Background: We developed a simplified variant of the ADV score, the AFP-PIVKAII (AP) score for post-transplant hepatocellular carcinoma (HCC) prognosis, which considers only AFP and PIVKA-II levels excluding morphometric tumor size information from the ADV score. This study investigated the prognostic performance of the AP score in predicting HCC recurrence and overall survival (OS) after living donor liver transplantation (LDLT). Methods: We analyzed 843 patients with HCC who underwent LDLT between 2006 and 2015, assessing HCC recurrence and OS in relation to AP score. Results: The median pretransplant AFP and PIVKA-II levels were 12.8 ng/mL and 27 mAU/mL, respectively. The median and mean AP scores were 2.6 log (range: 0.6–9.2 log) and 2.9±1.1 log, respectively. The 5-year time-dependent area under the receiver operating characteristic curve for the AP score in predicting post-transplant HCC recurrence was 0.672 (p<0.001). HCC recurrence and OS curves along AP score intervals of 1.0 log showed statistical differences in accordance with the AP scores (both p<0.001). Using a Youden index J-derived AP score cutoff of 4.0 log, two-tiered groups (ADV <4.0 log vs. ADV ≥4.0 log) showed statistically significant differences in HCC recurrence and OS (both p<0.001). Harrell’s c-indices for AP score with cutoff of 4.0 log and ADV scores with cutoff of 5.0 log regarding HCC recurrence and OS were similar. Conclusion The AP score functions as an integrated surrogate marker for predicting post-transplant outcomes in patients with HCC undergoing LDLT. It may serve as a simplified alternative to the ADV score, particularly in patients with small HCCs.

Purpose: The male predominance in the incidence of gastric cancer (GC) is established; however, sex differences in the prognosis of GC remain controversial. As such, this study analyzed the prognosis of patients with GC based on age and sex. Materials and Methods: Data from 14,739 patients diagnosed with GC at Seoul National University Bundang Hospital between 2003 and 2023 were analyzed. Baseline characteristics, histological types of GC, overall and GC-specific survival rates (age and stage stratification), and associated risk factors were analyzed. Results: Females were significantly younger (p < 0.001) and exhibited more gastric body cancers (p < 0.001) and tumors with diffuse-type or poorly differentiated histology (p < 0.001) than males. Females exhibited an advantage over males in terms of overall survival (p=0.004), but not in GC-specific survival. However, age stratification revealed significant sex differences, that females < 50 years of age exhibited survival disadvantages (p < 0.001); however, this trend was reversed with age, and females > 60 years exhibited survival advantages (p < 0.001) for both overall and GC-specific survival. This may be explained by the lower ratio of diffuse-type GC as females age. Furthermore, in the analysis according to stage, females with stage IV disease exhibited significant survival disadvantages, with significantly younger age and a higher proportion of diffuse-type GC which exhibits aggressive features, resulting in poorer survival than in males. Conclusion Age and stage stratification revealed significant differences in survival between the sexes, which can be helpful for public health strategies.

Background: Studies on whether donor-to-recipient sex match status affects long-term survival after liver transplantation (LT) have yielded contradictory results. This study evaluated whether donor-to-recipient sex match status influenced long-term survival after living donor liver transplantation (LDLT) or deceased donor liver transplantation (DDLT) at a high-volume center. Methods: The study included 6,664 patients who underwent primary LT between January 2000 and December 2022 at our institution. Patients were divided into four groups according to donor-to-recipient sex match status: male-to-male (n=3,427 [51.4%]), male-to-female (n=1,152 [17.3%]), female-to-male (n=1,385 [20.8%]), and female-to-female (n=700 [10.5%]). Results: Regarding clinical characteristics, the four groups differed significantly regarding background liver disease (P<0.001), model for end-stage liver disease score (P<0.001), serum protein induced by vitamin K absence or antagonist II level (P=0.003), presence of concurrent hepatocellular carcinoma (HCC; P<0.001), and type of LT (P=0.003). Overall survival (OS) of all LT recipients did not differ significantly among the groups (P=0.377). Donor-to-recipient sex match status did not affect long-term OS in either LDLT (P=0.176) or DDLT (P=0.220) groups. In addition, sex match status did not significantly influence posttransplant OS among patients who underwent LDLT without HCC (P=0.464), LDLT with HCC (P=0.236), DDLT without HCC (P=0.338), or DDLT with HCC (P=0.818). Conclusions Donor-to-recipient sex match status does not significantly affect posttransplant patient survival or HCC prognosis after LDLT or DDLT.

In patients with differentiated thyroid cancer (DTC), initial recurrence risk stratification based on clinical, histopathological, and perioperative data remains the key determinant for guiding management strategies during the first 1-2 years post-treatment. However, the adoption of ongoing risk stratification (ORS), which dynamically reassesses risk by integrating longitudinal clinical data and treatment response, enables more precise long-term prognostic assessment and facilitates highly individualized management. Building upon recent guidelines, the 2026 KTA guideline has been further refined by incorporating robust evidence from large-scale national cohorts and comprehensive systematic reviews. These updated recommendations outline contemporary concepts of ORS, risk-adapted TSH suppression targets, optimized surveillance modalities for recurrence detection, and disease-specific long-term follow-up strategies. Reflecting the paradigm shift toward de-escalated treatment, this revision integrates evolved perspectives on TSH suppression intensity, the clinical interpretation of thyroglobulin levels, and tailored follow-up intervals. These evidence-based recommendations aim to minimize unnecessary treatment and excessive surveillance in the large proportion of patients with excellent prognosis after initial therapy, while ensuring that each patient receives appropriately tailored and effective long-term management.

Purpose: Adjuvant treatment for craniopharyngioma after surgery is controversial. Adjuvant external beam radiation therapy (EBRT) can increase the risk of long-term sequelae. Stereotactic radiosurgery (SRS) is used to reduce treatment-related toxicity.In this study, we compared the treatment outcomes and toxicities of adjuvant therapies for craniopharyngioma. Materials and Methods: We analyzed patients who underwent craniopharyngioma tumor removal between 2000 and 2017. Of the 153 patients, 27 and 20 received adjuvant fractionated EBRT and SRS, respectively. We compared the local control (LC), progression-free survival (PFS), and overall survival between groups that received adjuvant fractionated EBRT, SRS, and surveillance. Results: The median follow-up period was 77.7 months. For SRS and surveillance, the 10-year LC was 57.2% and 57.4%, respectively. No local progression was observed after adjuvant fractionated EBRT. One patient in the adjuvant fractionated EBRT group died owing to glioma 94 months after receiving radiotherapy (10-year PFS: 80%). The 10-year PFS was 43.6% and 50.7% in the SRS and surveillance groups, respectively. The treatment outcomes significantly differed according to adjuvant treatment in nongross total resection (GTR) patients. Additional treatment-related toxicity was comparable in the adjuvant fractionated EBRT and other groups. Conclusion Adjuvant fractionated EBRT could be effective in controlling local failure, especially in patients with non-GTR, while maintaining acceptable treatment-related toxicity.

Background: Currently, little is known about the relationship between the temporal radiographic latent trajectories, which are based on the extent of coronavirus disease 2019 (COVID-19) pneumonia and clinical outcomes. This study aimed to elucidate the differences in the temporal trends of critical laboratory biomarkers, utilization of critical care support, and clinical outcomes according to temporal radiographic latent trajectories. Methods: We enrolled 2,385 patients who were hospitalized with COVID-19 and underwent serial chest radiographs from December 2019 to March 2022. The extent of radiographic pneumonia was quantified as a percentage using a previously developed deep-learning algorithm. A latent class growth model was used to identify the trajectories of the longitudinal changes of COVID-19 pneumonia extents during hospitalization. We investigated the differences in the temporal trends of critical laboratory biomarkers among the temporal radiographic trajectory groups. Cox regression analyses were conducted to investigate differences in the utilization of critical care supports and clinical outcomes among the temporal radiographic trajectory groups. Results: The mean age of the enrolled patients was 58.0 ± 16.9 years old, with 1,149 (48.2%) being male. Radiographic pneumonia trajectories were classified into three groups: The steady group (n = 1,925, 80.7%) exhibited stable minimal pneumonia, the downhill group (n = 135, 5.7%) exhibited initial worsening followed by improving pneumonia, and the uphill group (n = 325, 13.6%) exhibited progressive deterioration of pneumonia. There were distinct differences in the patterns of temporal blood urea nitrogen (BUN) and C-reactive protein (CRP) levels between the uphill group and the other two groups. Cox regression analyses revealed that the hazard ratios (HRs) for the need for critical care support and the risk of intensive care unit admission were significantly higher in both the downhill and uphill groups compared to the steady group. However, regarding in-hospital mortality, only the uphill group demonstrated a significantly higher risk than the steady group (HR, 8.2; 95% confidence interval, 3.08–21.98). Conclusion Stratified pneumonia trajectories, identified through serial chest radiographs, are linked to different patterns of temporal changes in BUN and CRP levels. These changes can predict the need for critical care support and clinical outcomes in COVID-19 pneumonia.Appropriate therapeutic strategies should be tailored based on these disease trajectories.

Background: Currently, little is known about the relationship between the temporal radiographic latent trajectories, which are based on the extent of coronavirus disease 2019 (COVID-19) pneumonia and clinical outcomes. This study aimed to elucidate the differences in the temporal trends of critical laboratory biomarkers, utilization of critical care support, and clinical outcomes according to temporal radiographic latent trajectories. Methods: We enrolled 2,385 patients who were hospitalized with COVID-19 and underwent serial chest radiographs from December 2019 to March 2022. The extent of radiographic pneumonia was quantified as a percentage using a previously developed deep-learning algorithm. A latent class growth model was used to identify the trajectories of the longitudinal changes of COVID-19 pneumonia extents during hospitalization. We investigated the differences in the temporal trends of critical laboratory biomarkers among the temporal radiographic trajectory groups. Cox regression analyses were conducted to investigate differences in the utilization of critical care supports and clinical outcomes among the temporal radiographic trajectory groups. Results: The mean age of the enrolled patients was 58.0 ± 16.9 years old, with 1,149 (48.2%) being male. Radiographic pneumonia trajectories were classified into three groups: The steady group (n = 1,925, 80.7%) exhibited stable minimal pneumonia, the downhill group (n = 135, 5.7%) exhibited initial worsening followed by improving pneumonia, and the uphill group (n = 325, 13.6%) exhibited progressive deterioration of pneumonia. There were distinct differences in the patterns of temporal blood urea nitrogen (BUN) and C-reactive protein (CRP) levels between the uphill group and the other two groups. Cox regression analyses revealed that the hazard ratios (HRs) for the need for critical care support and the risk of intensive care unit admission were significantly higher in both the downhill and uphill groups compared to the steady group. However, regarding in-hospital mortality, only the uphill group demonstrated a significantly higher risk than the steady group (HR, 8.2; 95% confidence interval, 3.08–21.98). Conclusion Stratified pneumonia trajectories, identified through serial chest radiographs, are linked to different patterns of temporal changes in BUN and CRP levels. These changes can predict the need for critical care support and clinical outcomes in COVID-19 pneumonia.Appropriate therapeutic strategies should be tailored based on these disease trajectories.