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Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
Published on: February 6, 2015
Modelling approaches for histology-independent cancer drugs to inform NICE appraisals: a systematic review and
Peter Murphy1, David Glynn2, Sofia Dias1
1Centre for Reviews and Dissemination, University of York, York, UK.
Background:
The first histology-independent marketing authorisation in Europe was granted in 2019. This was the first time that a cancer treatment was approved based on a common biomarker rather than the location in the body at which the tumour originated. This research aims to explore the implications for National Institute for Health and Care Excellence appraisals.
Methods:
Targeted reviews were undertaken to determine the type of evidence that is likely to be available at the point of marketing authorisation and the analyses required to support National Institute for Health and Care Excellence appraisals. Several challenges were identified concerning the design and conduct of trials for histology-independent products, the greater levels of heterogeneity within the licensed population and the use of surrogate end points. We identified approaches to address these challenges by reviewing key statistical literature that focuses on the design and analysis of histology-independent trials and by undertaking a systematic review to evaluate the use of response end points as surrogate outcomes for survival end points. We developed a decision framework to help to inform approval and research policies for histology-independent products. The framework explored the uncertainties and risks associated with different approval policies, including the role of further data collection, pricing schemes and stratified decision-making.
Results:
We found that the potential for heterogeneity in treatment effects, across tumour types or other characteristics, is likely to be a central issue for National Institute for Health and Care Excellence appraisals. Bayesian hierarchical methods may serve as a useful vehicle to assess the level of heterogeneity across tumours and to estimate the pooled treatment effects for each tumour, which can inform whether or not the assumption of homogeneity is reasonable. Our review suggests that response end points may not be reliable surrogates for survival end points. However, a surrogate-based modelling approach, which captures all relevant uncertainty, may be preferable to the use of immature survival data. Several additional sources of heterogeneity were identified as presenting potential challenges to National Institute for Health and Care Excellence appraisal, including the cost of testing, baseline risk, quality of life and routine management costs. We concluded that a range of alternative approaches will be required to address different sources of heterogeneity to support National Institute for Health and Care Excellence appraisals. An exemplar case study was developed to illustrate the nature of the assessments that may be required.
Conclusions:
Adequately designed and analysed basket studies that assess the homogeneity of outcomes and allow borrowing of information across baskets, where appropriate, are recommended. Where there is evidence of heterogeneity in treatment effects and estimates of cost-effectiveness, consideration should be given to optimised recommendations. Routine presentation of the scale of the consequences of heterogeneity and decision uncertainty may provide an important additional approach to the assessments specified in the current National Institute for Health and Care Excellence methods guide.
Further Research:
Further exploration of Bayesian hierarchical methods could help to inform decision-makers on whether or not there is sufficient evidence of homogeneity to support pooled analyses. Further research is also required to determine the appropriate basis for apportioning genomic testing costs where there are multiple targets and to address the challenges of uncontrolled Phase II studies, including the role and use of surrogate end points.
Funding:
This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 25, No. 76. See the NIHR Journals Library website for further project information.
Insights
Histology-independent cancer treatments approved based on biomarkers present unique challenges for health technology appraisals. Bayesian methods and careful trial design are recommended to address heterogeneity and inform decision-making for these novel therapies.
Area of Science:
- Oncology
- Health Technology Assessment
- Biostatistics
Background:
- First European marketing authorisation for a histology-independent cancer treatment granted in 2019.
- Approval based on common biomarkers, not tumour location.
- Research explores implications for National Institute for Health and Care Excellence (NICE) appraisals.
Purpose of the Study:
- To explore implications of histology-independent cancer treatments for NICE appraisals.
- To identify evidence requirements and analytical approaches for NICE appraisals.
- To develop a decision framework for histology-independent products.
Main Methods:
- Targeted reviews of evidence at marketing authorisation.
- Analysis of statistical literature on histology-independent trial design and analysis.
- Systematic review of response end points as surrogates for survival.
- Development of a decision framework for approval and research policies.
Main Results:
- Heterogeneity in treatment effects across tumour types is a key issue for NICE appraisals.
- Bayesian hierarchical methods can assess heterogeneity and estimate pooled treatment effects.
- Response end points may not be reliable surrogates for survival; surrogate-based modelling is preferable.
- Other challenges include testing costs, baseline risk, quality of life, and management costs.
Conclusions:
- Basket studies assessing homogeneity and allowing information borrowing are recommended.
- Optimised recommendations should consider heterogeneity in treatment effects and cost-effectiveness.
- Routine presentation of heterogeneity consequences and decision uncertainty is advised.

