Risk Estimation and Value‐of‐Information Analysis for Three Proposed Genetic Screening Programs for Chronic Beryllium Disease Prevention

Abstract

Genetic differences (polymorphisms) among members of a population are thought to influence susceptibility to various environmental exposures. In practice, however, this information is rarely incorporated into quantitative risk assessment and risk management. We describe an analytic framework for predicting the risk reduction and value-of-information (VOI) resulting from specific risk management applications of genetic biomarkers, and we apply the framework to the example of occupational chronic beryllium disease (CBD), an immune-mediated pulmonary granulomatous disease. One described Human Leukocyte Antigen gene variant, HLA-DP beta 1*0201, contains a substitution of glutamate for lysine at position 69 that appears to have high sensitivity (approximately 94%) but low specificity (approximately 70%) with respect to CBD among individuals occupationally exposed to respirable beryllium. The expected postintervention CBD prevalence rates for using the genetic variant (1) as a required job placement screen, (2) as a medical screen for semiannual in place of annual lymphocyte proliferation testing, or (3) as a voluntary job placement screen are 0.08%, 0.8%, and 0.6%, respectively, in a hypothetical cohort with 1% baseline CBD prevalence. VOI analysis is used to examine the reduction in total social cost, calculated as the net value of disease reduction and financial expenditures, expected for proposed CBD intervention programs based on the genetic susceptibility test. For the example cohort, the expected net VOI per beryllium worker for genetically based testing and intervention is $13,000, $1,800, and $5,100, respectively, based on a health valuation of $1.45 million per CBD case avoided. VOI results for alternative CBD evaluations are also presented. Despite large parameter uncertainty, probabilistic analysis predicts generally positive utility for each of the three evaluated programs when avoidance of a CBD case is valued at $1 million or higher. Although the utility of a proposed risk management program may be evaluated solely in terms of risk reduction and financial costs, decisions about genetic testing and program implementation must also consider serious social, legal, and ethical factors.

Comparative analysis between CFSE flow cytometric and tritiated thymidine incorporation tests for beryllium sensitivity

“…CD4 contributes to the formation of cooperative assembly of TCR-MHC class II complexes. During T-cell activation, surface expression of toxic CD4 T cells and triggered TCRs are down-regulated (37,38). We demonstrated down-regulation of cytotoxic beryllium specific proliferating CFSE/CD3 þ /CD4 þ T-cells by surface and intracellular staining, determined the optimal gating strategy and defined delta PD cutoff.…”

Diagnoses of chronic beryllium disease within cohorts of sarcoidosis patients

“…Progression to clinical disease seems to depend on exposure type [20]. Whether termination of exposure is mandatory to prevent progression is not known, but theoretical scenarios with risk estimation based on occupational epidemiology suggest a benefit from beryllium avoidance [21]. In addition, retrospective studies showed that CBD improved or even resolved with reduction or termination of exposure [22,23].…”

“…Thus, the presence of Glu69-positive HLA-DPB alleles can only serve as a marker for the risk of sensitisation and not as a diagnostic criterion [2]. Extended genetic testing for supratypic markers, as suggested for HLA-DRPheb47, might give additional information on the risk of beryllium sensitisation [31]; however, a high frequency of this named marker in sarcoidosis [21,32] makes it unlikely that this approach will improve diagnosis of CBD in the near future.…”

Pharmacogenomic testing: the cost factor

“…There have been only limited efforts to address this outside the realm of monogenetic diseases and diseases associated with known environmental agents producing disease. 17,[20][21][22][23] Disease has a much better defined cost range than therapeutic complications, and because most diseases are not cured, one can extrapolate expenses to get life-time cost estimates for the dis-…”