The costs and inequities of precision medicine for patients with prostate cancer: A call to action

Financial toxicity is a growing problem in the delivery of cancer care and contributes to inequities in outcomes across the cancer care continuum. Racial/ethnic inequities in prostate cancer, the most common cancer diagnosed in men, are well described, and threaten to widen in the era of precision oncology given the numerous structural barriers to accessing novel diagnostic studies and treatments, particularly for Black men. Gaps in insurance coverage and cost sharing are 2 such structural barriers that can perpetuate inequities in screening, diagnostic workup, guideline-concordant treatment, symptom management, survivorship, and access to clinical trials. Mitigating these barriers will be key to achieving equity in prostate cancer care, and will require a multi-pronged approach from policymakers, health systems, and individual providers. This narrative review will describe the current state of financial toxicity in prostate cancer care and its role in perpetuating racial inequities in the era of precision oncology.

Development of a computerized intervention to improve health literacy in older Hispanics with type 2 diabetes using a pharmacist supervised comprehensive medication management

Objective

The primary objective was to develop a computerized culturally adapted health literacy intervention for older Hispanics with type 2 diabetes (T2D). Secondary objectives were to assess the usability and acceptability of the intervention by older Hispanics with T2D and clinical pharmacists providing comprehensive medication management (CMM).

Materials and methods

The study occurred in three phases. During phase I, an integration approach (i.e., quantitative assessments, qualitative interviews) was used to develop the intervention and ensure cultural suitability. In phase II, the intervention was translated to Spanish and modified based on data obtained in phase I. During phase III, the intervention was tested for usability/acceptability.

Results

Thirty participants (25 older Hispanics with T2D, 5 clinical pharmacists) were included in the study. Five major themes emerged from qualitative interviews and were included in the intervention: 1) financial considerations, 2) polypharmacy, 3) social/family support, 4) access to medication/information, and 5) loneliness/sadness. Participants felt the computerized intervention developed was easy to use, culturally appropriate, and relevant to their needs. Pharmacists agreed the computerized intervention streamlined patient counseling, offered a tailored approach when conducting CMM, and could save them time.

Conclusion

The ability to offer individualized patient counseling based on information gathered from the computerized intervention allows for precision counseling. Future studies are needed to determine the effectiveness of the developed computerized intervention on adherence and health outcomes.

Genetic-guided pharmacotherapy for venous thromboembolism: a systematic and critical review of economic evaluations

Despite the known contributions of genes, genetic-guided pharmacotherapy has not been routinely implemented for venous thromboembolism (VTE). To examine evidence on cost-effectiveness of genetic-guided pharmacotherapy for VTE, we searched six databases, websites of four HTA agencies and citations, with independent double-reviewers in screening, data extraction, and quality rating. The ten eligible studies, all model-based, examined heterogeneous interventions and comparators. Findings varied widely; testing was cost-saving in two base-cases, cost-effective in four, not cost-effective in three, dominated in one. Of 22 model variables that changed decisions about cost-effectiveness, effectiveness/relative effectiveness of the intervention was the most frequent, albeit of poor quality. Studies consistently lacked details on the provision of interventions and comparators as well as on model development and validation. Besides improving the reporting of interventions, comparators, and methodological details, future economic evaluations should examine strategies recommended in guidelines and testing key model variables for decision uncertainty, to advise clinical implementations.

Clinical and cost outcomes following genomics-informed treatment for advanced cancers

BACKGROUND

Single-arm trials are common in precision oncology. Owing to the lack of randomized counterfactual, resultant data are not amenable to comparative outcomes analyses. Difference-in-difference (DID) methods present an opportunity to generate causal estimates of time-varying treatment outcomes. Using DID, our study estimates within-cohort effects of genomics-informed treatment versus standard care on clinical and cost outcomes.

METHODS

We focus on adults with advanced cancers enrolled in the single-arm BC Cancer Personalized OncoGenomics program between 2012 and 2017. All individuals had a minimum of 1-year follow up. Logistic regression explored baseline differences across patients who received a genomics-informed treatment versus a standard care treatment after genomic sequencing. DID estimated the incremental effects of genomics-informed treatment on time to treatment discontinuation (TTD), time to next treatment (TTNT), and costs. TTD and TTNT correlate with improved response and survival.

RESULTS

Our study cohort included 346 patients, of whom 140 (40%) received genomics-informed treatment after sequencing and 206 (60%) received standard care treatment. No significant differences in baseline characteristics were detected across treatment groups. DID estimated that the incremental effect of genomics-informed versus standard care treatment was 102 days (95% CI: 35, 167) on TTD, 91 days (95% CI: -9, 175) on TTNT, and CAD$91,098 (95% CI: $46,848, $176,598) on costs. Effects were most pronounced in gastrointestinal cancer patients.

CONCLUSIONS

Genomics-informed treatment had a statistically significant effect on TTD compared to standard care treatment, but at increased treatment costs. Within-cohort evidence generated through this single-arm study informs the early-stage comparative effectiveness of precision oncology.

Clinical and economic impact of current ALK rearrangement testing in Spain compared with a hypothetical no-testing scenario

BACKGROUND

Currently biomarkers play an essential role in diagnosis, treatment, and management of cancer. In non-small cell lung cancer (NSCLC) determination of biomarkers such as ALK, EGFR, ROS1 or PD-L1 is mandatory for an adequate treatment decision. The aim of this study is to determine the clinical and economic impact of current anaplastic lymphoma kinase testing scenario in Spain.

METHODS

A joint model, composed by decision-tree and Markov models, was developed to estimate the long-term health outcomes and costs of NSCLC patients, by comparing the current testing scenario for ALK in Spain vs a hypothetical no-testing. The current distribution of testing strategies for ALK determination and their sensitivity and specificity data were obtained from the literature. Treatment allocation based on the molecular testing result were defined by a panel of Spanish experts. To assess long-term effects of each treatment, 3-states Markov models were developed, where progression-free survival and overall survival curves were extrapolated using exponential models. Medical direct costs (expressed in €, 2019) were included. A lifetime horizon was used and a discount rate of 3% was applied for both costs and health effects. Several sensitivity analyses, both deterministic and probabilistic, were performed in order test the robustness of the analysis.

RESULTS

We estimated a target population of 7628 NSCLC patients, including those with non-squamous histology and those with squamous carcinomas who were never smokers. Over the lifetime horizon, the current ALK testing scenario produced additional 5060 and 3906 life-years and quality-adjusted life-years (QALY), respectively, compared with the no-testing scenario. Total direct costs were increased up to € 51,319,053 for testing scenario. The incremental cost-effectiveness ratio was 10,142 €/QALY. The sensitivity analyses carried out confirmed the robustness of the base-case results, being the treatment allocation and the test accuracy (sensitivity and specificity data) the key drivers of the model.

CONCLUSIONS

ALK testing in advanced NSCLC patients, non-squamous and never-smoker squamous, provides more than 3000 QALYs in Spain over a lifetime horizon. Comparing this gain in health outcomes with the incremental costs, the resulting incremental cost-effectiveness ratio reinforces that testing non-squamous and never-smoker squamous NSCLC is a cost-effective strategy in Spain.

Precision medicine testing in ovarian cancer: The growing inequity between patients with commercial vs medicaid insurance

INTRODUCTION

Precision medicine technologies have significant impact in the care of patients with ovarian cancer. Compared to affluent patients, socioeconomically vulnerable patients are less likely to have access to this testing. There is little data that demonstrate this inequity over time.

METHODS

We used the IBM Truven Health MarketScan Research Database to identify patients in the United States who underwent surgery for ovarian cancer between 2011 and 2017. The presence of claims for precision medicine testing within six months of surgery was assessed for each patient. Precision medicine testing included both molecular genetic testing (BRCA limited or full sequencing, somatic and germline testing) as well as ancillary pathology tests (immunohistochemistry, microsatellite instability). Demographic data was extracted.

RESULTS

We identified 27,181 patients who met eligibility. Of these, 88.6% had commercial insurance, and 11.4% had Medicaid. While the proportion of patients who underwent precision medicine testing increased over time for both cohorts (47.0% to 66.6% for commercially insured, 41.4% to 57.6% for Medicaid insured, p < 0.0001), the inequity in testing rates widened (5.6% disparity to 9.0%, p < 0.0001). This was driven by growing inequity in germline and somatic genetic testing (7.6% disparity to 21.3%, p < 0.0001).

CONCLUSIONS

There is widening inequity in precision medicine testing rates between commercially insured and Medicaid insured poate patients with ovarian cancer.

Are there socio-economic inequalities in utilization of predictive biomarker tests and biological and precision therapies for cancer? A systematic review and meta-analysis

BACKGROUND

Novel biological and precision therapies and their associated predictive biomarker tests offer opportunities for increased tumor response, reduced adverse effects, and improved survival. This systematic review determined if there are socio-economic inequalities in utilization of predictive biomarker tests and/or biological and precision cancer therapies.

METHODS

MEDLINE, Embase, Scopus, CINAHL, Web of Science, PubMed, and PsycINFO were searched for peer-reviewed studies, published in English between January 1998 and December 2019. Observational studies reporting utilization data for predictive biomarker tests and/or cancer biological and precision therapies by a measure of socio-economic status (SES) were eligible. Data was extracted from eligible studies. A modified ISPOR checklist for retrospective database studies was used to assess study quality. Meta-analyses were undertaken using a random-effects model, with sub-group analyses by cancer site and drug class. Unadjusted odds ratios (ORs) and 95% confidence intervals (CIs) were computed for each study. Pooled utilization ORs for low versus high socio-economic groups were calculated for test and therapy receipt.

RESULTS

Among 10,722 citations screened, 62 papers (58 studies; 8 test utilization studies, 37 therapy utilization studies, 3 studies on testing and therapy, 10 studies without denominator populations or which only reported mean socio-economic status) met the inclusion criteria. Studies reported on 7 cancers, 5 predictive biomarkers tests, and 11 biological and precision therapies. Thirty-eight studies (including 1,036,125 patients) were eligible for inclusion in meta-analyses. Low socio-economic status was associated with modestly lower predictive biomarker test utilization (OR 0.86, 95% CI 0.71-1.05; 10 studies) and significantly lower biological and precision therapy utilization (OR 0.83, 95% CI 0.75-0.91; 30 studies). Associations with therapy utilization were stronger in lung cancer (OR 0.71, 95% CI 0.51-1.00; 6 studies), than breast cancer (OR 0.93, 95% CI 0.78-1.10; 8 studies). The mean study quality score was 6.9/10.

CONCLUSIONS

These novel results indicate that there are socio-economic inequalities in predictive biomarker tests and biological and precision therapy utilization. This requires further investigation to prevent differences in outcomes due to inequalities in treatment with biological and precision therapies.

Implementing Interventions with Varying Marginal Cost-Effectiveness: An Application in Precision Medicine

Purpose. A range of barriers may constrain the effective implementation of strategies to deliver precision medicine. If the marginal costs and consequences of precision medicine vary at different levels of implementation, then such variation will have an impact on relative cost-effectiveness. This study aimed to illustrate the importance and quantify the impact of varying marginal costs and benefits on the value of implementation for a case study in precision medicine. Methods. An existing method to calculate the value of implementation was adapted to allow marginal costs and consequences of introducing precision medicine into practice to vary across differing levels of implementation. This illustrative analysis used a case study based on a published decision-analytic model-based cost-effectiveness analysis of a 70-gene recurrence score (MammaPrint) for breast cancer. The impact of allowing for varying costs and benefits for the value of the precision medicine and of implementation strategies was illustrated graphically and numerically in both static and dynamic forms. Results. The increasing returns to scale exhibited by introducing this specific example of precision medicine mean that a minimum level of implementation (51%) is required for using the 70-gene recurrence score to be cost-effective at a defined threshold of €20,000 per quality-adjusted life year. The observed variation in net monetary benefit implies that the value of implementation strategies was dependent on the initial and ending levels of implementation in addition to the magnitude of the increase in patients receiving the 70-gene recurrence score. In dynamic models, incremental losses caused by low implementation accrue over time unless implementation is improved. Conclusions. Poor implementation of approaches to deliver precision medicine, identified to be cost-effective using decision-analytic model-based cost-effectiveness analysis, can have a significant economic impact on health systems. Developing and evaluating the economic impact of strategies to improve the implementation of precision medicine will potentially realize the more cost-effective use of health care budgets.

An optimal posttreatment surveillance strategy for cancer survivors based on an individualized risk-based approach

The optimal post-treatment surveillance strategy that can detect early recurrence of a cancer within limited visits remains unexplored. Here we adopt nasopharyngeal carcinoma as the study model to establish an approach to surveillance that balances the effectiveness of disease detection versus costs. A total of 7,043 newly-diagnosed patients are grouped according to a clinic-molecular risk grouping system. We use a random survival forest model to simulate the monthly probability of disease recurrence, and thereby establish risk-based surveillance arrangements that can maximize the efficacy of recurrence detection per visit. Markov decision-analytic models further validate that the risk-based surveillance outperforms the control strategies and is the most cost-effective. These results are confirmed in an external validation cohort. Finally, we recommend the risk-based surveillance arrangement which requires 10, 11, 13 and 14 visits for group I to IV. Our surveillance strategies might pave the way for individualized and economic surveillance for cancer survivors.

Inequity in access to personalized medicine in France: Evidences from analysis of geo variations in the access to molecular profiling among advanced non-small-cell lung cancer patients: Results from the IFCT Biomarkers France Study

In this article, we studied geographic variation in the use of personalized genetic testing for advanced non-small cell lung cancer (NSCLC) and we evaluated the relationship between genetic testing rates and local socioeconomic and ecological variables. We used data on all advanced NSCLC patients who had a genetic test between April 2012 and April 2013 in France in the frame of the IFCT Biomarqueurs-France study (n = 15814). We computed four established measures of geographic variation of the sex-adjusted rates of genetic testing utilization at the "départment" (the French territory is divided into 94 administrative units called 'départements') level. We also performed a spatial regression model to determine the relationship between département-level sex-adjusted rates of genetic testing utilization and economic and ecological variables. Our results are the following: (i) Overall, 46.87% lung cancer admission patients obtained genetic testing for NSCLC; département-level utilization rates varied over 3.2-fold. Measures of geographic variation indicated a relatively high degree of geographic variation. (ii) there was a statistically significant relationship between genetic testing rates and per capita supply of general practitioners, radiotherapists and surgeons (negative correlation for the latter); lower genetic testing rates were also associated with higher local poverty rates. French policymakers should pursue effort toward deprived areas to obtain equal access to personalized medicine for advanced NSCLC patients.

Value-Based Pricing Alternatives for Personalised Drugs: Implications of Asymmetric Information and Competition

The market for new drugs is changing: personalised drugs will increase the heterogeneity in patients' responses and, possibly, costs. In this context, price regulation will play an increasingly important role. In this article, we argue that personalised medicine opens new scenarios in the relationship between value-based prices, regulation and industry listing strategies. Our focus is on the role of asymmetry of information and competition. We show that, if the firm has more information than the payer on the heterogeneity in patients' responses and it adopts a profit-maximising listing strategy, the outcome may be independent of the choice of the type of value-based price. In this case, the information advantage that the manufacturer has prevents the payer from using marginal value-based prices to extract part of the surplus. However, in a dynamic setting where competition by a new entrant is possible, the choice of the type of value-based price may matter. We suggest that more research should be devoted to the dynamic analysis of price regulation for personalised medicines.

Shedding Light on Reimbursement Policies of Companion Diagnostics in European Countries

OBJECTIVES

Ensuring access to precision medicine has been an issue because in some European countries, desynchronized reimbursement decision-making occurs between the medicine and the companion diagnostic (CDx). This has resulted in cases in which precision medicine is reimbursed but not the CDx. In overcoming this issue, an alignment of the decision-making process for reimbursement between the 2 entities should be considered. As pharmaceutical reimbursement procedures are meticulously covered in the literature, we set out to systematically map in vitro diagnostic (IVD) reimbursement procedures and identify policies for aligning these procedures with the pharmaceutical reimbursement procedures.

METHODS

We selected 8 European countries for this analysis. For each country, we characterized the national benefit basket entailing the IVD medical acts in outpatient care, evaluated the procedure for inclusion, and identified alternative reimbursement practices for CDx. Targeted searches, using publicly accessible sources, were conducted to identify relevant reimbursement policies and laws.

RESULTS

We systematically describe the reimbursement process in 8 European countries. Alternative procedures for CDx reimbursement were identified in Belgium and Germany. Alternative policies attributed to the practice of precision medicine were identified in England and Italy. In France, some CDx are included in the "coverage with evidence" development program. Specifically, the health technology assessment agencies of France and England commented on the assessment of companion diagnostics and their clinical utility.

CONCLUSION

CDx reimbursement procedures have recently been implemented in some countries. This was seemingly done primarily to ensure access to the precision medicine and only secondary to the value they would provide.

Insights From a Temporal Assessment of Increases in US Private Payer Coverage of Tumor Sequencing From 2015 to 2019

OBJECTIVES

To examine the temporal trajectory of insurance coverage for next-generation tumor sequencing (sequencing) by private US payers, describe the characteristics of coverage adopters and nonadopters, and explore adoption trends relative to the Centers for Medicare and Medicaid Services' National Coverage Determination (CMS NCD) for sequencing.

METHODS

We identified payers with positive coverage (adopters) or negative coverage (nonadopters) of sequencing on or before April 1, 2019, and abstracted their characteristics including size, membership in the BlueCross BlueShield Association, and whether they used a third-party policy. Using descriptive statistics, payer characteristics were compared between adopters and nonadopters and between pre-NCD and post-NCD adopters. An adoption timeline was constructed.

RESULTS

Sixty-nine payers had a sequencing policy. Positive coverage started November 30, 2015, with 1 payer and increased to 33 (48%) as of April 1, 2019. Adopters were less likely to be BlueCross BlueShield members (P < .05) and more likely to use a third-party policy (P < .001). Fifty-eight percent of adopters were small payers. Among adopters, 52% initiated coverage pre-NCD over a 25-month period and 48% post-NCD over 17 months.

CONCLUSIONS

We found an increase, but continued variability, in coverage over 3.5 years. Temporal analyses revealed important trends: the possible contribution of the CMS NCD to a faster pace of coverage adoption, the interdependence in coverage timing among BlueCross BlueShield members, the impact of using a third-party policy on coverage timing, and the importance of small payers in early adoption. Our study is a step toward systematic temporal research of coverage for precision medicine, which will inform policy and affordability assessments.

Payer Preferences and Willingness to Pay for Genomic Precision Medicine: A Discrete Choice Experiment

BACKGROUND

Although precision medicine using genetic information offers significant promise, its uptake and eventual clinical and economic impacts are uncertain. Health care payers will play an important role in evaluating evidence and costs to develop coverage and reimbursement policies.

OBJECTIVE

To elicit U.S. health care payer preference for genomic precision medicine to better understand trade-offs among clinical benefits, uncertainty, and cost.

METHODS

Using key informant interviewer discussions (N = 6 payers), we identified 6 key attributes of genetic tests important to payers: type of information the test provides (screening vs. treatment prediction), probability that the member has an informative genetic marker, expert agreement on changing medical care based on the marker, quality-of-life gains, life expectancy gains (with statistical uncertainty), and cost to the plan. We designed a stated preference discrete choice experiment using these attributes and administered a web survey to a sample of U.S. health care payers. We used effects coding and analyzed the data using an error component mixed logit modeling approach.

RESULTS

The survey response rate was 58% (150 participants completed the survey). Approximately 53% of respondents had previous experience evaluating genetic tests for reimbursement, and 85% had more than 5 years of health care decision-making experience. Payers valued improvements in quality of life the most (marginal willingness to pay [mWTP] of $1,513-$6,076), followed by medical expert agreement on the treatment change (mWTP of $2,881-$3,489). Payers placed a relatively lower value for genetic tests with lower marker probability (mWTP of $2,776 for highest marker probability to $423 for lowest marker probability). Payers mWTP was lowest for resolving uncertainty in quality of life (mWTP of $1,513-$2,031) and life expectancy gains ($536-$1,537).

CONCLUSIONS

Payers exhibited a strong preference for genetic tests that improved quality of life, had high expert agreement on changing medical care, and increased life expectancy. These findings suggest that payers will need evidence of clinical utility to support coverage and reimbursement of genomic precision medicine.

DISCLOSURES

This study was supported by a grant from the NIH Common Fund and NIA (1U01AG047109-01) via the Personalized Medicine Economics Research (PriMER) project. Unrelated to this study, Veenstra reports consulting fees from Bayer and Halozyme; Basu reports consulting fees from Salutis Consulting; and Reiger reports consulting fees from Roche. Carlson reports grants from Institute for Clinical and Economic Review, during the conduct of this study, and consulting fees from Bayer, Adaptive Biotechnologies, Allergan, Galderma, and Vifor Pharma, unrelated to this study.

The Use of the Nicotine Metabolite Ratio as a Biomarker to Personalize Smoking Cessation Treatment: Current Evidence and Future Directions

The nicotine metabolite ratio (NMR), a genetically informed biomarker of rate of nicotine metabolism, has been validated as a tool to select the optimal treatment for individual smokers, thereby improving treatment outcomes. This review summarizes the evidence supporting the development of the NMR as a biomarker of individual differences in nicotine metabolism, the relationship between the NMR and smoking behavior, the clinical utility of using the NMR to personalize treatments for smoking cessation, and the potential mechanisms that underlie the relationship between NMR and smoking cessation. We conclude with a call for additional research necessary to determine the ultimate benefits of using the NMR to personalize treatments for smoking cessation. These future directions include measurement and other methodologic considerations, disseminating this approach to at-risk subpopulations, expanding the NMR to evaluate its efficacy in predicting treatment responses to e-cigarettes and other noncigarette forms of nicotine, and implementation science including cost-effectiveness analyses.See all articles in this Special Collection Honoring Paul F. Engstrom, MD, Champion of Cancer Prevention.

Cost-minimization analysis of individually tailored or fixed-scheduled rituximab maintenance therapy for antineutrophil-cytoplasm antibody associated vasculitides

OBJECTIVE

Patients included in MAINRITSAN2 trial received either an individually tailored or a fixed-schedule therapy with rituximab as  maintenance treatment of antineutrophil cytoplasm antibody associated  vasculitides. The aim of this study was to compare the real-world costs  of both arms.

METHOD

We performed a cost-minimization analysis over an 18-month time period, estimating direct costs -drug acquisition,  preparation, administration and monitoring costs- from the health  system perspective. We conducted a number of additional sensitivity  analyses with different assumptions for unit costs, with further scenarios including the interquartile range of the tailored-infusion group results,  different number of monitoring visits for fixed-schedule regimen and  different number of reported severe adverse events. A cost- effectiveness analysis was conducted as a sensitivity analysis using the  absolute difference in the relapse rate and its confidence interval.

RESULTS

The individually tailored maintenance therapy with rituximab was shown to be a cost-saving treatment compared to the  fixed-schedule therapy (6,049 euros vs. 7,850 euros). Savings resulted  primarily from  lower drug acquisition costs (2,861 vs. 4,768 euros) and lower preparation and administration costs (892 vs. 1,486 euros), due to the lower number of infusions per patient in the tailored-infusion  regimen. The tailoredinfusion regimen presented higher monitoring  costs (2,296 vs. 1,596 euros). This result was replicated in all  assumptions considered in the sensitivity analysis of cost-minimization  approach.

CONCLUSIONS

From the perspective of the health system, the  tailoredtherapy regimen seems to be the preferable option in terms of  direct costs. Further studies assessing all the effects and costs  associated to vasculitides maintenance treatment with rituximab are  needed to support clinical management and healthcare planning.

Cost-Effectiveness of Multigene Pharmacogenetic Testing in Patients With Acute Coronary Syndrome After Percutaneous Coronary Intervention

OBJECTIVE

To evaluate the cost-effectiveness of multigene testing (CYP2C19, SLCO1B1, CYP2C9, VKORC1) compared with single-gene testing (CYP2C19) and standard of care (no genotyping) in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) from Medicare's perspective.

METHODS

A hybrid decision tree/Markov model was developed to simulate patients post-PCI for ACS requiring antiplatelet therapy (CYP2C19 to guide antiplatelet selection), statin therapy (SLCO1B1 to guide statin selection), and anticoagulant therapy in those that develop atrial fibrillation (CYP2C9/VKORC1 to guide warfarin dose) over 12 months, 24 months, and lifetime. The primary outcome was cost (2016 US dollar) per quality-adjusted life years (QALYs) gained. Costs and QALYs were discounted at 3% per year. Probabilistic sensitivity analysis (PSA) varied input parameters (event probabilities, prescription costs, event costs, health-state utilities) to estimate changes in the cost per QALY gained.

RESULTS

Base-case-discounted results indicated that the cost per QALY gained was $59 876, $33 512, and $3780 at 12 months, 24 months, and lifetime, respectively, for multigene testing compared with standard of care. Single-gene testing was dominated by multigene testing at all time horizons. PSA-discounted results indicated that, at the $50 000/QALY gained willingness-to-pay threshold, multigene testing had the highest probability of cost-effectiveness in the majority of simulations at 24 months (61%) and over the lifetime (81%).

CONCLUSIONS

On the basis of projected simulations, multigene testing for Medicare patients post-PCI for ACS has a higher probability of being cost-effective over 24 months and the lifetime compared with single-gene testing and standard of care and could help optimize medication prescribing to improve patient outcomes.

Demand for Precision Medicine: A Discrete-Choice Experiment and External Validation Study

BACKGROUND

A limited evidence base and lack of clear clinical guidelines challenge healthcare systems' adoption of precision medicine. The effect of these conditions on demand is not understood.

OBJECTIVE

This research estimated the public's preferences and demand for precision medicine outcomes.

METHODS

A discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer.

RESULTS

In total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval [CI] 916-1286). Respondents were willing to pay $US265 (95% CI 46-486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established.

CONCLUSIONS

Evidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.

Cost-Effectiveness of RAS Genetic Testing Strategies in Patients With Metastatic Colorectal Cancer: A Systematic Review

BACKGROUND

Monoclonal antibodies against epidermal growth factor receptor (EGFR) have proved beneficial for the treatment of metastatic colorectal cancer (mCRC), particularly when combined with predictive biomarkers of response. International guidelines recommend anti-EGFR therapy only for RAS (NRAS,KRAS) wild-type tumors because tumors with RAS mutations are unlikely to benefit.

OBJECTIVES

We aimed to review the cost-effectiveness of RAS testing in mCRC patients before anti-EGFR therapy and to assess how well economic evaluations adhere to guidelines.

METHODS

A systematic review of full economic evaluations comparing RAS testing with no testing was performed for articles published in English between 2000 and 2018. Study quality was assessed using the Quality of Health Economic Studies scale, and the British Medical Journal and the Philips checklists.

RESULTS

Six economic evaluations (2 cost-effectiveness analyses, 2 cost-utility analyses, and 2 combined cost-effectiveness and cost-utility analyses) were included. All studies were of good quality and adopted the perspective of the healthcare system/payer; accordingly, only direct medical costs were considered. Four studies presented testing strategies with a favorable incremental cost-effectiveness ratio under the National Institute for Clinical Excellence (£20 000-£30 000/QALY) and the US ($50 000-$100 000/QALY) thresholds.

CONCLUSIONS

Testing mCRC patients for RAS status and administering EGFR inhibitors only to patients with RAS wild-type tumors is a more cost-effective strategy than treating all patients without testing. The treatment of mCRC is becoming more personalized, which is essential to avoid inappropriate therapy and unnecessarily high healthcare costs. Future economic assessments should take into account other parameters that reflect the real world (eg, NRAS mutation analysis, toxicity of biological agents, genetic test sensitivity and specificity).

Precision medicine and its implementation in patients with NTRK fusion genes: perspective from developing countries

Precision oncology is the field that places emphasis on the diagnosis and treatment of tumors that harbor specific genomic alterations susceptible to inhibition or modulation. Although most alterations are only present in a minority of patients, a substantial effect on survival can be observed in this subgroup. Mass genome sequencing has led to the identification of a specific driver in the translocations of the tropomyosin receptor kinase family (NTRK) in a subset of rare tumors both in children and in adults, and to the development and investigation of Larotrectinib. This medication was granted approval by the US Food and Drug Administration for NTRK-positive tumors, regardless of histology or age group, as such, larotrectinib was the first in its kind to be approved under the premise that molecular pattern is more important than histology in terms of therapeutic approach. It yielded significant results in disease control with good tolerability across a wide range of diseases including rare pediatric tumors, salivary gland tumors, gliomas, soft-tissue sarcomas, and thyroid carcinomas. In addition, and by taking different approaches in clinical trial design and conducting allocation based on biomarkers, the effects of target therapies can be isolated and quantified. Moreover, and considering developing nations and resource-limited settings, precision oncology could offer a tool to reduce cancer-related disability and hospital costs. In addition, developing nations also present patients with rare tumors that lack a chance of treatment, outside of clinical trials. This, in turn, offers the possibility for international collaboration, and contributes to employment, education, and health service provisions. The reviews of this paper are available via the supplemental material section.

Personalized breast cancer screening strategies: A systematic review and quality assessment

BACKGROUND

The effectiveness of breast cancer screening is still under debate. Our objective was to systematically review studies assessing personalized breast cancer screening strategies based on women's individual risk and to conduct a risk of bias assessment.

METHODS

We followed the standard methods of The Cochrane Collaboration and PRISMA declaration and searched the MEDLINE, EMBASE and Clinical Trials databases for studies published in English. The quality of the studies was assessed using the ISPOR-AMCP-NPC Questionnaire and The Cochrane Risk of Bias Tool. Two independent reviewers screened full texts and evaluated the risk of bias.

RESULTS

Out of the 1533 initially retrieved citations, we included 13 studies. Three studies were randomized controlled trials, while nine were mathematical modeling studies, and one was an observational pilot study. The trials are in the recruitment phase and have not yet reported their results. All three trials used breast density and age to define risk groups, and two of them included family history, previous biopsies, and genetic information. Among the mathematical modeling studies, the main risk factors used to define risk groups were breast density, age, family history, and previous biopsies. Six studies used genetic information to define risk groups. The most common outcome measures were the gain in quality-adjusted life years (QALY), absolute costs, and incremental cost-effectiveness ratio (ICER), while the main outcome in the observational study was the detection rate. In all models, personalized screening strategies were shown to be effective. The randomized trials were of good quality. The modeling studies showed moderate risk of bias but there was wide variability across studies. The observational study showed a low risk of bias but its utility was moderate due to its pilot design and its relatively small scale.

CONCLUSIONS

There is some evidence of the effectiveness of screening personalization in terms of QUALYs and ICER from the modeling studies and the observational study. However, evidence is lacking on feasibility and acceptance by the target population.

REVIEW REGISTRATION

PROSPERO: CRD42018110483.

Patient-Level Modeling Approach Using Discrete-Event Simulation: A Cost-Effectiveness Study of Current Treatment Guidelines for Women with Postmenopausal Osteoporosis

Decision tree and Markov models have been the most commonly used modeling methods in health economic evaluations. Both methods are known for their limitations. Discrete-event simulation (DES), an event-driven model in continuous time at the patient level, is a relatively new method in health economic evaluations that addresses some limitations of the common modeling techniques. Specifically, with the advent of personalized medicine, conventional methods for value assessment that are based on population-level measures might not be appropriate. The best treatment would depend on patient characteristics and clinical profiles. Value assessment of health interventions can vary substantially and may lead to different health decision making due to patient heterogeneity. As such, modeling at the patient level is an appropriate approach for value assessment of health interventions. The DES model has several advantages, such as flexibility, ability to reflect patient heterogeneity, increased precision, and better characterization of modeling uncertainty, that may be preferred to decision tree and Markov models. In addition, with increasing health care spending and drug prices, it is important to quantify value of available treatment options for women with postmenopausal osteoporosis (PMO). The purpose of this Viewpoints article was to describe and demonstrate an application of a DES model to evaluate the cost-effectiveness of the current treatment guidelines for women with PMO. In particular, the DES model indicated that the optimal treatment at the common willingness-to-pay thresholds between $100,000 per quality-adjusted life-year (QALY) and $150,000 per QALY was denosumab. Analysis of patient heterogeneity in terms of low, medium, high, and very high risk of fractures resulted in a similar conclusion. DISCLOSURES: Funding for this study was received through the PhRMA Foundation Value Assessment Challenge Award. The author has no conflicts of interest to declare.

Are There Different Evidence Thresholds for Genomic Versus Clinical Precision Medicine? A Value of Information-Based Framework Applied to Antiplatelet Drug Therapy

BACKGROUND

The threshold of sufficient evidence for adoption of clinically- and genomically-guided precision medicine (PM) has been unclear.

OBJECTIVE

To evaluate evidence thresholds for clinically guided PM versus genomically guided PM.

METHODS

We develop an "evidence threshold criterion" (ETC), which is the time-weighted difference between expected value of perfect information and incremental net health benefit minus the cost of research, and use it as a measure of evidence threshold that is proportional to the upper bound of disutility to a risk-averse decision maker for adopting a new intervention under decision uncertainty. A larger (more negative) ETC value indicates that only decision makers with low risk aversion would adopt new intervention. We evaluated the ETC plus cost of research (ETCc), assuming the same cost of research for both interventions, over time for a pharmacogenomic (PGx) testing intervention and avoidance of a drug-drug interaction (aDDI) intervention for acute coronary syndrome patients indicated for antiplatelet therapy. We then examined how the ETC may explain incongruous decision making across different national decision-making bodies.

RESULTS

The ETCc for PGx increased over time, whereas the ETCc for aDDI decreased to a negative value over time, indicating that decision makers with even low risk aversion will have doubts in adopting PGx, whereas decision makers who are highly risk-averse will continue to have doubts about adopting aDDI. National recommendation bodies appear to be consistent over time within their own decision making, but had different levels of risk aversion.

CONCLUSION

The ETC may be a useful metric for assessing policy makers' risk preferences and, in particular, understanding differences in policy recommendations for genomic versus clinical PM.

Accounting for Capacity Constraints in Economic Evaluations of Precision Medicine: A Systematic Review

BACKGROUND AND OBJECTIVE

Precision (stratified or personalised) medicine is underpinned by the premise that it is feasible to identify known heterogeneity using a specific test or algorithm in patient populations and to use this information to guide patient care to improve health and well-being. This study aimed to understand if, and how, previous economic evaluations of precision medicine had taken account of the impact of capacity constraints.

METHODS

A meta-review was conducted of published systematic reviews of economic evaluations of precision medicine (test-treat interventions) and individual studies included in these reviews. Due to the volume of studies identified, a sample of papers published from 2007 to 2015 was collated. A narrative analysis identified whether potential capacity constraints were discussed qualitatively in the studies and, if relevant, which quantitative methods were used to account for capacity constraints.

RESULTS

A total of 45 systematic reviews of economic evaluations of precision medicine were identified, from which 222 studies focusing on test-treat interventions, published between 2007 and 2015, were extracted. Of these studies, 33 (15%) qualitatively discussed the potential impact of capacity constraints, including budget constraints; quality of tests and the testing process; ease of use of tests in clinical practice; and decision uncertainty. Quantitative methods (nine studies) to account for capacity constraints included static methods such as capturing inefficiencies in trials or models and sensitivity analysis around model parameters; and dynamic methods, which allow the impact of capacity constraints on cost effectiveness to change over time.

CONCLUSIONS

Understanding the cost effectiveness of precision medicine is necessary, but not sufficient, evidence for its successful implementation. There are currently few examples of evaluations that have quantified the impact of capacity constraints, which suggests an area of focus for future research.

A Review of the Challenges of Using Biomedical Big Data for Economic Evaluations of Precision Medicine

There is potential value in incorporating biomedical big data (BBD)-observational real-world patient-level genomic and clinical data in multiple sub-populations-into economic evaluations of precision medicine. However, health economists face practical and methodological challenges when using BBD in this context. We conducted a literature review to identify and summarise these challenges. Relevant articles were identified in MEDLINE, EMBASE, EconLit, University of York Centre for Reviews and Dissemination and Cochrane Library from 2000 to 2018. Articles were included if they studied issues relevant to the interconnectedness of biomedical big data, precision medicine, and health economic evaluation. Nineteen articles were included in the review. Challenges identified related to data management, data quality and data analysis. The availability of large volumes of data from multiple sources, the need to conduct data linkages within an environment of opaque data access and sharing procedures, and other data management challenges are primarily practical and may not be long-term obstacles if procedures for data sharing and access are improved. However, the existence of missing data across linked datasets, the need to accommodate dynamic data, and other data quality and analysis challenges may require an evolution in economic evaluation methods. Health economists face challenges when using BBD in economic evaluations of technologies that facilitate precision medicine. Potential solutions to some of these challenges do, however, exist. Going forward, health economists who present work that uses BBD should document challenges and the solutions they have applied to the challenges to support future researcher endeavours.

Precision medicines need precision patient assistance programs

The competing strategies of patient assistance programs and co-pay accumulator adjustment programs create confusion and administrative burden for clinicians and patients, potentially reducing adherence to clinically indicated services and worsening patient outcomes.

Primer on Precision Medicine for Complex Chronic Disorders

Precision medicine promises patients with complex disorders the right treatment for the right patient at the right dose at the right time with expectation of better health at a lower cost. The demand for precision medicine highlights the limitations of modern Western medicine. Modern Western medicine is a population-based, top-down approach that uses pathology to define disease. Precision medicine is a bottom-up approach that identifies predisease disorders using genetics, biomarkers, and modeling to prevent disease. This primer demonstrates the contrasting strengths and limitations of each paradigm and why precision medicine will eventually deliver on the promises.

Personalized Risk-Stratified Cancer Follow-Up Care: Its Potential for Healthier Survivors, Happier Clinicians, and Lower Costs

The growth in the number of cancer survivors in the face of projected health-care workforce shortages will challenge the US health-care system in delivering follow-up care. New methods of delivering follow-up care are needed that address the ongoing needs of survivors without overwhelming already overflowing oncology clinics or shuttling all follow-up patients to primary care providers. One potential solution, proposed for over a decade, lies in adopting a personalized approach to care in which survivors are triaged or risk-stratified to distinct care pathways based on the complexity of their needs and the types of providers their care requires. Although other approaches may emerge, we advocate for development, testing, and implementation of a risk-stratified approach as a means to address this problem. This commentary reviews what is needed to shift to a risk-stratified approach in delivering survivorship care in the United States.

Budget impact analysis of comprehensive genomic profiling in patients with advanced non-small cell lung cancer

AIMS

Broad molecular profiling of patients with advanced non-small cell lung cancer (NSCLC) is strongly advised to optimize genomic matching with available targeted treatment options or investigational agents. Unlike conventional molecular diagnostic testing, or smaller hotspot panels, comprehensive genomic profiling (CGP) identifies genomic alterations across hundreds of clinically relevant cancer genes from a single tissue specimen. The present study sought to estimate the budget impact of increased use of CGP using a 324-gene panel (FoundationOne) vs non-CGP (represented by a mix of conventional molecular diagnostic testing and smaller NGS hotspot panels) and the number needed to test with CGP to gain 1 life year.

MATERIALS AND METHODS

A decision analytic model was developed to assess the budget impact of increased CGP in advanced NSCLC from a US private payer perspective. Model inputs were based on published literature (epidemiology and treatment outcomes), real-world data (testing and rates, medical service costs), list prices for CGP and anti-cancer drugs, and assumptions for clinical trial participation.

RESULTS

Among 2 million covered lives, 532 had advanced NSCLC; 266 underwent molecular diagnostic testing. An increase in CGP among those tested, from 2% to 10%, was associated with $0.02 per member per month budget impact, of which $0.013 was attributable to costs of prolonged drug treatment and survival and $0.005 to testing cost. Approximately 12 patients would need to be tested with CGP to add 1 life year.

LIMITATIONS

The model incorporated certain assumptions to account for inputs with a limited evidence profile and simplify the possible post-CGP treatments.

CONCLUSIONS

An increase in CGP utilization from 2% to 10% among patients with advanced NSCLC undergoing molecular diagnostic testing was associated with a modest budget impact, most of which was attributable to increased use of more effective treatments and prolonged survival.

The genese of predictive-personified medicine and the problems of its implementation in Ukraine

The concepts, content and significance of predictive-personified medicine that are able to improve the quality of treatment, using genetic information when choosing the medical procedures that are necessary for a particular person are considered. Characteristic of the principles of predictive-personified medicine and its fundamental foundations are carried out: genomics; proteomics; metabolism; bioinformatics The history of the formation and development of predictive-personified medicine in the world is investigated, the relevant legal documents are analyzed. The main advantages of predictive-personified medicine are determined: detection of an illness at an earlier stage, when its treatment is more efficient and cheaper; division of patients into similar groups for the choice of optimal therapy; reduction of adverse reactions to drugs by more effective early assessment of individual negative reactions; improvement of the selection of new biochemical indicators, allowing to control the action of medicinal products; reducing the time, cost, and the number of failures in clinical trials of new treatments. It is noted that in Ukraine none of the well-known projects approved by the American and European committees on gene therapy are implemented. However, the priority direction of research in the field of genetics is chosen annually by more and more medical institutions of Ukraine. Examples of the introduction of predictive-personified medicine into medical institutions and scientific institutes in Ukraine are presented. It is concluded that ensuring the effectiveness of this direction of modern medicine depends on the elimination of many problems of socio-managerial and regulatory nature. In addition to their solution, the priority tasks in this area include the carrying out of significant informational and enlightening work with the population; increase of state funding for the development of preventive medicine; creation of public-private partnership of base centers.

Thought leader perspectives on benefits and harms in precision medicine research

Precision medicine research is underway to identify targeted approaches to improving health and preventing disease. However, such endeavors raise significant privacy and confidentiality concerns. The objective of this study was to elucidate the potential benefits and harms associated with precision medicine research through in-depth interviews with a diverse group of thought leaders, including primarily U.S.-based experts and scholars in the areas of ethics, genome research, health law, historically-disadvantaged populations, informatics, and participant-centric perspectives, as well as government officials and human subjects protections leaders. The results suggest the prospect of an array of individual and societal benefits, as well as physical, dignitary, group, economic, psychological, and legal harms. Relative to the way risks and harms are commonly described in consent forms for precision medicine research, the thought leaders we interviewed arguably emphasized a somewhat different set of issues. The return of individual research results, harm to socially-identifiable groups, the value-dependent nature of many benefits and harms, and the risks to the research enterprise itself emerged as important cross-cutting themes. Our findings highlight specific challenges that warrant concentrated care during the design, conduct, dissemination, and translation of precision medicine research and in the development of consent materials and processes.

Budget Impact of Next-Generation Sequencing for Molecular Assessment of Advanced Non-Small Cell Lung Cancer

BACKGROUND

Genetic testing for nonsquamous advanced non-small cell lung cancer (aNSCLC) is recommended to guide first-line therapy. Activating mutations can be identified via single-gene testing or next-generation sequencing (NGS).

OBJECTIVES

To evaluate the budget impact of NGS instead of single-gene testing for tissue-based molecular assessment of aNSCLC from the US health care payer perspective.

METHODS

An annual cohort of newly diagnosed patients with nonsquamous aNSCLC in a hypothetical 1-million-member health care plan was evaluated using a Markov model over 5 years. Epidemiology and testing rates (EGFR, ALK, ROS1, BRAF, MET, HER2, and RET) were from the literature. Treatments were determined by available genetic information. Safety, progression, and survival with targeted therapy or chemotherapy were from randomized clinical trials. Single-gene testing and first-line and maintenance treatment costs were from RED BOOK and Medicare fee schedules; NGS testing, adverse event, and progression costs to payers were from the literature.

RESULTS

Three hundred sixteen testing-eligible patients with aNSCLC were expected annually, of whom 179 undergo genetic testing. Of 57 patients expected to have activating mutations, single-gene testing identified 35, whereas NGS identified 54. NGS, instead of single-gene testing, decreased expected testing procedure-related costs to the health plan payer by $24,651. First-line and maintenance treatment costs increased by $842,205, offset by a $385,000 decrease in second-line treatment and palliative care costs. Over 5 years, total budget impact was $432,554 ($0.0072 per member per month).

CONCLUSIONS

NGS is expected to identify more patients with activating mutations, thereby better enabling selection for targeted therapy and clinical trial enrollment. The budget impact to US payers is expected to be minimally cost-additive.

Do cancer biomarkers make targeted therapies cost-effective? A systematic review in metastatic colorectal cancer

BACKGROUND

Recent advances in targeted therapies have raised expectations that the clinical application of biomarkers would improve patient's health outcomes and potentially save costs. However, the cost-effectiveness of biomarkers remains unclear irrespective of the cost-effectiveness of corresponding therapies. It is thus important to determine whether biomarkers for targeted therapies provide good value for money. This study systematically reviews economic evaluations of biomarkers for targeted therapies in metastatic colorectal cancer (mCRC) and assesses the cost-effectiveness of predictive biomarkers in mCRC.

METHODS

A literature search was performed using Medline, Embase, EconLit, NHSEED. Papers published from 2000 until June 2018 were searched. All economic evaluations assessing biomarker-guided therapies with companion diagnostics in mCRC were searched. To make studies more comparable, cost-effectiveness results were synthesized as per biomarker tests and corresponding therapies. Methodological quality was assessed using the Quality of Health Economic Studies (QHES) instrument.

RESULTS

Forty-six studies were included in this review. Of these, 17 studies evaluated the intrinsic value of cancer biomarkers, whereas the remaining studies focused on assessing the cost-effectiveness of corresponding drugs. Most studies indicated favourable cost-effectiveness of biomarkers for targeted therapies in mCRC. Some studies reported that biomarkers were cost-effective, while their corresponding therapies were not cost-effective. A considerable number of economic evaluations were conducted in pre-defined genetic populations and thus, often failed to fully capture the biomarker's clinical and economic values. The average QHES score was 73.6.

CONCLUSION

Cancer biomarkers for targeted therapies in mCRC were mostly found to be cost-effective; otherwise, they at least improved the cost-effectiveness of targeted therapies by saving some costs. However, this did not necessarily make their corresponding therapies cost-effective. While companion biomarkers reduced therapy costs, the savings were not sufficient to make the corresponding agents cost-effective. Evaluation of biomarkers was often restricted to the cost of tests and did not consider their clinical values or biomarker prevalence.

"Precision health" for high-need, high-cost patients

It is increasingly clear that high-need, high-cost patients are not a homogenous group, but rather a diverse set of patients with varied circumstances and needs. Acting on this insight requires comprehensive data networks we have not traditionally had, and most analyses to date have focused primarily on claims data. We argue that making clinical and financial gains will require data-sharing networks that integrate clinical factors, genomic information, and social determinants from multiple health systems. Investing in these networks may allow us to better anticipate the unique needs of patients, conceptualize care models to meet those needs, and put targeted interventions into action.

Rapid proteomic analysis for solid tumors reveals LSD1 as a drug target in an end-stage cancer patient

Recent advances in mass spectrometry (MS)-based technologies are now set to transform translational cancer proteomics from an idea to a practice. Here, we present a robust proteomic workflow for the analysis of clinically relevant human cancer tissues that allows quantitation of thousands of tumor proteins in several hours of measuring time and a total turnaround of a few days. We applied it to a chemorefractory metastatic case of the extremely rare urachal carcinoma. Quantitative comparison of lung metastases and surrounding tissue revealed several significantly upregulated proteins, among them lysine-specific histone demethylase 1 (LSD1/KDM1A). LSD1 is an epigenetic regulator and the target of active development efforts in oncology. Thus, clinical cancer proteomics can rapidly and efficiently identify actionable therapeutic options. While currently described for a single case study, we envision that it can be applied broadly to other patients in a similar condition.

Consequences of Biomarker Analysis on the Cost-Effectiveness of Cetuximab in Combination with FOLFIRI as a First-Line Treatment of Metastatic Colorectal Cancer: Personalised Medicine at Work

BACKGROUND

Therapies may be more efficacious when targeting a patient subpopulation with specific attributes, thereby enhancing the cost-effectiveness of treatment. In the CRYSTAL study, patients with metastatic colorectal cancer (mCRC) were treated with cetuximab plus FOLFIRI or FOLFIRI alone until disease progression, unacceptable toxic effects or withdrawal of consent.

OBJECTIVE

To determine if stratified use of cetuximab based on genetic biomarker detection improves cost-effectiveness.

METHODS

We used individual patient data from CRYSTAL to compare the cost-effectiveness, cost per life-year (LY) and cost per quality-adjusted LY (QALY) gained of cetuximab plus FOLFIRI versus FOLFIRI alone in three cohorts of patients with mCRC: all randomised patients (intent-to-treat; ITT), tumours with no detectable mutations in codons 12 and 13 of exon 2 of the KRAS protein ('KRAS wt') and no detectable mutations in exons 2, 3 and 4 of KRAS and exons 2, 3 and 4 of NRAS ('RAS wt'). Survival analysis was conducted using RStudio, and a cost-utility model was modified to allow comparison of the three cohorts.

RESULTS

The deterministic base-case ICER (cost per QALY gained) was £130,929 in the ITT, £72,053 in the KRAS wt and £44,185 in the RAS wt cohorts for cetuximab plus FOLFIRI compared with FOLFIRI alone. At a £50,000 willingness-to-pay threshold, cetuximab plus FOLFIRI has a 2.8, 20 and 63% probability of being cost-effective for the ITT, KRAS wt and RAS wt cohorts, respectively, versus FOLFIRI alone.

CONCLUSION

Screening for mutations in both KRAS and NRAS may provide the most cost-effective approach to patient selection.

Personalized Mammography Screening and Screening Adherence-A Simulation and Economic Evaluation

OBJECTIVE

Personalized breast cancer screening has so far been economically evaluated under the assumption of full screening adherence. This is the first study to evaluate the effects of nonadherence on the evaluation and selection of personalized screening strategies.

METHODS

Different adherence scenarios were established on the basis of findings from the literature. A Markov microsimulation model was adapted to evaluate the effects of these adherence scenarios on three different personalized strategies.

RESULTS

First, three adherence scenarios describing the relationship between risk and adherence were identified: 1) a positive association between risk and screening adherence, 2) a negative association, or 3) a curvilinear relationship. Second, these three adherence scenarios were evaluated in three personalized strategies. Our results show that it is more the absolute adherence rate than the nature of the risk-adherence relationship that is important to determine which strategy is the most cost-effective. Furthermore, probabilistic sensitivity analyses showed that there are risk-stratified screening strategies that are more cost-effective than routine screening if the willingness-to-pay threshold for screening is below US $60,000.

CONCLUSIONS

Our results show that "nonadherence" affects the relative performance of screening strategies. Thus, it is necessary to include the true adherence level to evaluate personalized screening strategies and to select the best strategy.

Personalized Medicine and Pay for Performance: Should Pharmaceutical Firms be Fully Penalized when Treatment Fails?

In this article, we model the behavior of a pharmaceutical firm that has marketing authorization for a new therapy believed to be a candidate for personalized use in a subset of patients, but that lacks information as to why a response is seen only in some patients. We characterize the optimal outcome-based reimbursement policy a health authority should follow to encourage the pharmaceutical firm to undertake research and development activities to generate the information needed to effectively stratify patients. Consistent with the literature, we find that for a pharmaceutical firm that does not undertake research and development activities, when the treatment fails, the total price of the drug must be returned to the healthcare system (full penalization). By contrast, if the firm undertakes research and development activities that make the implementation of personalized medicine possible, treatment failure should not be fully penalized. Surprisingly, in some cases, particularly for high-efficacy drugs and small target populations, the optimal policy may not require any penalty for treatment failure. To illustrate the main results of the analysis, we provide a numerical simulation and a graphical analysis.

Exploring the potential cost-effectiveness of precision medicine treatment strategies for diffuse large B-cell lymphoma

Activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL) is associated with worse survival after standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) chemoimmunotherapy compared to germinal center B-cell-like (GCB) subtype. Preliminary evidence suggests that benefits from novel agents may vary by subtype. Hypothesizing that treatment stratified by DLBCL subtype could be potentially cost-effective, we developed micro-simulation models to compare three first-line treatment strategies: (1) standard RCHOP for all patients (2) subtype testing followed by RCHOP for GCB and novel treatment for ABC DLBCL, and (3) novel treatment for all patients. Based on phase 2 evidence, we used lenalidomide + RCHOP as a surrogate novel treatment. The subtype-based approach showed a favorable incremental cost-effectiveness ratio of $15,015/quality-adjusted life year compared with RCHOP. Although our exploratory analyses demonstrated a wide range of conditions where subtype-based treatment remained cost-effective, data from phase 3 trials are needed to validate our models' findings and draw definitive conclusions.

Economic Outcomes of a Precision Medicine Blood Test To Assess Obstructive Coronary Artery Disease: Results from the PRESET Registry

PURPOSE

The evaluation of obstructive coronary artery disease (CAD) is inefficient and costly. Previous studies of an age/sex/gene expression score (ASGES) in this diagnostic workup have shown a 96% negative predictive value, as well as an 85% decreased likelihood of cardiac referral among low-score outpatients at 45 days. The objective was to explore the one-year cost implications of ASGES use among symptomatic outpatients.

DESIGN

A prospective PRESET Registry (NCT01677156) enrolled stable, nonacute adult patients presenting with symptoms suggestive of obstructive CAD at 21 U.S. primary care practices.

METHODOLOGY

Demographics, clinical factors, and ASGES (defined as low <=15 or elevated >15), as well as management plans post-ASGES, were collected. The economic endpoint analysis was based on the cost of cardiovascular-related tests, procedures, office visits, emergency room visits, and hospitalizations during one year after testing.

RESULTS

The analysis included 566 patients, 51% of whom were women and the median age was 56. Forty-five percent had a low ASGES. The mean cost of cardiovascular care for patients in the year following ASGES was $1,647 for patients with a low ASGES versus $2,709 for those with an elevated score (39% reduction, P=.03 by Wilcoxon rank test). This relationship remained after multivariate analysis that adjusted for patient demographics and clinical covariates (P<.001).

CONCLUSION

The ASGES helped identify patients with low current likelihood of obstructive CAD. These patients had lower costs of cardiovascular care during one year of follow-up. Early reductions in cardiac referrals at 45 days among these patients persisted at one year.

Delivering on the value proposition of precision medicine: the view from healthcare payers

A long-held assumption and expectation has been that genomics-based precision medicine will provide clinicians with the tools and therapies they need to consistently deliver the right treatment to the right patient while simultaneously reducing waste and yielding cost savings for health systems. The pace of discovery within the field of precision medicine has been remarkable, yet optimal uptake of new genetic tests and genetically targeted therapies will occur only if payers recognize their value and opt to cover them. Coverage decisions require clear evidence of clinical effectiveness and utility and an understanding of how adoption will impact healthcare costs and utilization within a payer's network. Research in precision medicine has often not considered the payer's perspective, and despite demonstrations of clinical effectiveness for many promising precision medicine innovations, coverage determinations have been deferred because relevant findings that payers can use to make informed decisions are lacking. Collaboration among payers, scientists, and clinicians is essential for accelerating uptake and value creation. By pairing clinical outcomes with claims and cost data and collaboratively conducting well-designed pragmatic clinical or observational studies, all stakeholders can learn from more meaningful and relevant outcomes. In turn, there will be a collective understanding of how precision medicine innovations impact the health of populations and care delivery within healthcare systems.

Why precision medicine is not the best route to a healthier world

Precision medicine has been announced as a new health revolution. The term precision implies more accuracy in healthcare and prevention of diseases, which could yield substantial cost savings. However, scientific debate about precision medicine is needed to avoid wasting economic resources and hype. In this commentary, we express the reasons why precision medicine cannot be a health revolution for population health. Advocates of precision medicine neglect the limitations of individual-centred, high-risk strategies (reduced population health impact) and the current crisis of evidence-based medicine. Overrated "precision medicine" promises may be serving vested interests, by dictating priorities in the research agenda and justifying the exorbitant healthcare expenditure in our finance-based medicine. If societies aspire to address strong risk factors for non-communicable diseases (such as air pollution, smoking, poor diets, or physical inactivity), they need less medicine and more investment in population prevention strategies.

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary classifier in detecting future seroconverters (and hence offering them PrEP regimens) with the total number of PrEP regimens that is financially and logistically feasible for the program. In this article, we consider a general class of constrained binary classification problems wherein the objective function and the constraint are both monotonic with respect to a threshold. These include the minimization of the rate of positive predictions subject to a minimum sensitivity, the maximization of sensitivity subject to a maximum rate of positive predictions, and the Neyman-Pearson paradigm, which minimizes the type II error subject to an upper bound on the type I error. We propose an ensemble approach to these binary classification problems based on the Super Learner methodology. This approach linearly combines a user-supplied library of scoring algorithms, with combination weights and a discriminating threshold chosen to minimize the constrained optimality criterion. We then illustrate the application of the proposed classifier to develop an individualized PrEP targeting strategy in a resource-limited setting, with the goal of minimizing the number of PrEP offerings while achieving a minimum required sensitivity. This proof of concept data analysis uses baseline data from the ongoing Sustainable East Africa Research in Community Health study. Copyright © 2017 John Wiley & Sons, Ltd.

Advances in ovarian cancer therapy

Epithelial ovarian cancer is typically diagnosed at an advanced stage. Current state-of-the-art surgery and chemotherapy result in the high incidence of complete remissions; however, the recurrence rate is also high. For most patients, the disease eventually becomes a continuum of symptom-free periods and recurrence episodes. Different targeted treatment approaches and biological drugs, currently under development, bring the promise of turning ovarian cancer into a manageable chronic disease. In this review, we discuss the current standard in the therapy for ovarian cancer, major recent studies on the new variants of conventional therapies, and new therapeutic approaches, recently approved and/or in clinical trials. The latter include anti-angiogenic therapies, polyADP-ribose polymerase (PARP) inhibitors, inhibitors of growth factor signaling, or folate receptor inhibitors, as well as several immunotherapeutic approaches. We also discuss cost-effectiveness of some novel therapies and the issue of better selection of patients for personalized treatment.

Public Funding for Genomics and the Return on Investment: A Public Health Perspective

This article traces the emergence of lean principles in genomics research and connects this new way of doing science with many of the current pitfalls of precision medicine in its attempts at improving population health outcomes. Precision medicine has a history of public funding, yet the benefits in clinical settings are very slowly being realized due to a variety of factors, such as uncertainty regarding relevant treatments after identifying disease risk, lack of cost-effectiveness studies for general population-level interventions, and letting a culture of "over promise and under deliver" permeate some areas of genomics research. The article concludes with insights into the challenges and opportunities that will need careful consideration and consultation with the wider society in order to decide whether to turn off the "tap" for investment of public funds in research on genomics and other "omics." Ultimately, this article argues for a moderate course correction in how public funds are invested to truly improve the health of all of us, and not just some of us.