A Cost–Consequence Analysis of Preemptive SLCO1B1 Testing for Statin Myopathy Risk Compared to Usual Care

There is a well-validated association between SLCO1B1 (rs4149056) and statin-associated muscle symptoms (SAMS). Preemptive SLCO1B1 pharmacogenetic (PGx) testing may diminish the incidence of SAMS by identifying individuals with increased genetic risk before statin initiation. Despite its potential clinical application, the cost implications of SLCO1B1 testing are largely unknown. We conducted a cost–consequence analysis of preemptive SLCO1B1 testing (PGx+) versus usual care (PGx−) among Veteran patients enrolled in the Integrating Pharmacogenetics in Clinical Care (I-PICC) Study. The assessment was conducted using a health system perspective and 12-month time horizon. Incremental costs of SLCO1B1 testing and downstream medical care were estimated using data from the U.S. Department of Veterans Affairs’ Managerial Cost Accounting System. A decision analytic model was also developed to model 1-month cost and SAMS-related outcomes in a hypothetical cohort of 10,000 Veteran patients, where all patients were initiated on simvastatin. Over 12 months, 13.5% of PGx+ (26/193) and 11.2% of PGx− (24/215) participants in the I-PICC Study were prescribed Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline-concordant statins (Δ2.9%, 95% CI −4.0% to 10.0%). Differences in mean per-patient costs for lipid therapy prescriptions, including statins, for PGx+ compared to PGx− participants were not statistically significant (Δ USD 9.53, 95% CI −0.86 to 22.80 USD). Differences in per-patient costs attributable to the intervention, including PGx testing, lipid-lowering prescriptions, SAMS, laboratory and imaging expenses, and primary care and cardiology services, were also non-significant (Δ− USD 1004, 95% CI −2684 to 1009 USD). In the hypothetical cohort, SLCO1B1-informed statin therapy averted 109 myalgias and 3 myopathies at 1-month follow up. Fewer statin discontinuations (78 vs. 109) were also observed, but the SLCO1B1 testing strategy was 96 USD more costly per patient compared to no testing (124 vs. 28 USD). The implementation of SLCO1B1 testing resulted in small, non-significant increases in the proportion of patients receiving CPIC-concordant statin prescriptions within a real-world primary care context, diminished the incidence of SAMS, and reduced statin discontinuations in a hypothetical cohort of 10,000 patients. Despite these effects, SLCO1B1 testing administered as a standalone test did not result in lower per-patient health care costs at 1 month or over 1 year of treatment. The inclusion of SLCO1B1, among other well-validated pharmacogenes, into preemptive panel-based testing strategies may provide a better balance of clinical benefit and cost.

A risk-based approach for structural assessment against fire considering escalation and passive fire protection (PFP) optimization

PurposeAccidental loadings such as fire constitute a great majority of potential and actual fatalities in both onshore and offshore installations. In order to prevent human loss and for a safe design of an asset, the risk of fire loading needs to be quantified, in terms of both probability/frequency and consequence aspects. In this paper the authors propose a novel risk-based approach for the assessment against accidental fire loading.Design/methodology/approachIn a conventional passive fire protection (PFP) analysis using ductility level analysis (DLA), fire loads are deterministically applied to a structure whose response is then analyzed. The initial PFP scheme is developed based on the analysis and then optimized. This approach is sometimes misinterpreted as a “risk-based” approach; however, it does not take into account the frequency aspect of the risk assessment. In a risk-based PFP analysis using DLA, fire scenarios are developed in a particular target zone. Then DLA is performed to determine the structural consequence. If personnel safety is of interest, the consequence of the structure is then linked to individual risk (IR) to determine fatalities. The amount of PFP to be applied on the structure is fully based on the risk that is produced by the fire scenarios in target zones.FindingsA new perspective on safe design of onshore/offshore structures for accidental loadings is outlined to estimate the associated risk to potential targets such as personnel as well as asset. The proposed assessment methodology will contribute toward identifying the mitigation measures and safety-critical procedures and equipment and toward a safer design.Originality/valueThis paper presents a new perspective in a safer design of onshore and offshore structures for a fire accidental loading based on risk calculation. Risk is defined as a combination of the frequency and consequence. An event frequency analysis is carried out to determine how often one should expect the event to occur. A consequence analysis is carried out to determine the severity levels of the event. In a risk-based consequence analysis, the severity levels are fully determined based on the risk associated with the event. The proposed novel risk-based assessment methodology against accidental fire loading contributes toward fully understanding the risk from an impact to personnel and to asset perspectives and leads toward safer and optimal design.

A Cost-Consequence Analysis of Different Screening Procedures in Alzheimer’s Disease: Results from the MOPEAD Project

Background: For care planning and support, under-detection and late diagnosis of Alzheimer’s disease (AD) is a great challenge. Models of Patient-Engagement for Alzheimer’s Disease (MOPEAD) is an EU-funded project aiming at testing different strategies to improve this situation. Objective: To make a cost-consequence analysis of MOPEAD. Methods: Four screening strategies were tested in five countries (Germany, the Netherlands, Slovenia, Spain, and Sweden): 1) a web-approach; 2) Open-House initiative; 3) in primary care; and 4) by diabetes specialists. Persons-at-risk of AD in all strategies were offered referral to a hospital-based specialist. The primary health-economic outcome was the cost per true-positive case (TP) of AD from the screened population. Results: Of 2,847 screened persons, 1,121 screened positive (39%), 402 were evaluated at memory clinics (14%), and 236 got an AD diagnosis (8%). The cost per TP of those screened was 3,115€ with the web-approach, 2,722€ with the Open-House, 1,530€ in primary care, and 1,190€ by diabetes specialists. Sensitivity analyses that more likely reflect the real-world situation confirmed the results. The number-needed-to-screen was 30 with the web-approach, 8 with the Open-House and primary care, and 6 with the diabetes specialists. There were country differences in terms of screening rates, referrals to memory clinics, staff-types involved, and costs per TP. Conclusion: In primary care and by the diabetes specialist, the costs per TP/screened population were lowest, but the capacity of such settings to identify cases with AD-risk must be discussed. Hence new diagnostic strategies such as web-solutions and Open-House initiatives may be valuable after modifications.