Kristoffer Nilsson, Adam Fridhammar, Riku Ota, Morten Sall Jensen, Michael Willis, Sofie Persson
{"title":"在日本临床环境中验证IHE 2型糖尿病队列模型。","authors":"Kristoffer Nilsson, Adam Fridhammar, Riku Ota, Morten Sall Jensen, Michael Willis, Sofie Persson","doi":"10.1080/13696998.2025.2517506","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Economic simulation models, such as the IHE Type 2 Diabetes Cohort Model (IHE-DCM-T2), are used widely to inform resource allocation for Type 2 Diabetes (T2D) treatments. Recently, IHE-DCM-T2 was augmented with Japanese-specific risk equations to align with the Japanese healthcare context. This study extends prior model validation of IHE-DCM-T2 to cover the Japanese risk equations for applications in Japan's clinical setting and healthcare system.</p><p><strong>Materials and methods: </strong>Face validity was assessed through expert review of model assumptions and structure. Model programming was verified by code review and 728 stress tests. Predictive accuracy was tested by comparing model predictions to real-world outcomes from 28 Japanese studies, assessing concordance visually, with regression lines, and with mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), mean squared logarithmic error (MSLE), and mean squared log-accuracy ratio (MSLAR). Subgroup analyses examined dependent and independent endpoints, along with mortality, microvascular, and macrovascular outcomes. Sensitivity analyses assessed robustness to variations in scale and sample size.</p><p><strong>Results: </strong>IHE-DCM-T2 demonstrated face validity and correct implementation. External validation against 120 endpoints showed good alignment between predicted and observed events, with regression line slope=0.96 and R<sup>2</sup>=0.98. Overall, prediction errors were: MAPE=0.83, RMSPE=1.21, MSLE=0.61, and MSLAR=0.53. Predictions were more accurate for dependent than independent endpoints. Among endpoint categories, macrovascular events had the lowest average errors, whereas mortality endpoints had the highest MAPE and RMSPE, and microvascular endpoints had highest MSLE and MSLAR. Predictive accuracy was consistent across alternative test specifications.</p><p><strong>Limitations: </strong>Limitations included gaps in validation data, and the requirement for long-term follow-up that inherently reflects past treatment patterns. Only studies with at least 1,000 patients were included, which may introduce selection bias.</p><p><strong>Conclusions: </strong>This comprehensive validation of the IHE-DCM-T2, augmented with Japanese-specific risk equations, demonstrated its suitability for health technology assessments and resource allocation decisions for T2D in the Japanese clinical setting and healthcare system.</p>","PeriodicalId":16229,"journal":{"name":"Journal of Medical Economics","volume":" ","pages":"944-963"},"PeriodicalIF":3.0000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of the IHE type 2 diabetes cohort model in the Japanese clinical setting.\",\"authors\":\"Kristoffer Nilsson, Adam Fridhammar, Riku Ota, Morten Sall Jensen, Michael Willis, Sofie Persson\",\"doi\":\"10.1080/13696998.2025.2517506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>Economic simulation models, such as the IHE Type 2 Diabetes Cohort Model (IHE-DCM-T2), are used widely to inform resource allocation for Type 2 Diabetes (T2D) treatments. Recently, IHE-DCM-T2 was augmented with Japanese-specific risk equations to align with the Japanese healthcare context. This study extends prior model validation of IHE-DCM-T2 to cover the Japanese risk equations for applications in Japan's clinical setting and healthcare system.</p><p><strong>Materials and methods: </strong>Face validity was assessed through expert review of model assumptions and structure. Model programming was verified by code review and 728 stress tests. Predictive accuracy was tested by comparing model predictions to real-world outcomes from 28 Japanese studies, assessing concordance visually, with regression lines, and with mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), mean squared logarithmic error (MSLE), and mean squared log-accuracy ratio (MSLAR). Subgroup analyses examined dependent and independent endpoints, along with mortality, microvascular, and macrovascular outcomes. Sensitivity analyses assessed robustness to variations in scale and sample size.</p><p><strong>Results: </strong>IHE-DCM-T2 demonstrated face validity and correct implementation. External validation against 120 endpoints showed good alignment between predicted and observed events, with regression line slope=0.96 and R<sup>2</sup>=0.98. Overall, prediction errors were: MAPE=0.83, RMSPE=1.21, MSLE=0.61, and MSLAR=0.53. Predictions were more accurate for dependent than independent endpoints. Among endpoint categories, macrovascular events had the lowest average errors, whereas mortality endpoints had the highest MAPE and RMSPE, and microvascular endpoints had highest MSLE and MSLAR. Predictive accuracy was consistent across alternative test specifications.</p><p><strong>Limitations: </strong>Limitations included gaps in validation data, and the requirement for long-term follow-up that inherently reflects past treatment patterns. Only studies with at least 1,000 patients were included, which may introduce selection bias.</p><p><strong>Conclusions: </strong>This comprehensive validation of the IHE-DCM-T2, augmented with Japanese-specific risk equations, demonstrated its suitability for health technology assessments and resource allocation decisions for T2D in the Japanese clinical setting and healthcare system.</p>\",\"PeriodicalId\":16229,\"journal\":{\"name\":\"Journal of Medical Economics\",\"volume\":\" \",\"pages\":\"944-963\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Economics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/13696998.2025.2517506\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/6/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Economics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/13696998.2025.2517506","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Validation of the IHE type 2 diabetes cohort model in the Japanese clinical setting.
Aims: Economic simulation models, such as the IHE Type 2 Diabetes Cohort Model (IHE-DCM-T2), are used widely to inform resource allocation for Type 2 Diabetes (T2D) treatments. Recently, IHE-DCM-T2 was augmented with Japanese-specific risk equations to align with the Japanese healthcare context. This study extends prior model validation of IHE-DCM-T2 to cover the Japanese risk equations for applications in Japan's clinical setting and healthcare system.
Materials and methods: Face validity was assessed through expert review of model assumptions and structure. Model programming was verified by code review and 728 stress tests. Predictive accuracy was tested by comparing model predictions to real-world outcomes from 28 Japanese studies, assessing concordance visually, with regression lines, and with mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), mean squared logarithmic error (MSLE), and mean squared log-accuracy ratio (MSLAR). Subgroup analyses examined dependent and independent endpoints, along with mortality, microvascular, and macrovascular outcomes. Sensitivity analyses assessed robustness to variations in scale and sample size.
Results: IHE-DCM-T2 demonstrated face validity and correct implementation. External validation against 120 endpoints showed good alignment between predicted and observed events, with regression line slope=0.96 and R2=0.98. Overall, prediction errors were: MAPE=0.83, RMSPE=1.21, MSLE=0.61, and MSLAR=0.53. Predictions were more accurate for dependent than independent endpoints. Among endpoint categories, macrovascular events had the lowest average errors, whereas mortality endpoints had the highest MAPE and RMSPE, and microvascular endpoints had highest MSLE and MSLAR. Predictive accuracy was consistent across alternative test specifications.
Limitations: Limitations included gaps in validation data, and the requirement for long-term follow-up that inherently reflects past treatment patterns. Only studies with at least 1,000 patients were included, which may introduce selection bias.
Conclusions: This comprehensive validation of the IHE-DCM-T2, augmented with Japanese-specific risk equations, demonstrated its suitability for health technology assessments and resource allocation decisions for T2D in the Japanese clinical setting and healthcare system.
期刊介绍:
Journal of Medical Economics'' mission is to provide ethical, unbiased and rapid publication of quality content that is validated by rigorous peer review. The aim of Journal of Medical Economics is to serve the information needs of the pharmacoeconomics and healthcare research community, to help translate research advances into patient care and be a leader in transparency/disclosure by facilitating a collaborative and honest approach to publication.
Journal of Medical Economics publishes high-quality economic assessments of novel therapeutic and device interventions for an international audience