OBJECTIVE To optimize the management model of drugs used in investigator-initiated trial （IIT）. METHODS With benchmarking analysis， based on the practical work experience of a tertiary specialized hospital in the field of IIT drug management in Shanghai， a thorough review was conducted， involving relevant laws， regulations， and academic literature to establish benchmark criteria and the evaluation standards. Starting from the initiation of IIT projects， a detailed comparative analysis of key processes was carried out， such as the receipt， storage， distribution， use and recycling of drugs for trial. The deficiencies in the current management of IIT drugs were reviewed in detail and a series of optimization suggestions were put forward. RESULTS It was found that the authorized records of drug management were missing， the training before project implementation was insufficient， and the records of receipt and acceptance of IIT drugs were incomplete. In light of these existing problems， improvement measures were put forward， including strengthening the training of drug administrators and stipulating that only drug administrators with pharmacist qualifications be eligible to inspect and accept drugs， etc. The related systems were improved， and 17 key points of quality control for the management of IIT drugs were developed. CONCLUSIONS A preliminary IIT drug management system for medical institutions has been established， which helps to improve the institutional X2023076） framework of medical institutions in this field.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Based on the theory of "spleen functions as wei qi"， this paper believes that the disease mechanism of allergic rhinitis （AR） in children is the nasal dysfunction caused by the loss of spleen's wei qi. The root cause of AR is the failure of splenic transportation as well as its inability to properly distribute nutrients. The inducement of AR is the invasion of pathogenic qi coupled with insecurity of the wei exterior. The key to AR recurrence lies in the deficiency of healthy qi and lingering of pathogenic qi， with pathogenic qi lodging inside the body. The treatment should adhere to the principle of helping the spleen restore wei qi. During the acute phase， the treatment should dispel wind， conso-lidate the wei qi， and relieve stuffy orifices， and the modified Qufeng Tongqiao Decoction （祛风通窍汤） is used. During the remission phase， the treatment should fortify the spleen， raise the clear， and harmonize the wei qi， and the modified Yuhan Decoction （御寒汤） is applied. During the recovery phase， the treatment should reinforce the healthy qi， consolidate the constitution， and strengthen the wei qi， and the modified Huangqi Jianzhong Decoction （黄芪建中汤） is employed.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

BACKGROUND: Pulmonary arterial hypertension (PAH) presents a significant health burden in Asia and remains a critical challenge. This study aims to delineate the PAH burden in Asia from 1990 to 2021. METHODS: Using the latest data from the Global Burden of Disease 2021, we evaluated and analyzed the distributions and patterns of PAH disease burden among various age groups, sexes, regions, and countries in Asia. Additionally, we examined the associations between PAH disease burden and key health system indicators, including the socio-demographic index (SDI) and the universal health coverage (UHC) index. RESULTS: In 2021, there were 25,989 new PAH cases, 103,382 existing cases, 13,909 PAH-associated deaths, and 385,755 DALYs attributed to PAH in Asia, which accounted for approximately 60% of global PAH cases. The age-standardized rates (ASRs) for prevalence and deaths were 2.05 (95% uncertainty interval [UI]: 1.66-2.52) per 100,000 population and 0.31 (95% UI: 0.23-0.38) per 100,000 population, respectively. From 1990 to 2021, Asia reported the lowest ASRs for PAH prevalence but the highest ASRs for deaths compared to other continents. While the ASRs for prevalence increased slightly, ASRs for mortality and DALYs decreased over time. This increasing burden of PAH was primarily driven by population growth and aging. The burden was especially pronounced among individuals aged ≥60 years and <9 years, who collectively accounted for the majority of deaths and DALYs. Moreover, higher SDI and UHC levels were linked to reduced incidence, but higher prevalence rates. CONCLUSIONS Although progress has been made in reducing PAH-related mortality and DALYs, the disease continues to impose a substantial burden in Asia, particularly among older adults and young children. Region-specific health policies should focus on improving early diagnosis, expanding access to treatment, and effectively addressing the growing PAH burden in the region.
Humans ; Global Burden of Disease ; Male ; Female ; Middle Aged ; Adult ; Asia/epidemiology* ; Prevalence ; Aged ; Pulmonary Arterial Hypertension/mortality* ; Adolescent ; Young Adult ; Child ; Child, Preschool ; Infant ; Hypertension, Pulmonary/epidemiology*

BACKGROUND: The burden of breast cancer for older adults has been rising with the increasing population aging. This study aims to describe the burden of breast cancer in older adults worldwide, analyze the temporal trends for older breast cancer incidence, and assess the socioeconomic inequalities of breast cancer incidence and mortality with human development index (HDI) levels, which will provide valuable information in preventing and controlling the increasing breast cancer burden in older women. METHODS: The incidence and mortality rates of specific cancer types in older individuals in 2022 were sourced from the Global Cancer Today database. Trends in breast cancer incidence acquired from the Cancer Incidence in Five Continents (CI5) database. HDI and other risk factors were obtained from the United Nations. We used a generalized linear model to estimate the rate ratio and 95% confidence interval (CI) between HDI levels and breast cancer burden in older people. RESULTS: It was estimated approximately 1,058,466 newly diagnosed breast cancer cases and 383,774 breast cancer deaths in women ≥60 years, accounting for 18.9% and 12.7% of global cancer cases and deaths. The age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) were 172.9 and 57.7 per 100,000, ranking first and second among all cancer incidence and mortality in older women. The highest ASIR and ASMR were four-fold higher than the lowest, with ASIR ranging from a peak of 399.1 per 100,000 in Australia-New Zealand to a low of 90.6 per 100,000 in South Central Asia, and ASMR varying from a high of 118.6 per 100,000 in Melanesia to a low of 28.8 per 100,000 in East Asia. The largest increases in ASIR from 1998-2002 to 2013-2017 were observed in South Korea, China, and Estonia. The corresponding estimated 5-year average percentage changes (EAPC) were 6.01%, 2.89%, and 1.93%, respectively. CONCLUSIONS The global burden of breast cancer in older women is increasing fast and varies greatly across countries. Effective prevention strategies are essential to address the increasing breast cancer burden for older women.
Humans ; Female ; Breast Neoplasms/epidemiology* ; Aged ; Incidence ; Middle Aged ; Registries ; Aged, 80 and over ; Risk Factors