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.

Characterizing the Strength of Evidence in FDA Labels for Pharmacogenomic Biomarker-Guided Medication Use.

There is great heterogeneity in drug treatment response that is thought to be due to individual-level allelic variation in pharmacogenomic biomarkers. FDA Drug Labels provide information to guide pharmacogenomic biomarker use. Yet, the strength of evidence for clinical validity and clinical utility is lacking. We characterized the strength of evidence and treatment recommendations contained in FDA Drug Labels as of December 2015. Pharmacogenomic biomarker information was provided for 137 drugs, involving 49 pharmacogenomic biomarkers, constituting 166 drug-biomarker pairs. Convincing/adequate evidence of clinical validity was found for 46% of pairs, of clinical utility for 29% of pairs, and of both, for 27% of pairs. Despite evidence of convincing/adequate validity/utility, no treatment recommendation was provided for 37% of pairs. Germline biomarkers represented nearly three-quarters of all drug-biomarker pairs, however, only 29% and 16% of pairs had convincing/adequate evidence for clinical validity and clinical utility, respectively. Separately, somatic biomarkers that serve as molecular targets for targeted therapies, had convincing/adequate evidence for 95% of pairs for clinical validity, and for 67% for clinical utility. The strength of evidence for pharmacogenomic biomarker use is low, underscoring the need for additional research to achieve the promise of precision medicine.

Drug Treatment of Idiopathic Pulmonary Fibrosis: Systematic Review and Network Meta-Analysis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a form of chronic progressive fibrosing interstitial lung disease of unknown origin. Recently, nintedanib and pirfenidone demonstrated efficacy in slowing disease progression and were approved by the US Food and Drug Administration. Although numerous treatments have been evaluated in IPF, none have shown significant decreases in mortality. The objective of this study was to identify all pharmacologic treatments evaluated for IPF and analyze their efficacy via Bayesian network meta-analysis and pairwise indirect treatment comparisons. This review did not evaluate the effect of steroid therapy. METHODS: We searched MEDLINE, Embase, and the Cochrane Library for studies published on or before August 2014. Studies were required to contain a randomized evaluation of nonsteroidal drug therapy for treatment of IPF and be published in English. Key outcomes of interest for this analysis were pulmonary function as measured by FVC as well as all-cause and respiratory-specific death. All outcomes were analyzed via a Bayesian framework. RESULTS: Our review identified 30 eligible studies that evaluated 16 unique treatments. Under both the fixed-effect and random-effect models for respiratory-specific mortality, no treatments performed better than placebo. For all-cause mortality, pirfenidone and nintedanib had effects approaching significance with credible intervals slightly crossing the null under a fixed-effect model. Notably, for respiratory-specific mortality, all-cause mortality, and decline in percent predicted FVC, nintedanib and pirfenidone were virtually indistinguishable and no clear advantage was detected. CONCLUSIONS: Although two treatments have been approved for IPF on the basis of reduced decline in pulmonary function, neither one has a clear advantage on mortality outcomes.

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.

Clinical evidence supporting pharmacogenomic biomarker testing provided in US Food and Drug Administration drug labels.

IMPORTANCE: Genetic biomarkers that predict a drug's efficacy or likelihood of toxicity are assuming increasingly important roles in the personalization of pharmacotherapy, but concern exists that evidence that links use of some biomarkers to clinical benefit is insufficient. Nevertheless, information about the use of biomarkers appears in the labels of many prescription drugs, which may add confusion to the clinical decision-making process. OBJECTIVE: To evaluate the evidence that supports pharmacogenomic biomarker testing in drug labels and how frequently testing is recommended. DATA SOURCES: Publicly available US Food and Drug Administration databases. MAIN OUTCOMES AND MEASURES: We identified drug labels that described the use of a biomarker and evaluated whether the label contained or referenced convincing evidence of its clinical validity (ie, the ability to predict phenotype) and clinical utility (ie, the ability to improve clinical outcomes) using guidelines published by the Evaluation of Genomic Applications in Practice and Prevention Working Group. We graded the completeness of the citation of supporting studies and determined whether the label recommended incorporation of biomarker test results in therapeutic decision making. RESULTS: Of the 119 drug-biomarker combinations, only 43 (36.1%) had labels that provided convincing clinical validity evidence, whereas 18 (15.1%) provided convincing evidence of clinical utility. Sixty-one labels (51.3%) made recommendations about how clinical decisions should be based on the results of a biomarker test; 36 (30.3%) of these contained convincing clinical utility data. A full description of supporting studies was included in 13 labels (10.9%). CONCLUSIONS AND RELEVANCE: Fewer than one-sixth of drug labels contained or referenced convincing evidence of clinical utility of biomarker testing, whereas more than half made recommendations based on biomarker test results. It may be premature to include biomarker testing recommendations in drug labels when convincing data that link testing to patient outcomes do not exist.

Genetic factors affecting statin concentrations and subsequent myopathy: a HuGENet systematic review.

Statins, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors, have proven efficacy in both lowering low-density-lipoprotein levels and preventing major coronary events, making them one of the most commonly prescribed drugs in the United States. Statins exhibit a class-wide side effect of muscle toxicity and weakness, which has led regulators to impose both dosage limitations and a recall. This review focuses on the best-characterized genetic factors associated with increased statin muscle concentrations, including the genes encoding cytochrome P450 enzymes (CYP2D6, CYP3A4, and CYP3A5), a mitochondrial enzyme (GATM), an influx transporter (SLCO1B1), and efflux transporters (ABCB1 and ABCG2). A systematic literature review was conducted to identify relevant research evaluating the significance of genetic variants predictive of altered statin concentrations and subsequent statin-related myopathy. Studies eligible for inclusion must have incorporated genotype information and must have associated it with some measure of myopathy, either creatine kinase levels or self-reported muscle aches and pains. After an initial review, focus was placed on seven genes that were adequately characterized to provide a substantive review: CYP2D6, CYP3A4, CYP3A5, GATM, SLCO1B1, ABCB1, and ABCG2. All statins were included in this review. Among the genetic factors evaluated, statin-related myopathy appears to be most strongly associated with variants in SLCO1B1.

Impact of CYP2C19 genetic testing on provider prescribing patterns for antiplatelet therapy after acute coronary syndromes and percutaneous coronary intervention.

BACKGROUND: Patients treated with clopidogrel who have ≥1 loss of function alleles for CYP2C19 have an increased risk for adverse cardiovascular events. In 2010, the US Food and Drug Administration issued a boxed warning cautioning against the use of clopidogrel in such patients. We sought to assess the impact of CYP2C19 genetic testing on prescribing patterns for antiplatelet therapy among patients with acute coronary syndrome or percutaneous coronary intervention. METHODS AND RESULTS: Patients with recent acute coronary syndrome or percutaneous coronary intervention prescribed clopidogrel were offered CYP2C19 testing. Genotype and phenotype results were provided to patients and their physicians, but no specific treatment recommendations were suggested. Patients were categorized based on their genotype (carriers versus noncarriers) and phenotype (extensive, intermediate, and poor metabolizers). The primary outcome was intensification in antiplatelet therapy defined as either dose escalation of clopidogrel or replacement of clopidogrel with prasugrel. Between July 2010 and April 2012, 6032 patients were identified, and 499 (8.3%) underwent CYP2C19 genotyping, of whom 146 (30%) were found to have ≥1 reduced function allele, including 15 (3%) with 2 reduced function alleles. Although reduced function allele carriers were significantly more likely than noncarriers to have an intensification of their antiplatelet therapy, only 20% of poor metabolizers of clopidogrel had their antiplatelet therapy intensified. CONCLUSIONS: Providers were significantly more likely to intensify antiplatelet therapy in CYP2C19 allele carriers, but only 20% of poor metabolizers of clopidogrel had an escalation in the dose of clopidogrel or were switched to prasugrel. These prescribing patterns likely reflect the unclear impact and evolving evidence for clopidogrel pharmacogenomics.

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.

Healthcare payers: a gate or translational bridge to personalized medicine?

Healthcare payers represent stakeholders who can act as either a bridge or a gate to the translation of personalized medicine into routine clinical practice. To date, the slow realization of the promise of personalized medicine has been partly attributable to the lack of clear evidence supporting the clinical utility of genetic and genomic tests and the lag in development of clinical guidelines for the use and interpretation of tests. These factors, along with a paucity of clear guidance from healthcare payers and clinical experience with genomic tests, serve as impediments to timely and consistent reimbursement decisions. The design of alternative strategies for collaborative evidence-generation, clinical decision support and educational initiatives for healthcare providers, patients and the payers themselves are critical needs to achieve the full benefit of personalized medicine in day-to-day healthcare settings.

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.