Comparing the performance of statistical methods that generalize effect estimates from randomized controlled trials to much larger target populations.

Policymakers use results from randomized controlled trials to inform decisions about whether to implement treatments in target populations. Various methods - including inverse probability weighting, outcome modeling, and Targeted Maximum Likelihood Estimation - that use baseline data available in both the trial and target population have been proposed to generalize the trial treatment effect estimate to the target population. Often the target population is significantly larger than the trial sample, which can cause estimation challenges.

Immune-stimulating antibody conjugates elicit robust myeloid activation and durable antitumor immunity.

Innate pattern recognition receptor agonists, including Toll-like receptors (TLRs), alter the tumor microenvironment and prime adaptive antitumor immunity. However, TLR agonists present toxicities associated with widespread immune activation after systemic administration. To design a TLR-based therapeutic suitable for systemic delivery and capable of safely eliciting tumor-targeted responses, we developed immune-stimulating antibody conjugates (ISACs) comprising a TLR7/8 dual agonist conjugated to tumor-targeting antibodies.

Embryology outcomes after oocyte vitrification with super-cooled slush nitrogen are similar to outcomes with conventional liquid nitrogen: a randomized controlled trial.

Objective: To determine whether the use of slush nitrogen (SN), a super-cooled form of nitrogen with a temperature from -207 to -210 °C, can improve oocyte survival after vitrification and warming compared with conventional liquid nitrogen (LN).

Design: Randomized controlled trial.

Setting: Academic-affiliated private practice.

Calibrating validation samples when accounting for measurement error in intervention studies.

Many lifestyle intervention trials depend on collecting self-reported outcomes, such as dietary intake, to assess the intervention's effectiveness. Self-reported outcomes are subject to measurement error, which impacts treatment effect estimation. External validation studies measure both self-reported outcomes and accompanying biomarkers, and can be used to account for measurement error.

Generalizability of Subgroup Effects.

Generalizability methods are increasingly used to make inferences about the effect of interventions in target populations using a study sample. Most existing methods to generalize effects from sample to population rely on the assumption that subgroup-specific effects generalize directly. However, researchers may be concerned that in fact subgroup-specific effects differ between sample and population.