Thalassaemia in China

Wang, Weida; Hu, Fang; Zhou, Dun-Hua; Gale, Robert Peter; Lai, Yongrong; Yao, Hongxia; Li, Chunfu; Wu, Bingyi; Chen, Zhu; Fang, Jian-Pei; Chen, Sai‐Juan; Yang, Lijian

doi:10.1016/j.blre.2023.101074

Cited by 13 publications

(5 citation statements)

References 73 publications

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“…Furthermore, 11 cases of acombined with b-thalassemia were observed, resulting in a positive rate of 0.14%. These prevalence rates were found to be lower compared to coastal cities such as Guangdong, particularly in relation to a thalassemia, indicating a significant difference as compared to previous studies (4,15). To mitigate the cost and time associated with genetic diagnosis of thalassemia, a machine learning model was constructed in this study.…”

Section: Discussioncontrasting

confidence: 72%

“…It is particularly prevalent in regions such as South Africa, the Middle East, and Southeast Asia, as well as in low-and middle-income areas like coastal cities in southern China and rural areas in western China. China bears the highest burden of thalassemia globally, with approximately 30 million individuals affected by thalassemia-related mutations and 3 million suffering from moderate to severe forms, posing significant challenges to families and society (3)(4)(5). Due to the autosomal recessive inheritance pattern of thalassemia, parents who are asymptomatic can still have children affected by thalassemia.…”

Section: Introductionmentioning

confidence: 99%

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Constructing a novel clinical indicator model to predict the occurrence of thalassemia in pregnancy through machine learning algorithm

Long,

Bai

2024

Front. Hematol.

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Thalassemia is one of the inherited hemoglobin disorders worldwide, resulting in ineffective erythropoiesis, chronic hemolytic anemia, compensatory hemopoietic expansion, hypercoagulability, etc., and when a mother carries the thalassemia gene, the child is more likely to have severe thalassemia. Furthermore, the economic and time costs of genetic testing for thalassemia prevent many thalassemia patients from being diagnosed in time. To solve this problem, we performed least absolute shrinkage and selection operator (LASSO) regression to analyze the correlation between thalassemia and blood routine indicators containing mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and red blood cell (RBC). We then built a nomogram to predict the occurrence of thalassemia, and receiver operating characteristic (ROC) curve was used to verify the prediction efficiency of this model. In total, we obtained 7,621 cases, including 847 thalassemia patients and 6,774 non-thalassemia. Among the 847 thalassemia patients, with a positivity rate of 67.2%, 569 cases were positive for α-thalassemia, and with a rate of 31.5%, 267 cases were positive for β-thalassemia. The remaining 11 cases were positive for both α- and β-thalassemia. Based on machine learning algorithm, we screened four optimal indicators, namely, MCV, MCH, RBC, and MCHC. The AUC value of MCV, MCH, RBC, and MCHC were 0.907, 0.906, 0.796, and 0.795, respectively. Moreover, the AUC value of the prediction model was 0.911. In summary, a novel and effective machine learning model was built to predict thalassemia, which functioned accurately, and may provide new insights for the early screening of thalassemia in the future.

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Section: Discussioncontrasting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Constructing a novel clinical indicator model to predict the occurrence of thalassemia in pregnancy through machine learning algorithm

Long,

Bai

2024

Front. Hematol.

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“…Children born with β-thalassemia major (β-TM) occur in the highest incidence in western Guangxi [15,16], making this area the forefront of prevention and control of severe thalassemia in China. For the children with β-TM, long course of disease, severe clinical manifestations, numerous complications, and lack of a specific cure bring heavy burden to the children and their families, which seriously threatens their…”

Section: Discussionmentioning

confidence: 99%

Effects of multidisciplinary team continuous care model on psychological behavior and quality of life in children with β-thalassemia major

Huang

2024

Am J Transl Res

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Objective: To explore the effects of a multidisciplinary team (MDT) continuous care model on psychological behavior and quality of life in children with β-thalassemia major (β-TM). Methods: A retrospective study was conducted on 90 children with β-TM who were hospitalized in the Department of Pediatrics, Affiliated Hospital of Youjiang Medical University for Nationalities from October 2021 to May 2022. According to nursing methods, the children were divided into a routine group and an experimental group, with 45 cases in each group. The routine group was intervened with routine nursing approaches, and the experimental group was intervened with the MDT continuous nursing mode on the basis of the control group. The psychological behavior [Positive and Negative Affect Scale for Children (PANAS-C)], quality of life (QoL) [Pediatric Quality of Life Inventory TM (PedsQLTM)] and satisfaction were compared between the two groups before and 6 months after intervention. The hemoglobin level and ferritin level of children after 3 months and 6 months of intervention were measured. The occurrence of complications and nursing satisfaction were recorded. The prognostic factors were further analyzed. Results: After the intervention, the positive emotion score, QoL score, hemoglobin level, satisfaction score in the experimental group were all higher than those in the conventional group, and the negative emotion score and ferritin level in the experimental group were all lower than those in the conventional group (all P < 0.05). The results of Cox analysis showed that the use of iron-removing drugs and arrhythmia/heart rate failure were risk factors affecting the prognosis of children with β-TM, while the MDT continuous nursing mode was a protective factor (all P < 0.05). Conclusion: The MDT continuous care model can effectively promote mental health in children with β-TM, improve their quality of life, medical satisfaction, ameliorate the degree of anemia in children, reduce the incidence of complications and improve the prognosis; thus, it is worthy of wide clinical application.

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“…[ 1 ] Patients with thalassemia suffer from the most common monogenic hereditary disease worldwide and also represent the largest monogenic hereditary disease in China. [ 2 ] It originates from the Mediterranean, the Middle East, and Southeast Asia. The disease has a widespread distribution among populations and affects a large number of individuals, with an estimated carrier rate of the β-thalassemia gene at around 1.5% globally.…”

Section: Introductionmentioning

confidence: 99%

β-Thalassemia gene editing therapy: Advancements and difficulties

Hu,

Zhong,

et al. 2024

Medicine

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β-Thalassemia is the world’s number 1 single-gene genetic disorder and is characterized by suppressed or impaired production of β-pearl protein chains. This results in intramedullary destruction and premature lysis of red blood cells in peripheral blood. Among them, patients with transfusion-dependent β-thalassemia face the problem of long-term transfusion and iron chelation therapy, which leads to clinical complications and great economic stress. As gene editing technology improves, we are seeing the dawn of a cure for the disease, with its reduction of ineffective erythropoiesis and effective prolongation of survival in critically ill patients. Here, we provide an overview of β-thalassemia distribution and pathophysiology. In addition, we focus on gene therapy and gene editing advances. Nucleic acid endonuclease tools currently available for gene editing fall into 3 categories: zinc finger nucleases, transcription activator-like effector nucleases, and regularly interspaced short palindromic repeats (CRISPR-Cas9) nucleases. This paper reviews the exploratory applications and exploration of emerging therapeutic tools based on 3 classes of nucleic acid endonucleases in the treatment of β-thalassemia diseases.

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Thalassaemia in China

Cited by 13 publications

References 73 publications

Constructing a novel clinical indicator model to predict the occurrence of thalassemia in pregnancy through machine learning algorithm

Constructing a novel clinical indicator model to predict the occurrence of thalassemia in pregnancy through machine learning algorithm

Effects of multidisciplinary team continuous care model on psychological behavior and quality of life in children with β-thalassemia major

β-Thalassemia gene editing therapy: Advancements and difficulties

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