Randomized trials remain the most accepted design for estimating the effects of interventions, but they do not necessarily answer a question of primary interest: will the programme be effective in a ...target population in which it may be implemented? In other words, are the results generalizable? There has been very little statistical research on how to assess the generalizability, or `external validity', of randomized trials. We propose the use of propensity-score-based metrics to quantify the similarity of the participants in a randomized trial and a target population. In this setting the propensity score model predicts participation in the randomized trial, given a set of covariates. The resulting propensity scores are used first to quantify the difference between the trial participants and the target population, and then to match, subclassify or weight the control group outcomes to the population, assessing how well the propensity-score-adjusted outcomes track the outcomes that are actually observed in the population. These metrics can serve as a first step in assessing the generalizability of results from randomized trials to target populations. The paper lays out these ideas, discusses the assumptions underlying the approach and illustrates the metrics by using data on the evaluation of a schoolwide prevention programme called `Positive behavioral interventions and supports'.
Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or ...decreases precision without affecting bias. We define overadjustment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.
The ever-growing abundance of data found in heterogeneous sources, such as scientific publications, has forced the development of automated techniques for data extraction. While in the past, in the ...physical sciences domain, the focus has been on the precise extraction of individual properties, attention has recently been devoted to the extraction of higher-level relationships. Here, we present a framework for an automated population of ontologies. That is, the direct extraction of a larger group of properties linked by a semantic network. We exploit data-rich sources, such as tables within documents, and present a new model concept that enables data extraction for chemical and physical properties with the ability to organize hierarchical data as nested information. Combining these capabilities with automatically generated parsers for data extraction and forward-looking interdependency resolution, we illustrate the power of our approach via the automatic extraction of a crystallographic hierarchy of information. This includes 18 interrelated submodels of nested data, extracted from an evaluation set of scientific articles, yielding an overall precision of 92.2%, across 26 different journals. Our method and associated toolkit, ChemDataExtractor 2.0, offers a key step toward the seamless integration of primary literature sources into a data-driven scientific framework.
The effect of highly active antiretroviral therapy (HAART) on the survival of HIV-infected children has not been well quantified. Because most pediatric HIV occurs in low- and middle-income ...countries, our objective was to provide a first estimate of this effect among children living in a resource-deprived setting.
Observational data from HAART-naïve children enrolled into an HIV care and treatment program in Kinshasa, Democratic Republic of the Congo, between December 2004 and May 2010 were analyzed. We used marginal structural models to estimate the effect of HAART on survival while accounting for time-dependent confounders affected by exposure. At the start of follow-up, the median age of the 790 children was 5.9 y, 528 (66.8%) had advanced or severe immunodeficiency, and 405 (51.3%) were in HIV clinical stage 3 or 4. The children were observed for a median of 31.2 mo and contributed a total of 2,089.8 person-years. Eighty children (10.1%) died, 619 (78.4%) initiated HAART, six (0.8%) transferred to a different care provider, and 76 (9.6%) were lost to follow-up. The mortality rate was 3.2 deaths per 100 person-years (95% confidence interval CI 2.4-4.2) during receipt of HAART and 6.0 deaths per 100 person-years (95% CI 4.1-8.6) during receipt of primary HIV care only. The mortality hazard ratio comparing HAART with no HAART from a marginal structural model was 0.25 (95% CI 0.06-0.95).
HAART reduced the hazard of mortality in HIV-infected children in Kinshasa by 75%, an estimate that is similar in magnitude but with lower precision than the reported effect of HAART on survival among children in the United States. Please see later in the article for the Editors' Summary.
That conditioning on a common effect of exposure and outcome may cause selection, or collider-stratification, bias is not intuitive. We provide two hypothetical examples to convey concepts underlying ...bias due to conditioning on a collider. In the first example, fever is a common effect of influenza and consumption of a tainted egg-salad sandwich. In the second example, case-status is a common effect of a genotype and an environmental factor. In both examples, conditioning on the common effect imparts an association between two otherwise independent variables; we call this selection bias.
Cross-ecosystem subsidies to food webs can alter metabolic balances in the receiving (subsidized) system and free the food web, or particular consumers, from the energetic constraints of local ...primary production. Although cross-ecosystem subsidies between terrestrial and aquatic systems have been well recognized for benthic organisms in streams, rivers, and the littoral zones of lakes, terrestrial subsidies to pelagic consumers are more difficult to demonstrate and remain controversial. Here, we adopt a unique approach by using stable isotopes of H, C, and N to estimate terrestrial support to zooplankton in two contrasting lakes. Zooplankton (Holopedium, Daphnia, and Leptodiaptomus) are comprised of almost equal to20-40% of organic material of terrestrial origin. These estimates are as high as, or higher than, prior measures obtained by experimentally manipulating the inorganic ¹³C content of these lakes to augment the small, natural contrast in ¹³C between terrestrial and algal photosynthesis. Our study gives credence to a growing literature, which we review here, suggesting that significant terrestrial support of pelagic crustaceans (zooplankton) is widespread.
Directional change in environmental drivers sometimes triggers regime shifts in ecosystems. Theory and experiments suggest that regime shifts can be detected in advance, and perhaps averted, by ...monitoring resilience indicators such as variance and autocorrelation of key ecosystem variables. However, it is uncertain whether management action prompted by a change in resilience indicators can prevent an impending regime shift. We caused a cyanobacterial bloom by gradually enriching an experimental lake while monitoring an unenriched reference lake and a continuously enriched reference lake. When resilience indicators exceeded preset boundaries, nutrient enrichment was stopped in the experimental lake. Concentrations of algal pigments, dissolved oxygen saturation, and pH rapidly declined following cessation of nutrient enrichment and became similar to the unenriched lake, whereas a large bloom occurred in the continuously enriched lake. This outcome suggests that resilience indicators may be useful in management to prevent unwanted regime shifts, at least in some situations. Nonetheless, a safer approach to ecosystem management would build and maintain the resilience of desirable ecosystem conditions, for example, by preventing excessive nutrient input to lakes and reservoirs.
Previous research identified differences in breast cancer-specific mortality across 4 intrinsic tumor subtypes: luminal A, luminal B, basal-like, and human epidermal growth factor receptor 2 ...positive/estrogen receptor negative (HER2(+)/ER(-)).
We used immunohistochemical markers to subtype 1,149 invasive breast cancer patients (518 African American, 631 white) in the Carolina Breast Cancer Study, a population-based study of women diagnosed with breast cancer. Vital status was determined through 2006 using the National Death Index, with median follow-up of 9 years.
Cancer subtypes luminal A, luminal B, basal-like, and HER2(+)/ER(-) were distributed as 64%, 11%, 11%, and 5% for whites, and 48%, 8%, 22%, and 7% for African Americans, respectively. Breast cancer mortality was higher for participants with HER2(+)/ER(-) and basal-like breast cancer compared with luminal A and B. African Americans had higher breast cancer-specific mortality than whites, but the effect of race was statistically significant only among women with luminal A breast cancer. However, when compared with the luminal A subtype within racial categories, mortality for participants with basal-like breast cancer was higher among whites (HR = 2.0, 95% CI: 1.2-3.4) than African Americans (HR = 1.5, 95% CI: 1.0-2.4), with the strongest effect seen in postmenopausal white women (HR = 3.9, 95% CI: 1.5-10.0).
Our results confirm the association of basal-like breast cancer with poor prognosis and suggest that basal-like breast cancer is not an inherently more aggressive disease in African American women compared with whites. Additional analyses are needed in populations with known treatment profiles to understand the role of tumor subtypes and race in breast cancer mortality, and in particular our finding that among women with luminal A breast cancer, African Americans have higher mortality than whites.
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