Hodges, James S.

Abstract Recent work in causally interpretable meta-analysis (CIMA) has bridged the gap between traditional meta-analysis and causal inference. Whereas traditional meta-analysis results generally do not apply to any well-defined population, CIMA approaches specify a target population to which meta-analytic treatment effect estimates are transported. Although theoretically attractive, these approaches currently have some practical limitations. Most assume that all studies in the meta-analysis have individual participant data (IPD), which is rare in practice because most trials share only aggregate data. We propose a method to perform CIMA using a combination of aggregate data and IPD. This method borrows information from studies with IPD to augment the aggregate data and create aggregate-matched synthetic IPD (AMSIPD), which can be used readily in the existing CIMA framework. By allowing use of both aggregate data and IPD, the method opens CIMA to more applications and can avoid biases arising from using only studies with IPD. We present a case study and simulations showing the AMSIPD approach is promising and merits further investigation as an advancement of CIMA.

Abstract Context Single-tier newborn screening (NBS) for congenital adrenal hyperplasia (CAH) using 17-hydroxyprogesterone (17OHP) measured by fluoroimmunoassay (FIA) in samples collected at 24 to 48 hours produces a high false-positive rate (FPR). Second-tier steroid testing can reduce the FPR and has been widely implemented. Objective We investigated the accuracy of an alternative multitier CAH NBS protocol that incorporates molecular testing of the CYP21A2 gene and reduces the first-tier 17OHP cutoff to minimize missed cases. Methods We create a Minnesota-specific CYP21A2 pathogenic variants panel; developed a rapid, high-throughput multiplex, allele-specific-primer-extension assay; and performed a 1-year retrospective analysis of Minnesota NBS results comparing metrics between a conventional steroid-based 2-tier protocol and a molecular-based multitier NBS protocol, applied post hoc. Results CYP21A2 gene sequencing of 103 Minnesota families resulted in a Minnesota-specific panel of 21 pathogenic variants. The Centers for Disease Control and Prevention created a molecular assay with 100% accuracy and reproducibility. Two-tier steroid-based screening of 68 659 live births during 2015 resulted in 2 false negatives (FNs), 91 FPs, and 1 true positive (TP). A 3-tier protocol with a lower first-tier steroid cutoff, second-tier 21-variant CYP21A2 panel, and third-tier CYP21A2 sequencing would have resulted in 0 FNs, 52 FPs, and 3 TPs. Conclusion Incorporation of molecular testing could improve the accuracy of CAH NBS, although some distinct challenges of molecular testing may need to be considered before implementation by NBS programs.

AbstractMeta‐analysis is commonly used to combine results from multiple clinical trials, but traditional meta‐analysis methods do not refer explicitly to a population of individuals to whom the results apply and it is not clear how to use their results to assess a treatment's effect for a population of interest. We describe recently‐introduced causally interpretable meta‐analysis methods and apply their treatment effect estimators to two individual‐participant data sets. These estimators transport estimated treatment effects from studies in the meta‐analysis to a specified target population using the individuals' potentially effect‐modifying covariates. We consider different regression and weighting methods within this approach and compare the results to traditional aggregated‐data meta‐analysis methods. In our applications, certain versions of the causally interpretable methods performed somewhat better than the traditional methods, but the latter generally did well. The causally interpretable methods offer the most promise when covariates modify treatment effects and our results suggest that traditional methods work well when there is little effect heterogeneity. The causally interpretable approach gives meta‐analysis an appealing theoretical framework by relating an estimator directly to a specific population and lays a solid foundation for future developments.

Objective In contrast to intentionally restricting energy intake, restricting the eating window may be an option for treating obesity. By comparing time‐restricted eating (TRE) with an unrestricted (non‐TRE) control, it was hypothesized that TRE facilitates weight loss, alters body composition, and improves metabolic measures. Methods Participants (17 women and 3 men; mean [SD]: 45.5 [12.1] years; BMI 34.1 [7.5] kg/m 2 ) with a prolonged eating window (15.4 [0.9] hours) were randomized to TRE ( n = 11: 8‐hour window, unrestricted eating within window) versus non‐TRE ( n = 9: unrestricted eating) for 12 weeks. Weight, body composition (dual x‐ray absorptiometry), lipids, blood pressure, 2‐hour oral glucose tolerance, 2‐week continuous glucose monitoring, and 2‐week physical activity (actigraphy assessed) were measured during the pre‐ and end‐intervention periods. Results The TRE group significantly reduced the eating window (end‐intervention window: 9.9 [2.0] hours) compared with the non‐TRE group (end‐intervention window: 15.1 [1.1] hours) ( P < 0.01). Compared with non‐TRE, TRE decreased the number of eating occasions, weight, lean mass, and visceral fat (all P ≤ 0.05). Compared with preintervention measures, the TRE group reduced the number of eating occasions (−21.9% [30.1%]) and reduced weight (−3.7% [1.8%]), fat mass (−4% [2.9%]), lean mass (−3.0% [2.7%]), and visceral fat (−11.1% [13.4%]) (all P ≤ 0.05). Physical activity and metabolic measures remained unchanged. Conclusions In the setting of a randomized trial, TRE presents a simplified view of food intake that reduces weight.

The universally accepted concept of delay-loaded dental implants has recently been challenged. This study hypothesizes that early loading (decreased implant healing time) leads to increased bone formation and decreased crestal bone loss. We used 17 minipigs to study implants under a controlled load, with non-loaded implants for comparison. Radiographic and histological assessments were made of the osseointegrated bone changes for 3 healing times (between implant insertion and loading), following 5 months of loading. The effect of loading on crestal bone loss depended on the healing time. Early loading preserved the most crestal bone. Delayed loading had significantly more crestal bone loss compared with the non-loaded controls (2.4 mm vs. 0.64 mm; P < 0.05). The histological assessment and biomechanical analyses of the healing bone suggested that loading and bioactivities of osteoblasts exert a synergistic effect on osseointegration that is likely to support the hypothesis that early loading produces more favorable osseointegration.