Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Gastric cancer is one of the most common cancers in Korea and the world. Since 2004, this is the 4th gastric cancer guideline published in Korea which is the revised version of previous evidence-based approach in 2018. Current guideline is a collaborative work of the interdisciplinary working group including experts in the field of gastric surgery, gastroenterology, endoscopy, medical oncology, abdominal radiology, pathology, nuclear medicine, radiation oncology and guideline development methodology. Total of 33 key questions were updated or proposed after a collaborative review by the working group and 40 statements were developed according to the systematic review using the MEDLINE, Embase, Cochrane Library and KoreaMed database. The level of evidence and the grading of recommendations were categorized according to the Grading of Recommendations, Assessment, Development and Evaluation proposition. Evidence level, benefit, harm, and clinical applicability was considered as the significant factors for recommendation. The working group reviewed recommendations and discussed for consensus. In the earlier part, general consideration discusses screening, diagnosis and staging of endoscopy, pathology, radiology, and nuclear medicine. Flowchart is depicted with statements which is supported by meta-analysis and references. Since clinical trial and systematic review was not suitable for postoperative oncologic and nutritional follow-up, working group agreed to conduct a nationwide survey investigating the clinical practice of all tertiary or general hospitals in Korea. The purpose of this survey was to provide baseline information on follow up. Herein we present a multidisciplinary-evidence based gastric cancer guideline.

Purpose: Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers (ARBs) are frequently employed to counteract the detrimental effects of proteinuria on glomerular diseases. However, the effects of ARBs remain poorly examined in pediatric patients with immunoglobulin A (IgA) nephropathy. Herein, we evaluated the efficacy and safety of losartan, an ARB, in pediatric IgA nephropathy with proteinuria. Methods: This prospective, single-arm, multicenter study included children with IgA nephropathy exhibiting proteinuria. Changes in proteinuria, blood pressure, and kidney function were prospectively evaluated before and 4 and 24 weeks after losartan administration. The primary endpoint was the difference in proteinuria between baseline and 24 weeks. Results: In total, 29 patients were enrolled and received losartan treatment. The full analysis set included 28 patients who received losartan at least once and had pre- and post-urinary protein to creatinine ratio measurements (n=28). The per-protocol analysis group included 22 patients who completed all scheduled visits without any serious violations during the study period. In both groups, the mean log (urine protein to creatinine ratio) value decreased significantly at 6 months. After 24 weeks, the urinary protein to creatinine ratio decreased by more than 50% in approximately 40% of the patients. The glomerular filtration rate was not significantly altered during the observation period. Conclusions Losartan decreased proteinuria without decreasing kidney function in patients with IgA nephropathy over 24 weeks. Losartan could be safely employed to reduce proteinuria in this patient population. ClinicalTrials.gov trial registration (NCT0223277)

Purpose: Various clinical practice guidelines recommend at least 12 regional lymph nodes should be removed for resected colon cancer. According to a recent study, the lymph node yield (LNY) in colon cancer surgery in the last 20 years has tended to increase from 14.91 to 21.30. However, it is unclear whether these guidelines adequately reflect recent findings on the number of harvested lymph nodes in colon cancer surgery. The aim of this study is to assess the impact of an LNY of more than 25 on survival in right-sided colon cancer. Methods: We included 285 patients who underwent a right hemicolectomy during the period from January 2010 through December 2015. Patients were divided into two groups (<25 nodes and ≥25 nodes). Primary endpoints included 5-year and 10-year survival including disease-free and overall. Results: We found that survival outcomes of patients with a harvest of ≥25 nodes were not significantly different compared with a <25 group. Large tumor size (5 cm) is significantly associated with poor 5-year and 10-year overall survival. Conclusion Survival outcomes of patients with a harvest of ≥25 nodes were not significantly different compared with the <25 group in stage II colon cancer with no risk.

Background and Objectives: This study aimed to investigate the association between cardiovascular events and 2 different levels of elevated on-treatment diastolic blood pressures (DBP) in the presence of achieved systolic blood pressure targets (SBP). Methods: A nation-wide population-based cohort study comprised 237,592 patients with hypertension treated. The primary endpoint was a composite of cardiovascular death, myocardial infarction, and stroke. Elevated DBP was defined according to the Seventh Report of Joint National Committee (JNC7; SBP <140 mmHg, DBP ≥90 mmHg) or to the 2017 American College of Cardiology/American Heart Association (ACC/AHA) definitions (SBP <130 mmHg, DBP ≥80 mmHg). Results: During a median follow-up of 9 years, elevated on-treatment DBP by the JNC7 definition was associated with an increased risk of the occurrence of primary endpoint compared with achieved both SBP and DBP (adjusted hazard ratio [aHR], 1.14; 95% confidence interval [CI], 1.05–1.24) but not in those by the 2017 ACC/AHA definition. Elevated ontreatment DBP by the JNC7 definition was associated with a higher risk of cardiovascular mortality (aHR, 1.42; 95% CI, 1.18–1.70) and stroke (aHR, 1.19; 95% CI, 1.08–1.30). Elevated on-treatment DBP by the 2017 ACC/AHA definition was only associated with stroke (aHR, 1.10;95% CI, 1.04–1.16). Similar results were seen in the propensity-score-matched cohort. Conclusion Elevated on-treatment DBP by the JNC7 definition was associated a high risk of major cardiovascular events, while elevated DBP by the 2017 ACC/AHA definition was only associated with a higher risk of stroke. The result of study can provide evidence of DBP targets in subjects who achieved SBP targets.

Objective: Recent studies have suggested that deep-learning models can satisfactorily assist in fracture diagnosis. We aimed to evaluate the performance of two of such models in wrist fracture detection. Methods: We collected image data of patients who visited with wrist trauma at the emergency department. A dataset extracted from January 2018 to May 2020 was split into training (90%) and test (10%) datasets, and two types of convolutional neural networks (i.e., DenseNet-161 and ResNet-152) were trained to detect wrist fractures. Gradient-weighted class activation mapping was used to highlight the regions of radiograph scans that contributed to the decision of the model. Performance of the convolutional neural network models was evaluated using the area under the receiver operating characteristic curve. Results: For model training, we used 4,551 radiographs from 798 patients and 4,443 radiographs from 1,481 patients with and without fractures, respectively. The remaining 10% (300 radiographs from 100 patients with fractures and 690 radiographs from 230 patients without fractures) was used as a test dataset. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DenseNet-161 and ResNet-152 in the test dataset were 90.3%, 90.3%, 80.3%, 95.6%, and 90.3% and 88.6%, 88.4%, 76.9%, 94.7%, and 88.5%, respectively. The area under the receiver operating characteristic curves of DenseNet-161 and ResNet-152 for wrist fracture detection were 0.962 and 0.947, respectively. Conclusion We demonstrated that DenseNet-161 and ResNet-152 models could help detect wrist fractures in the emergency room with satisfactory performance.

Objective: Recent studies have suggested that deep-learning models can satisfactorily assist in fracture diagnosis. We aimed to evaluate the performance of two of such models in wrist fracture detection. Methods: We collected image data of patients who visited with wrist trauma at the emergency department. A dataset extracted from January 2018 to May 2020 was split into training (90%) and test (10%) datasets, and two types of convolutional neural networks (i.e., DenseNet-161 and ResNet-152) were trained to detect wrist fractures. Gradient-weighted class activation mapping was used to highlight the regions of radiograph scans that contributed to the decision of the model. Performance of the convolutional neural network models was evaluated using the area under the receiver operating characteristic curve. Results: For model training, we used 4,551 radiographs from 798 patients and 4,443 radiographs from 1,481 patients with and without fractures, respectively. The remaining 10% (300 radiographs from 100 patients with fractures and 690 radiographs from 230 patients without fractures) was used as a test dataset. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DenseNet-161 and ResNet-152 in the test dataset were 90.3%, 90.3%, 80.3%, 95.6%, and 90.3% and 88.6%, 88.4%, 76.9%, 94.7%, and 88.5%, respectively. The area under the receiver operating characteristic curves of DenseNet-161 and ResNet-152 for wrist fracture detection were 0.962 and 0.947, respectively. Conclusion We demonstrated that DenseNet-161 and ResNet-152 models could help detect wrist fractures in the emergency room with satisfactory performance.