Extending Inferences from Randomized Clinical Trials to Target Populations: A Scoping Review of Transportability Methods

Objective: Randomized controlled trial (RCT) results often inform clinical decision-making, but the highly curated populations of trials and the care provided during the trial are often not reflective of real-world practice. The objective of this scoping review is to identify the ability of methods to transport findings from RCTs to target populations. Study design: A scoping review was conducted on the literature focusing on the transportability of the results from RCTs to observational cohorts. Each study was assessed based on the methodology used for transportability and the extent to which the treatment effect from the RCT was estimated in the target population in observational data. Results: A total of 15 published papers were included. The research topics include cardiovascular diseases, infectious diseases, psychiatry, oncology, orthopedics, anesthesiology, and hematology. These studies show that the findings from RCTs could be translated to real-world settings, with varying degrees of effect size and precision. In some cases, the estimated treatment effect for the target population were statistically significantly different from those in RCTs. Conclusion: Despite variations in the magnitude of effects between RCTs and real-world studies, transportability methods play an important role in effectively bridging the RCTs and real-world care delivery, offering valuable insights for evidence-based medicine

A Calibration Approach to Transportability with Observational Data

An important consideration in clinical research studies is proper evaluation of internal and external validity. While randomized clinical trials can overcome several threats to internal validity, they may be prone to poor external validity. Conversely, large prospective observational studies sampled from a broadly generalizable population may be externally valid, yet susceptible to threats to internal validity, particularly confounding. Thus, methods that address confounding and enhance transportability of study results across populations are essential for internally and externally valid causal inference, respectively. We develop a weighting method which estimates the effect of an intervention on an outcome in an observational study which can then be transported to a second, possibly unrelated target population. The proposed methodology employs calibration estimators to generate complementary balancing and sampling weights to address confounding and transportability, respectively, enabling valid estimation of the target population average treatment effect. A simulation study is conducted to demonstrate the advantages and similarities of the calibration approach against alternative techniques. We also test the performance of the calibration estimator-based inference in a motivating real data example comparing whether the effect of biguanides versus sulfonylureas - the two most common oral diabetes medication classes for initial treatment - on all-cause mortality described in a historical cohort applies to a contemporary cohort of US Veterans with diabetes

A Review of Generalizability and Transportability

When assessing causal effects, determining the target population to which the results are intended to generalize is a critical decision. Randomized and observational studies each have strengths and limitations for estimating causal effects in a target population. Estimates from randomized data may have internal validity but are often not representative of the target population. Observational data may better reflect the target population, and hence be more likely to have external validity, but are subject to potential bias due to unmeasured confounding. While much of the causal inference literature has focused on addressing internal validity bias, both internal and external validity are necessary for unbiased estimates in a target population. This paper presents a framework for addressing external validity bias, including a synthesis of approaches for generalizability and transportability, the assumptions they require, as well as tests for the heterogeneity of treatment effects and differences between study and target populations.Comment: 30 pages, 3 figure

Estimating Oral Anticoagulant Comparative Effectiveness in the Setting of Effect Heterogeneity: Comparing Clinical Trial Transport and Non-experimental Epidemiologic Methods

Oral anticoagulation is vital to the health of patients with atrial fibrillation at elevated risk of stroke. The first treatment for these patients, warfarin, was approved in the 1990s. Since 2010, dabigatran has been available for use after demonstrating non-inferiority to warfarin in a randomized controlled trial. Non-experimental studies comparing dabigatran to warfarin and censoring at treatment discontinuation have shown greater benefits than the original trial for all-cause mortality and attenuated harms for gastrointestinal bleeding. The goals of this dissertation, then, were to compute and compare 1) estimates of the absolute-scale effects of dabigatran vs warfarin initiation on ischemic stroke (IS), death, and gastrointestinal bleeding (GIB) in trial-eligible older adults using non-experimental Medicare data and 2) estimates of those effects in the same populations using inverse odds of sampling weights to transport results from the Randomized Evaluation of Long-Term Anticoagulation (RE-LY) trial. First, we conducted a propensity score weighted non-experimental study with the new user active comparator design in a 20% random sample of Medicare beneficiares. We estimated on-treatment two-year risk differences for IS (RD for dabigatran users, RDdabi: -0.67%, 95% CI -1.10%, -0.24%), mortality (RDdabi: -2.98%, 95% CI -3.97%, -1.95%) and GIB (RDdabi: 0.51%, 95% CI -0.30%, 1.31%). Intention-to-treat estimates showed attenuation for mortality (RDdabi: -1.65%, 95% CI -2.32%, -0.98%) and reversal for IS (RDdabi: 0.16%, 95% CI -0.20%, 0.52%). Next, we reweighted RE-LY to resemble the Medicare new users of warfarin or dabigatran (restricted to those with less than 15% predicted probability of frailty). After weighting, we estimated on-treatment two-year risk differences for IS (RDdabi: -0.77%, 95% CI -1.69%, 0.14%), death (RDdabi: -0.57%, 95% CI -1.83%, 0.68%) and GIB (RDdabi: 1.75%, 95% CI 0.76%, 2.74%). These twin studies show non-experimental and weighted trial analyses comparing dabigatran to warfarin agree much better for IS than they do for mortality or GIB. This could be due to confounding in the non-experimental estimates, missing treatment effect modifiers, or outcome misclassification. Researchers should be cautious about comparing studies without considering treatment effect heterogeneity and differences in adherence across study populations.Doctor of Philosoph

Population screening for colorectal cancer means getting FIT:the past, present, and future of colorectal cancer screening using the fecal immunochemical test for hemoglobin (FIT)

Fecal immunochemical tests for hemoglobin (FIT) are changing the manner in which colorectal cancer (CRC) is screened. Although these tests are being performed worldwide, why is this test different from its predecessors? What evidence supports its adoption? How can this evidence best be used? This review addresses these questions and provides an understanding of FIT theory and practices to expedite international efforts to implement the use of FIT in CRC screening