Population genomic screening of young adults for familial hypercholesterolaemia: a cost-effectiveness analysis

Cost-effectiveness analysis of microwave ablation versus robot-assisted partial nephrectomy for patients with small renal masses in Australia

OBJECTIVES

Microwave ablation (MWA) has gained attention as a minimally invasive and safe alternative to surgical intervention for patients with small renal masses; however, its cost-effectiveness in Australia remains unclear. This study conducted a cost-effectiveness analysis to evaluate the relative clinical and economic merits of MWA compared to robotic-assisted partial nephrectomy (RA-PN) in the treatment of small renal masses.

METHODS

A Markov state-transition model was constructed to simulate the progression of Australian patients with small renal masses treated with MWA versus RA-PN over a 10-year horizon. Transition probabilities and utility data were sourced from comprehensive literature reviews, and cost data were estimated from the Australian health system perspective. Life-years, quality-adjusted life-years (QALYs), and lifetime costs were estimated. Modelled uncertainty was assessed using both deterministic and probabilistic sensitivity analyses. A willingness-to-pay (WTP) threshold of $50,000 per QALY was adopted. All costs are expressed in 2022 Australian dollars and discounted at 3% annually. To assess the broader applicability of our findings, a validated cost-adaptation method was employed to extend the analysis to 8 other high-income countries.

RESULTS

Both the base case and cost-adaptation analyses revealed that MWA dominated RA-PN, producing both lower costs and greater effectiveness over 10 years. The cost-effectiveness outcome was robust across all model parameters. Probabilistic sensitivity analyses confirmed that MWA was dominant in 98.3% of simulations at the designated WTP threshold, underscoring the reliability of the model under varying assumptions.

CONCLUSION

For patients with small renal masses in Australia and comparable healthcare settings, MWA is the preferred strategy to maximize health benefits per dollar, making it a highly cost-effective alternative to RA-PN.

Synthesized economic evidence on the cost-effectiveness of screening familial hypercholesterolemia

BACKGROUND

Familial hypercholesterolemia (FH) is a prevalent genetic disorder with global implications for severe cardiovascular diseases. Motivated by the growing recognition of the need for early diagnosis and treatment of FH to mitigate its severe consequences, alongside the gaps in understanding the economic implications and equity impacts of FH screening, this study aims to synthesize the economic evidence on the cost-effectiveness of FH screening and to analyze the impact of FH screening on health inequality.

METHODS

We conducted a systematic review on the economic evaluations of FH screening and extracted information from the included studies using a pre-determined form for evidence synthesis. We synthesized the cost-effectiveness components involving the calculation of synthesized incremental cost-effectiveness ratios (ICERs) and net health benefit (NHB) of different FH screening strategies. Additionally, we applied an aggregate distributional cost-effectiveness analysis (DCEA) to assess the impact of FH screening on health inequality.

RESULTS

Among the 19 studies included, over half utilized Markov models, and 84% concluded that FH screening was potentially cost-effective. Based on the synthesized evidence, cascade screening was likely to be cost-effective, with an ICER of $49,630 per quality-adjusted life year (QALY). The ICER for universal screening was $20,860 per QALY as per evidence synthesis. The aggregate DCEA for six eligible studies presented that the incremental equally distributed equivalent health (EDEH) exceeded the NHB. The difference between EDEH and NHB across the six studies were 325, 137, 556, 36, 50, and 31 QALYs, respectively, with an average positive difference of 189 QALYs.

CONCLUSIONS

Our research offered valuable insights into the economic evaluations of FH screening strategies, highlighting significant heterogeneity in methods and outcomes across different contexts. Most studies indicated that FH screening is cost-effective and contributes to improving overall population health while potentially reducing health inequality. These findings offer implications that policies should promote the implementation of FH screening programs, particularly among younger population. Optimizing screening strategies based on economic evidence can help identify the most effective measures for improving health outcomes and maximizing cost-effectiveness.

Implementation of a primary-tertiary shared care model to improve the detection of familial hypercholesterolaemia (FH): a mixed methods pre-post implementation study protocol

INTRODUCTION

Familial hypercholesterolaemia (FH) is an autosomal dominant inherited disorder of lipid metabolism and a preventable cause of premature cardiovascular disease. Current detection rates for this highly treatable condition are low. Early detection and management of FH can significantly reduce cardiac morbidity and mortality. This study aims to implement a primary-tertiary shared care model to improve detection rates for FH. The primary objective is to evaluate the implementation of a shared care model and support package for genetic testing of FH. This protocol describes the design and methods used to evaluate the implementation of the shared care model and support package to improve the detection of FH.

METHODS AND ANALYSIS

This mixed methods pre-post implementation study design will be used to evaluate increased detection rates for FH in the tertiary and primary care setting. The primary-tertiary shared care model will be implemented at NSW Health Pathology and Sydney Local Health District in NSW, Australia, over a 12-month period. Implementation of the shared care model will be evaluated using a modification of the implementation outcome taxonomy and will focus on the acceptability, evidence of delivery, appropriateness, feasibility, fidelity, implementation cost and timely initiation of the intervention. Quantitative pre-post and qualitative semistructured interview data will be collected. It is anticipated that data relating to at least 62 index patients will be collected over this period and a similar number obtained for the historical group for the quantitative data. We anticipate conducting approximately 20 interviews for the qualitative data.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the ethics review committee (Royal Prince Alfred Hospital Zone) of the Sydney Local Health District (Protocol ID: X23-0239). Findings will be disseminated through peer-reviewed publications, conference presentations and an end-of-study research report to stakeholders.

Cost-Effectiveness of Screening Strategies for Familial Hypercholesterolaemia: An Updated Systematic Review

BACKGROUND

OBJECTIVE: This study aimed to systematically synthesise the cost-effectiveness of screening strategies to detect heterozygous familial hypercholesterolemia (FH).

METHODS

We searched seven databases from inception to 2 February , 2023, for eligible cost-effective analysis (CEA) that evaluated screening strategies for FH versus the standard care for FH detection. Independent reviewers performed the screening, data extraction and quality evaluation. Cost results were adapted to 2022 US dollars (US$) to facilitate comparisons between studies using the same screening strategies. Cost-effectiveness thresholds were based on the original study criteria.

RESULTS

A total of 21 studies evaluating 62 strategies were included in this review, most of the studies (95%) adopted a healthcare perspective in the base case, and majority were set in high-income countries. Strategies analysed included cascade screening (23 strategies), opportunistic screening (13 strategies), systematic screening (11 strategies) and population-wide screening (15 strategies). Most of the strategies relied on genetic diagnosis for case ascertainment. The most common comparator was no screening, but some studies compared the proposed strategy versus current screening strategies or versus the best next alternative. Six studies evaluated screening in children while the remaining were targeted at adults. From a healthcare perspective, cascade screening was cost-effective in 78% of the studies [cost-adapted incremental cost-effectiveness ratios (ICERs) ranged from dominant to 2022 US$ 104,877], opportunistic screening in 85% (ICERs from US$4959 to US$41,705), systematic screening in 80% (ICERs from US$2763 to US$69,969) and population-wide screening in 60% (ICERs from US$1484 to US$223,240). The most common driver of ICER identified in the sensitivity analysis was the long-term cost of lipid-lowering treatment.

CONCLUSIONS

Based on reported willingness to pay thresholds for each setting, most CEA studies concluded that screening for FH compared with no screening was cost-effective, regardless of the screening strategy. Cascade screening resulted in the largest health benefits per person tested.

Advances in familial hypercholesterolemia

Familial hypercholesterolemia (FH), a semi-dominant genetic disease affecting more than 25 million people worldwide, is associated with severe hypercholesterolemia and premature atherosclerotic cardiovascular disease. Over the last decade, advances in data analysis, screening, diagnosis and cardiovascular risk stratification has significantly improved our ability to deliver precision medicine for these patients. Furthermore, recent updates on guideline recommendations and new therapeutic approaches have also proven to be highly beneficial. It is anticipated that both ongoing and upcoming clinical trials will offer further insights for the care and treatment of FH patients.

Cost Effectiveness of Genomic Population Health Screening in Adults: A Review of Modeling Studies and Future Directions

BACKGROUND

Detecting actionable health risks for genetic diseases prior to symptomatic presentation at population scale using genomic test technologies is a preventive health innovation being piloted in multiple locations. Standard practice is to screen for risks only in those with personal or family history of specific disease. Genomic population heath screening has proven feasible and potentially scalable. The value of this intervention in terms of economic benefit has been scientifically modeled by several groups.

CONTENT

Eight recent cost-effectiveness modeling studies for high penetrance monogenic dominant diseases that used input parameters from 3 different countries are reviewed. Results and their uses in refining implementations are analyzed and the roles for laboratory medicine in facilitating success are discussed.

SUMMARY

The reviewed studies generally found evidence for cost-effectiveness of genomic population health screening in at least a subset of their base case screening scenario. Sensitivity analyses identified opportunities for improving the likelihood of cost-effectiveness. On the whole, the modeling results suggest genomic population health screening is likely to be cost-effective for high penetrance disorders in younger adults, especially with achievable reductions in test cost effected partially through combining tests for individual disorders into one screening procedure. Policies founded on the models studied should consider limitations of the modeling methods and the potential for impacts on equity and access in the design and implementation of genomic screening programs.

Combined population genomic screening for three high-risk conditions in Australia: a modelling study

Background

No previous health-economic evaluation has assessed the impact and cost-effectiveness of offering combined adult population genomic screening for mutliple high-risk conditions in a national public healthcare system.

Methods

This modeling study assessed the impact of offering combined genomic screening for hereditary breast and ovarian cancer, Lynch syndrome and familial hypercholesterolaemia to all young adults in Australia, compared with the current practice of clinical criteria-based testing for each condition separately. The intervention of genomic screening, assumed as an up-front single cost in the first annual model cycle, would detect pathogenic variants in seven high-risk genes. The simulated population was 18-40 year-olds (8,324,242 individuals), modelling per-sample test costs ranging AU$100-$1200 (base-case AU$200) from the year 2023 onwards with testing uptake of 50%. Interventions for identified high-risk variant carriers follow current Australian guidelines, modelling imperfect uptake and adherence. Outcome measures were morbidity and mortality due to cancer (breast, ovarian, colorectal and endometrial) and coronary heart disease (CHD) over a lifetime horizon, from healthcare-system and societal perspectives. Outcomes included quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER), discounted 5% annually (with 3% discounting in scenario analysis).

Findings

Over the population lifetime (to age 80 years), the model estimated that genomic screening per-100,000 individuals would lead to 747 QALYs gained by preventing 63 cancers, 31 CHD cases and 97 deaths. In the total model population, this would translate to 31,094 QALYs gained by preventing 2612 cancers, 542 non-fatal CHD events and 4047 total deaths. At AU$200 per-test, genomic screening would require an investment of AU$832 million for screening of 50% of the population. Our findings suggest that this intervention would be cost-effective from a healthcare-system perspective, yielding an ICER of AU$23,926 (∼£12,050/€14,110/US$15,345) per QALY gained over the status quo. In scenario analysis with 3% discounting, an ICER of AU$4758/QALY was obtained. Sensitivity analysis for the base case indicated that combined genomic screening would be cost-effective under 70% of simulations, cost-saving under 25% and not cost-effective under 5%. Threshold analysis showed that genomic screening would be cost-effective under the AU$50,000/QALY willingness-to-pay threshold at per-test costs up to AU$325 (∼£164/€192/US$208).

Interpretation

Our findings suggest that offering combined genomic screening for high-risk conditions to young adults would be cost-effective in the Australian public healthcare system, at currently realistic testing costs. Other matters, including psychosocial impacts, ethical and societal issues, and implementation challenges, also need consideration.

Funding

Australian Government, Department of Health, Medical Research Future Fund, Genomics Health Futures Mission (APP2009024). National Heart Foundation Future Leader Fellowship (102604).

Barriers to and Facilitators of Implementing Guidelines for Detecting Familial Hypercholesterolaemia in Australia

BACKGROUND

Familial hypercholesterolaemia (FH) is a genetic condition that is a preventable cause of premature cardiovascular morbidity and mortality. High-level evidence and clinical practice guidelines support preventative care for people with FH. However, it is estimated that less than 10% of people at risk of FH have been detected using any approach across Australian health settings. The aim of this study was to identify the implementation barriers to and facilitators of the detection of FH in Australia.

METHODS

Four, 2-hour virtual focus groups were facilitated by implementation scientists and a clinicians as part of the 2021 Australasian FH Summit. Template analysis was used to identify themes.

RESULTS

There were 28 workshop attendees across four groups (n=6-8 each), yielding 13 barriers and 10 facilitators across three themes: (1) patient related, (2) provider related, and (3) system related. A "lack of care pathways" and "upskilling clinicians in identifying and diagnosing FH" were the most interconnected barriers and facilitators for the detection of FH.

CONCLUSIONS

The relationships between barriers and facilitators across the patient, provider, and system themes indicates that a comprehensive implementation strategy is needed to address these different levels. Future research is underway to develop a model for implementing the Australian FH guidelines into practice.

A Machine Learning Model to Aid Detection of Familial Hypercholesterolemia

Background

People with monogenic familial hypercholesterolemia (FH) are at an increased risk of premature coronary heart disease and death. With a prevalence of 1:250, FH is relatively common; but currently there is no population screening strategy in place and most carriers are identified late in life, delaying timely and cost-effective interventions.

Objectives

The purpose of this study was to derive an algorithm to identify people with suspected monogenic FH for subsequent confirmatory genomic testing and cascade screening.

Methods

A least absolute shrinkage and selection operator logistic regression model was used to identify predictors that accurately identified people with FH in 139,779 unrelated participants of the UK Biobank. Candidate predictors included information on medical and family history, anthropometric measures, blood biomarkers, and a low-density lipoprotein cholesterol (LDL-C) polygenic score (PGS). Model derivation and evaluation were performed in independent training and testing data.

Results

A total of 488 FH variant carriers were identified using whole-exome sequencing of the low-density lipoprotein receptor, apolipoprotein B, apolipoprotein E, proprotein convertase subtilisin/kexin type 9 genes. A 14-variable algorithm for FH was derived, with an area under the curve of 0.77 (95% CI: 0.71-0.83), where the top 5 most important variables included triglyceride, LDL-C, apolipoprotein A1 concentrations, self-reported statin use, and LDL-C PGS. Excluding the PGS as a candidate feature resulted in a 9-variable model with a comparable area under the curve: 0.76 (95% CI: 0.71-0.82). Both multivariable models (w/wo the PGS) outperformed screening-prioritization based on LDL-C adjusted for statin use.

Conclusions

Detecting individuals with FH can be improved by considering additional predictors. This would reduce the sequencing burden in a 2-stage population screening strategy for FH.

Genetic Testing for Familial Hypercholesterolemia in Clinical Practice

PURPOSE OF REVIEW

Genetic testing has proven utility in identifying and diagnosing individuals with FH. Here we outline the current landscape of genetic testing for FH, recommendations for testing practices and the efforts underway to improve access, availability, and uptake.

RECENT FINDINGS

Alternatives to the traditional genetic testing and counseling paradigm for FH are being explored including expanding screening programs, testing in primary care and/or cardiology clinics, leveraging electronic communication tools like chatbots, and implementing direct contact approaches to facilitate genetic testing of both probands and at-risk relatives. There is no consensus on if, when, and how genetic testing or accompanying genetic counseling should be provided for FH, though traditional genetic counseling and/or testing in specialty lipid clinics is often recommended in expert statements and professional guidelines. More evidence is needed to determine whether alternative approaches to the implementation of genetic testing for FH may be more effective.

Familial Hypercholesterolemia in the Electronic Medical Records and Genomics Network: Prevalence, Penetrance, Cardiovascular Risk, and Outcomes After Return of Results

BACKGROUND

The implications of secondary findings detected in large-scale sequencing projects remain uncertain. We assessed prevalence and penetrance of pathogenic familial hypercholesterolemia (FH) variants, their association with coronary heart disease (CHD), and 1-year outcomes following return of results in phase III of the electronic medical records and genomics network.

METHODS

Adult participants (n=18 544) at 7 sites were enrolled in a prospective cohort study to assess the clinical impact of returning results from targeted sequencing of 68 actionable genes, including LDLR, APOB, and PCSK9. FH variant prevalence and penetrance (defined as low-density lipoprotein cholesterol >155 mg/dL) were estimated after excluding participants enrolled on the basis of hypercholesterolemia. Multivariable logistic regression was used to estimate the odds of CHD compared to age- and sex-matched controls without FH-associated variants. Process (eg, referral to a specialist or ordering new tests), intermediate (eg, new diagnosis of FH), and clinical (eg, treatment modification) outcomes within 1 year after return of results were ascertained by electronic health record review.

RESULTS

The prevalence of FH-associated pathogenic variants was 1 in 188 (69 of 13,019 unselected participants). Penetrance was 87.5%. The presence of an FH variant was associated with CHD (odds ratio, 3.02 [2.00-4.53]) and premature CHD (odds ratio, 3.68 [2.34-5.78]). At least 1 outcome occurred in 92% of participants; 44% received a new diagnosis of FH and 26% had treatment modified following return of results.

CONCLUSIONS

In a multisite cohort of electronic health record-linked biobanks, monogenic FH was prevalent, penetrant, and associated with presence of CHD. Nearly half of participants with an FH-associated variant received a new diagnosis of FH and a quarter had treatment modified after return of results. These results highlight the potential utility of sequencing electronic health record-linked biobanks to detect FH.

From the patient to the population: Use of genomics for population screening

Genomic medicine is expanding from a focus on diagnosis at the patient level to prevention at the population level given the ongoing under-ascertainment of high-risk and actionable genetic conditions using current strategies, particularly hereditary breast and ovarian cancer (HBOC), Lynch Syndrome (LS) and familial hypercholesterolemia (FH). The availability of large-scale next-generation sequencing strategies and preventive options for these conditions makes it increasingly feasible to screen pre-symptomatic individuals through public health-based approaches, rather than restricting testing to high-risk groups. This raises anew, and with urgency, questions about the limits of screening as well as the moral authority and capacity to screen for genetic conditions at a population level. We aimed to answer some of these critical questions by using the WHO Wilson and Jungner criteria to guide a synthesis of current evidence on population genomic screening for HBOC, LS, and FH.

Implementation of a biochemical, clinical, and genetic screening programme for familial hypercholesterolemia in 26 centres in Spain: The ARIAN study

Background: Familial hypercholesterolemia (FH) is clearly underdiagnosed and undertreated. The aim of this present study is to assess the benefits of FH screening through a joint national program implemented between clinical laboratories and lipid units.

Methods: All clinical laboratory tests from 1 January 2017 to 31 December 2018 were reviewed, and those with LDL cholesterol (LDL-C) levels >250 mg/dl were identified in subjects >18 years of age of both sexes. Once secondary causes had been ruled out, the treating physician was contacted and advised to refer the patient to an LU to perform the Dutch Lipid Clinic Network score and to request genetic testing if the score was ≥6 points. Next Generation Sequencing was used to analyse the promoter and coding DNA sequences of four genes associated with FH (LDLR, APOB, PCSK9, APOE) and two genes that have a clinical overlap with FH characteristics (LDLRAP1 and LIPA). A polygenic risk score based on 12 variants was also obtained.

Results: Of the 3,827,513 patients analyzed in 26 centers, 6,765 had LDL-C levels >250 mg/dl. Having ruled out secondary causes and known cases of FH, 3,015 subjects were included, although only 1,205 treating physicians could be contacted. 635 patients were referred to an LU and genetic testing was requested for 153 of them. This resulted in a finding of sixty-seven pathogenic variants for FH, 66 in the LDLR gene and one in APOB. The polygenic risk score was found higher in those who had no pathogenic variant compared to those with a pathogenic variant.

Conclusion: Despite its limitations, systematic collaboration between clinical laboratories and lipid units allows for the identification of large numbers of patients with a phenotypic or genetic diagnosis of FH, which will reduce their vascular risk. This activity should be part of the clinical routine.

Integrated guidance to enhance the care of children and adolescents with familial hypercholesterolaemia: Practical advice for the community clinician

Familial hypercholesterolaemia (FH) is a highly penetrant monogenic disorder present from birth that markedly elevates plasma low-density lipoprotein (LDL)-cholesterol (LDL-C) concentration and, if untreated, leads to premature atherosclerosis and coronary artery disease (CAD). At a prevalence of 1:250 individuals, with over 90% undiagnosed, recent estimates suggest that there are approximately 22 000 children and adolescents with FH in Australia and New Zealand. However, the overwhelming majority remain undetected and inadequately treated until adulthood or after their first cardiac event. The guidance in this paper aims to increase awareness about paediatric FH and provide practical advice for the diagnosis and management of FH in children and adolescents. Recommendations are given on the detection, diagnosis, assessment and management of FH in children and adolescents. Recommendations are also made on genetic testing, including counselling and the potential for universal screening programmes. Practical guidance on management includes treatment of non-cholesterol risk factors, and safe and appropriate use of LDL-C lowering therapies, including statins, ezetimibe, PCSK9 inhibitors and lipoprotein apheresis. Models of care for FH need to be adapted to local and regional health care needs and available resources. Targeting the detection of FH as a priority in children and young adults has the potential to alter the natural history of atherosclerotic cardiovascular disease and recognise the promise of early detection for improving long-term health outcomes. A comprehensive implementation strategy, informed by further research, including assessments of cost-benefit, will be required to ensure that this new guidance benefits all families with or at risk of FH.

Estimated Yield of Screening for Heterozygous Familial Hypercholesterolemia With and Without Genetic Testing in US Adults

Background Heterozygous familial hypercholesterolemia (FH) is a common genetic disorder causing premature cardiovascular disease. Despite this, there is no national screening program in the United States to identify individuals with FH or likely pathogenic FH genetic variants. Methods and Results The clinical characteristics and FH variant status of 49 738 UK Biobank participants were used to develop a regression model to predict the probability of having any FH variants. The regression model and modified Dutch Lipid Clinic Network criteria were applied to 39 790 adult participants (aged ≥20 years) in the National Health and Nutrition Examination Survey to estimate the yield of FH screening programs using Dutch Lipid Clinic Network clinical criteria alone (excluding genetic variant status), genetic testing alone, or combining clinical criteria with genetic testing. The regression model accurately predicted FH variant status in UK Biobank participants (observed prevalence, 0.27%; predicted, 0.26%; area under the receiver-operator characteristic curve, 0.88). In the National Health and Nutrition Examination Survey, the estimated yield per 1000 individuals screened (95% CI) was 3.7 (3.0-4.6) FH cases with the Dutch Lipid Clinic Network clinical criteria alone, 3.8 (2.7-5.1) cases with genetic testing alone, and 6.6 (5.3-8.0) cases by combining clinical criteria with genetic testing. In young adults aged 20 to 39 years, using clinical criteria alone was estimated to yield 1.3 (95% CI, 0.6-2.5) FH cases per 1000 individuals screened, which was estimated to increase to 4.2 (95% CI, 2.6-6.4) FH cases when combining clinical criteria with genetic testing. Conclusions Screening for FH using a combination of clinical criteria with genetic testing may increase identification and the opportunity for early treatment of individuals with FH.