BackgroundApproximately 70% of all breast cancers express the estrogen receptor, and are regulated by estrogen. While the ovaries are the primary source of estrogen in premenopausal women, most breast cancer is diagnosed following menopause, when systemic levels of this hormone decline. Estrogen production from androgen precursors is catalyzed by the aromatase enzyme. Although aromatase expression and local estrogen production in breast adipose tissue have been implicated in the development of primary breast cancer, the source of estrogen involved in the regulation of estrogen receptor-positive (ER+) metastatic breast cancer progression is less clear.MethodsBone is the most common distant site of breast cancer metastasis, particularly for ER+ breast cancers. We employed a co-culture model using trabecular  bone tissues obtained from total hip replacement (THR) surgery specimens to study ER+ and estrogen receptor-negative (ER-) breast cancer cells within the human bone microenvironment. Luciferase-expressing ER+ (MCF-7, T-47D, ZR-75) and ER- (SK-BR-3, MDA-MB-231, MCF-10A) breast cancer cells were cultured directly on bone tissue fragments or in bone tissue-conditioned media, and monitored over time with bioluminescence imaging (BLI). Bone tissue-conditioned media were generated in the presence vs. absence of aromatase inhibitors, and testosterone. Bone tissue fragments were analyzed for aromatase expression by immunohistochemistry.ResultsER+ breast cancer cells were preferentially sustained in co-cultures with bone tissues and bone tissue-conditioned media relative to ER- cells. Bone fragments analyzed by immunohistochemistry revealed expression of the aromatase enzyme. Bone tissue-conditioned media generated in the presence of testosterone had increased estrogen levels and heightened capacity to stimulate ER+ breast cancer cell proliferation. Pretreatment of cultured bone tissues with aromatase inhibitors, which inhibited estrogen production, reduced the capacity of conditioned media to stimulate ER+ cell proliferation.ConclusionsThese results suggest that a local estrogen signaling axis regulates ER+ breast cancer cell viability and proliferation within the bone metastatic niche, and that aromatase inhibitors modulate this axis. Although endocrine therapies are highly effective in the treatment of ER+ breast cancer, resistance to these treatments reduces their efficacy. Characterization of estrogen signaling networks within the bone microenvironment will identify new strategies for combating metastatic progression and endocrine resistance.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-017-0910-x) contains supplementary material, which is available to authorized users.

PURPOSE: To estimate the value of cancer care and to compare value among episodes of care, a transparent, reproducible, and standardized cost computation methodology is needed. Charges, claims, and reimbursements are related to cost but are nontransparent and proprietary. We developed a method to measure the cost of the following phases of care: (1) initial treatment with curative intent, (2) surveillance and survivorship care, and (3) relapse and end-of-life care. METHODS: We combined clinical data from our electronic health record, the state cancer registry, and the Social Security Death Index. We analyzed the care of patients with breast cancer and mapped Common Procedural Terminology (CPT) codes to the corresponding cost conversion factor and date in the CMS Medicare fee schedule. To account for varying duration of episodes of care, we computed a cost of care per day (CCPD) for each patient. RESULTS: Median CCPD for initial treatment was $29.45 in US dollars (USD), the CCPD for surveillance and survivorship care was $2.45 USD, and the CCPD for relapse care was $13.80 USD. Among the three breast cancer types (hormone receptor-positive or human epidermal growth factor receptor 2 [HER2]-negative, HER2-positive, and triple-negative), there was no difference in CCPD. Relapsed patients in the most expensive surveillance CCPD group had significantly shorter survival. CONCLUSION: We developed a method to identify high-value oncology care—cost of care per patient per day (CCPD)—in episodes of initial, survivorship, and relapse care. The methodology can help identify positive deviants (who have developed best practices) delivering high-value care. Merging our data with claims data from third-party payers can increase the accuracy and validity of the CCPD.

10 Background: Cost of breast cancer survivor surveillance, of survivorship care and of variation in care practices are unknown. Furthermore, it is not known whether intense surveillance care adds value. We developed a method to measure the cost of surveillance to account for varying follow-up duration [cost of care per day (CCPD)], and explored the impact of surveillance cost on survival. Methods: We queried the Oncoshare database {Kurian et al Cancer 2014}, which amalgamates data from Stanford Health Care’s (SHC) electronic health record (EHR) (imaging, infused drugs, inpatient and outpatient facility and professional services), from the California Cancer Registry, and the Social Security Death Index. We included breast cancer patients diagnosed 2000-2014, Stages 0-III who had surgery, chemotherapy or radiation treatment at SHC, and who had more than two visits at SHC within 3 years of their treatment completion. We tallied Common Procedural Terminology (CPT©) codes assigned to each service, and mapped each CPT code to the corresponding code and date in the CMS Medicare fee schedule. For patients with breast cancer relapse, we explored the post-relapse survival of the costliest 20% compared with the other patients. Results: CCPD was $2.45 for care delivered at SHC. Among the three breast cancer subtypes (luminal, Her-2 over-expressed and triple negative) there was no difference in cost. Among patients who relapsed, those in the most expensive 20% CCPD had significantly shorter survival than other patients. The high-cost patients had more co-morbidity [cerebrovascular disease (4% for low cost vs 7% for high), chronic pulmonary disease (5% vs 10%), CHF (2% vs 7%), diabetes (4% vs 7%), liver disease (4% vs 9%)]. Conclusions: Cost of care per day (CCPD) is a useful metric to assess value of surveillance and survivorship care, and is also applicable to initial treatment and post-relapse care, to identify “positive deviants” ( those who have developed best practices) in high value care delivery. We captured only costs for treatment at SHC, and merging our data with claims data from 3rd party carriers could increase the accuracy and validity of the CCPD. We identified a model for further testing to reduce total spending for high-quality oncology care.

INTRODUCTION Autoimmune hemolytic anemia (AIHA) is a rare autoimmune disorder in which auto-antibodies target red blood cell surface antigens, causing hemolysis. The incidence is estimated to be 0.8 per 100,000 (Lechner and Jager, Blood 2010). Depending on the temperature at which the auto-antibodies are most active, AIHA is classified as warm, cold, or mixed. Main risk factors include malignancy, viral infection, and rheumatologic disorders. Thromboembolism is an important complication of AIHA that has received increasing attention in case series and small observational reports. However, there has not yet been a study that compares the risk of thromboembolism in AIHA with that of matched, non-AIHA patients in a longitudinal fashion. OBJECTIVES 1) To assess the risk of arterial and venous thromboembolism in AIHA patients using a longitudinal, retrospective cohort study. 2) To define the contribution from usual thrombosis risk factors (defined in Methods section) in the development of thromboembolism in AIHA patients. METHODS We derived our cohorts from Stanford University's Standards-Based Translational Research Informatics Platform (STRIDE). The STRIDE database houses records since 2003 for over 2.1 million patients who receive their care at Stanford Hospital and Clinics. We identified 156 patients diagnosed with AIHA of any type and matched them with 312 non-AIHA patients (control) in a 1:2 ratio. To achieve stringent matching, patients in the control group were selected to have known risk factors for AIHA--malignancy, viral infections, and rheumatologic diseases--without developing AIHA itself. We assessed the incidence of arterial and venous thromboembolism in the AIHA and non-AIHA groups. Within each group, we assessed the association between thromboembolism and the presence of thrombosis risk factors, which we based on the PADUA criteria (Barbar et al, J Throm Haemost 2010). The PADUA risk factors comprise a weighted sum known as the PADUA score (max score of 20), and we compared the median PADUA score between AIHA and non-AIHA patients with thromboembolism using the Mann-Whitney rank sum test. Interquartile ranges (IQR) of PADUA scores were calculated. Finally, using inverse-probability weighting to achieve matching thromboembolism propensity scores between AIHA and non-AIHA patients, we derived an odds ratio for the development of thromboembolism given a diagnosis of AIHA. RESULTS A significantly higher proportion of AIHA patients developed arterial and venous thromboembolism than non-AIHA patients (29% vs. 19%, respectively; p < 0.05). Notably, the median PADUA score was not different between AIHA and non-AIHA patients with thromboembolism (4, IQR [2-7] vs 4.5, IQR [3-7], respectively, n.s.), despite the aforementioned difference in thromboembolism incidence. However, the distribution of PADUA risk factors in each group did differ: malignancy was seen in a smaller proportion of AIHA patients with thromboembolism than in non-AIHA counterparts (31% vs 57%, respectively; p < 0.05), while acute infection and/or rheumatologic disorders was seen in a larger proportion of AIHA patients with thromboembolism than non-AIHA counterparts (53% vs 25%, respectively; p < 0.05; see Table 1). After additional analysis to ensure propensity score matching, we found that AIHA confers an odds ratio of 2.44 (95% CI [1.16-5.10], p < 0.05) for the development of thromboembolism. CONCLUSION Different thrombosis risk factors contribute to the development of thromboembolism in AIHA patients than in non-AIHA patients. However, AIHA patients carry a significantly higher risk of thromboembolism than non-AIHA patients, and this risk is not attributable to the usual thrombosis risk factors considered in the PADUA criteria. Our finding suggests a need for clinical trials to study the role of thrombo-prevention in AIHA patients. Table 1 Percentage of PADUA risk factors in AIHA and non-AIHA patients with thromboembolism. Table 1. Percentage of PADUA risk factors in AIHA and non-AIHA patients with thromboembolism. Disclosures Chen: True North Therapeutics: Research Funding. Loftus:True North Therapeutics: Research Funding. Weber:True North Therapeutics: Research Funding. Hoang:True North Therapeutics: Research Funding. Gilbert:True North Therapeutics: Employment. Kummar:True North Therapeutics: Research Funding.

Gas turbine engine compressor increases the pressure and temperature of the air stream through it before entering the combustion chamber. Due to the extreme in rotational speed and high temperature, the gas turbine engine compressor is subjected to a complex force system that causes different failures mode in the compressor disc. Therefore, the design and calculation of compressor discs always consist of very high requirements with the problem of reducing the volume and increasing the durability of the disc structure. This paper presents a computational method that optimizes the design of a compressor disc geometry that meets performance and durability parameters but has the lowest mass based on finite element method. The calculation program is implemented by software Abaqus 6.13, algorithms and analysis results are processed through the Python 3 programming language. A post-publication change was made to this article on 11 Jun 2020 to correct the pdf so that it matched the webpage.