1.Frequent association of malignant effusions in plasmablastic lymphoma:a single‑institutional experience of nine cases in Taiwan
Bo‑Jung CHEN ; Yu‑Ting KUO ; Sheng‑Tsung CHANG ; Khin‑Than WIN ; Shang‑Wen CHEN ; Sheng‑Yen HSIAO ; Yin‑Hsun FENG ; Yen‑Chuan HSIEH ; Shih‑Sung CHUANG
Blood Research 2025;60():22-
Purpose:
Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare.
Methods:
This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024.
Results:
We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse.
Conclusion
In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.
2.Frequent association of malignant effusions in plasmablastic lymphoma:a single‑institutional experience of nine cases in Taiwan
Bo‑Jung CHEN ; Yu‑Ting KUO ; Sheng‑Tsung CHANG ; Khin‑Than WIN ; Shang‑Wen CHEN ; Sheng‑Yen HSIAO ; Yin‑Hsun FENG ; Yen‑Chuan HSIEH ; Shih‑Sung CHUANG
Blood Research 2025;60():22-
Purpose:
Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare.
Methods:
This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024.
Results:
We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse.
Conclusion
In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.
3.Frequent association of malignant effusions in plasmablastic lymphoma:a single‑institutional experience of nine cases in Taiwan
Bo‑Jung CHEN ; Yu‑Ting KUO ; Sheng‑Tsung CHANG ; Khin‑Than WIN ; Shang‑Wen CHEN ; Sheng‑Yen HSIAO ; Yin‑Hsun FENG ; Yen‑Chuan HSIEH ; Shih‑Sung CHUANG
Blood Research 2025;60():22-
Purpose:
Plasmablastic lymphoma (PBL) is a rare, aggressive lymphoma that is characterized by terminal B-cell differ‑ entiation. In the West, PBL usually occurs in patients with immunodeficiencies, particularly those induced by human immunodeficiency virus (HIV) infection. We investigated the clinicopathological features of PBL at a single institute in Taiwan, where HIV infection is rare.
Methods:
This retrospective chart review identified PBL cases that were treated at a single institute in southern Tai‑ wan between 2008 and 2024.
Results:
We identified nine patients (four males and five females; median age 71 years). Of the eight patients tested for HIV, only one tested positive. Pathologically, the tumors showed plasmablastic morphology and immunopheno‑ type, and three (33%) cases tested positive for Epstein–Barr virus. Six (67%) patients presented with Stage IV disease, including five (56%) with malignant effusion. Six patients were treated with chemotherapy and the remaining three received only supportive care. During a median follow-up of 10 months, five patients died of progressive disease, two died of unrelated diseases, and two were alive with PBL relapse.
Conclusion
In Taiwan, PBL constitutes a rare and aggressive clinical condition and is frequently associated with malignant effusion. In contrast to Western patients, the PBL in most patients from Taiwan was unrelated to HIV infection.
4.Comedications and potential drug-drug interactions with direct-acting antivirals in hepatitis C patients on hemodialysis
Po-Yao HSU ; Yu-Ju WEI ; Jia-Jung LEE ; Sheng-Wen NIU ; Jiun-Chi HUANG ; Cheng-Ting HSU ; Tyng-Yuan JANG ; Ming-Lun YEH ; Ching-I HUANG ; Po-Cheng LIANG ; Yi-Hung LIN ; Ming-Yen HSIEH ; Meng-Hsuan HSIEH ; Szu-Chia CHEN ; Chia-Yen DAI ; Zu-Yau LIN ; Shinn-Cherng CHEN ; Jee-Fu HUANG ; Jer-Ming CHANG ; Shang-Jyh HWANG ; Wan-Long CHUANG ; Chung-Feng HUANG ; Yi-Wen CHIU ; Ming-Lung YU
Clinical and Molecular Hepatology 2021;27(1):186-196
Background/Aims:
Direct‐acting antivirals (DAAs) have been approved for hepatitis C virus (HCV) treatment in patients with end-stage renal disease (ESRD) on hemodialysis. Nevertheless, the complicated comedications and their potential drug-drug interactions (DDIs) with DAAs might limit clinical practice in this special population.
Methods:
The number, class, and characteristics of comedications and their potential DDIs with five DAA regimens were analyzed among HCV-viremic patients from 23 hemodialysis centers in Taiwan.
Results:
Of 2,015 hemodialysis patients screened in 2019, 169 patients seropositive for HCV RNA were enrolled (mean age, 65.6 years; median duration of hemodialysis, 5.8 years). All patients received at least one comedication (median number, 6; mean class number, 3.4). The most common comedication classes were ESRD-associated medications (94.1%), cardiovascular drugs (69.8%) and antidiabetic drugs (43.2%). ESRD-associated medications were excluded from DDI analysis. Sofosbuvir/velpatasvir/voxilaprevir had the highest frequency of potential contraindicated DDIs (red, 5.6%), followed by glecaprevir/pibrentasvir (4.0%), sofosbuvir/ledipasvir (1.3%), sofosbuvir/velpatasvir (1.3%), and elbasvir/grazoprevir (0.3%). For potentially significant DDIs (orange, requiring close monitoring or dose adjustments), sofosbuvir/velpatasvir/voxilaprevir had the highest frequency (19.9%), followed by sofosbuvir/ledipasvir (18.2%), glecaprevir/pibrentasvir (12.6%), sofosbuvir/velpatasvir (12.6%), and elbasvir/grazoprevir (7.3%). Overall, lipid-lowering agents were the most common comedication class with red-category DDIs to all DAA regimens (n=62), followed by cardiovascular agents (n=15), and central nervous system agents (n=10).
Conclusions
HCV-viremic patients on hemodialysis had a very high prevalence of comedications with a broad spectrum, which had varied DDIs with currently available DAA regimens. Elbasvir/grazoprevir had the fewest potential DDIs, and sofosbuvir/velpatasvir/voxilaprevir had the most potential DDIs.
5.Predictors for Failed Removal of Nasogastric Tube in Patients With Brain Insult
Shih-Ting HUANG ; Tyng-Guey WANG ; Mei-Chih PENG ; Wan-Ming CHEN ; An-Tzu JAO ; Fuk Tan TANG ; Yu-Ting HSIEH ; Chun Sheng HO ; Shu-Ming YEH
Annals of Rehabilitation Medicine 2024;48(3):220-227
Objective:
To construct a prognostic model for unsuccessful removal of nasogastric tube (NGT) was the aim of our study.
Methods:
This study examined patients with swallowing disorders receiving NGT feeding due to stroke or traumatic brain injury in a regional hospital. Clinical data was collected, such as age, sex, body mass index (BMI), level of activities of daily living (ADLs) dependence. Additionally, gather information regarding the enhancement in Functional Oral Intake Scale (FOIS) levels and the increase in food types according to the International Dysphagia Diet Standardization Initiative (IDDSI) after one month of swallowing training. A stepwise logistic regression analysis model was employed to predict NGT removal failure using these parameters.
Results:
Out of 203 patients, 53 patients (26.1%) had experienced a failed removal of NGT after six months of follow-up. The strongest predictors for failed removal were age over 60 years, underweight BMI, total dependence in ADLs, and ischemic stroke. The admission prediction model categorized patients into high, moderate, and low-risk groups for removal failure. The failure rate of NGT removal was high not only in the high-risk group but also in the moderate-risk groups when there was no improvement in FOIS levels and IDDSI food types.
Conclusion
Our predictive model categorizes patients with brain insults into risk groups for swallowing disorders, enabling advanced interventions such as percutaneous endoscopic gastrostomy for high-risk patients struggling with NGT removal, while follow-up assessments using FOIS and IDDSI aid in guiding rehabilitation decisions for those at moderate risk.
7.Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program
Ming-Ying LU ; Chung-Feng HUANG ; Chao-Hung HUNG ; Chi‐Ming TAI ; Lein-Ray MO ; Hsing-Tao KUO ; Kuo-Chih TSENG ; Ching-Chu LO ; Ming-Jong BAIR ; Szu-Jen WANG ; Jee-Fu HUANG ; Ming-Lun YEH ; Chun-Ting CHEN ; Ming-Chang TSAI ; Chien-Wei HUANG ; Pei-Lun LEE ; Tzeng-Hue YANG ; Yi-Hsiang HUANG ; Lee-Won CHONG ; Chien-Lin CHEN ; Chi-Chieh YANG ; Sheng‐Shun YANG ; Pin-Nan CHENG ; Tsai-Yuan HSIEH ; Jui-Ting HU ; Wen-Chih WU ; Chien-Yu CHENG ; Guei-Ying CHEN ; Guo-Xiong ZHOU ; Wei-Lun TSAI ; Chien-Neng KAO ; Chih-Lang LIN ; Chia-Chi WANG ; Ta-Ya LIN ; Chih‐Lin LIN ; Wei-Wen SU ; Tzong-Hsi LEE ; Te-Sheng CHANG ; Chun-Jen LIU ; Chia-Yen DAI ; Jia-Horng KAO ; Han-Chieh LIN ; Wan-Long CHUANG ; Cheng-Yuan PENG ; Chun-Wei- TSAI ; Chi-Yi CHEN ; Ming-Lung YU ;
Clinical and Molecular Hepatology 2024;30(1):64-79
Background/Aims:
Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy.
Methods:
We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment.
Results:
The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset.
Conclusions
Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.