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.

Purpose: We investigated the role of prostate-specific antigen (PSA) variation as a predictor of prostate cancer in patients who underwent prebiopsy multiparametric magnetic resonance imaging (MRI). Materials and Methods: The clinicopathological data of 266 patients with PSA ≤20 ng/mL who underwent prebiopsy MRI and prostate biopsy between September 2019 and February 2021 were included. PSA variation was defined as the difference in PSA values taken when a prostate biopsy was recommended and performed (median 20 days). Receiver operating characteristic (ROC) curves and area under the ROC curves (AUCs) for predicting prostate cancer were analyzed through 4 models that considered conventional clinical variables and PSA variation. Results: Of the 258 patients, 166 (64.3%) were diagnosed with prostate cancer. The prostate cancer (+) group had a lower median PSA variation (-0.09 mg/mL vs. -0.27 ng/mL, p=0.006) and higher proportion of patients with PSA variation within -0.54 to 0.05 ng/mL (40 ng/mL [range, 24.1%] vs. 9 ng/mL [9.8%], p=0.002) than the prostate cancer (-) group. There was no significant difference in the duration between the 2 PSA measurements. When PSA variation and conventional variables, such as age, PSA density, prostate biopsy history, number of target lesions, were considered, the highest AUC value was 0.870. In a subgroup analysis of patients with PSA ≤10 ng/mL, the highest AUC value was 0.860 when PSA variation and conventional variables were considered. Conclusions A large PSA variation within 1 month was a negative predictor of prostate cancer among patients who underwent prebiopsy MRI.

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.