Mapping the value for money of precision medicine: a systematic literature review and meta-analysis.

Objective: This study aimed to quantify heterogeneity in the value for money of precision medicine (PM) by application types across contexts and conditions and to quantify sources of heterogeneity to areas of particular promises or concerns as the field of PM moves forward. Methods: A systemic search was performed in Embase, Medline, EconLit, and CRD databases for studies published between 2011 and 2021 on cost-effectiveness analysis (CEA) of PM interventions. Based on a willingness-to-pay threshold of one-time GDP per capita of each study country, the net monetary benefit (NMB) of PM was pooled using random-effects meta-analyses. Sources of heterogeneity and study biases were examined using random-effects meta-regressions, jackknife sensitivity analysis, and the biases in economic studies checklist. Results: Among the 275 unique CEAs of PM, publicly sponsored studies found neither genetic testing nor gene therapy cost-effective in general, which was contradictory to studies funded by commercial entities and early stage evaluations. Evidence of PM being cost-effective was concentrated in a genetic test for screening, diagnosis, or as companion diagnostics (pooled NMBs, $48,152, $8,869, $5,693, p < 0.001), in the form of multigene panel testing (pooled NMBs = $31,026, p < 0.001), which only applied to a few disease areas such as cancer and high-income countries. Incremental effectiveness was an essential value driver for varied genetic tests but not gene therapy. Conclusion: Precision medicine's value for money across application types and contexts was difficult to conclude from published studies, which might be subject to systematic bias. The conducting and reporting of CEA of PM should be locally based and standardized for meaningful comparisons.

Expanding access to high-cost medicines under the Universal Health Coverage scheme in Thailand: review of current practices and recommendations.

BACKGROUND: There has been an increasing demand to reimburse high-cost medicines, through public health insurance schemes in Thailand. METHODS: A mixed method approach was employed. First, a rapid review of select high-income countries was conducted, followed by expert consultations and an in-depth review of three countries: Australia, England and Republic of Korea to understand reimbursement mechanisms of high-cost medicines. In Thailand, current pathways for reimbursing high-cost medicines reviewed, the potential opportunity cost estimated, and stakeholder consultations were conducted to identify context specific considerations. RESULTS: High-income countries reviewed have implemented a variety of pathways and mechanisms for reimbursing high-cost medicines under specific eligibility criteria, listing processes, varying cost-effectiveness thresholds and special funding arrangements. In Thailand, high-cost medicines that do not offer good value-for-money are excluded from the reimbursement process. A framework for reimbursing high-cost medicines that are not cost-effective at the current willingness-to-pay threshold was proposed for Thailand. Under this framework, specific criteria are proposed to determine their eligibility for reimbursement such life-saving nature, treatment of conditions with no alternative treatment options, and affordability. CONCLUSION: High-cost medicines may become eligible for reimbursement through alternative mechanisms based on specific criteria which depend on each context. The application of HTA methods and processes is important in guiding these decisions to support sustainable access to affordable healthcare in pursuit of Universal Health Coverage (UHC).

Evaluating the Value for Money of Precision Medicine from Early Cycle to Market Access: A Comprehensive Review of Approaches and Challenges.

OBJECTIVES: This study aimed to perform a comprehensive review of modeling approaches and methodological and policy challenges in the economic evaluation (EE) of precision medicine (PM) across clinical stages. METHODS: First, a systematic review was performed to assess the approaches of EEs in the past 10 years. Next, a targeted review of methodological articles was conducted for methodological and policy challenges in performing EEs of PM. All findings were synthesized into a structured framework that focused on patient population, Intervention, Comparator, Outcome, Time, Equity and ethics, Adaptability and Modeling aspects, named the "PICOTEAM" framework. Finally, a stakeholder consultation was conducted to understand the major determinants of decision making in PM investment. RESULTS: In 39 methodological articles, we identified major challenges to the EE of PM. These challenges include that PM applications involve complex and evolving clinical decision space, that clinical evidence is sparse because of small subgroups and complex pathways in PM settings, a one-time PM application may have lifetime or intergenerational impacts but long-term evidence is often unavailable, and that equity and ethics concerns are exceptional. In 275 EEs of PM, current approaches did not sufficiently capture the value of PM compared with targeted therapies, nor did they differentiate Early EEs from Conventional EEs. Finally, policy makers perceived the budget impact, cost savings, and cost-effectiveness of PM as the most important determinants in decision making. CONCLUSIONS: There is an urgent need to modify existing guidelines or develop a new reference case that fits into the new healthcare paradigm of PM to guide decision making in research and development and market access.

Assessing the cost-effectiveness of precision medicine: protocol for a systematic review and meta-analysis.

INTRODUCTION: Precision medicine (PM) involves gene testing to identify disease risk, enable early diagnosis or guide therapeutic choice, and targeted gene therapy. We aim to perform a systematic review and meta-analysis to quantify the cost-effectiveness profile of PM stratified by intervention type, identify sources of heterogeneity in the value-for-money of PM. METHODS AND ANALYSIS: We will perform a systematic search in Embase, MEDLINE, EconLit and CRD databases for studies published in English language or with translation in English between 1 January 2011 and 8 July 2021 on the topic of cost-effectiveness analysis of PM interventions. The focus will be on studies that reported health and economic outcomes. Study quality will be assessed using the Biases in Economic Studies checklist. The incremental net benefit of PM screening, diagnostic, treatment-targeting and therapeutic interventions over conventional strategies will be respectively pooled across studies using a random-effect model if heterogeneity is present, otherwise a fixed-effect model. Subgroup analyses will be performed based on disease area, WHO region and World Bank country-income level. Additionally, we will identify the potential sources of heterogeneity with random-effect meta-regressions. Finally, biases will be detected using jackknife sensitivity analysis, funnel plot assessment and Egger's tests. ETHICS AND DISSEMINATION: For this type of study ethics approval or formal consent is not required. The results will be disseminated at various presentations and feedback sessions, in conference abstracts and manuscripts that will be submitted to peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42021272956.

Cost-effectiveness of Tamoxifen, Aromatase Inhibitor, and Switch Therapy (Adjuvant Endocrine Therapy) for Breast Cancer in Hormone Receptor Positive Postmenopausal Women in India.

BACKGROUND: Breast cancer is the leading cause of cancer among women in India. Treatment with hormone therapy reduces recurrence. We undertook this cost-effectiveness study to ascertain the treatment option offering the best value for money. METHODS: The lifetime costs and health outcomes of using tamoxifen, AI and switch therapy were measured in a cohort of 50-year-old women with HR-positive early stage breast cancer. A Markov model of disease was developed using a societal perspective with a lifetime study horizon. Local, contralateral, and distant recurrence were modelled along with treatment related adverse effects. Primary data collected to obtain estimates of out-of-pocket expenditure (OOPE) and utility weights. Both health system cost and OOPE were included. The future costs and consequences were discounted at 3%. A probabilistic sensitivity analysis was used. RESULTS: The lifetime cost of hormone therapy with tamoxifen, AI and switch therapy was to be ₹1,472,037 (I$ 68,947), ₹1,306,794 (I$ 61,208) and ₹1,281,811 (I$ 60,038). The QALYs lived per patient receiving tamoxifen, AI and switch were 13.12, 13.42 and 13.32. tamoxifen was found to be more expensive and less effective. As compared to switch therapy, AI for five years incurred an incremental cost of ₹259,792 (I$12,168) per QALY gained. At the willingness to pay equals to per capita GDP of India, there is 55% probability of AI therapy to be cost-effective compared to switch therapy. CONCLUSION: In postmenopausal women with HR-positive early-stage breast cancer, switch therapy is recommended for use on the basis of cost-effectiveness.