American Society for Blood and Marrow Transplantation Pharmacy Special Interest Group Survey on Chimeric Antigen Receptor T Cell Therapy Administrative, Logistic, and Toxicity Management Practices in the United States.

Administration of immune effector cell (IEC) therapy is a complex endeavor requiring extensive coordination and communication of various healthcare and administrative teams. Chimeric antigen receptor (CAR) T cells are the most established IEC therapy available. As of July 2018 two commercial gene therapy products, tisagenlecleucel and axicabtagene ciloleucel, have been approved by the US Food and Drug Administration. To gain insight into the infrastructure and practices across the country, the American Society for Blood and Marrow Transplantation Pharmacy Special Interest Group conducted an electronic survey on the current administrative, logistic, and toxicity management practices of CAR T cell therapy across the United States. This survey consists of 52 responses from institutions of varying sizes, most of which (∼80%) had previous investigational experience with CAR T cell therapy. Absorbing the energy of this exciting new treatment has challenged hematopoietic cell transplant programs across the country to strengthen department infrastructure, develop new committees and policies, and implement significant education to ensure safe administration. With the variety of experience with CAR T cell therapy, we hope this survey can contribute to the existing published literature and provide support and consensus to established and developing IEC programs and practice guidelines.

Harmonization of Busulfan Plasma Exposure Unit (BPEU): A Community-Initiated Consensus Statement.

Busulfan therapeutic drug monitoring (TDM) is often used to achieve target plasma exposures. Variability in busulfan plasma exposure units (BPEU) is a potential source for misinterpretation of publications and protocols and is a barrier to data capture by hematopoietic cell transplantation (HCT) registry databases. We sought to harmonize to a single BPEU for international use. Using Delphi consensus methodology, iterative surveys were sent to an increasing number of relevant clinical stakeholders. In survey 1, 14 stakeholders were asked to identify ideal properties of a BPEU. In survey 2, 52 stakeholders were asked (1) to evaluate BPEU candidates according to ideal BPEU properties established by survey 1 and local position statements for TDM and (2) to identify potential facilitators and barriers to adoption of the harmonized BPEU. The most frequently used BPEU identified, in descending order, were area under the curve (AUC) in µM × min, AUC in mg × h/L, concentration at steady state (Css) in ng/mL, AUC in µM × h, and AUC in µg × h/L. All respondents conceptually agreed on the ideal properties of a BPEU and to adopt a harmonized BPEU. Respondents were equally divided between selecting AUC in µM × min versus mg × h/L for harmonization. AUC in mg × h/L was finally selected as the harmonized BPEU, because it satisfied most of the survey-determined ideal properties for the harmonized BPEU and is read easily understood in the clinical practice environment. Furthermore, 10 major professional societies have endorsed AUC in mg × h/L as the harmonized unit for reporting to HCT registry databases and for use in future protocols and publications.

Sex Differences in the Rate, Timing, and Principal Diagnoses of 30-Day Readmissions in Younger Patients with Acute Myocardial Infarction.

BACKGROUND: Young women (<65 years) experience a 2- to 3-fold greater mortality risk than younger men after an acute myocardial infarction. However, it is unknown whether they are at higher risk for 30-day readmission, and if this association varies by age. We examined sex differences in the rate, timing, and principal diagnoses of 30-day readmissions, including the independent effect of sex following adjustment for confounders. METHODS AND RESULTS: We included patients aged 18 to 64 years with a principal diagnosis of acute myocardial infarction. Data were used from the Healthcare Cost and Utilization Project-State Inpatient Database for California (07-09). Readmission diagnoses were categorized by using an aggregated version of the Centers for Medicare and Medicaid Services' Condition Categories, and readmission timing was determined from the day after discharge. Of 42,518 younger patients with acute myocardial infarction (26.4% female), 4775 (11.2%) had at least 1 readmission. The 30-day all-cause readmission rate was higher for women (15.5% versus 9.7%, P<0.0001). For both sexes, readmission risk was highest on days 2 to 4 after discharge and declined thereafter, and women were more likely to present with noncardiac diagnoses (44.4% versus 40.6%, P=0.01). Female sex was associated with a higher rate of 30-day readmission, which persisted after adjustment (hazard ratio, 1.22; 95% confidence interval, 1.15-1.30). There was no significant interaction between age and sex on readmission. CONCLUSIONS: In comparison with men, younger women have a higher risk for readmission, even after the adjustment for confounders. The timing of 30-day readmission was similar in women and men, and both sexes were susceptible to a wide range of causes for readmission.

National trends in heart failure hospitalization after acute myocardial infarction for Medicare beneficiaries: 1998-2010.

BACKGROUND: Previous studies have reported conflicting findings regarding how the incidence of heart failure (HF) after acute myocardial infarction (AMI) has changed over time, and data on contemporary national trends are sparse. METHODS AND RESULTS: Using a complete national sample of 2 789 943 AMI hospitalizations of Medicare fee-for-service beneficiaries from 1998 through 2010, we evaluated annual changes in the incidence of subsequent HF hospitalization and mortality using Poisson and survival analysis models. The number of patients hospitalized for HF within 1 year after AMI declined modestly from 16.1 per 100 person-years in 1998 to 14.2 per 100 person years in 2010 (P<0.001). After adjusting for demographic factors, a relative 14.6% decline for HF hospitalizations after AMI was observed over the study period (incidence risk ratio, 0.854; 95% confidence interval, 0.809-0.901). Unadjusted 1-year mortality following HF hospitalization after AMI was 44.4% in 1998, which decreased to 43.2% in 2004 to 2005, but then increased to 45.5% by 2010. After adjusting for demographic factors and clinical comorbidities, this represented a 2.4% relative annual decline (hazard ratio, 0.976; 95% confidence interval, 0.974-0.978) from 1998 to 2007, but a 5.1% relative annual increase from 2007 to 2010 (hazard ratio, 1.051; 95% confidence interval, 1.039-1.064). CONCLUSIONS: In a national sample of Medicare beneficiaries, HF hospitalization after AMI decreased from 1998 to 2010, which may indicate improvements in the management of AMI. In contrast, survival after HF following AMI remains poor, and has worsened from 2007 to 2010, demonstrating that challenges still remain for the treatment of this high-risk condition after AMI.

Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.

BACKGROUND: Patients aged ≥ 65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18-64 years with patients aged ≥ 65 years. METHODS AND FINDINGS: We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n=206,141), AMI (n=107,256), and pneumonia (n=199,620) from 2007-2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18-64 years exceeded the readmission rate in patients aged ≥ 65 years in the HF cohort (23.4% vs. 22.0%, p<0.001), but was lower in the AMI (11.2% vs. 17.5%, p<0.001) and pneumonia (14.4% vs. 17.3%, p<0.001) cohorts. When adjusted for sex, race, comorbidities, and payer status, the 30-day readmission risk in patients aged 18-64 years was similar to patients ≥ 65 years in the HF (HR 0.99; 95%CI 0.97-1.02) and pneumonia (HR 0.97; 95%CI 0.94-1.01) cohorts and was marginally lower in the AMI cohort (HR 0.92; 95%CI 0.87-0.96). For all cohorts, the timing of readmission was similar; readmission risks were highest between days 2 and 5 and declined thereafter across all age groups. Diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions among age groups <65 years; a non-cardiac diagnosis represented 39-44% of readmissions in the HF cohort and 37-45% of readmissions in the AMI cohort, while a non-pulmonary diagnosis represented 61-64% of patients in the pneumonia cohort. CONCLUSION: When adjusted for differences in patient characteristics, young and middle-aged adults have 30-day readmission rates that are similar to elderly patients for HF, AMI, and pneumonia. A generalized risk after hospitalization is present regardless of age. Please see later in the article for the Editors' Summary.

Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia.

IMPORTANCE: To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race. OBJECTIVE: To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia. DESIGN, SETTING, AND PATIENTS: We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge. MAIN OUTCOME MEASURES: We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing. RESULTS: From 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race. CONCLUSION AND RELEVANCE: Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.

Comparative effectiveness of first-line nab-paclitaxel versus paclitaxel monotherapy in triple-negative breast cancer.

Aim: This observational study evaluated the effectiveness of nab-paclitaxel versus paclitaxel monotherapy as first-line (1L) treatment for metastatic triple-negative breast cancer (mTNBC). Materials & methods: 200 patients from the US Flatiron Health electronic health record-derived database (mTNBC diagnosis, January 2011-October 2016) who received 1L nab-paclitaxel (n = 105) or paclitaxel (n = 95) monotherapy were included. Overall survival and time to next treatment were evaluated. Results: The adjusted overall survival hazard ratio was 0.98 (95% CI: 0.67-1.44), indicating a similar risk of death between groups. Adjusted time to next treatment hazard ratio was 0.89 (95% confidence interval: 0.62-1.29). Conclusion: Nab-paclitaxel and paclitaxel monotherapy showed similar efficacy, suggesting their interchangeability as 1L treatments for mTNBC.

Variation in and Hospital Characteristics Associated With the Value of Care for Medicare Beneficiaries With Acute Myocardial Infarction, Heart Failure, and Pneumonia.

Importance: Payers and policy makers have advocated for transitioning toward value-based payment models. However, little is known about what is the extent of hospital variation in the value of care and whether there are any hospital characteristics associated with high-value care. Objectives: To investigate the association between hospital-level 30-day risk-standardized mortality rates (RSMRs) and 30-day risk-standardized payments (RSPs) for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PNA); to characterize patterns of value in care; and to identify hospital characteristics associated with high-value care (defined by having lower than median RSMRs and RSPs). Design, Setting, and Participants: This national cross-sectional study applied weighted linear correlation to investigate the association between hospital RSMRs and RSPs for AMI, HF, and PNA between July 1, 2011, and June 30, 2014, among all hospitals; examined correlations in subgroups of hospitals based on key characteristics; and assessed the proportion and characteristics of hospitals delivering high-value care. The data analysis was completed in October 2017. The setting was acute care hospitals. Participants were Medicare fee-for-service beneficiaries discharged with AMI, HF, or PNA. Main Outcomes and Measures: Hospital-level 30-day RSMRs and RSPs for AMI, HF, and PNA. Results: The AMI sample consisted of 4339 hospitals with 487 141 hospitalizations for mortality and 462 905 hospitalizations for payment. The HF sample included 4641 hospitals with 960 960 hospitalizations for mortality and 903 721 hospitalizations for payment. The PNA sample contained 4685 hospitals with 952 022 hospitalizations for mortality and 901 764 hospitalizations for payment. The median (interquartile range [IQR]) RSMRs and RSPs, respectively, was 14.3% (IQR, 13.8%-14.8%) and $21 620 (IQR, $20 966-$22 567) for AMI, 11.7% (IQR, 11.0%-12.5%) and $15 139 (IQR, $14 310-$16 118) for HF, and 11.5% (IQR, 10.6%-12.6%) and $14 220 (IQR, $13 342-$15 097) for PNA. There were statistically significant but weak inverse correlations between the RSMRs and RSPs of -0.08 (95% CI, -0.11 to -0.05) for AMI, -0.21 (95% CI, -0.24 to -0.18) for HF, and -0.07 (95% CI, -0.09 to -0.04) for PNA. The largest shared variance between the RSMRs and RSPs was only 4.4% (for HF). The correlations between the RSMRs and RSPs did not differ significantly across teaching status, safety-net status, urban/rural status, or the proportion of patients with low socioeconomic status. Approximately 1 in 4 hospitals (20.9% for AMI, 23.0% for HF, and 23.9% for PNA) had both lower than median RSMRs and RSPs. Conclusions and Relevance: These findings suggest that there is significant potential for improvement in the value of AMI, HF, and PNA care and also suggest that high-value care for these conditions is attainable across most hospital types.

Sex Differences in Trajectories of Risk After Rehospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia.

BACKGROUND: Women have an increased risk of rehospitalization in the immediate postdischarge period; however, few studies have determined how readmission risk dynamically changes on a day-to-day basis over the full year after hospitalization by sex and how these differences compare with the risk for mortality. METHODS AND RESULTS: We identified >3 000 000 hospitalizations of patients with a principal discharge diagnosis of heart failure, acute myocardial infarction, or pneumonia and estimated sex differences in the daily risk of rehospitalization/death 1 year after discharge from a population of Medicare fee-for-service beneficiaries aged 65 years and older. We calculated the (1) time required for adjusted rehospitalization/mortality risks to decline 50% from maximum values after discharge, (2) time required for the adjusted readmission risk to approach plateau periods of minimal day-to-day change, and (3) extent to which adjusted risks are greater among recently hospitalized patients versus Medicare patients. We identified 1 392 289, 530 771, and 1 125 231 hospitalizations for heart failure, acute myocardial infarction, and pneumonia, respectively. The adjusted daily risk of rehospitalization varied by admitting condition (hazard rate ratio for women versus men, 1.10 for acute myocardial infarction; hazard rate ratio, 1.04 for heart failure; and hazard rate ratio, 0.98 for pneumonia). However, for all conditions, the adjusted daily risk of death was higher among men versus women (hazard rate ratio women versus with men, <1). For both sexes, there was a similar timing of peak daily risk, half daily risk, and reaching plateau. CONCLUSIONS: Although the association of sex with daily risk of rehospitalization varies across conditions, women are at highest risk after discharge for acute myocardial infarction. Future studies should focus on understanding the determinants of sex differences in rehospitalization risk among conditions.

Relationship Between Age and Trajectories of Rehospitalization Risk in Older Adults.

OBJECTIVES: To characterize the magnitude and duration of risk of rehospitalization according to age after hospitalization for heart failure (HF), acute myocardial infarction (AMI), or pneumonia. DESIGN: Retrospective cohort study. SETTING: U.S. hospitals (n = 4,767). PARTICIPANTS: All Medicare fee-for-service beneficiaries aged 65 and older surviving hospitalization for HF, AMI, or pneumonia between October 2012 and December 2013. MEASUREMENTS: Daily risk of first rehospitalization for 1 year after hospital discharge was calculated according to age category (65-74, 75-84, ≥85) after adjustment for sex, race, comorbidities, and median ZIP code income. Time required for adjusted rehospitalization risk to decline 50% from maximum value after discharge, time required for adjusted risk to approach a plateau period of minimal day-to-day change, and degree to which adjusted risk was higher in recently hospitalized individuals than in the general elderly population were identified. RESULTS: There were 414,720 hospitalizations for HF, 177,752 for AMI, and 568,304 for pneumonia. The adjusted risk of rehospitalization declined with increasing age after HF hospitalization (P < .001), rose with increasing age after AMI hospitalization (P < .001), and was slightly lower with increasing age after pneumonia hospitalization (P = .002). Adjusted risks of rehospitalization were high beyond 30 days after hospitalization for all ages. CONCLUSION: Although older age has heterogeneous relationships with rehospitalization risk, risk of readmission remains high for an extended time after discharge regardless of age or admitting condition. Condition-specific data on risk can be used to guide discussions on advanced care planning and strategies for longitudinal follow-up after hospitalization.

Describing the performance of U.S. hospitals by applying big data analytics.

Public reporting of measures of hospital performance is an important component of quality improvement efforts in many countries. However, it can be challenging to provide an overall characterization of hospital performance because there are many measures of quality. In the United States, the Centers for Medicare and Medicaid Services reports over 100 measures that describe various domains of hospital quality, such as outcomes, the patient experience and whether established processes of care are followed. Although individual quality measures provide important insight, it is challenging to understand hospital performance as characterized by multiple quality measures. Accordingly, we developed a novel approach for characterizing hospital performance that highlights the similarities and differences between hospitals and identifies common patterns of hospital performance. Specifically, we built a semi-supervised machine learning algorithm and applied it to the publicly-available quality measures for 1,614 U.S. hospitals to graphically and quantitatively characterize hospital performance. In the resulting visualization, the varying density of hospitals demonstrates that there are key clusters of hospitals that share specific performance profiles, while there are other performance profiles that are rare. Several popular hospital rating systems aggregate some of the quality measures included in our study to produce a composite score; however, hospitals that were top-ranked by such systems were scattered across our visualization, indicating that these top-ranked hospitals actually excel in many different ways. Our application of a novel graph analytics method to data describing U.S. hospitals revealed nuanced differences in performance that are obscured in existing hospital rating systems.

Trajectories of Risk for Specific Readmission Diagnoses after Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia.

BACKGROUND: The risk of rehospitalization is elevated in the immediate post-discharge period and declines over time. It is not known if the extent and timing of risk vary across readmission diagnoses, suggesting that recovery and vulnerability after discharge differ by physiologic system. OBJECTIVE: We compared risk trajectories for major readmission diagnoses in the year after discharge among all Medicare fee-for-service beneficiaries hospitalized with heart failure (HF), acute myocardial infarction (AMI), or pneumonia from 2008-2010. METHODS: We estimated the daily risk of rehospitalization for 12 major readmission diagnostic categories after accounting for the competing risk of death after discharge. For each diagnostic category, we identified (1) the time required for readmission risk to peak and then decline 50% from maximum values after discharge; (2) the time required for readmission risk to approach plateau periods of minimal day-to-day change; and (3) the extent to which hospitalization risks are higher among patients recently discharged from the hospital compared with the general elderly population. RESULTS: Among >3,000,000 hospitalizations, the yearly rate of rehospitalization was 67.0%, 49.5%, and 55.3% after hospitalization for HF, AMI, and pneumonia, respectively. The extent and timing of risk varied by readmission diagnosis and initial admitting condition. Risk of readmission for gastrointestinal bleeding/anemia peaked particularly late after hospital discharge, occurring 10, 6, and 7 days after hospitalization for HF, AMI, and pneumonia, respectively. Risk of readmission for trauma/injury declined particularly slowly, requiring 38, 20, and 38 days to decline by 50% after hospitalization for HF, AMI, and pneumonia, respectively. CONCLUSIONS: Patterns of vulnerability to different conditions that cause rehospitalization vary by time after hospital discharge. This finding suggests that recovery of various physiologic systems occurs at different rates and that post-discharge interventions to minimize vulnerability to specific conditions should be tailored to their underlying risks.

Trajectories of risk after hospitalization for heart failure, acute myocardial infarction, or pneumonia: retrospective cohort study.

OBJECTIVE: To characterize the absolute risks for older patients of readmission to hospital and death in the year after hospitalization for heart failure, acute myocardial infarction, or pneumonia. DESIGN: Retrospective cohort study. SETTING: 4767 hospitals caring for Medicare fee for service beneficiaries in the United States, 2008-10. PARTICIPANTS: More than 3 million Medicare fee for service beneficiaries, aged 65 years or more, surviving hospitalization for heart failure, acute myocardial infarction, or pneumonia. MAIN OUTCOME MEASURES: Daily absolute risks of first readmission to hospital and death for one year after discharge. To illustrate risk trajectories, we identified the time required for risks of readmission to hospital and death to decline 50% from maximum values after discharge; the time required for risks to approach plateau periods of minimal day to day change, defined as 95% reductions in daily changes in risk from maximum daily declines after discharge; and the extent to which risks are higher among patients recently discharged from hospital compared with the general elderly population. RESULTS: Within one year of hospital discharge, readmission to hospital and death, respectively, occurred following 67.4% and 35.8% of hospitalizations for heart failure, 49.9% and 25.1% for acute myocardial infarction, and 55.6% and 31.1% for pneumonia. Risk of first readmission had declined 50% by day 38 after hospitalization for heart failure, day 13 after hospitalization for acute myocardial infarction, and day 25 after hospitalization for pneumonia; risk of death declined 50% by day 11, 6, and 10, respectively. Daily change in risk of first readmission to hospital declined 95% by day 45, 38, and 45; daily change in risk of death declined 95% by day 21, 19, and 21. After hospitalization for heart failure, acute myocardial infarction, or pneumonia, the magnitude of the relative risk for hospital admission over the first 90 days was 8, 6, and 6 times greater than that of the general older population; the relative risk of death was 11, 8, and 10 times greater. CONCLUSIONS: Risk declines slowly for older patients after hospitalization for heart failure, acute myocardial infarction, or pneumonia and is increased for months. Specific risk trajectories vary by discharge diagnosis and outcome. Patients should remain vigilant for deterioration in health for an extended time after discharge. Health providers can use knowledge of absolute risks and their changes over time to better align interventions designed to reduce adverse outcomes after discharge with the highest risk periods for patients.

Geranylgeranylacetone blocks doxorubicin-induced cardiac toxicity and reduces cancer cell growth and invasion through RHO pathway inhibition.

Doxorubicin is a widely used chemotherapy for solid tumors and hematologic malignancies, but its use is limited due to cardiotoxicity. Geranylgeranylacetone (GGA), an antiulcer agent used in Japan for 30 years, has no significant adverse effects, and unexpectedly reduces ovarian cancer progression in mice. Because GGA reduces oxidative stress in brain and heart, we hypothesized that GGA would prevent oxidative stress of doxorubicin cardiac toxicity and improve doxorubicin's chemotherapeutic effects. Nude mice implanted with MDA-MB-231 breast cancer cells were studied after chronic treatment with doxorubicin, doxorubicin/GGA, GGA, or saline. Transthoracic echocardiography was used to monitor systolic heart function and xenografts evaluated. Mice were euthanized and cardiac tissue evaluated for reactive oxygen species generation, TUNEL assay, and RHO/ROCK pathway analysis. Tumor metastases were evaluated in lung sections. In vitro studies using Boyden chambers were performed to evaluate GGA effects on RHO pathway activator lysophosphatidic acid (LPA)-induced motility and invasion. We found that GGA reduced doxorubicin cardiac toxicity, preserved cardiac function, prevented TUNEL-positive cardiac cell death, and reduced doxorubicin-induced oxidant production in a nitric oxide synthase-dependent and independent manner. GGA also reduced heart doxorubicin-induced ROCK1 cleavage. Remarkably, in xenograft-implanted mice, combined GGA/doxorubicin treatment decreased tumor growth more effectively than doxorubicin treatment alone. As evidence of antitumor effect, GGA inhibited LPA-induced motility and invasion by MDA-MB-231 cells. These anti-invasive effects of GGA were suppressed by geranylgeraniol suggesting GGA inhibits RHO pathway through blocking geranylation. Thus, GGA protects the heart from doxorubicin chemotherapy-induced injury and improves anticancer efficacy of doxorubicin in breast cancer.

Hospital readmission performance and patterns of readmission: retrospective cohort study of Medicare admissions.

OBJECTIVES: To determine whether high performing hospitals with low 30 day risk standardized readmission rates have a lower proportion of readmissions from specific diagnoses and time periods after admission or instead have a similar distribution of readmission diagnoses and timing to lower performing institutions. DESIGN: Retrospective cohort study. SETTING: Medicare beneficiaries in the United States. PARTICIPANTS: Patients aged 65 and older who were readmitted within 30 days after hospital admission for heart failure, acute myocardial infarction, or pneumonia in 2007-09. MAIN OUTCOME MEASURES: Readmission diagnoses were classified with a modified version of the Centers for Medicare and Medicaid Services' condition categories, and readmission timing was classified by day (0-30) after hospital discharge. Hospital 30 day risk standardized readmission rates over the three years of study were calculated with public reporting methods of the US federal government, and hospitals were categorized with bootstrap analysis as having high, average, or low readmission performance for each index condition. High and low performing hospitals had ≥ 95% probability of having an interval estimate respectively less than or greater than the national 30 day readmission rate over the three year period of study. All remaining hospitals were considered average performers. RESULTS: For readmissions in the 30 days after the index admission, there were 320,003 after 1,291,211 admissions for heart failure (4041 hospitals), 102,536 after 517,827 admissions for acute myocardial infarction (2378 hospitals), and 208,438 after 1,135,932 admissions for pneumonia (4283 hospitals). The distribution of readmissions by diagnosis was similar across categories of hospital performance for all three conditions. High performing hospitals had fewer readmissions for all common diagnoses. Median time to readmission was similar by hospital performance for heart failure and acute myocardial infarction, though was 1.4 days longer among high versus low performing hospitals for pneumonia (P<0.001). Findings were unchanged after adjustment for other hospital characteristics potentially associated with readmission patterns. CONCLUSIONS: High performing hospitals have proportionately fewer 30 day readmissions without differences in readmission diagnoses and timing, suggesting the possible benefit of strategies that lower risk of readmission globally rather than for specific diagnoses or time periods after hospital stay.

A pilot study of website information regarding aromatase inhibitors: dietary supplement interactions.

OBJECTIVES: Patients who have hormone receptor-positive breast cancer and who are taking aromatase inhibitors (AIs) should understand the benefits and risks of concomitant dietary supplement (DS) use. The International Society for Integrative Oncology (SIO) encourages patients to discuss DS use with their health care practitioners. The objective was to conduct a pilot study rating Internet websites from the perspective of health care practitioners for information about AI-DS interactions. DESIGN: Five (5) Internet websites suggested by SIO were evaluated using the DISCERN instrument rating tool. The available AI-DS information on these websites was rated by 4 evaluators: 2 naturopathic doctors, 1 oncology pharmacy resident, and a pharmacy student. RESULTS: The overall rankings ranged from 1.6 to 3.9, with considerable variability in the type of information available from the websites. The interevaluator rankings of the websites ranged from 0.44 to 0.89. The evaluators consistently found the most reliable, unbiased, and comprehensive information on AI-DS interactions at the Natural Medicines Comprehensive Database and Memorial Sloan-Kettering Cancer Center websites. However, more than one database was needed for provision of optimal patient information on AI-DS interactions. CONCLUSIONS: In order to effectively advise patients regarding AI-DS interactions, more than one website should be evaluated to assess the potential efficacy and safety of DS in women whose breast cancer is being treated with an AI.