Several preference-based health-related quality of life (HRQoL) instruments have been published and widely used in different populations. However no consensus has emerged regarding the most appropriate instrument in therapeutic area of stable angina. This study compared and validated the psychometric properties of two generic preference-based instruments, the EQ-5D and SF-6D, among Chinese stable angina patients. Convergent validity of the EQ-5D and SF-6D was examined with eight a priori hypotheses from stable angina patients in conjunction with Seattle Angina Questionnaire (SAQ). Responsiveness was compared using the effect size (ES), relative efficiency (RE) and receiver operating characteristic (ROC) curves. Agreement between the EQ-5D and SF-6D was tested using intra-class correlation coefficient (ICC) and Bland-Altman plot. Factors affecting utility difference were explored with multiple linear regression analysis. In 411 patients (mean age 68.08 ± 11.35), mean utility scores (SD) were 0.78 (0.15) for the EQ-5D and 0.68 (0.12) for the SF-6D. Validity was demonstrated by the moderate to strong correlation coefficients (Range: 0.368-0.594, P< 0.001) for five of the eight hypotheses in both the EQ-5D and SF-6D. There were no serious floor effects for the EQ-5D and SF-6D, but ceiling effects for the EQ-5D were large. The areas under ROC of them all exceeded 0.5 (0.660-0.814, P< 0.001). The SF-6D showed a better discriminative capacity (ES: 0.573 to 1.179) between groups with different stable-angina-specific health status than the EQ-5D (ES: 0.426 to 1.126). RE suggested that the SF-6D (RE: 44.8 to 177.8%) was more efficient than the EQ-5D except for physical function. Poor agreement between them was observed with ICC (0.448, P< 0.001) and Bland-Altman plot analysis. Multiple liner regression showed that clinical variables significantly (P< 0.05) influenced differences in utility scores between the EQ-5D and SF-6D. Both EQ-5D and SF-6D are valid and sensitive preference-based HRQoL instruments in Chinese stable angina patients. The SF-6D may be a more effective tool with lower ceiling effect and greater sensitivity. Further study is needed to compare other properties, such as reliability and longitudinal response.

Background: Physiologically based pharmacokinetic (PBPK) modeling is a mathematical approach that integrates human physiological parameters with drug-specific characteristics (including both active pharmaceutical ingredients and excipients), and it has emerged as one of the core technologies for optimizing the efficiency and reliability of drug development. Methods: This study synthesizes applications of PBPK models in FDA-approved drugs (2020–2024), systematically analyzing model utilization frequency, indication distribution, application domains and choice of modeling platforms, to reveal their substantive contributions to regulatory submissions. Additionally, we conducted an in-depth analysis of the PBPK models for 2024, classifying models into three tiers based on critical assessment of FDA reviewer comments. Results: Among 245 FDA-approved new drugs during this period, 65 NDAs/BLAs (26.5%) submitted PBPK models as pivotal evidence. Oncology drugs accounted for the highest proportion (42%). In application scenarios, drug–drug interaction (DDI) was predominant (81.9%), followed by dose recommendations for patients with organ impairment (7.0%), pediatric population dosing prediction (2.6%), and food-effect evaluation. Regarding modeling platforms, Simcyp^® emerged as the industry-preferred modeling platform, with an 80% usage rate. In terms of regulatory evaluation, a core concern for reviewers is whether the model establishes a complete and credible chain of evidence from in vitro parameters to clinical predictions. Conclusions: Detailed regulatory reviews demonstrate that although some PBPK models exhibit certain limitations and shortcomings, this does not preclude them from demonstrating notable strengths and practical value in critical applications. Benefiting from the strong support these successful implementations provide for regulatory decision-making, the technology is gaining increasing recognition across the industry. Looking forward, the integration of PBPK modeling with artificial intelligence (AI) and multi-omics data will unprecedentedly enhance predictive accuracy, thereby providing critical and actionable insights for decision-making in precision medicine and global regulatory strategies.

To compare health-related quality of life (HRQoL) between patients with stable angina and the general population in China and to examine factors associated with HRQoL among patients with stable angina. A cross-sectional HRQoL survey of stable angina patients recruited from 4 hospitals (n = 411) and the general population recruited from 3 Physical Examination Centers (n = 549) was conducted from July to December, 2011 in two large cities, Tianjin and Chengdu. HRQoL was assessed using the EQ-5D, EQ-VAS, and SF-6D instruments. The health status specific to patients with stable angina was assessed using the Seattle Angina Questionnaire (SAQ). Information on socio-demographic, clinical, and lifestyle factors were also collected. Nested regressions were performed to explore how these factors were associated with HRQoL in patients with stable angina. Compared with the general population (44.2±10 years, 49.9% females), stable angina patients (68.1±12 years, 50.4% females) had significantly lower HRQoL scores in EQ-5D utility index (0.75±0.19 vs. 0.90±0.20, p<0.05), SF-6D utility index (0.68±0.12 vs. 0.85±0.11, p<0.05), and EQ-VAS (71.2±12.3 vs. 83.9±10.9, p<0.05). The differences remained (−0.05 for EQ-5D, −9.27 for EQ-VAS and −0.13 for SF-6D) after controlling for socio-economic characteristics. SAQ scores showed that stable angina patients experienced impaired disease-specific health status, especially in angina stability (40.5±34.6). Nested regressions indicated stable angina-specific health status explained most of the variation in HRQoL, among which disease perception, physical limitation, and angina stability were the strongest predictors. More physical exercise and better sleep were positively related with HRQoL. Compared to the general population, stable angina patients were associated with lower HRQoL and lower health utility scores, which were largely impacted by clinical symptoms. Further studies are needed to characterize the influence of geographic and cultural factors on the variations of health-related utility in stable angina patients.