ArticlePharmacoEconomics2024
Mixture and Non-mixture Cure Models for Health Technology Assessment: What You Need to Know.
Article in PharmacoEconomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Defining and modeling 'cure' in early-stage melanoma: perspectives from a systematic literature review.Frontiers in oncology · 2026Pooled it
- Economic Evaluation of Axicabtagene Ciloleucel as a Second-Line Therapy for Relapsed/Refractory Diffuse Large B-Cell Lymphoma in South Korea: A Cost-Utility Analysis Based on the ZUMA-7 Trial.Clinical drug investigation · 2026Article
- Comparative Cost-Effectiveness Analysis of Multiple First-Line Treatments for HER2-Negative Unresectable Advanced or Recurrent Gastric Cancer in Japan.PharmacoEconomics - open · 2026Article
- Incorporating the possibility of cure into network meta-analyses: A case study from resected Stage III/IV melanoma.Research synthesis methods · 2026Article
- Validation of Cure Assumptions when Analyzing ZUMA-7 Follow-up Data of Axicabtagene Ciloleucel and Standard of Care Therapy in Second-Line Relapsed/Refractory Large B-cell Lymphoma.Transplantation and cellular therapy · 2025Article
- Evaluating the Role and Policy Implications of Using External Evidence in Survival Extrapolations: A Case Study of Axicabtagene Ciloleucel Therapy for Second-Line DLBCL.PharmacoEconomics · 2025Article
- Cost-Effectiveness of Pembrolizumab Monotherapy for High Programmed Death Ligand 1 Advanced or Metastatic Non-small Cell Lung Cancer Depends on Long-Term Survivors.Clinical drug investigation · 2025Article
- A Multistate Model Incorporating Relative Survival Extrapolation and Mixed Time Scales for Health Technology Assessment.PharmacoEconomics · 2025Article
- An Evaluation of an Algorithm for the Selection of Flexible Survival Models for Cancer Immunotherapies: Pass or Fail?PharmacoEconomics · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
There is increasing interest in the use of cure modelling to inform health technology assessment (HTA) due to the development of new treatments that appear to offer the potential for cure in some patients. However, cure models are often not included in evidence dossiers submitted to HTA agencies, and they are relatively rarely relied upon to inform decision-making. This is likely due to a lack of understanding of how cure models work, what they assume, and how reliable they are. In this tutorial we explain why and when cure models may be useful for HTA, describe the key characteristics of mixture and non-mixture cure models, and demonstrate their use in a range of scenarios, providing Stata code. We highlight key issues that must be taken into account by analysts when fitting these models and by reviewers and decision-makers when interpreting their predictions. In particular, we note that flexible parametric non-mixture cure models have not been used in HTA, but they offer advantages that make them well suited to an HTA context when a cure assumption is valid but follow-up is limited.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.