1.3-15.9), and a high proportion of Treg cells in CD4⁺ T cells (aOR 3.7, 95% CI 1.1-12.7) at T1. In the responder group, the proportion of Treg cells was significantly increased after 12 weeks of treatment (P=0.004), while TGF-β mRNA expression was decreased (P=0.017). Our results suggest that a subgroup of patients with a specific AD phenotype showing an immunologically active state (high total IgE, increased expression of TGF-β, high numbers of Treg cells) may benefit from probiotic treatment with L. plantarum CJLP133.