Allergen immunotherapy (AIT) has been used for over a century and has been demonstrated to be effective in treating patients with various allergic diseases. AIT allergens can be administered through various routes, including subcutaneous, sublingual, intralymphatic, oral, or epicutaneous routes. Sublingual immunotherapy (SLIT) has recently gained clinical interest, and it is considered an alternative treatment for allergic rhinitis (AR) and asthma. This review provides an overview of the current evidence-based studies that address the use of SLIT for treating AR, including (1) mechanisms of action, (2) appropriate patient selection for SLIT, (3) the current available SLIT products in Korea, and (4) updated information on its efficacy and safety. Finally, this guideline aims to provide the clinician with practical considerations for SLIT.

Allergen immunotherapy (AIT) is a causative treatment of allergic diseases in which allergen extracts are regularly administered in a gradually escalated doses, leading to immune tolerance and consequent alleviation of allergic diseases. The need for uniform practice guidelines in AIT is continuously growing as the number of potential candidates for AIT increases and new therapeutic approaches are tried. This updated version of the Korean Academy of Asthma Allergy and Clinical Immunology recommendations for AIT, published in 2010, proposes an expert opinion by specialists in allergy, pediatrics, and otorhinolaryngology. This guideline deals with the basic knowledge of AIT, including mechanisms, clinical efficacy, allergen standardization, important allergens in Korea, and special consideration in pediatrics. The article also covers the methodological aspects of AIT, including patient selection, allergen selection, schedule and doses, follow-up care, efficacy measurements, and management of adverse reactions. Although this guideline suggests the optimal dosing schedule, an individualized approach and modifications are recommended considering the situation for each patient and clinic.

A 45-year-old woman diagnosed with breast cancer reported disease progression in the form of metastatic lung and recurrent breast lesions following chemotherapy and human epidermal growth factor receptor 2 (HER2)-targeted therapy. The patient underwent 64 Cu-tetra-azacyclododecanetetra-acetic acid (DOTA)-trastuzumab positron emission tomography/computed tomography (PET/CT) to evaluate the HER2 expression status.64 Cu-DOTA-trastuzumab accumulated in the left breast and lymph nodes but not in the lung lesions. Following trastuzumab emtansine treatment, there was a significant improvement in the lesions with 64 Cu-DOTA-trastuzumab accumulation. However, the lesions that did not accumulate 64 Cu-DOTA-trastuzumab aggravated. Therefore, it was concluded that 64 CuDOTA-trastuzumab PET/CT can be used to predict the outcome of HER2-targeted treatment by evaluating HER2 expression in breast cancer patients.

Purpose: We aimed to investigate the risk factors and patterns of locoregional recurrence (LRR) after radical nephrectomy (RN) in patients with locally advanced renal cell carcinoma (RCC). Materials and Methods: We retrospectively analyzed 245 patients who underwent RN for non-metastatic pT3-4 RCC from January 2006 to January 2016. We analyzed the risk factors associated with poor locoregional control using Cox regression. Anatomical mapping was performed on reference computed tomography scans showing intact kidneys. Results: The median follow-up duration was 56 months (range, 1 to 128 months). Tumor extension to renal vessels or the inferior vena cava (IVC) and Fuhrman’s nuclear grade IV were identified as independent risk factors of LRR. The 5-year actuarial LRR rates in groups with no risk factor, one risk factor, and two risk factors were 2.3%, 19.8%, and 30.8%, respectively (p < 0.001). The locations of LRR were distributed as follows: aortocaval area (n=2), paraaortic area (n=4), retrocaval area (n=5), and tumor bed (n=11). No LRR was observed above the celiac axis (CA) or under the inferior mesenteric artery (IMA). Conclusion Tumor extension to renal vessels or the IVC and Fuhrman’s nuclear grade IV were the independent risk factors associated with LRR after RN for pT3-4 RCC. The locations of LRR after RN for RCC were distributed in the tumor bed and regional lymphatic area from the bifurcation of the CA to that of the IMA.

Background: and Purpose We aimed to develop a model predicting early recanalization after intravenous tissue plasminogen activator (t-PA) treatment in large-vessel occlusion. Methods: Using data from two different multicenter prospective cohorts, we determined the factors associated with early recanalization immediately after t-PA in stroke patients with large-vessel occlusion, and developed and validated a prediction model for early recanalization. Clot volume was semiautomatically measured on thin-section computed tomography using software, and the degree of collaterals was determined using the Tan score. Follow-up angiographic studies were performed immediately after t-PA treatment to assess early recanalization. Results: Early recanalization, assessed 61.0±44.7 minutes after t-PA bolus, was achieved in 15.5% (15/97) in the derivation cohort and in 10.5% (8/76) in the validation cohort. Clot volume (odds ratio [OR], 0.979; 95% confidence interval [CI], 0.961 to 0.997; P=0.020) and good collaterals (OR, 6.129; 95% CI, 1.592 to 23.594; P=0.008) were significant factors associated with early recanalization. The area under the curve (AUC) of the model including clot volume was 0.819 (95% CI, 0.720 to 0.917) and 0.842 (95% CI, 0.746 to 0.938) in the derivation and validation cohorts, respectively. The AUC improved when good collaterals were added (derivation cohort: AUC, 0.876; 95% CI, 0.802 to 0.950; P=0.164; validation cohort: AUC, 0.949; 95% CI, 0.886 to 1.000; P=0.036). The integrated discrimination improvement also showed significantly improved prediction (0.097; 95% CI, 0.009 to 0.185; P=0.032). Conclusions The model using clot volume and collaterals predicted early recanalization after intravenous t-PA and had a high performance. This model may aid in determining the recanalization treatment strategy in stroke patients with large-vessel occlusion.

Decision-making for treatment of newly diagnosed prostate cancer (PCa) is complex due to the multiple initial treatment modalities available. We aimed to externally validate the SCaP (Severance Study Group of Prostate Cancer) Survival Calculator that incorporates a long short-term memory artificial neural network (ANN) model to estimate survival outcomes of PCa according to initial treatment modality. Materials and Methods The validation cohort consisted of clinicopathological data of 4,415 patients diagnosed with biopsy-proven PCa between April 2005 and November 2018 at three institutions. Area under the curves (AUCs) and time-to-event calibration plots were utilized to determine the predictive accuracies of the SCaP Survival Calculator in terms of progression to castration-resistant PCa (CRPC)–free survival, cancer-specific survival (CSS), and overall survival (OS). Results Excellent discrimination was observed for CRPC-free survival, CSS, and OS outcomes, with AUCs of 0.962, 0.944, and 0.884 for 5-year outcomes and 0.959, 0.928, and 0.854 for 10-year outcomes, respectively. The AUC values were higher for all survival endpoints compared to those of the development cohort. Calibration plots showed that predicted probabilities of 5-year survival endpoints had concordance comparable to those of the observed frequencies. However, calibration performances declined for 10-year predictions with an overall underestimation. Conclusion The SCaP Survival Calculator is a reliable and useful tool for determining the optimal initial treatment modality and for guiding survival predictions for patients with newly diagnosed PCa. Further modifications in the ANN model incorporating cases with more extended follow-up periods are warranted to improve the ANN model for long-term predictions.

Background: The clinical features of pediatric rhabdomyolysis differ from those of the adults with rhabdomyolysis; however, multicenter studies are lacking. This study aimed to investigate the characteristics of pediatric rhabdomyolysis and reveal the risk factors for acute kidney injury (AKI) in such cases. Methods: This retrospective study analyzed the medical records of children and adolescents diagnosed with rhabdomyolysis at 23 hospitals in South Korea between January 2007 and December 2016. Results: Among 880 patients, those aged 3 to 5 years old composed the largest subgroup (19.4%), and all age subgroups were predominantly male. The incidence of AKI was 11.3%. Neurological disorders (53%) and infection (44%) were the most common underlying disorder and cause of rhabdomyolysis, respectively. The median age at diagnosis in the AKI subgroup was older than that in the non-AKI subgroup (12.2 years vs. 8.0 years). There were no significant differences in body mass index, myalgia, dark-colored urine, or the number of causal factors between the two AKI-status subgroups. The multivariate logistic regression model indicated that the following factors were independently associated with AKI: multiorgan failure, presence of an underlying disorder, strong positive urine occult blood, increased aspartate aminotransferase and uric acid levels, and reduced calcium levels. Conclusions Our study revealed characteristic clinical and laboratory features of rhabdomyolysis in a Korean pediatric population and highlighted the risk factors for AKI in these cases. Our findings will contribute to a greater understanding of pediatric rhabdomyolysis and may enable early intervention against rhabdomyolysis-induced AKI.

Decision-making for treatment of newly diagnosed prostate cancer (PCa) is complex due to the multiple initial treatment modalities available. We aimed to externally validate the SCaP (Severance Study Group of Prostate Cancer) Survival Calculator that incorporates a long short-term memory artificial neural network (ANN) model to estimate survival outcomes of PCa according to initial treatment modality. Materials and Methods The validation cohort consisted of clinicopathological data of 4,415 patients diagnosed with biopsy-proven PCa between April 2005 and November 2018 at three institutions. Area under the curves (AUCs) and time-to-event calibration plots were utilized to determine the predictive accuracies of the SCaP Survival Calculator in terms of progression to castration-resistant PCa (CRPC)–free survival, cancer-specific survival (CSS), and overall survival (OS). Results Excellent discrimination was observed for CRPC-free survival, CSS, and OS outcomes, with AUCs of 0.962, 0.944, and 0.884 for 5-year outcomes and 0.959, 0.928, and 0.854 for 10-year outcomes, respectively. The AUC values were higher for all survival endpoints compared to those of the development cohort. Calibration plots showed that predicted probabilities of 5-year survival endpoints had concordance comparable to those of the observed frequencies. However, calibration performances declined for 10-year predictions with an overall underestimation. Conclusion The SCaP Survival Calculator is a reliable and useful tool for determining the optimal initial treatment modality and for guiding survival predictions for patients with newly diagnosed PCa. Further modifications in the ANN model incorporating cases with more extended follow-up periods are warranted to improve the ANN model for long-term predictions.

Background: and Purpose We aimed to develop a model predicting early recanalization after intravenous tissue plasminogen activator (t-PA) treatment in large-vessel occlusion. Methods: Using data from two different multicenter prospective cohorts, we determined the factors associated with early recanalization immediately after t-PA in stroke patients with large-vessel occlusion, and developed and validated a prediction model for early recanalization. Clot volume was semiautomatically measured on thin-section computed tomography using software, and the degree of collaterals was determined using the Tan score. Follow-up angiographic studies were performed immediately after t-PA treatment to assess early recanalization. Results: Early recanalization, assessed 61.0±44.7 minutes after t-PA bolus, was achieved in 15.5% (15/97) in the derivation cohort and in 10.5% (8/76) in the validation cohort. Clot volume (odds ratio [OR], 0.979; 95% confidence interval [CI], 0.961 to 0.997; P=0.020) and good collaterals (OR, 6.129; 95% CI, 1.592 to 23.594; P=0.008) were significant factors associated with early recanalization. The area under the curve (AUC) of the model including clot volume was 0.819 (95% CI, 0.720 to 0.917) and 0.842 (95% CI, 0.746 to 0.938) in the derivation and validation cohorts, respectively. The AUC improved when good collaterals were added (derivation cohort: AUC, 0.876; 95% CI, 0.802 to 0.950; P=0.164; validation cohort: AUC, 0.949; 95% CI, 0.886 to 1.000; P=0.036). The integrated discrimination improvement also showed significantly improved prediction (0.097; 95% CI, 0.009 to 0.185; P=0.032). Conclusions The model using clot volume and collaterals predicted early recanalization after intravenous t-PA and had a high performance. This model may aid in determining the recanalization treatment strategy in stroke patients with large-vessel occlusion.

The Korean Society of Urogenital Radiology (KSUR) aimed to present a consensus statement for patient preparation, standard technique, and pain management in relation to transrectal ultrasound-guided prostate biopsy (TRUS-Bx) to reduce the variability in TRUS-Bx methodologies and suggest a nationwide guideline. The KSUR guideline development subcommittee constructed questionnaires assessing prebiopsy anticoagulation, the cleansing enema, antimicrobial prophylaxis, local anesthesia methods such as periprostatic neurovascular bundle block (PNB) or intrarectal lidocaine gel application (IRLA), opioid usage, and the number of biopsy cores and length and diameter of the biopsy needle. The survey was conducted using an Internet-based platform, and responses were solicited from the 90 members registered on the KSUR mailing list as of 2018. A comprehensive search of relevant literature from Medline database was conducted. The strength of each recommendation was graded on the basis of the level of evidence. Among the 90 registered members, 29 doctors (32.2%) responded to this online survey. Most KSUR members stopped anticoagulants (100%) and antiplatelets (76%) one week before the procedure. All respondents performed a cleansing enema before TRUS-Bx. Approximately 86% of respondents administered prophylactic antibiotics before TRUS-Bx. The most frequently used antibiotics were third-generation cephalosporins. PNB was the most widely used pain control method, followed by a combination of PNB plus IRLA. Opioids were rarely used (6.8%), and they were used only as an adjunctive pain management approach during TRUS-Bx. The KSUR members mainly chose the 12-core biopsy method (89.7%) and 18G 16-mm or 22-mm (96.5%) needles. The KSUR recommends the 12-core biopsy scheme with PNB with or without IRLA as the standard protocol for TRUS-Bx. Anticoagulants and antiplatelet agents should be discontinued at least 5 days prior to the procedure, and antibiotic prophylaxis is highly recommended to prevent infectious complications. Glycerin cleansing enemas and administration of opioid analogues before the procedure could be helpful in some situations. The choice of biopsy needle is dependent on the practitioners' situation and preferences.