Background: Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP) is a crucial initial step. However, the established method for determining the NCP, manual counting by a pathologist, is time-consuming and not easily executable. Methods: To address this, artificial intelligence (AI) models were developed to estimate the NCP using nine convolutional neural networks and the scanned images of 39 cases of urinary tract cancer. The performance of the AI models was compared to that of six pathologists for 119 cases in the validation cohort. The ground truth value was obtained through multiplexed immunofluorescence. The AI model was then applied to 41 cases in the application cohort that underwent next-generation sequencing testing, and its impact on the copy number variation (CNV) was analyzed. Results: Each AI model demonstrated high reliability, with intraclass correlation coefficients (ICCs) ranging from 0.82 to 0.88. These values were comparable or better to those of pathologists, whose ICCs ranged from 0.78 to 0.91 in urothelial carcinoma cases, both with and without divergent differentiation/ subtypes. After applying AI-driven NCP, 190 CNV (24.2%) were reclassified with 66 (8.4%) and 78 (9.9%) moved to amplification and loss, respectively, from neutral/minor CNV. The neutral/minor CNV proportion decreased by 6%. Conclusions These results suggest that AI models could assist human pathologists in repetitive and cumbersome NCP calculations.

The aim of this study was to develop evidence-based recommendations for determining the surgical extent in patients with locally invasive differentiated thyroid cancer (DTC). Locally invasive DTC with gross extrathyroidal extension invading surrounding anatomical structures may lead to several functional deficits and poor oncological outcomes. At present, the optimal extent of surgery in locally invasive DTC remains a matter of debate, and there are no adequate guidelines. On October 8, 2021, four experts searched the PubMed, Embase, and Cochrane Library databases; the identified papers were reviewed by 39 experts in thyroid and head and neck surgery. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to assess the quality of evidence, and to develop and report recommendations. The strength of a recommendation reflects the confidence of a guideline panel that the desirable effects of an intervention outweigh any undesirable effects, across all patients for whom the recommendation is applicable. After completing the draft guidelines, Delphi questionnaires were completed by members of the Korean Society of Head and Neck Surgery. Twenty-seven evidence-based recommendations were made for several factors, including the preoperative workup; surgical extent of thyroidectomy; surgery for cancer invading the strap muscles, recurrent laryngeal nerve, laryngeal framework, trachea, or esophagus; and surgery for patients with central and lateral cervical lymph node involvement. Evidence-based guidelines were devised to help clinicians make safer and more efficient clinical decisions for the optimal surgical treatment of patients with locally invasive DTC.

Background: The purpose of this study was to verify the accuracy and validity of using machine learning (ML) to select risk factors, to discriminate differences in feature selection by ML between men and women, and to develop predictive models for patients with osteoporosis in a big database. Methods: The data on 968 observed features from a total of 3,484 the Korea National Health and Nutrition Examination Survey participants were collected. To find preliminary features that were well-related to osteoporosis, logistic regression, random forest, gradient boosting, adaptive boosting, and support vector machine were used. Results: In osteoporosis feature selection by 5 ML models in this study, the most selected variables as risk factors in men and women were body mass index, monthly alcohol consumption, and dietary surveys. However, differences between men and women in osteoporosis feature selection by ML models were age, smoking, and blood glucose level. The receiver operating characteristic (ROC) analysis revealed that the area under the ROC curve for each ML model was not significantly different for either gender. Conclusions ML performed a feature selection of osteoporosis, considering hidden differences between men and women. The present study considers the preprocessing of input data and the feature selection process as well as the ML technique to be important factors for the accuracy of the osteoporosis prediction model.

Background: Dual energy X-ray absorptiometry (DXA) is a preferred modality for screening or diagnosis of osteoporosis and can predict the risk of hip fracture. However, the DXA test is difficult to implement easily in some developing countries, and fractures have been observed before patients underwent DXA. The purpose of this systematic review is to search for studies that predict the risk of hip fracture using artificial intelligence (AI) or machine learning, organize the results of each study, and analyze the usefulness of this technology. Methods: The PubMed, OVID Medline, Cochrane Collaboration Library, Web of Science, EMBASE, and AHRQ databases were searched including “hip fractures” AND “artificial intelligence”. Results: A total of 7 studies are included in this study. The total number of subjects included in the 7 studies was 330,099. There were 3 studies that included only women, and 4 studies included both men and women. One study conducted AI training after 1:1 matching between fractured and non-fractured patients. The area under the curve of AI prediction model for hip fracture risk was 0.39 to 0.96. The accuracy of AI prediction model for hip fracture risk was 70.26% to 90%. Conclusions We believe that predicting the risk of hip fracture by the AI model will help select patients with high fracture risk among osteoporosis patients. However, to apply the AI model to the prediction of hip fracture risk in clinical situations, it is necessary to identify the characteristics of the dataset and AI model and use it after performing appropriate validation.

Growth hormone (GH) deficiency is caused by congenital or acquired causes and occurs in childhood or adulthood. GH replacement therapy brings benefits to body composition, exercise capacity, skeletal health, cardiovascular outcomes, and quality of life. Before initiating GH replacement, GH deficiency should be confirmed through proper stimulation tests, and in cases with proven genetic causes or structural lesions, repeated GH stimulation testing is not necessary. The dosing regimen of GH replacement therapy should be individualized, with the goal of minimizing side effects and maximizing clinical improvements. The Korean Endocrine Society and the Korean Society of Pediatric Endocrinology have developed a position statement on the diagnosis and treatment of GH deficiency. This position statement is based on a systematic review of evidence and expert opinions.

The Korean Endocrine Society (KES) published clinical practice guidelines for the treatment of acromegaly in 2011. Since then, the number of acromegaly cases, publications on studies addressing medical treatment of acromegaly, and demands for improvements in insurance coverage have been dramatically increasing. In 2017, the KES Committee of Health Insurance decided to publish a position statement regarding the use of somatostatin analogues in acromegaly. Accordingly, consensus opinions for the position statement were collected after intensive review of the relevant literature and discussions among experts affiliated with the KES, and the Korean Neuroendocrine Study Group. This position statement includes the characteristics, indications, dose, interval (including extended dose interval in case of lanreotide autogel), switching and preoperative use of somatostatin analogues in medical treatment of acromegaly. The recommended approach is based on the expert opinions in case of insufficient clinical evidence, and where discrepancies among the expert opinions were found, the experts voted to determine the recommended approach.
Acromegaly ; Consensus ; Expert Testimony ; Insurance Coverage ; Insurance, Health ; Octreotide ; Somatostatin

Korean Society of Thyroid-Head and Neck Surgery appointed a Task Force to provide guidance on the implementation of a surgical treatment of oral cancer. MEDLINE databases were searched for articles on subjects related to “surgical management of oral cancer” published in English. Results were restricted to systematic reviews, randomized control trials/controlled clinical trials, and observational studies. The quality of evidence was rated with use RoBANS (Risk of Bias Assessment Tool for Nonrandomized Studies) and AMSTAR (A Measurement Tool to Assess the Methodological Quality of Systematic Reviews). Evidence-based recommendations for practice were ranked according to the American College of Physicians grading system. Additional directives are provided as expert opinions and Delphi questionnaire when insufficient evidence existed. The Committee developed 68 evidence-based recommendations in 34 categories intended to assist clinicians and patients and counselors, and health policy-makers. Proper surgical treatment selection for oral cancer, which is directed by patient- and subsite-specific factors, remains the greatest predictor of successful treatment outcomes. These guidelines are intended for use in conjunction with the individual patient's treatment goals.
Advisory Committees ; Bias (Epidemiology) ; Carcinoma, Squamous Cell ; Counseling ; Expert Testimony ; Humans ; Mouth Neoplasms ; Neck ; Republic of Korea

Acromegaly is a chronic disorder caused by excessive growth hormone (GH) secretion. In most cases, the excess GH originates from GH-producing pituitary adenomas. Surgery is the preferred first-line treatment for patients with acromegaly, but medical management is considered when the disease persists after surgery or in cases where patients refuse surgery or are poor candidates for surgery. Somatostatin analogues are commonly used to treat acromegaly. The Korean Endocrine Society and the Korean Neuroendocrine Study Group have developed a position statement for the use of somatostatin analogues in the medical treatment of acromegaly. This position statement is based on evidence from the current literature and expert opinions. In the case of discrepancies among expert opinions, the experts voted to determine the recommended approach.
Acromegaly ; Expert Testimony ; Growth Hormone ; Humans ; Octreotide ; Pituitary Neoplasms ; Somatostatin

Acromegaly is a chronic disorder caused by excessive growth hormone (GH) secretion. In most cases, the excess GH originates from GH-producing pituitary adenomas. Surgery is the preferred first-line treatment for patients with acromegaly, but medical management is considered when the disease persists after surgery or in cases where patients refuse surgery or are poor candidates for surgery. Somatostatin analogues are commonly used to treat acromegaly. The Korean Endocrine Society and the Korean Neuroendocrine Study Group have developed a position statement for the use of somatostatin analogues in the medical treatment of acromegaly. This position statement is based on evidence from the current literature and expert opinions. In the case of discrepancies among expert opinions, the experts voted to determine the recommended approach.

PURPOSE: The endoscopic management of a fully covered self-expandable metal stent (SEMS) has been suggested for the primary treatment of patients with anastomotic leaks after total gastrectomy. Embedded stents due to tissue ingrowth and migration are the main obstacles in endoscopic stent management. MATERIALS AND METHODS: The effectiveness and safety of endoscopic management were evaluated for anastomotic leaks when using a benign fully covered SEMS with an anchoring thread and thick silicone covering the membrane to prevent stent embedding and migration. We retrospectively reviewed the data of 14 consecutive patients with gastric cancer and anastomotic leaks after total gastrectomy treated from January 2009 to December 2016. RESULTS: The technical success rate of endoscopic stent replacement was 100%, and the rate of complete leaks closure was 85.7% (n=12). The mean size of leaks was 13.1 mm (range, 3–30 mm). The time interval from operation to stent replacement was 10.7 days (range, 3–35 days) and the interval from stent replacement to extraction was 32.3 days (range, 18–49 days). The complication rate was 14.1%, and included a single jejunal ulcer and delayed stricture at the site of leakage. No embedded stent or migration occurred. Two patients died due to progression of pneumonia and septic shock 2 weeks after stent replacement. CONCLUSIONS: A benign fully covered SEMS with an anchoring thread and thick membrane is an effective and safe stent in patients with anastomotic leaks after total gastrectomy. The novelty of this stent is that it provides complete prevention of stent migration and embedding, compared with conventional fully covered SEMS.
Anastomotic Leak* ; Constriction, Pathologic ; Gastrectomy* ; Humans ; Membranes* ; Pneumonia ; Retrospective Studies ; Self Expandable Metallic Stents ; Shock, Septic ; Silicon ; Silicones ; Stents* ; Stomach Neoplasms ; Ulcer