Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment.

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

Favorable and publicly funded studies are more likely to be published: a systematic review and meta-analysis.

OBJECTIVES: The aim of this study was to identify and quantify the characteristics of studies associated with the likelihood of publication. STUDY DESIGN AND SETTING: We searched for manuscripts that tracked cohorts of clinical studies ("cohorts") that from launch to publication. We explored the association of study characteristics with the probability of publication via traditional meta-analyses and meta-regression using random effects models. RESULTS: The literature review identified 85 cohorts of studies that met our inclusion criteria. The probability of publication was significantly higher for studies whose characteristics were favorable (odds ratio [OR] = 2.04; 95% confidence interval [CI]: 1.62, 2.57) or statistically significant (OR = 2.07; 95% CI: 1.52, 2.81), had a multicenter design (OR = 1.32; 95% CI: 1.16, 1.45), and were of later regulatory phase (3/4 vs. 1/2, OR = 1.34; 95% CI: 1.14, 1.49). Industry funding was modestly associated with lower (OR = 0.81; 95% CI: 0.67, 0.99) probability of publication. An exploratory analysis of effect modification revealed that the effect of the study characteristic "favorable results" on likelihood for publication was stronger for industry-funded studies. CONCLUSION: The study characteristics of favorable and significant results were associated with greater probability of publication.

Improving the Efficiency and Quality of the Value Assessment Process for Companion Diagnostic Tests: The Companion test Assessment Tool (CAT).

BACKGROUND: Companion diagnostic tests (CDTs) have emerged as a vital technology in the effective use of an increasing number of targeted drug therapies. Although CDTs can offer a multitude of potential benefits, assessing their value within a health technology appraisal process can be challenging because of a complex array of factors that influence clinical and economic outcomes. OBJECTIVE: To develop a user-friendly tool to assist managed care and other health care decision makers in screening companion tests and determining whether an intensive technology review is necessary and, if so, where the review should be focused to improve efficiency. METHODS: First, we conducted a systematic literature review of CDT cost-effectiveness studies to identify value drivers. Second, we conducted key informant interviews with a diverse group of stakeholders to elicit feedback and solicit any additional value drivers and identify desirable attributes for an evidence review tool. A draft tool was developed based on this information that captured value drivers, usability features, and had a particular focus on practical use by nonexperts. Finally, the tool was pilot tested with test developers and managed care evidence evaluators to assess face-validity and usability. The tool was also evaluated using several diverse examples of existing companion diagnostics and refined accordingly. RESULTS: We identified 65 cost-effectiveness studies of companion diagnostic technologies. The following factors were most commonly identified as value drivers from our literature review: clinical validity of testing; efficacy, safety, and cost of baseline and alternative treatments; cost and mortality of health states; and biomarker prevalence and testing cost. Stakeholders identified the following additional factors that they believed influenced the overall value of a companion test: regulatory status, actionability, utility, and market penetration. These factors were used to maximize the efficiency of the evidence review process. Stakeholders also stated that a tool should be easy to use and time efficient. Cognitive interviews with stakeholders led to minor changes in the draft tool to improve usability and relevance. The final tool consisted of 4 sections: (1) eligibility for review (2 questions), (2) prioritization of review (3 questions), (3) clinical review (3 questions), and (4) economic review (5 questions). CONCLUSIONS: Although the evaluation of CDTs can be challenging because of limited evidence and the added complexity of incorporating a diagnostic test into drug treatment decisions, using a pragmatic tool to identify tests that do not need extensive evaluation may improve the efficiency and effectiveness of CDT value assessments.

Cost-effectiveness of oral anticoagulants for treatment of atrial fibrillation.

BACKGROUND: New anticoagulants may improve health outcomes in patients with atrial fibrillation, but it is unclear whether their use is cost-effective. METHODS AND RESULTS: A Markov state transition was created to compare 4 therapies: dabigatran 150 mg BID, apixaban 5 mg BID, rivaroxaban 20 mg QD, and warfarin therapy. The population included those with newly diagnosed atrial fibrillation who were eligible for treatment with warfarin. Compared with warfarin, apixaban, rivaroxaban, and dabigatran, costs were $93 063, $111 465, and $140 557 per additional quality-adjusted life year gained, respectively. At a threshold of $100 000 per quality-adjusted life year, apixaban provided the greatest absolute benefit while still being cost-effective, although warfarin would be superior if apixaban was 2% less effective than expected. Although apixaban was the optimal strategy in our base case, in probabilistic sensitivity analysis, warfarin was optimal in an equal number of iterations at a cost-effectiveness threshold of $100 000 per quality-adjusted life year. CONCLUSIONS: While at a standard cost-effectiveness threshold of $100 000 per quality-adjusted life year, apixaban seems to be the optimal anticoagulation strategy; this finding is sensitive to assumptions about its efficacy and cost. In sensitivity analysis, warfarin seems to be the optimal choice in an equal number of simulations. As a result, although all the novel oral anticoagulants produce greater quality-adjusted life expectancy than warfarin, they may not represent good value for money.

Statin pharmacogenomics: opportunities to improve patient outcomes and healthcare costs with genetic testing.

HMG-CoA reductase inhibitors, commonly known as statins, are some of the most widely prescribed medications worldwide and have been shown to be effective at lowering cholesterol in numerous long-term prospective trials, yet there are significant limitations to their use. First, patients receiving statin therapy have relatively low levels of medication adherence compared with other drug classes. Next, numerous statin formulations are available, each with its own unique safety and efficacy profile, and it may be unclear to prescribers which treatment is optimal for their patients. Finally, statins have class-wide side effects of myopathy and rhabdomyolysis that have resulted in a product recall and dosage limitations. Recent evidence suggests that two genomic markers, KIF6 and SLCO1B1, may inform the therapy choice of patients initiating statins. Given the prevalence of statin usage, their potential health advantages and their overall cost to the healthcare system, there could be significant clinical benefit from creating personalized treatment regimens. Ultimately, if this approach is effective it may encourage higher adoption of generic statins when appropriate, promote adherence, lower rates of myopathy, and overall achieve higher value cardiovascular care. This paper will review the evidence for personalized prescribing of statins via KIF6 and SLCO1B1 and consider some of the implications for testing these markers as part of routine clinical care.