Rectal cancer, which accounts for approximately 40% of colorectal cancers, remains a major clinical concern. Recent advances in diagnostic imaging, surgical techniques, radiotherapy, and systemic treatment have steadily improved rectal cancer outcomes. Considering this, the Korean Rectal Cancer Multidisciplinary (KRCM) Committee has aimed to provide clinicians and policymakers with up-to-date, evidence-based clinical practice guidelines to support optimal decision-making, reflecting current evidence, the Korean healthcare context, and patient values and preferences. The Clinical Practice Guidelines for Rectal Cancer version 2.0 were developed through multidisciplinary collaboration with related academic societies, building upon and updating the KRCM Clinical Practice Guidelines version 1.0 (titled “Multidisciplinary guidelines for the management of rectal cancer”). These consensus guidelines of the KRCM were established based on a comprehensive literature review, evidence synthesis, with recommendation development guided by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology, and consideration of applicability in real-world clinical practice under the national health insurance system. Each recommendation has been presented with its strength and level of evidence.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Background: and Purpose: Plasma biomarkers, including phosphorylated tau (ptau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), are promising tools for detecting Alzheimer’s disease (AD) pathology. However, cross-laboratory reproducibility remains a challenge, even when using identical analytical platforms such as single-molecule array (Simoa). This study aimed to compare plasma biomarker measurements (ptau217, GFAP, and NfL) between 2 laboratories, the University of Gothenburg (UGOT) and DNAlink, and evaluate their associations with amyloid positron emission tomography (PET) imaging. Methods: Plasma biomarkers were measured using Simoa platforms at both laboratories:the UGOT and DNAlink Incorporation. Diagnostic performance for predicting amyloid PET positivity, cross-laboratory agreement, and the impact of normalization techniques were assessed. Bland-Altman plots and correlation analyses were employed to evaluate agreement and variability. Results: Plasma ptau217 concentrations exhibited strong correlations with amyloid PET global centiloid values, with comparable diagnostic performance between laboratories (area under the curve=0.94 for UGOT and 0.95 for DNAlink). Cross-laboratory agreement for ptau217 was excellent (r=0.96), improving further after natural log transformation. GFAP and NfL also demonstrated moderate to strong correlations (r=0.86 for GFAP and r=0.99 for NfL), with normalization reducing variability. Conclusions Plasma biomarker measurements were consistent across laboratories using identical Simoa platforms, with strong diagnostic performance and improved agreement after normalization. These findings support the scalability of plasma biomarkers for multicenter studies and underscore their potential for standardized applications in AD research and clinical practice.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

Immunoglobulin A nephropathy (IgAN) is a major cause of end-stage kidney disease (ESKD). The International IgA Nephropathy Prediction Tool (IIgAN-PT) predicts IgAN prognosis, but improvement in the prediction performance using machine learning (ML)-based methods is needed. Methods: We analyzed 4,425 biopsy-confirmed patients with IgAN and ≥6 months of follow-up from nine tertiary university hospitals in Korea. The study population was divided into development and validation cohorts. Using the collected 87 clinicodemographic and pathological variables, ML-based prediction models for ESKD or estimated glomerular filtration rate decline (50% reduction or <15 mL/min/1.73 m2 ) were constructed: 1) the conventional CatBoost model, 2) the optimized CatBoost model with Cox proportional hazards, 3) the deep Cox proportional hazards model, and 4) the deep Cox mixture model. The area under the curve (AUC) and calibration plots were used to investigate the discriminative and calibration performance of the models, which were then compared with those of the IIgAN-PT full model. Results: The full model showed excellent performance (AUC [95% confidence interval] for 5-year outcome, 0.896 [0.853–0.940]), with acceptable calibration results. The ML-based models showed good performance in predicting adverse kidney outcomes and revealed acceptable discrimination performance in the external validation (AUC [95% confidence interval] for the 5-year outcome: 1) 0.829 [0.791–0.866]; 2) 0.847 [0.804–0.890]; 3) 0.823 [0.784–0.862]; and 4) 0.832 [0.794–0.870]), although the models showed underestimation in calibration analysis of the external validation cohort. With the validation data, the overall performance of the IIgAN-PT was non-inferior to that of the ML-based model. Conclusions: Our ML-based models showed good performance in predicting adverse kidney outcomes in patients with IgAN but they did not outperform the IIgAN-PT.

Patients with sensitization and blood type O experience increased waiting times for deceased-donor kidney transplantation (DDKT). While allocation benefits are needed to resolve inequity in DDKT opportunity, whether DDKT has comparable outcomes in this disadvantaged population requires further study. This study assessed these outcomes and developed a new allocation system that balances equity and utility. Methods: Patients from national and hospital cohorts from two centers in Korea were categorized as B1 to B4 (according to panel reactive antibody [PRA] positivity and ABO blood type) and A1 to A4 (based on the maximal PRA% and blood type), respectively. Competing risk and Cox regression analyses were performed to assess the effects of PRA and blood type on graft failure and mortality, respectively. Based on DDKT opportunities and posttransplant outcomes, a new scoring system for kidney allocation was developed. Results: The national and hospital cohorts included 3,311 and 819 patients, respectively, who underwent DDKT. Despite the disparities in DDKT opportunities, the graft failure rates and mortality did not differ among the different PRA and blood type groups. Furthermore, posttransplantation outcomes did not differ according to the categories with different DDKT opportunities. A new scoring system to provide additional points to disadvantaged populations was developed based on the hazard ratios for DDKT. Conclusion: A new allocation approach based on PRA and ABO blood types offers benefits to disadvantaged patients with fewer DDKT opportunities and could enhance equity without sacrificing utility in Korea, which has a long waiting time for DDKT.