1.The Effect of Hematopoietic Stem Cell Transplantation on Treatment Outcome in Children with Acute Lymphoblastic Leukemia
Hee Young JU ; Na Hee LEE ; Eun Sang YI ; Young Bae CHOI ; So Jin KIM ; Ju Kyung HYUN ; Hee Won CHO ; Jae Kyung LEE ; Ji Won LEE ; Ki Woong SUNG ; Hong Hoe KOO ; Keon Hee YOO
Cancer Research and Treatment 2025;57(1):240-249
Purpose:
Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups.
Materials and Methods:
A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease.
Results:
Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment.
Conclusion
HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.
2.Predicting Parkinson’s Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data
Youngwook KOO ; Minki KIM ; Woong-Woo LEE
Journal of Clinical Neurology 2025;21(1):21-30
Background:
and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information.
Methods:
We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods.
Results:
During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922.
Conclusions
A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.
3.The Effect of Hematopoietic Stem Cell Transplantation on Treatment Outcome in Children with Acute Lymphoblastic Leukemia
Hee Young JU ; Na Hee LEE ; Eun Sang YI ; Young Bae CHOI ; So Jin KIM ; Ju Kyung HYUN ; Hee Won CHO ; Jae Kyung LEE ; Ji Won LEE ; Ki Woong SUNG ; Hong Hoe KOO ; Keon Hee YOO
Cancer Research and Treatment 2025;57(1):240-249
Purpose:
Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups.
Materials and Methods:
A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease.
Results:
Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment.
Conclusion
HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.
4.Predicting Parkinson’s Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data
Youngwook KOO ; Minki KIM ; Woong-Woo LEE
Journal of Clinical Neurology 2025;21(1):21-30
Background:
and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information.
Methods:
We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods.
Results:
During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922.
Conclusions
A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.
5.The Effect of Hematopoietic Stem Cell Transplantation on Treatment Outcome in Children with Acute Lymphoblastic Leukemia
Hee Young JU ; Na Hee LEE ; Eun Sang YI ; Young Bae CHOI ; So Jin KIM ; Ju Kyung HYUN ; Hee Won CHO ; Jae Kyung LEE ; Ji Won LEE ; Ki Woong SUNG ; Hong Hoe KOO ; Keon Hee YOO
Cancer Research and Treatment 2025;57(1):240-249
Purpose:
Hematopoietic stem cell transplantation (HSCT) has been an important method of treatment in the advance of pediatric acute lymphoblastic leukemia (ALL). The indications for HSCT are evolving and require updated establishment. In this study, we aimed to investigate the efficacy of HSCT on the treatment outcome of pediatric ALL, considering the indications for HSCT and subgroups.
Materials and Methods:
A retrospective analysis was conducted on ALL patients diagnosed and treated at a single center. Risk groups were categorized based on age at diagnosis, initial white blood cell count, disease lineage (B/T), and cytogenetic study results. Data on the patients’ disease status at HSCT and indications of HSCT were collected. Indications for HSCT were categorized as upfront HSCT at 1st complete remission, relapse, and refractory disease.
Results:
Among the 549 screened patients, a total of 418 patients were included in the study; B-cell ALL (n=379) and T-cell ALL (T-ALL) (n=39). HSCT was conducted on a total of 106 patients (25.4%), with a higher frequency as upfront HSCT in higher-risk groups and specific cytogenetics. The overall survival (OS) was significantly better when done upfront than in relapsed or refractory state in T-ALL patients (p=0.002). The KMT2A-rearranged ALL patients showed superior event-free survival (p=0.002) and OS (p=0.022) when HSCT was done as upfront treatment.
Conclusion
HSCT had a substantial positive effect in a specific subset of pediatric ALL. In particular, frontline HSCT for T-ALL and KMT2A-rearranged ALL offered a better prognosis than when HSCT was conducted in a relapsed or refractory setting.
6.Predicting Parkinson’s Disease Using a Deep-Learning Algorithm to Analyze Prodromal Medical and Prescription Data
Youngwook KOO ; Minki KIM ; Woong-Woo LEE
Journal of Clinical Neurology 2025;21(1):21-30
Background:
and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information.
Methods:
We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods.
Results:
During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922.
Conclusions
A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.
7.Evaluating a 3D-printed biodegradable paclitaxel-eluting stent for biliary stricture management after liver transplantation: An in vivo porcine study
Jiyoung KIM ; YoungRok CHOI ; Joon Koo HAN ; Jae Hyun KIM ; Dong-Heon HA ; Eui Soo HAN ; Jiwon KOH ; Jae-Yoon KIM ; Jaewon LEE ; Hyun Hwa CHOI ; Su young HONG ; Jeong-Moo LEE ; Suk Kyun HONG ; Kwang-Woong LEE
Annals of Liver Transplantation 2025;5(2):89-97
Background:
Liver transplantation (LT) is the standard treatment for end-stage liver disease; however, it can lead to biliary strictures in 25%–30% of cases. We aimed to develop a biodegradable stent loaded with paclitaxel that could be inserted during surgery without requiring removal. We evaluated the safety and efficacy of this stent using a porcine model.
Methods:
Fourteen pigs underwent simulated ischemic injury during LT, and a biodegradable paclitaxel-eluting stent was inserted after duct-to-duct anastomosis.Pigs were divided into four groups: no stent (n=3), bare stent (n=3), 300 µg paclitaxel stent (n=4), and 900 µg paclitaxel stent (n=4). After 3 months of follow-up, autopsies were conducted to obtain common bile duct tissue samples, and inflammation and fibrosis thicknesses were assessed under a microscope.
Results:
Most tissues had resolved the inflammatory reactions by the 3-month mark. The thinnest fibrosis thickness was observed in the 900 µg group (359.08±167.23 µm); however, no statistical significance was observed.
Conclusion
This study demonstrated the safety of paclitaxel-eluting biodegradable biliary stents and their positive effects on fibrosis in an ischemic bile duct porcine model. This biodegradable stent represents a potential approach for overcoming the complications associated with biliary strictures after LT.
8.Korean Thyroid Association Guidelines on the Management of Differentiated Thyroid Cancers; Part III. Management of Advanced Differentiated Thyroid Cancers - Chapter 1-2. Locally Recurred/Persistent Thyroid Cancer Management Strategies 2024
Ho-Ryun WON ; Min Kyoung LEE ; Ho-Cheol KANG ; Bon Seok KOO ; Hyungju KWON ; Sun Wook KIM ; Won Woong KIM ; Jung-Han KIM ; Young Joo PARK ; Jun-Ook PARK ; Young Shin SONG ; Seung Hoon WOO ; Chang Hwan RYU ; Eun Kyung LEE ; Joon-Hyop LEE ; Ji Ye LEE ; Cho Rok LEE ; Dong-Jun LIM ; Jae-Yol LIM ; Yun Jae CHUNG ; Kyorim BACK ; Dong Gyu NA ;
International Journal of Thyroidology 2024;17(1):147-152
These guidelines aim to establish the standard practice for diagnosing and treating patients with differentiated thyroid cancer (DTC). Based on the Korean Thyroid Association (KTA) Guidelines on DTC management, the “Treatment of Advanced DTC” section was revised in 2024 and has been provided through this chapter. Especially, this chapter covers surgical and nonsurgical treatments for the local (previous surgery site) or regional (cervical lymph node metastasis) recurrences. After drafting the guidelines, it was finalized by collecting opinions from KTA members and related societies. Surgical resection is the preferred treatment for local or regional recurrence of advanced DTC. If surgical resection is not possible, nonsurgical resection treatment under ultrasonography guidance may be considered as an alternative treatment for local or regional recurrence of DTC. Furthermore, if residual lesions are suspected even after surgical resection or respiratory-digestive organ invasion, additional radioactive iodine and external radiation treatments are considered.
9.Korean Thyroid Association Guidelines on the Management of Differentiated Thyroid Cancers; Part V. Pediatric Differentiated Thyroid Cancer 2024
Jung-Eun MOON ; So Won OH ; Ho-Cheol KANG ; Bon Seok KOO ; Keunyoung KIM ; Sun Wook KIM ; Won Woong KIM ; Jung-Han KIM ; Dong Gyu NA ; Sohyun PARK ; Young Joo PARK ; Jun-Ook PARK ; Ji-In BANG ; Kyorim BACK ; Youngduk SEO ; Young Shin SONG ; Seung Hoon WOO ; Ho-Ryun WON ; Chang Hwan RYU ; Sang-Woo LEE ; Eun Kyung LEE ; Joon-Hyop LEE ; Jieun LEE ; Cho Rok LEE ; Dong-Jun LIM ; Jae-Yol LIM ; Ari CHONG ; Yun Jae CHUNG ; Chae Moon HONG ; Hyungju KWON ; Young Ah LEE ;
International Journal of Thyroidology 2024;17(1):193-207
Pediatric differentiated thyroid cancers (DTCs), mostly papillary thyroid cancer (PTC, 80-90%), are diagnosed at more advanced stages with larger tumor sizes and higher rates of locoregional and/or lung metastasis. Despite the higher recurrence rates of pediatric cancers than of adult thyroid cancers, pediatric patients demonstrate a lower mortality rate and more favorable prognosis. Considering the more advanced stage at diagnosis in pediatric patients, preoperative evaluation is crucial to determine the extent of surgery required. Furthermore, if hereditary tumor syndrome is suspected, genetic testing is required. Recommendations for pediatric DTCs focus on the surgical principles, radioiodine therapy according to the postoperative risk level, treatment and follow-up of recurrent or persistent diseases, and treatment of patients with radioiodine-refractory PTCs on the basis of genetic drivers that are unique to pediatric patients.
10.Korean Thyroid Association Guidelines on the Management of Differentiated Thyroid Cancers; Overview and Summary 2024
Young Joo PARK ; Eun Kyung LEE ; Young Shin SONG ; Bon Seok KOO ; Hyungju KWON ; Keunyoung KIM ; Mijin KIM ; Bo Hyun KIM ; Won Gu KIM ; Won Bae KIM ; Won Woong KIM ; Jung-Han KIM ; Hee Kyung KIM ; Hee Young NA ; Shin Je MOON ; Jung-Eun MOON ; Sohyun PARK ; Jun-Ook PARK ; Ji-In BANG ; Kyorim BACK ; Youngduk SEO ; Dong Yeob SHIN ; Su-Jin SHIN ; Hwa Young AHN ; So Won OH ; Seung Hoon WOO ; Ho-Ryun WON ; Chang Hwan RYU ; Jee Hee YOON ; Ka Hee YI ; Min Kyoung LEE ; Sang-Woo LEE ; Seung Eun LEE ; Sihoon LEE ; Young Ah LEE ; Joon-Hyop LEE ; Ji Ye LEE ; Jieun LEE ; Cho Rok LEE ; Dong-Jun LIM ; Jae-Yol LIM ; Yun Kyung JEON ; Kyong Yeun JUNG ; Ari CHONG ; Yun Jae CHUNG ; Chan Kwon JUNG ; Kwanhoon JO ; Yoon Young CHO ; A Ram HONG ; Chae Moon HONG ; Ho-Cheol KANG ; Sun Wook KIM ; Woong Youn CHUNG ; Do Joon PARK ; Dong Gyu NA ;
International Journal of Thyroidology 2024;17(1):1-20
Differentiated thyroid cancer demonstrates a wide range of clinical presentations, from very indolent cases to those with an aggressive prognosis. Therefore, diagnosing and treating each cancer appropriately based on its risk status is important. The Korean Thyroid Association (KTA) has provided and amended the clinical guidelines for thyroid cancer management since 2007. The main changes in this revised 2024 guideline include 1) individualization of surgical extent according to pathological tests and clinical findings, 2) application of active surveillance in low-risk papillary thyroid microcarcinoma, 3) indications for minimally invasive surgery, 4) adoption of World Health Organization pathological diagnostic criteria and definition of terminology in Korean, 5) update on literature evidence of recurrence risk for initial risk stratification, 6) addition of the role of molecular testing, 7) addition of definition of initial risk stratification and targeting thyroid stimulating hormone (TSH) concentrations according to ongoing risk stratification (ORS), 8) addition of treatment of perioperative hypoparathyroidism, 9) update on systemic chemotherapy, and 10) addition of treatment for pediatric patients with thyroid cancer.

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