Oriana Ciani1,2, Bogdan Grigore2, Hedwig Blommestein3, Saskia de Groot3, Meilin Möllenkamp4, Stefan Rabbe4, Rita Daubner-Bendes5,6, Rod S Taylor2,6. 1. Centre for Research on Health and Social Care Management, SDA Bocconi, Milan, Lombardia, Italy. 2. Evidence Synthesis & Modelling for Health Improvement, University of Exeter Medical School, Exeter, Devon, UK. 3. Institute for Medical Technology Assessment, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands. 4. Hamburg Center for Health Economics, Universität Hamburg, Hamburg, Germany. 5. Syreon Research Institute, Budapest, Hungary. 6. MRC/CSO Social and Public Health Sciences Unit & Robertson Centre for Biostatistics, Institute of Health and Well Being, University of Glasgow, Glasgow, Scotland, UK.
Abstract
BACKGROUND: Surrogate endpoints (i.e., intermediate endpoints intended to predict for patient-centered outcomes) are increasingly common. However, little is known about how surrogate evidence is handled in the context of health technology assessment (HTA). OBJECTIVES: 1) To map methodologies for the validation of surrogate endpoints and 2) to determine their impact on acceptability of surrogates and coverage decisions made by HTA agencies. METHODS: We sought HTA reports where evaluation relied on a surrogate from 8 HTA agencies. We extracted data on the methods applied for surrogate validation. We assessed the level of agreement between agencies and fitted mixed-effects logistic regression models to test the impact of validation approaches on the agency's acceptability of the surrogate endpoint and their coverage recommendation. RESULTS: Of the 124 included reports, 61 (49%) discussed the level of evidence to support the relationship between the surrogate and the patient-centered endpoint, 27 (22%) reported a correlation coefficient/association measure, and 40 (32%) quantified the expected effect on the patient-centered outcome. Overall, the surrogate endpoint was deemed acceptable in 49 (40%) reports (k-coefficient 0.10, P = 0.004). Any consideration of the level of evidence was associated with accepting the surrogate endpoint as valid (odds ratio [OR], 4.60; 95% confidence interval [CI], 1.60-13.18, P = 0.005). However, we did not find strong evidence of an association between accepting the surrogate endpoint and agency coverage recommendation (OR, 0.71; 95% CI, 0.23-2.20; P = 0.55). CONCLUSIONS: Handling of surrogate endpoint evidence in reports varied greatly across HTA agencies, with inconsistent consideration of the level of evidence and statistical validation. Our findings call for careful reconsideration of the issue of surrogacy and the need for harmonization of practices across international HTA agencies.
BACKGROUND: Surrogate endpoints (i.e., intermediate endpoints intended to predict for patient-centered outcomes) are increasingly common. However, little is known about how surrogate evidence is handled in the context of health technology assessment (HTA). OBJECTIVES: 1) To map methodologies for the validation of surrogate endpoints and 2) to determine their impact on acceptability of surrogates and coverage decisions made by HTA agencies. METHODS: We sought HTA reports where evaluation relied on a surrogate from 8 HTA agencies. We extracted data on the methods applied for surrogate validation. We assessed the level of agreement between agencies and fitted mixed-effects logistic regression models to test the impact of validation approaches on the agency's acceptability of the surrogate endpoint and their coverage recommendation. RESULTS: Of the 124 included reports, 61 (49%) discussed the level of evidence to support the relationship between the surrogate and the patient-centered endpoint, 27 (22%) reported a correlation coefficient/association measure, and 40 (32%) quantified the expected effect on the patient-centered outcome. Overall, the surrogate endpoint was deemed acceptable in 49 (40%) reports (k-coefficient 0.10, P = 0.004). Any consideration of the level of evidence was associated with accepting the surrogate endpoint as valid (odds ratio [OR], 4.60; 95% confidence interval [CI], 1.60-13.18, P = 0.005). However, we did not find strong evidence of an association between accepting the surrogate endpoint and agency coverage recommendation (OR, 0.71; 95% CI, 0.23-2.20; P = 0.55). CONCLUSIONS: Handling of surrogate endpoint evidence in reports varied greatly across HTA agencies, with inconsistent consideration of the level of evidence and statistical validation. Our findings call for careful reconsideration of the issue of surrogacy and the need for harmonization of practices across international HTA agencies.
Entities:
Keywords:
health technology assessment; outcomes research; surrogate; validation
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