Purpose: We are reporting a case of transient posterior capsular opacity after intravitreal Bevacizumab (Avastin®, Roche Pharma Schweis AG, Zurich, Switzerland) injection in a phakic patient.Case summary: A 34-year-old man visited our clinic with sudden blurred vision in his left eye one day after the intravitreal injection for central serous chorioretinopathy. His visual acuity was 1.0 before the injection and decreased to 0.1 at the presentation. On slit-lamp examination, a snow-flake appearance opacity was noted behind the posterior capsule. No newly appearing lesion was presented on fundus exam, so topical antibiotics and steroid eyedrops were continued. One week after the injection, the visual acuity improved to 1.0 and posterior capsular opacity remained but decreased. Five weeks after the injection, the posterior capsular opacity resolved. Fundus exam revealed improved but persistent subretinal fluid, so he overwent another intravitreal injection. The posterior capsular opacity did not recur for seven months. Conclusions Iatrogenic lens damage or the turbidity formed by medication can cause a posterior capsular opacity after intravitreal injection. If structural damage is uncertain, close monitoring is needed and ultimately, cataract surgery may be required for chronic crystalline lens opacity.

Purpose: We investigated the consistent efficacy and safety of eflapegrastim, a novel long-acting granulocyte-colony stimulating factor (G-CSF), in Koreans and Asians compared with the pooled population of two global phase 3 trials. Materials and Methods: Two phase 3 trials (ADVANCE and RECOVER) evaluated the efficacy and safety of fixed-dose eflapegrastim (13.2 mg/0.6 mL [3.6 mg G-CSF equivalent]) compared to pegfilgrastim (6 mg based on G-CSF) in breast cancer patients who received neoadjuvant or adjuvant docetaxel/cyclophosphamide. The primary objective was to demonstrate non-inferiority of eflapegrastim compared to pegfilgrastim in mean duration of severe neutropenia (DSN) in cycle 1, in Korean and Asian subpopulations. Results: Among a total of 643 patients randomized to eflapegrastim (n=314) or pegfilgrastim (n=329), 54 Asians (29 to eflapegrastim and 25 to pegfilgrastim) including 28 Koreans (14 to both eflapegrastim and pegfilgrastim) were enrolled. The primary endpoint, DSN in cycle 1 in the eflapegrastim arm was non-inferior to the pegfilgrastim arm in Koreans and Asians. The DSN difference between the eflapegrastim and pegfilgrastim arms was consistent across populations: –0.120 days (95% confidence interval [CI], –0.227 to –0.016), –0.288 (95% CI, –0.714 to 0.143), and –0.267 (95% CI, –0.697 to 0.110) for pooled population, Koreans and Asians, respectively. There were few treatment-related adverse events that caused discontinuation of eflapegrastim (1.9%) or pegfilgrastim (1.5%) in total and no notable trends or differences across patient populations. Conclusion This study may suggest that eflapegrastim showed non-inferior efficacy and similar safety compared to pegfilgrastim in Koreans and Asians, consistently with those of pooled population.

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions.However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

With the widespread use of broad-spectrum antibiotics in clinical practice, the emergence of multidrug-resistant (MDR) gram-negative bacteria has become a global problem. The MDR Pseudomonas aeruginosa infection is especially difficult to treat and increases mortality in critically ill patients. Ceftolozane-tazobactam (Zerbaxa™) is a fifth-generation cephalosporin and beta-lactamase inhibitor that has proved to be effective for treating complicated urinary tract infections and complicated intra-abdominal infections caused by MDR P. aeruginosa. Herein, we report the first case of pediatric hematologic cancer in Korea that was successfully treated for MDR P. aeruginosa bacteremia with Ceftolozane-tazobactam.