Publications

UNLABELLED

Although high mammographic density is considered one of the strongest risk factors for invasive breast cancer, the genes involved in modulating this clinical feature are unknown. Tissues of high mammographic density share key histologic features with stromal components within malignant lesions of tumor tissues, specifically low adipocyte and high extracellular matrix (ECM) content. We show that CD36, a transmembrane receptor that coordinately modulates multiple protumorigenic phenotypes, including adipocyte differentiation, angiogenesis, cell-ECM interactions, and immune signaling, is greatly repressed in multiple cell types of disease-free stroma associated with high mammographic density and tumor stroma. Using both in vitro and in vivo assays, we show that CD36 repression is necessary and sufficient to recapitulate the above-mentioned phenotypes observed in high mammographic density and tumor tissues. Consistent with a functional role for this coordinated program in tumorigenesis, we observe that clinical outcomes are strongly associated with CD36 expression.

SIGNIFICANCE

CD36 simultaneously controls adipocyte content and matrix accumulation and is coordinately repressed in multiple cell types within tumor and high mammographic density stroma, suggesting that activation of this stromal program is an early event in tumorigenesis. Levels of CD36 and extent of mammographic density are both modifiable factors that provide potential for intervention.

CONTEXT

Some veterans are eligible to enroll simultaneously in a Medicare Advantage (MA) plan and the Veterans Affairs health care system (VA). This scenario produces the potential for redundant federal spending because MA plans would receive payments to insure veterans who receive care from the VA, another taxpayer-funded health plan.

OBJECTIVE

To quantify the prevalence of dual enrollment in VA and MA, the concurrent use of health services in each setting, and the estimated costs of VA care provided to MA enrollees.

DESIGN

Retrospective analysis of 1,245,657 veterans simultaneously enrolled in the VA and an MA plan between 2004-2009.

MAIN OUTCOME MEASURES

Use of health services and inflation-adjusted estimated VA health care costs.

RESULTS

Among individuals who were eligible to enroll in the VA and in an MA plan, the number of persons dually enrolled increased from 485,651 in 2004 to 924,792 in 2009. In 2009, 8.3% of the MA population was enrolled in the VA and 5.0% of MA beneficiaries were VA users. The estimated VA health care costs for MA enrollees totaled $13.0 billion over 6 years, increasing from $1.3 billion in 2004 to $3.2 billion in 2009. Among dual enrollees, 10% exclusively used the VA for outpatient and acute inpatient services, 35% exclusively used the MA plan, 50% used both the VA and MA, and 4% received no services during the calendar year. The VA financed 44% of all outpatient visits (n = 21,353,841), 15% of all acute medical and surgical admissions (n = 177,663), and 18% of all acute medical and surgical inpatient days (n = 1,106,284) for this dually enrolled population. In 2009, the VA billed private insurers $52.3 million to reimburse care provided to MA enrollees and collected $9.4 million (18% of the billed amount; 0.3% of the total cost of care).

CONCLUSIONS

The federal government spends a substantial and increasing amount of potentially duplicative funds in 2 separate managed care programs for the care of same individuals.

BACKGROUND

The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration.

METHODS AND RESULTS

A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%-5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals.

CONCLUSIONS

The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality.