Why the Gap in Evaluating the Social Constructs and the Value of Medicines?

The Health Inequality Impact of Liquid Biopsy to Inform First-Line Treatment of Advanced Non-Small Cell Lung Cancer: A Distributional Cost-Effectiveness Analysis

OBJECTIVES

To perform a distributional cost-effectiveness analysis of liquid biopsy (LB) followed by, if needed, tissue biopsy (TB) (LB-first strategy) relative to a TB-only strategy to inform first-line treatment of advanced non-small cell lung cancer (aNSCLC) from a US payer perspective by which we quantify the impact of LB-first on population health inequality according to race and ethnicity.

METHODS

With a health economic model, quality-adjusted life-years (QALYs) and costs per patient were estimated for each subgroup. Given the lifetime risk of aNSCLC, and assuming equally distributed opportunity costs, the incremental net health benefits of LB-first were calculated, which were used to estimate general population quality-adjusted life expectancy at birth (QALE) by race and ethnicity with and without LB-first. The degree of QALYs and QALE differences with the strategies was expressed with inequality indices. Their differences were defined as the inequality impact of LB-first.

RESULTS

LB-first resulted in an additional 0.21 (95% uncertainty interval: 0.07-0.39) QALYs among treated patients, with the greatest gain observed among Asian patients (0.31 QALYs [0.09-0.61]). LB-first resulted in an increase in relative inequality in QALYs among patients, but a minor decrease in relative inequality in QALE.

CONCLUSIONS

LB-first to inform first-line aNSCLC therapy can improve health outcomes. With current diagnostic performance, the benefit is the greatest among Asian patients, thereby potentially widening racial and ethnic differences in survival among patients with aNSCLC. Assuming equally distributed opportunity costs and access, LB-first does not worsen and, in fact, may reduce inequality in general population health according to race and ethnicity.

Multivariate Assessment of Vaccine Equity in Cambodia: A Longitudinal VERSE Tool Case Study Using Demographic and Health Survey 2004, 2010, and 2014

Cambodia has exhibited great progress in achieving high coverage in nationally recommended immunizations. As vaccination program managers plan interventions to reach last-mile children, it is important to consider issues of equity immunization priority setting. In this analysis, we apply the VERSE Equity Tool to Cambodia’s Demographic and Health Survey for the years 2004, 2010, and 2014 to evaluate multivariate equity in vaccine coverage for 11 vaccination statuses, emphasizing the results of the 2014 survey for MCV1, DTP3, fully immunized for age (FULL), and zero dose (ZERO). The largest drivers of vaccination inequity are socioeconomic status and the educational attainment of the child’s mother. MCV1, DTP3, and FULL exhibit increasing levels of both coverage and equity with increasing survey years. The national composite Wagstaff concentration index values from the 2014 survey for DTP3, MCV1, ZERO, and FULL are 0.089, 0.068, 0.573, and 0.087, respectively. The difference in vaccination status coverage between the most and least advantaged quintiles of Cambodia’s population, using multivariate ranking criteria, is 23.5% for DTP3, 19.5% for MCV1, 9.1% for ZERO, and 30.3% for FULL. By utilizing these VERSE Equity Tool outputs, immunization program leaders in Cambodia can identify subnational regions in need of targeted interventions.

Assessments of the Value of New Interventions Should Include Health Equity Impact

A formal evaluation of the health equity impact of a new intervention is hardly ever performed as part of a health technology assessment to understand its value. This should change, in our view. An evidence-based quantitative assessment of the health equity impact can help decision makers develop coverage policies, programme designs, and quality initiatives focused on optimizing both total health and health equity given the treatment options available. We outline the conceptual basis of how a new intervention can impact health equity and adopt distributional cost-effectiveness analysis based on decision-analytic models to assess this quantitatively, using a newly US FDA-approved drug for Alzheimer's disease (aducanumab) as an example. We argue that gaps in the evidence base for the new intervention, for example, due to limited clinical research participation among racial and ethnic minority groups, do not preclude such an evaluation. Understanding these uncertainties has implications for fair pricing, decision making, and future research. If we are serious about population-level decision making that not only is focused on improving total health but also aims to improve health equity, we should consider routinely assessing the health equity impact of new interventions.