Extrapolation of Time-to-Event Survival Outcomes of Histology-Independent Therapies Using a Bayesian Hierarchical Model.
Introduction: Health technology assessment of histology-independent therapies (HITs) requires statistical methods that can capture heterogeneity in outcomes while allowing borrowing of information between tumor sites to inform cost-effectiveness analysis. In this study, we extend previous work on bi...
| Publicado en: | Medical Decision Making Vol. 46; no. 5; pp. 637 - 649 |
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| Autores principales: | , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Jul2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194357021&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194357021 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0272989X DKI jtl: Medical Decision Making issn: 0272989X maglogo: Y pubinfo: dt: Jul2026 vid: 46 iid: 5 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 194357021 192974332 194357021 194357021 10.1177/0272989X261434969 194357021 ppf: 637 ppct: 12 formats: tig: atl: Extrapolation of Time-to-Event Survival Outcomes of Histology-Independent Therapies Using a Bayesian Hierarchical Model. aug: au: Mikelson, Jan Birnie, Richard McCarthy, Grant Madin-Warburton, Matthew Xu, Ruifeng Chumbley, Justin Aguiar-Ibáñez, Raquel Amonkar, Mayur Baio, Gianluca Young, Kate affil: Makerere University, Kampala sug: subj: Neoplasms Drug Therapy Antibodies, Monoclonal Therapeutic Use Antineoplastic Agents Therapeutic Use Overall Survival Evaluation Pathologic Processes DNA Repair Models, Statistical Histology Funding Source Human Male Female Survival Analysis Probability Colorectal Neoplasms Endometrial Neoplasms Stomach Neoplasms Intestinal Neoplasms Biliary Tract Neoplasms Cost Effectiveness Analysis Uncertainty Parametric Statistics Kaplan-Meier Estimator Confidence Intervals Data Analysis Software Descriptive Statistics Male Female ab: Introduction: Health technology assessment of histology-independent therapies (HITs) requires statistical methods that can capture heterogeneity in outcomes while allowing borrowing of information between tumor sites to inform cost-effectiveness analysis. In this study, we extend previous work on binary outcomes to the application of Bayesian hierarchical models (BHMs) for extrapolation of overall survival from pembrolizumab-treated patients with microsatellite instability-high/deficient mismatch repair solid tumors. Methods: We considered BHMs based on 1- or 2-parameter distributions for extrapolation of survival outcomes. The scale or rate parameter of each model was assumed exchangeable among tumor types, and the shape parameter was assumed the same for all tumor types in the 2-parameter models. We compared overall survival (OS) and estimated mean survival time for each BHM with the corresponding nonhierarchical model. Results: Extrapolated OS showed similar results between the BHM and standard models for colorectal, endometrial, and gastric cancers. Small intestine and biliary cancers showed higher OS estimates with a BHM than the standard models due to a combination of smaller sample sizes, information sharing in the BHM, and the use of a common shape parameter. Estimated mean survival times were similar between the BHM and equivalent standard model. However, the BHM showed reduced uncertainty in all cases. Conclusions: We have demonstrated that BHMs provide a suitable framework to extrapolate time-to-event outcomes for HITs. The results provide extrapolated curves for OS that vary by tumor site, thus capturing and quantifying the inherent heterogeneity within the patient population. BHMs offer advantages in terms of reduced uncertainty around parameters that are often key drivers in cost-effectiveness analyses, such as estimated OS, through the borrowing of information between tumor sites. Highlights: Bayesian hierarchical models (BHMs) reduced uncertainty in extrapolation of time-to-event outcomes for histology-independent treatments compared with nonhierarchical models fit to each tumor site. Reduced uncertainty around the mean survival time is a key factor of cost-effectiveness analyses of histology-independent treatments. BHMs provide a suitable framework for extrapolating histology-independent survival outcomes, effectively integrating prior knowledge and explicitly capturing heterogeneity between different tumor sites. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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