Lung cancer is the leading cause of cancer death in Republic of Korea. After their initial diagnosis, only 10-20% of patients with advanced non-small cell lung cancer (NSCLC) survive for 5 years of longer. Given enormous advances in therapeutics such as novel targeted therapies and immunotherapies, survival rates are improving for advanced patients with NSCLC; 5-year survival rates range from 15% to 50%, contingent upon the biomarker. Detection of the specific molecular alteration as biomarker is thus crucial for identifying subgroups of NSCLC that contain therpapeutically targetable oncogenic drivers. This review examines the process of diagnosing lung adenocarcinoma with dominant biomarkers in order to customize treatment with appropriate targeted therapy.

Lung cancer is the leading cause of cancer death in Republic of Korea. After their initial diagnosis, only 10-20% of patients with advanced non-small cell lung cancer (NSCLC) survive for 5 years of longer. Given enormous advances in therapeutics such as novel targeted therapies and immunotherapies, survival rates are improving for advanced patients with NSCLC; 5-year survival rates range from 15% to 50%, contingent upon the biomarker. Detection of the specific molecular alteration as biomarker is thus crucial for identifying subgroups of NSCLC that contain therpapeutically targetable oncogenic drivers. This review examines the process of diagnosing lung adenocarcinoma with dominant biomarkers in order to customize treatment with appropriate targeted therapy.

Lung cancer is the leading cause of cancer death in Republic of Korea. After their initial diagnosis, only 10-20% of patients with advanced non-small cell lung cancer (NSCLC) survive for 5 years of longer. Given enormous advances in therapeutics such as novel targeted therapies and immunotherapies, survival rates are improving for advanced patients with NSCLC; 5-year survival rates range from 15% to 50%, contingent upon the biomarker. Detection of the specific molecular alteration as biomarker is thus crucial for identifying subgroups of NSCLC that contain therpapeutically targetable oncogenic drivers. This review examines the process of diagnosing lung adenocarcinoma with dominant biomarkers in order to customize treatment with appropriate targeted therapy.

Lung cancer is the leading cause of cancer death in Republic of Korea. After their initial diagnosis, only 10-20% of patients with advanced non-small cell lung cancer (NSCLC) survive for 5 years of longer. Given enormous advances in therapeutics such as novel targeted therapies and immunotherapies, survival rates are improving for advanced patients with NSCLC; 5-year survival rates range from 15% to 50%, contingent upon the biomarker. Detection of the specific molecular alteration as biomarker is thus crucial for identifying subgroups of NSCLC that contain therpapeutically targetable oncogenic drivers. This review examines the process of diagnosing lung adenocarcinoma with dominant biomarkers in order to customize treatment with appropriate targeted therapy.

Background/Aims: Synchronous multiple gastric cancer (SMGC) accounts for approximately 6% to 14% of gastric cancer (GC) cases. This study aimed to identify risk factors for SMGC. Methods: A total of 14,603 patients diagnosed with GC were prospectively enrolled. Data including age, sex, body mass index, smoking, alcohol consumption, family history, p53 expression, microsatellite instability, cancer classification, lymph node metastasis, and treatment were collected. Risk factors were analyzed using logistic regression analysis between a single GC and SMGC. Results: The incidence of SMGC was 4.04%, and that of early GC (EGC) and advanced GC (AGC) was 5.43% and 3.11%, respectively. Patients with SMGC were older (65.33 years vs 61.75 years, p<0.001) and more likely to be male. Lymph node metastasis was found in 27% of patients with SMGC and 32% of patients with single GC. Multivariate analysis showed that SMGC was associated with sex (male odds ratio [OR], 1.669; 95% confidence interval [CI], 1.223 to 2.278; p=0.001), age (≥65 years OR, 1.532; 95% CI, 1.169 to 2.008; p=0.002), and EGC (OR, 1.929; 95% CI, 1.432 to 2.600; p<0.001). Survival rates were affected by Lauren classification, sex, tumor size, cancer type, distant metastasis, and venous invasion but were not related to the number of GCs. However, the survival rate of AGC with SMGC was very high. Conclusions SMGC had unique characteristics such as male sex, older age, and EGC, and the survival rate of AGC, in which the intestinal type was much more frequent, was very good (Trial registration number: NCT04973631).

Background: Nonsteroidal anti-inflammatory drugs (NSAID) are currently among the most prescribed medications worldwide to relieve pain and reduce inflammation, especially in patients suffering osteoarthritis (OA). However, NSAIDs are known to have adverse effects on the gastrointestinal system. If a gastric ulcer occurs, planned OA treatment needs to be changed, incurring additional treatment costs and causing discomfort for both patients and clinicians. Therefore, it is necessary to create a gastric ulcer prediction model that can reflect the detailed health status of each individual and to use it when making treatment plans. Methods: Using sample cohort data from 2008 to 2013 from the National Health Insurance Service in South Korea, we developed a prediction model for NSAID-induced gastric ulcers using machine-learning algorithms and investigated new risk factors associated with medication and comorbidities. Results: The population of the study consisted of 30,808 patients with OA who were treated with NSAIDs between 2008 and 2013. After a 2-year follow-up, these patients were divided into two groups: without gastric ulcer (n=29,579) and with gastric ulcer (n=1,229). Five machine-learning algorithms were used to develop the prediction model, and a gradient boosting machine (GBM) was selected as the model with the best performance (area under the curve, 0.896; 95% confidence interval, 0.883–0.909). The GBM identified 5 medications (loxoprofen, aceclofenac, talniflumate, meloxicam, and dexibuprofen) and 2 comorbidities (acute upper respiratory tract infection [AURI] and gastroesophageal reflux disease) as important features. AURI did not have a dose-response relationship, so it could not be interpreted as a significant risk factor even though it was initially detected as an important feature and improved the prediction performance. Conclusions We obtained a prediction model for NSAID-induced gastric ulcers using the GBM method. Since personal prescription period and the severity of comorbidities were considered numerically, individual patients’ risk could be well reflected. The prediction model showed high performance and interpretability, so it is meaningful to both clinicians and NSAID users.

With the recent development of digital dentistry, fully digitalized methods for fabricating dentures, using intraoral scans and computer-aided design/computer-aided manufacturing (CAD-CAM), are getting popular. Digital methods have the advantage of simplifying the fabrication process in the clinic and laboratory, supplementing digital data. This case report shows a fully digital fabrication method for interim removable dentures in a patient with anterior tooth loss in which implant placement is impossible or delayed. Interim removable dentures were fabricated using two methods. One method is printing tooth and base parts separately and combining, and the other method is printing the whole denture at one time and coloring on the base part. Afterward, dentures were delivered and adaptation was evaluated using the triple scan technique. The extracted site was scanned intraorally (first scan) and the interim removable denture was digitally scanned both intraorally (second scan) and, after removal extraorally (Third scan). In both method, denture adaptation was shown favorable. We report this case report as both the patient and the operator were satisfied with a simplified process using a fully digital method in the clinic.

Background/Aims: There are few reports regarding mixed carcinoma, defined as a mixture of glandular and poorly cohesive components, in patients with gastric cancer (GC). The aim of this study was to evaluate the proportion and characteristics of mixed carcinoma in GC patients. Methods: A total of 7,215 patients diagnosed with GC at Seoul National University Bundang Hospital were enrolled from March 2011 to February 2020. GC was divided into four groups (wellmoderately differentiated GC, poorly differentiated GC, poorly cohesive carcinoma, and mixed carcinoma). The proportion of each GC type and the clinicopathological features were analyzed and divided into early GC and advanced GC. Results: The proportion of mixed carcinoma was 10.9% (n=787). In early GC, submucosal invasion was the most common in poorly differentiated (53.7%), and mixed carcinoma ranked second (41.1%). Mixed carcinoma showed the highest proportion of lymph node metastasis in early GC (23.0%) and advanced GC (78.3%). In advanced GC, the rate of distant metastasis was 3.6% and 3.9% in well-moderately differentiated GC and mixed carcinoma, respectively, lower than that in poorly differentiated GC (6.4%) and poorly cohesive carcinoma (5.7%), without statistical significance. Conclusions Mixed carcinoma was associated with lymph node metastasis compared to other histological GC subtypes. And it showed relatively common submucosal invasion in early GC, but the rates of venous invasion and distant metastasis were lower in advanced GC. Further research is needed to uncover the mechanism underlying these characteristics of mixed carcinoma (Trial registration number: NCT04973631).

Background/Aims: Low-level viremia (LLV) after nucleos(t)ide analog treatment was presented as a possible cause of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). However, detailed information on patients’ adherence in the real world was lacking. This study aimed to evaluate the effects of LLV on HCC development, mortality, and cirrhotic complications among patients according to their adherence to entecavir (ETV) treatment. Methods: We performed a retrospective observational analysis of data from 894 consecutive adult patients with treatment-naïve CHB undergoing ETV treatment. LLV was defined according to either persistent or intermittent episodes of <2,000 IU/mL detectable hepatitis B virus DNA during the follow-up period. Good adherence to medication was defined as a cumulative adherence ≥90% per study period. Results: Without considering adherence in the entire cohort (n=894), multivariate analysis of the HCC incidence showed that LLV was an independent prognostic factor in addition to other traditional risk factors in the entire cohort (P=0.031). Good adherence group comprised 617 patients (69.0%). No significant difference was found between maintained virologic response and LLV groups in terms of the incidence of liver-related death or transplantation, HCC, and hepatic decompensation in good adherence group, according to multivariate analyses. Conclusions In patients with treatment-naïve CHB and good adherence to ETV treatment in the real world, LLV during treatment is not a predictive factor for HCC and cirrhotic complications. It may be unnecessary to adjust their antiviral agent for patients with good adherence who experience LLV during ETV treatment.

Background: The digits-in-noise (DiN) test is a speech-in-noise test to measure speech recognition threshold in noise adaptively. Herein, we aimed to develop the Korean version of the DiN test to provide a useful hearing screening tool for clinical as well as research purposes.Method: Spoken monosyllabic digits from 0 to 9 were recorded by a female speaker. The test list was constructed such that each digit was placed in three different positions. An optimization procedure was conducted to equate the audibility of each digit. After the optimization, the smartphone application for the Korean DiN (K-DiN) test was developed. For the adaptive measurement procedure, 180 new DiN triplets separated into six lists of 30 were created. Mean speech recognition threshold values for each list and session were measured to examine the test-retest and training effects of the test materials. In addition, speech recognition threshold values measured by different devices were compared to determine whether the speech recognition threshold levels differed. Results: Optimization results showed that the mean speech recognition threshold and slope were −11.55 dB signal-to-noise ratio and 10.21%/dB, respectively, which are comparable to levels shown in different-language versions of the DiN test. The results of the test-retest and training effects revealed no significant differences among the test sessions and lists. Additionally, the mean speech recognition threshold values measured by four different devices were not different, indicating the reliability of the test materials. Conclusion We believe this study is the first to attempt to develop a K-DiN test. Our results indicate that this test can be used as a potentially reliable hearing screening tool.