Causal inference methodologies have been developed for the past decade to estimate the unconfounded effect of an exposure under several key assumptions. These assumptions include, but are not limited to, the stable unit treatment value assumption, the strong ignorability of treatment assignment assumption, and the assumption that propensity scores be bounded away from zero and one (the positivity assumption). Of these assumptions, the first two have received much attention in the literature. Yet the positivity assumption has been recently discussed in only a few papers. Propensity scores of zero or one are indicative of deterministic exposure so that causal effects cannot be defined for these subjects. Therefore, these subjects need to be removed because no comparable comparison groups can be found for such subjects. In this paper, using currently available causal inference methods, we evaluate the effect of arbitrary cutoffs in the distribution of propensity scores and the impact of those decisions on bias and efficiency. We propose a tree-based method that performs well in terms of bias reduction when the definition of positivity is based on a single confounder. This tree-based method can be easily implemented using the statistical software program, R. R code for the studies is available online.

Interest in incorporating historical data in the clinical trial has increased with the rising cost of conducting clinical trials. The intervention arm for the current trial often requires prospective data to assess a novel treatment, and thus borrowing historical control data commensurate in distribution to current control data is motivated in order to increase the allocation ratio to the current intervention arm. Existing historical control borrowing adaptive designs adjust allocation ratios based on the commensurability assessed through study-level summary statistics of the response agnostic of the distributions of the trial subject characteristics in the current and historical trials. This can lead to distributional imbalance of the current trial subject characteristics across the treatment arms as well as between current control data and borrowed historical control data. Such covariate imbalance may threaten the internal validity of the current trial by introducing confounding factors that affect study endpoints. In this article, we propose a Bayesian design which borrows and updates the treatment allocation ratios both covariate-adaptively and commensurate to covariate dependently assessed similarity between the current and historical control data. We employ covariate-dependent discrepancy parameters which are allowed to grow with the sample size and propose a regularized local regression procedure for the estimation of the parameters. The proposed design also permits the current and the historical controls to be similar to varying degree, depending on the subject level characteristics. We evaluate the proposed design extensively under the settings derived from two placebo-controlled randomized trials on vertebral fracture risk in post-menopausal women.

OBJECTIVE: Apply quantile regression for a high-resolution analysis of changes in wait time to treatment and assess its applicability to quality improvement data compared with least-squares regression. DATA SOURCE: Addiction treatment programs participating in the Network for the Improvement of Addiction Treatment. METHODS: We used quantile regression to estimate wait time changes at 5, 50, and 95 percent and compared the results with mean trends by least-squares regression. PRINCIPAL FINDINGS: Quantile regression analysis found statistically significant changes in the 5 and 95 percent quantiles of wait time that were not identified using least-squares regression. CONCLUSIONS: Quantile regression enabled estimating changes specific to different percentiles of the wait time distribution. It provided a high-resolution analysis that was more sensitive to changes in quantiles of the wait time distributions.

High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors.

Phase I trials aim to establish appropriate clinical and statistical parameters to guide future clinical trials. With individual trials typically underpowered, systematic reviews and meta-analysis are desired to assess the totality of evidence. A high percentage of zero or missing outcomes often complicate such efforts. We use a systematic review of pediatric phase I oncology trials as an example and illustrate the utility of advanced Bayesian analysis. Standard random-effects methods rely on the exchangeability of individual trial effects, typically assuming that a common normal distribution sufficiently describes random variation among the trial level effects. Summary statistics of individual trial data may become undefined with zero counts, and this assumption may not be readily examined. We conduct Bayesian semi-parametric analysis with a Dirichlet process prior and examine the assumption. The Bayesian semi-parametric analysis is also useful for visually summarizing individual trial data. It provides alternative statistics that are computed free of distributional assumptions about the shape of the population of trial level effects. Outcomes are rarely entirely missing in clinical trials. We utilize available information and conduct Bayesian incomplete data analysis. The advanced Bayesian analyses, although illustrated with the specific example, are generally applicable. © 2016 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd.

Background

Steroid-avoidance protocols have gained popularity in pediatric kidney transplant recipients at low immunologic risk. The long-term safety of steroid avoidance in children with immunologic risk factors remains unknown.

Methods

Pediatric kidney transplant recipients from 2004 to 2014 in the Organ Procurement and Transplantation Network database who received tacrolimus and mycophenolate immunosuppression were investigated. Propensity score matching was used to compare graft survival in 1624 children who received steroid avoidance with 1624 children who received steroid-based immunosuppression. The effect of steroid avoidance on graft failure among immunologic risk strata was estimated using Cox proportional hazards regression in this propensity score-matched cohort.

Results

It was observed that 5-year graft survival was mildly improved in children receiving steroid avoidance (84.8% versus 81.2%, P = 0.03). This improvement in graft survival occurred in the first 2 years following transplant, when the hazard ratio (HR) for allograft failure in children receiving steroid avoidance was 0.62 [95% confidence interval (CI) 0.45-0.86]. In contrast, steroid avoidance was not associated with improved allograft survival during Years 2-10 following transplant (HR = 0.93; 95% CI 0.75-1.15). During this time period, HRs (95% CIs) for allograft failure within immunologic risk strata were not significantly different from the null value of 1: repeat kidney transplants, 1.84 (0.84-4.05); African-Americans, 1.02 (0.67-1.56); sensitized recipients, 1.24 (0.63-2.43); recipients of deceased donor kidneys, 1.02 (0.79-1.32); recipients of completely human leukocyte antigen-mismatched kidneys, 0.80 (0.47-1.37); and recipients with pretransplant glomerular disease, 0.94 (0.71-1.23).

Conclusions

In pediatric kidney transplant recipients receiving tacrolimus- and mycophenolate-based immunosuppression, steroid avoidance can be safely practiced in children with immunologic risk factors.

Background

Despite guidelines recommending narrow-spectrum perioperative antibiotics (NSPA) as prophylaxis for most children undergoing congenital heart disease (CHD) surgery, broad-spectrum perioperative antibiotics (BSPA) are variably used, and their impact on postoperative outcomes is poorly understood.

Methods

We used administrative data from U.S. hospitals participating in the Vizient Clinical Data Base. Admissions from 2011 to 2018 containing a qualifying CHD surgery in children 0-17 years old were evaluated for exposure to BSPA versus NSPA. Propensity score-adjusted models were used to compare postoperative length of hospital stay (PLOS) by exposure group, while adjusting for confounders. Secondary outcomes included subsequent antimicrobial treatment and in-hospital mortality.

Results

Among 18 088 eligible encounters from 24 U.S. hospitals, BSPA were given in 21.4% of CHD surgeries, with mean BSPA use varying from 1.7% to 96.1% between centers. PLOS was longer for BSPA-exposed cases (adjusted hazard ratio 0.79; 95% confidence interval [CI]: 0.71-0.89, P < .0001). BSPA was associated with higher adjusted odds of subsequent antimicrobial treatment (odds ratio [OR] 1.24; 95% CI: 1.06-1.48), and there was no significant difference in adjusted mortality between exposure groups (OR 2.06; 95% CI: 1.0-4.31; P = .05). Analyses of subgroups with the most BSPA exposure, including high-complexity procedures and delayed sternal closure, also did not find (but could not exclude) a measurable benefit from BSPA on PLOS.

Conclusions

BSPA use was common in high-risk populations, and varied substantially between centers. Standardizing perioperative antibiotic practices between centers may reduce unnecessary broad-spectrum antibiotic exposure and improve clinical outcomes.

Glucocorticoids (GCs) are the cornerstone of acute lymphoblastic leukemia (ALL) therapy. Although mutations in NR3C1, which encodes the GC receptor (GR), and other genes involved in GC signaling occur at relapse, additional mechanisms of adaptive GC resistance are uncertain. We transplanted and treated 10 primary mouse T-lineage acute lymphoblastic leukemias (T-ALLs) initiated by retroviral insertional mutagenesis with GC dexamethasone (DEX). Multiple distinct relapsed clones from 1 such leukemia (T-ALL 8633) exhibited discrete retroviral integrations that upregulated Jdp2 expression. This leukemia harbored a Kdm6a mutation. In the human T-ALL cell line CCRF-CEM, enforced JDP2 overexpression conferred GC resistance, whereas KDM6A inactivation unexpectedly enhanced GC sensitivity. In the context of KDM6A knockout, JDP2 overexpression induced profound GC resistance, counteracting the sensitization conferred by KDM6A loss. These resistant double mutant cells with combined KDM6A loss and JDP2 overexpression exhibited decreased NR3C1 mRNA and GR protein upregulation upon DEX exposure. Analysis of paired samples from 2 patients with KDM6A-mutant T-ALL in a relapsed pediatric ALL cohort revealed a somatic NR3C1 mutation at relapse in 1 patient and a markedly elevated JDP2 expression in the other. Together, these data implicate JDP2 overexpression as a mechanism of adaptive GC resistance in T-ALL, which functionally interacts with KDM6A inactivation.

PURPOSE: This study characterizes attitudes and decision-making around the desire for future children in young women newly diagnosed with early-stage breast cancer and assesses how clinical factors and perceived risk may impact these attitudes. METHODS: This is a prospective study in women < 45 years with newly diagnosed stage 1-3 breast cancer. Patients completed a REDCap survey on fertility and family-building in the setting of hypothetical risk scenarios. Patient, tumor, and treatment characteristics were collected through surveys and medical record. RESULTS: Of 140 study patients [median age = 41.4 (range 23-45)], 71 (50.7%) were interested in having children. Women interested in future childbearing were younger than those who were not interested (mean = 35.2 [SD = 5.2] vs 40.9 years [3.90], respectively, p < 0.001), and more likely to be childless (81% vs 31%, p < 0.001). 54 women (77.1% of patients interested in future children) underwent/planned to undergo oocyte/embryo cryopreservation before chemotherapy. Interest in future childbearing decreased with increasing hypothetical recurrence risk, however 17% of patients wanted to have children despite a 75-100% hypothetical recurrence risk. 24.3% of patients wanted to conceive < 2 years from diagnosis, and 35% of patients with hormone receptor positive tumors were not willing to complete 5 years of hormone therapy. CONCLUSION: Many young women diagnosed with early-stage breast cancer prioritize childbearing. Interest in having a biologic child was not associated with standard prognostic risk factors. Interest decreased with increasing hypothetical recurrence risk, though some patients remained committed to future childbearing despite near certain hypothetical risk. Individual risk assessment should be included in family-planning discussions throughout the continuum of care as it can influence decision-making.

BACKGROUND: Crohns disease (CD) patients with elevated granulocyte-macrophage colony-stimulating factor autoantibodies (GM-CSF Ab) are more likely to develop stricturing behavior requiring surgery. Computed tomography or magnetic resonance enterography (CTE or MRE) may detect luminal narrowing (LN) before stricture development. The objective of this study was to determine whether CD patients with elevated GM-CSF Ab (≥1.6 μg/mL) have a higher prevalence of LN and stricturing on CTE or MRE. METHODS: A single-center, cross-sectional study of 153 pediatric patients with CD and control subjects undergoing diagnostic CTE or MRE. Examinations were evaluated for disease activity using a novel scoring system and for the presence of LN, stricture, intra-abdominal abscess, or fistulae. Dichotomous outcomes were compared with respect to antibody status (high or low) using Fishers exact test and logistic regression, whereas continuous outcomes were evaluated using unpaired t test. RESULTS: GM-CSF Ab were elevated in CD patients (n = 114) with a median (interquartile range) GM-CSF Ab level of 2.3 μg/mL (0.5-6.6 μg/mL) compared with 0.6 μg/mL (0.3-1.3 μg/mL) in healthy and disease control subjects (n = 39) (P = 0.001). Ileal disease location was more common in CD patients with high GM-CSF Ab (P < 0.001). LN increased from 39% in CD patients with low GM-CSF Ab to 71% in those with high levels (P = 0.004) and remained significantly associated with high GM-CSF Ab in a multivariate logistic model, which included age, gender, small bowel location, and duration of disease. Stricturing prevalence on CTE or MRE examination increased from 4% in CD patients with low GM-CSF Ab to 19% in those with high GM-CSF Ab (P = 0.03). CONCLUSIONS: Pediatric CD patients with high GM-CSF Ab levels have a higher prevalence of LN on CTE or MRE. Further study will be needed to determine whether medical therapy will reduce progression to stricturing behavior in these patients.