OBJECTIVE To review the current research progress on pharmacoeconomics evaluation related to spinal muscular atrophy （SMA）， in order to provide valuable insights for clinical treatment， screening and medical insurance payment decision- making. METHODS A computerized search was conducted across multiple databases including PubMed， Web of Science， Embase， Scopus， Cochrane Library， EBSCOhost， CNKI， VIP， CBM and Wanfang database as well as other important health technology assessment （HTA） websites， such as National Institute for Health and Care Research，International Society of Technology Assessment in Health Care， Agency for Healthcare Research and Quality， etc. The pharmacoeconomics evaluation studies related to SMA were collected from the inception to December 31st， 2023. The literature/reports were rigorously screened based on predefined inclusion and exclusion criteria by two researchers， and the essential information from the included literature/ reports was extracted using Excel 2019. The quality of the included literature/reports was evaluated by Consolidated Health Economic Evaluation Reporting Standards 2022. RESULTS Finally， 9 articles and 15 HTA reports were included， with overall good quality of literature， but poor quality of HTA reports. There were a total of 24 studies on the pharmacoeconomics evaluation of SMA， including treatment options such as nusinersen sodium， sovaprevir， risperidone， and best supportive therapy.The review results showed that nusinersen sodium was not cost-effective in the treatment of SMA； there was no consensus on the economic viability of treatment options such as risperidone and sovaprevir； newborn/prenatal screening combined withmedication therapy was cost-effective. CONCLUSIONS newborn/prenatal screening combined with SMA medication therapy demonstrates economic advantages. It is suggested to further investigate the cost-effectiveness of new SMA drugs and SMA screening in China， taking localization parameters and medical insurance prices into account， and gradually incorporate SMA screening into the scope of neonatal genetic disease detection， in order to alleviate the financial burden of patients’ families and healthcare systems.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

Objective:Evaluating the impact of various hypoglycemic events on the Health-Related Quality of Life(HRQoL)of diabetes patients to provide empirical data for health technology assessment.Methods:The data was collected from a tertiary hospital in Jinan,Shandong Province,China.Health utility was measured using the Time Trade-off(TTO)method,and disutility was calculated based on the formula.Subsequently,the intergroup differences among various hypoglycemic event groups were analyzed.Results:The hypoglycemic events'average utility was all lower than the average utility for diabetics without hypoglycemic events(baseline status).Severe hypoglycemic events(0.108)had higher disutility compared to non-severe hypoglycemic events(0.008).Furthermore,nocturnal severe/non-severe hypoglycemic events(0.118/0.008)exhibited higher average disutility than daytime severe/non-severe hypoglycemic events(0.098/0.007).Conclusion:Optimal diabetes management demands prioritizing the prevention of both severe hypoglycemic events and nocturnal hypoglycemic events.

The prevention and treatment of rare diseases is an important public health issue in China.Rare diseases are characterized by diverse types,complex conditions,and heavy burdened to patients,leading to a series of issues in the urgent demand in prevention and treatment of rare diseases in terms of individuals'health and the national responsibilities.Related legislation is an effective way to promote multi-disease preven-tion and treatment of rare diseases,and patients'protection in multi-level.We tease out and analyze the legal system on national and local level related to rare diseases,and recommend the coping strategies and give sug-gestions to improve and optimize the legal system for the prevention and treatment of rare diseases from the three dimensions of completeness,normalization and feasibility of the legislation,hoping to improve the competence of China's rare disease prevention and treatment and raise the level of protection for the patients.