The economic value of companion diagnostics and stratified medicines

Blair, Edward D.; Stratton, Elyse; Kaufmann, Martina

doi:10.1586/erm.12.129

Cited by 7 publications

(5 citation statements)

References 17 publications

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“…As the technology surrounding genomic testing improves and the price of the technology decreases, the ability of clinicians to order multiple genetic tests, use panels of genetic markers and even whole tumor genome sequencing methods will increase dramatically [68]. This advancement will further individualize oncology treatment, but a number of issues will arise when trying to assess the economic value of these more complex diagnostic testing methods and how they relate to the use of a targeted therapy [69][70][71][72].…”

Section: Five-year Viewmentioning

confidence: 99%

Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist

Doble

Tan

Harris

et al. 2014

Expert Review of Molecular Diagnostics

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The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics of companion diagnostics into model-based economic evaluations to ensure consistent and transparent reimbursement decisions are made.

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Section: Five-year Viewmentioning

confidence: 99%

Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist

Doble

Tan

Harris

et al. 2014

Expert Review of Molecular Diagnostics

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“…With the evolution of molecular biology and laboratory techniques, especially the emergence of large‐scale “omics” platforms (genomics, epigenomics, transcriptomics, proteomics, metabolomics, and others) and whole‐genome sequencing, more attention and efforts have been devoted to the development of novel molecular biomarkers and companion diagnostic tools . A well‐defined molecular diagnosis could maximize treatment efficiency and the cost‐benefit ratio . We are facing unprecedented opportunities for the integration of molecular diagnostics into the clinic, which promotes progress toward the personalized management of patients with cancer.…”

Section: Molecular Diagnosismentioning

confidence: 99%

“…63 A well-defined molecular diagnosis could maximize treatment efficiency and the cost-benefit ratio. 64 We are facing unprecedented opportunities for the integration of molecular diagnostics into the clinic, which promotes progress toward the personalized management of patients with cancer.…”

Section: Molecular Diagnosismentioning

confidence: 99%

Development and validation of risk models and molecular diagnostics to permit personalized management of cancer

2013

Cancer

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Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. Cancer 2014;120:11-9. V C 2013 American Cancer Society.KEYWORDS: cancer, risk prediction model, molecular diagnosis, personalized management, model assessment. INTRODUCTIONWe are entering an era of personalized medicine, whereby the development of risk prediction models and molecular diagnostics are emerging to provide guidelines for clinical decision-making and the personalized management of cancer. After Gail et al published what to our knowledge is the first risk prediction model for the absolute risk of breast cancer, 1 many risk prediction models were developed, including those for bladder cancer, 2 breast cancer, 3,4 colorectal cancer, 5,6 liver cancer, 7,8 lung cancer, 9,10 and melanoma. 11,12 With advances in technology, several molecular biomarkers and corresponding diagnostic assays have been developed. 13 In this review, we summarize the development, evaluation, and validation of risk prediction models and contributions from modern molecular diagnostics, and discuss some of the challenges for clinical translation.

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“…As one approach, value-based pricing of new drugs aims to maximise the health-related and economic outcomes given a prespecified willingness to pay; in many countries, this has become a widespread method to assess the pricing and reimbursement of new pharmaceuticals entering the market [ 3 , 4 ]. In recent years, attention has also expanded towards companion diagnostics for innovative treatments: highly specialised diagnostic tests paired to a specific drug in the context of what is labelled personalised medicine [ 5 , 6 ]. Personalised medicine entails that drugs are targeted more to specific patient subgroups, with the aim of reducing the uncertainty of whether the drug will be effective before administration and correspondingly improve cost effectiveness of the drug considered.…”

Section: Introductionmentioning

confidence: 99%