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AimsCONCERT-HF is an NHLBI-sponsored, double-blind, placebo-controlled, Phase II trial designed to determine whether treatment with autologous bone marrow-derived mesenchymal stromal cells (MSCs) and c-kit positive cardiac cells (CPCs), given alone or in combination, is feasible, safe, and beneficial in patients with heart failure (HF) caused by ischaemic cardiomyopathy.Methods and resultsPatients were randomized (1:1:1:1) to transendocardial injection of MSCs combined with CPCs, MSCs alone, CPCs alone, or placebo, and followed for 12 months. Seven centres enrolled 125 participants with left ventricular ejection fraction of 28.6 ± 6.1% and scar size 19.4 ± 5.8%, in New York Heart Association class II or III. The proportion of major adverse cardiac events (MACE) was significantly decreased by CPCs alone (-22% vs. placebo, P = 0.043). Quality of life (Minnesota Living with Heart Failure Questionnaire score) was significantly improved by MSCs alone (P = 0.050) and MSCs + CPCs (P = 0.023) vs. placebo. Left ventricular ejection fraction, left ventricular volumes, scar size, 6-min walking distance, and peak oxygen consumption did not differ significantly among groups.ConclusionsThis is the first multicentre trial assessing CPCs and a combination of two cell types from different tissues in HF patients. The results show that treatment is safe and feasible. Even with maximal guideline-directed therapy, both CPCs and MSCs were associated with improved clinical outcomes (MACE and quality of life, respectively) in ischaemic HF without affecting left ventricular function or structure, suggesting possible systemic or paracrine cellular mechanisms. Combining MSCs with CPCs was associated with improvement in both these outcomes. These results suggest potential important beneficial effects of CPCs and MSCs and support further investigation in HF patients.

BackgroundAnthracycline-induced cardiomyopathy (AIC) may be irreversible with a poor prognosis, disproportionately affecting women and young adults. Administration of allogeneic bone marrow-derived mesenchymal stromal cells (allo-MSCs) is a promising approach to heart failure (HF) treatment.ObjectivesSENECA (Stem Cell Injection in Cancer Survivors) was a phase 1 study of allo-MSCs in AIC.MethodsCancer survivors with chronic AIC (mean age 56.6 years; 68% women; NT-proBNP 1,426 pg/ml; 6 enrolled in an open-label, lead-in phase and 31 subjects randomized 1:1) received 1 × 108 allo-MSCs or vehicle transendocardially. Primary objectives were safety and feasibility. Secondary efficacy measures included cardiac function and structure measured by cardiac magnetic resonance imaging (CMR), functional capacity, quality of life (Minnesota Living with Heart Failure Questionnaire), and biomarkers.ResultsA total of 97% of subjects underwent successful study product injections; all allo-MSC-assigned subjects received the target dose of cells. Follow-up visits were well-attended (92%) with successful collection of endpoints in 94% at the 1-year visit. Although 58% of subjects had non-CMR compatible devices, CMR endpoints were successfully collected in 84% of subjects imaged at 1 year. No new tumors were reported. There were no significant differences between allo-MSC and vehicle groups with regard to clinical outcomes. Secondary measures included 6-min walk test (p = 0.056) and Minnesota Living with Heart Failure Questionnaire score (p = 0.048), which tended to favor the allo-MSC group.ConclusionsIn this first-in-human study of cell therapy in patients with AIC, transendocardial administration of allo-MSCs appears safe and feasible, and CMR was successfully performed in the majority of the HF patients with devices. This study lays the groundwork for phase 2 trials aimed at assessing efficacy of cell therapy in patients with AIC.

In this article, using conditional power, we extended the widely used classical Brownian motion (Bm) technique for monitoring clinical trial data to a larger class of stochastic processes fractional Brownian motion (fBm) with drift, and compare these results. We applied a Bayesian method to estimate parameters. The simulation study is presented as an example to illustrate scenarios under classical and fractional Brownian motion. We demonstrated the drift fractional Brownian motion in sequential monitoring of clinical trials and provided a formula for calculating conditional power under an alternative hypothesis for interim analysis. We investigated cases commonly used in clinical trials, with the Hurst parameter H = 0.5 and H > 0.5, respectively. Our simulation study suggests that the conditional power under the fBm assumption is generally higher than that under the Bm assumption when H > 0.5 and also matches better with our empirical results. [ABSTRACT FROM AUTHOR]

After the first large scale national sampling survey on handicapped persons in 1987, China conducted its second national sampling survey in 2006. Using the data from these two surveys and the national life tables, we computed and compared the expected years of life free of handicapped condition by the Sullivan method. The expected years of life lived with handicap for the Chinese population increased from 4.87 years for males and 5.81 years for females in 1987 to 5.55 years and 6.32 years in 2006, respectively. The same trend was observed for people in working ages (15-64) and old ages (65+). However, the expected years of life lived with handicap decreased for children (0-14). Our results also showed that the effect of skeletal handicap increased notably for both sexes. Healthy life expectancy is an important indicator in measuring quality of life of a population. Our study utilized this measurement to quantify one aspect of quality of life of the Chinese population.

In this article, we report statistical properties of two classes of generalized Gini coefficients (G1 and G2). The theoretical results were assessed via Monte Carlo simulations. Further, we used G1 and G2 on life expectancy to measure health inequalities among the provinces of China and the states of the United States. For China, the results indicated that there was statistically significant health inequality by both G1 and G2. However, for the US, the results showed that there was significant health inequality by G1 but no statistical significance was found in health inequality by G2. Overall, from our study, China has higher health inequality than the United States.

Utilizing data from the Census of India, this study compared child sex ratio in rural and urban regions of India and analyzed whether the child sex ratio was associated with mother's education level. The child sex ratios in the rural and urban regions throughout India were analyzed using the two-sample and paired Student's t-test. Further, the Chi-square test for trend in binomial proportions was used to assess the association between child sex ratios and mother's education levels in rural and urban areas. Analysis of the data showed that there was a significant difference between the child sex ratios in rural areas versus urban areas. In addition, the Chi-square test for trend showed that there was a significant association of the child sex ratio and the educational levels of their mothers. This trend occurred in both rural and urban areas.

Based on the recent three population censuses of China, in this article, we used life table technique to compute the expected years of working life for the Chinese labor force in the primary, secondary and tertiary industries in 1982, 1990 and 2000. We found, after two decades of economic reform, the expected years of working life in the primary industry decreased from 32.04 and 26.74 years for males and females in 1982 to 27.07 and 26.12 years, respectively, in 2000. For the tertiary industry, the expected years of working life increased from 5.70 and 2.94 years for males and females in 1982 to 8.05 and 5.66 years in 2000, respectively. For the secondary industry, there was virtually no change in terms of the expected years of working life.

It remains unclear when the fetus is most susceptible to the effects of particulate air pollution. We conducted a population-based study in a large urban area to evaluate associations between preterm birth (PTB) and fetal growth and exposures to fine particles ([PM.sub.2.5]) during narrow periods of gestation. We identified 177,816 births during 2005-2007 among mothers who resided in Harris County, Texas at the time of delivery. We created three mutually exclusive categories of mildly (33-36 completed weeks of gestation), moderately (29-32 weeks of gestation), and severely (20-28 weeks of gestation) PTB, and among full term infants, we identified those who were born small for their gestational age. Using routine air monitoring data, we generated county-level daily time series of estimated ambient air levels of [PM.sub.2.5] and then computed exposure metrics during every 4 weeks of a mother's pregnancy. We evaluated associations in each 4-week period using multiple logistic regression. A 10 µg/[m.sup.3] increase in [PM.sub.2.5] exposure in the first 4 weeks of pregnancy significantly increased the odds of mildly, moderately and severely PTB by 16, 71 and 73 %, respectively. Associations were stronger when infants with birth defects were excluded. Our findings indicate an association between [PM.sub.2.5] and PTB, with stronger associations for moderately and severely PTB infants. Efforts should continue to implement stricter air quality standards and improve ambient air quality. Keywords Air pollution * Particulate matter * [PM.sub.2.5] * Preterm birth * Small for gestational age, Introduction The air quality in the Houston area (Harris County, TX) is influenced by multiple sources of air pollutants due to extensive road traffic, proximity to one of the largest [...]

Kolmogorov–Smirnov (KS) statistic is a non-parametric statistic based on the empirical distribution function. For the one-sample case, it uses the supremum distance between an empirical distribution function (EDF) and a pre-specified cumulative distribution function (CDF). For two-sample case, it measures the maximum of the distance between two EDFs. KS test, as well as other EDF-based tests such as the Anderson-Darling (AD) test and Cramer-von Mises (CvM) test, has been widely used in statistical analysis. To address and compare the performance of these test statistics, we have conducted a simulation study comparing the type I error and power of the KS test, the CvM test, the AD test, and the Chi-squared test. Our study includes both one sample and two sample tests and for both independent and correlated samples. Our study showed that if we do not have prior information about the tested distributions, EDF-based tests are better. However, so long as we have prior information about the tested distribution and the density of two distributions is bell-shaped and we are expecting differences in variance/sparseness, then the Chi-squared test may be more preferable. When correlation exists between tested samples, adjustment on the informative sample size is important and required. [ABSTRACT FROM AUTHOR]