Reduction in Unnecessary Clinical Laboratory Testing Through Utilization Management at a US Government Veterans Affairs Hospital

Objectives: To implement an electronic laboratory utilization management system (laboratory expert system [LES]) to provide safe and effective reductions in unnecessary clinical laboratory testing. Methods: The LES is a set of frequency filter subroutines within the Veterans Affairs hospital and laboratory information system that was formulated by an interdisciplinary medical team.Results: Since implementing the LES, total test volume has decreased by a mean of 11.18% per year compared with our pre-LES test volume. This change was not attributable to fluctuations in outpatient visits or inpatient days of care. Laboratory cost savings were estimated at $151,184 and$163,751 for 2012 and 2013, respectively. A significant portion of these cost savings was attributable to reductions in high-volume, large panel testing. No adverse effects on patient care were reported, and mean length of stay for patients remained unchanged. Conclusions: Electronic laboratory utilization systems can effectively reduce unnecessary laboratory testing without compromising patient care

MHC-I Genotype Restricts the Oncogenic Mutational Landscape.

MHC-I molecules expose the intracellular protein content on the cell surface, allowing T cells to detect foreign or mutated peptides. The combination of six MHC-I alleles each individual carries defines the sub-peptidome that can be effectively presented. We applied this concept to human cancer, hypothesizing that oncogenic mutations could arise in gaps in personal MHC-I presentation. To validate this hypothesis, we developed and applied a residue-centric patient presentation score to 9,176 cancer patients across 1,018 recurrent oncogenic mutations. We found that patient MHC-I genotype-based scores could predict which mutations were more likely to emerge in their tumor. Accordingly, poor presentation of a mutation across patients was correlated with higher frequency among tumors. These results support that MHC-I genotype-restricted immunoediting during tumor formation shapes the landscape of oncogenic mutations observed in clinically diagnosed tumors and paves the way for predicting personal cancer susceptibilities from knowledge of MHC-I genotype

Reduction in Unnecessary Clinical Laboratory Testing Through Utilization Management at a US Government Veterans Affairs Hospital

Objectives: To implement an electronic laboratory utilization management system (laboratory expert system [LES]) to provide safe and effective reductions in unnecessary clinical laboratory testing. Methods: The LES is a set of frequency filter subroutines within the Veterans Affairs hospital and laboratory information system that was formulated by an interdisciplinary medical team.Results: Since implementing the LES, total test volume has decreased by a mean of 11.18% per year compared with our pre-LES test volume. This change was not attributable to fluctuations in outpatient visits or inpatient days of care. Laboratory cost savings were estimated at $151,184 and$163,751 for 2012 and 2013, respectively. A significant portion of these cost savings was attributable to reductions in high-volume, large panel testing. No adverse effects on patient care were reported, and mean length of stay for patients remained unchanged. Conclusions: Electronic laboratory utilization systems can effectively reduce unnecessary laboratory testing without compromising patient care

MHC-I Genotype Restricts the Oncogenic Mutational Landscape.

MHC-I molecules expose the intracellular protein content on the cell surface, allowing T cells to detect foreign or mutated peptides. The combination of six MHC-I alleles each individual carries defines the sub-peptidome that can be effectively presented. We applied this concept to human cancer, hypothesizing that oncogenic mutations could arise in gaps in personal MHC-I presentation. To validate this hypothesis, we developed and applied a residue-centric patient presentation score to 9,176 cancer patients across 1,018 recurrent oncogenic mutations. We found that patient MHC-I genotype-based scores could predict which mutations were more likely to emerge in their tumor. Accordingly, poor presentation of a mutation across patients was correlated with higher frequency among tumors. These results support that MHC-I genotype-restricted immunoediting during tumor formation shapes the landscape of oncogenic mutations observed in clinically diagnosed tumors and paves the way for predicting personal cancer susceptibilities from knowledge of MHC-I genotype

Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer.

Recent studies have characterized the extensive somatic alterations that arise during cancer. However, the somatic evolution of a tumor may be significantly affected by inherited polymorphisms carried in the germline. Here, we analyze genomic data for 5,954 tumors to reveal and systematically validate 412 genetic interactions between germline polymorphisms and major somatic events, including tumor formation in specific tissues and alteration of specific cancer genes. Among germline-somatic interactions, we found germline variants in RBFOX1 that increased incidence of SF3B1 somatic mutation by 8-fold via functional alterations in RNA splicing. Similarly, 19p13.3 variants were associated with a 4-fold increased likelihood of somatic mutations in PTEN. In support of this association, we found that PTEN knockdown sensitizes the MTOR pathway to high expression of the 19p13.3 gene GNA11 Finally, we observed that stratifying patients by germline polymorphisms exposed distinct somatic mutation landscapes, implicating new cancer genes. This study creates a validated resource of inherited variants that govern where and how cancer develops, opening avenues for prevention research.Significance: This study systematically identifies germline variants that directly affect tumor evolution, either by dramatically increasing alteration frequency of specific cancer genes or by influencing the site where a tumor develops. Cancer Discovery; 7(4); 410-23. ©2017 AACR.See related commentary by Geeleher and Huang, p. 354This article is highlighted in the In This Issue feature, p. 339