OBJECTIVE To evaluate the cost-effectiveness of anlotinib combined with penpulimab versus sorafenib as first- line treatment for unresectable hepatocellular carcinoma （uHCC） from the perspective of China’s healthcare system. METHODS Based on data from the APOLLO study， a partitioned survival model was established with a 21-day model cycle to simulate patient survival status over 10 years under anlotinib combined with penpulimab regimen or sorafenib monotherapy. Quality-adjusted life year （QALY） was used as the core evaluation parameter to assess the incremental cost-effectiveness ratio （ICER） of different treatment regimens. Using 3 times China’s per capita gross domestic product （GDP） in 2024 （287 247 yuan/QALY） as the willingness-to-pay （WTP） threshold， cost-utility analysis was performed to evaluate the cost-effectiveness of the treatment regimens. Sensitivity analysis was conducted to validate the robustness of the baseline analysis conclusion. Scenario analysis was performed to consider the impact of anlotinib and penpulimab assistance programs on the results； the price reduction of penpulimab to ensure the cost-effectiveness of the combination regimen was examined under varying WTP thresholds （specifically， 1， 2， and 3 times China’s per capita GDP in 2024）. RESULTS The baseline analysis revealed that the ICER of anlotinib combined with penpulimab regimen relative to the sorafenib regimen was 338 611.20 yuan/QALY， which exceeded the WTP threshold set in this study. Univariate sensitivity analysis indicated that the utility value of progression free survival and penpulimab price significantly influenced the baseline analysis results. Probabilistic sensitivity analysis validated the robustness of the baseline results. The results of scenario analysis indicated that when considering the assistance programs for anlotinib and penpulimab， the obtained ICER values were all below the WTP threshold set at 3 times China’s per capita GDP in 2024. When the price of penpulimab was reduced by 58%， 35%， and 13%， the ICER values were below the WTP threshold， which was 1， 2 and 3 times the per capita GDP of China in 2024， respectively. CONCLUSIONS From the perspective of China’s healthcare system， anlotinib combined with penpulimab regimen for first-line treatment of uHCC lacks cost-effectiveness compared to sorafenib regimen. However， this conclusion would be reversed if the anlotinib and penpulimab assistance programs are taken into account or if the price of penpulimab is reduced by more than 13% and above.

OBJECTIVE To evaluate the cost-effectiveness of amivantamab combined with lazertinib （hereinafter referred to as “AL”） regimen as first-line treatment for EGFR -mutated advanced non-small cell lung cancer （NSCLC） from the perspective of China’s healthcare system. METHODS A partitioned survival model was established based on updated data from the MARIPOSA study， with a 10-year time horizon and 28-day cycles. The primary outcome index was quality adjusted life year （QALY）， and the willingness-to-pay （WTP） threshold was set at three times China’s per capita GDP in 2024 （287 247 yuan/QALY）. Cost-utility analysis was used to calculate the incremental cost-effectiveness ratio （ICER） of AL regimen versus osimertinib monotherapy regimen as first-line treatment for EGFR -mutated advanced NSCLC. One-way and probabilistic sensitivity analyses were performed to test model robustness. Scena rio analyses were conducted to explore the impact of utility values for different health states on the outcomes and determine the required price reductions of amivantamab and lazertinib to achieve cost-effectiveness. RESULTS Compared with the osimertinib monotherapy regimen， the ICER for the AL regimen as first-line treatment for advanced EGFR -mutated NSCLC was 2 062 096.15 yuan/QALY， significantly exceeding the WTP threshold established in this study. One-way sensitivity analysis revealed that the utility value of progression-free survival state and the price of amivantamab were the primary factors influencing the ICER. Probabilistic sensitivity analysis revealed that the AL regimen only became cost-effective when the WTP threshold was set at 2 050 000 yuan/QALY. Scenario analysis indicated that altering the utility value still rendered the AL regimen non-cost-effective. When amivantamab （350 mg） prices decreased by 80%， 85%， and 90% respectively， lazertinib （80 mg） prices would need to decrease by 95.97%， 40.63%， 5.29%， respectively. This would enable the AL regimen’s ICER to consistently fall within the WTP threshold established in this study. CONCLUSIONS At the WTP threshold established in this study， the AL regimen does not demonstrate cost-effectiveness for first-line treatment of advanced EGFR -mutated NSCLC compared to the osimertinib monotherapy regimen. Significant price reductions for both drugs would be required to alleviate the financial burden on patients.

OBJECTIVE To evaluate the cost-effectiveness of culmerciclib combined with fulvestrant as second-line treatment for patients with hormone receptor-positive（HR+）/human epidermal growth factor receptor 2-negative （HER2–） locally advanced or metastatic breast cancer， within the context of the Chinese healthcare system. METHODS A partitioned survival model was established based on the CULMATE-1 study， with a simulation time horizon set at 15 years and a cycle length of 28 days. The incremental cost-effectiveness ratio （ICER） of culmerciclib combined with fulvestrant versus fulvestrant monotherapy as second-line treatment for HR+/HER2– breast cancer was calculated. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to assess the robustness of the model. Meanwhile， scenario analysis of culmerciclib price reduction was conducted； the required price reduction and price to reach the willingness-to-pay （WTP） threshold in this study were calculated. RESULTS The results of the base-case analysis indicated that， compared with the fulvestrant monotherapy regimen， culmerciclib combined with fulvestrant yielded an additional 0.823 quality-adjusted life year （QALY）， with a corresponding ICER of 371 696.26 yuan/QALY， which exceeded the WTP threshold （199 330 yuan/QALY）. The results of the univariate sensitivity analysis indicated that the cost of culmerciclib， the discount rate， the utility values for progression disease and progression free survival status were significant factors influencing the ICER； both the univariate sensitivity analysis and the probabilistic sensitivity analysis validated the robustness of the model results. Scenario analysis indicated that when the price of culmerciclib was reduced by 30%， 55% and 85% respectively， the corresponding ICER values fell below 3， 2， and 1 times China’s per capita GDP in 2025， with the probability of cost-effectiveness being 3.00%， 94.90%， 100%. When the cost of culmerciclib （60 mg） was reduced by 52.6% to 50.96 yuan， the ICER value met the WTP threshold established in this study. CONCLUSIONS When the WTP threshold is set at twice China’s per capita GDP in 2025， second-line treatment with culmerciclib combined with fulvestrant for HR+/HER2– locally advanced or metastatic breast cancer does not exhibit cost-effectiveness advantage over fulvestrant monotherapy. Therefore， a reasonable price reduction is required to alleviate the financial burden on patients.

OBJECTIVE To evaluate the cost-effectiveness of sacituzumab tirumotecan （ST） versus chemotherapy treatment physician’s choice （TPC） as second-line and later-line treatment for metastatic triple-negative breast cancer （mTNBC） from the perspective of China’s healthcare system. METHODS A partitioned survival model was constructed based on the OptiTROP-Breast 01 trial， with a cycle length of 4 weeks and a time horizon of 10 years， applying a 5% discount rate. Quality adjusted life year （QALY） and costs were used as outcome measures， and the incremental cost-effectiveness ratio （ICER） of ST versus TPC for second-line and later-line treatment of mTNBC was calculated. Sensitivity analyses were conducted to validate the robustness of the base-case results. RESULTS At a willingness-to-pay threshold （WTP） of 3 times China’s 2024 per capita gross domestic product （GDP） （287 247 yuan/QALY）， patients receiving ST gained incremental utility （0.42 QALY） at a higher cost， yielding an ICER of 205 562.07 yuan/QALY， which was lower than WTP， indicating that ST was more cost-effective compared to TPC. One-way sensitivity analysis revealed that key factors influencing the ICER included the utility value of progression-free survival and the price of ST. Probabilistic sensitivity analysis and scenario analysis showed that the base-case results were robust. CONCLUSIONS From the perspective of China’s healthcare system， at a WTP of 3 times China’s per capita GDP， ST is more cost-effective than TPC as second-line and later-line treatment for mTNBC.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Background China is a major coal producer and consumer country in the world. Coal workers' pneumoconiosis (CWP) is a primary factor endangering the occupational health of coal miners. Research on the disease burden of CWP and its changing trend is significant for disease prevention & control and associated policies. Objective To analyze the disease burden of CWP in China from 1990 to 2021 and its changing trend, and predict the disease burden from 2022 to 2035. Methods Using the Global Burden of Disease Study (GBD) database of 2021, numbers ofincident cases, prevalent cases, deaths, and disability-adjusted life years (DALYs) as well as crude and age-standardized rates of CWP in China were retrieved. Linear regression model was used to calculate the estimated annual percentage change (EAPC) of the age-standardized rates. Joinpoint regression model was used to analyze the temporal trend of disease burden and the disease burden of different sexes and age groups, and Bayesian age-period-cohort (BAPC) model was used to forecast the trend of CWP disease burden. Results In 1990, the incident, prevalent, and deaths cases of CWP in China were 3266, 18872, and 1561, respectively, and the DALYs of CWP were 44614.718 person-years. In 2021, the incident, prevalent, and deaths cases of CWP were 3446, 23975, and 1229, respectively, and the DALYs of CWP were 29610.754 person-years. From 1990 to 2021, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP in China all showed a downward trend, with the EAPCs of −3.121%, −2.532%, −4.018%, and −4.268%, respectively. The disease burden of CWP in China was mainly concentrated in the male population. The annual average percent change analysis indicated that each standardized rate showed a fluctuating downward trend in different periods. The BAPC model showed that from 2022 to 2035, the age-standardized rates of CWP in China would continue to decline steadily. In 2035, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP would be reduced to 0.10 per 100000, 0.74 per 100000, 0.03 per 100000, and 0.74 per 100000, respectively. Conclusion The disease burden contributed by CWP in China generally show a downward trend from 1990 to 2021, and it is expected that the age-standardized rates will continue to decline steadily from 2022 to 2035.

OBJECTIVE: To review the application and progress of unilateral biportal endoscopy (UBE) technology in the treatment of cervical degenerative diseases, and to provide reference for clinical treatment decisions. METHODS: The literature related to UBE technology in the treatment of cervical spondylotic radiculopathy (CSR) and cervical spondylotic myelopathy (CSM) at home and abroad was extensively reviewed, and the surgical methods, indications, effectiveness, and safety were analyzed and summarized. RESULTS: UBE technology is effective in the treatment of CSR and CSM, and has the advantages of good surgical field, reducing the injury of the posterior structure of the cervical spine, and protecting the facet joint process, but in general, the indications are relatively narrow, limited to single-segment or adjacent double-segment lesions, and the requirements for the operator are relatively high, and the learning curve is long. CONCLUSION UBE technology can be applied to the treatment of CSR and CSM, but it needs to be carried out by experienced UBE surgeons for specific cases.
Humans ; Cervical Vertebrae/surgery* ; Endoscopy/methods* ; Radiculopathy/surgery* ; Spondylosis/surgery* ; Decompression, Surgical/methods* ; Spinal Cord Diseases/surgery* ; Treatment Outcome

Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.