Publications

A goal of evidence synthesis for trials of complex interventions is to inform the design or implementation of novel versions of complex interventions by predicting expected outcomes with each intervention version. Conventional aggregate data meta-analyses of studies comparing complex interventions have limited ability to provide such information. We argue that evidence synthesis for trials of complex interventions should forgo aspirations of estimating causal effects and instead model the response surface of study results to 1) summarize the available evidence and 2) predict the average outcomes of future studies or in new settings. We illustrate this modeling approach using data from a systematic review of diabetes quality improvement (QI) interventions involving at least 1 of 12 QI strategy components. We specify a series of meta-regression models to assess the association of specific components with the posttreatment outcome mean and compare the results to conventional meta-analysis approaches. Compared with conventional approaches, modeling the response surface of study results can better reflect the associations between intervention components and study characteristics with the posttreatment outcome mean. Modeling study results using a response surface approach offers a useful and feasible goal for evidence synthesis of complex interventions that rely on aggregate data.

IMPORTANCE: The National Lung Screening Trial (NLST) found that screening for lung cancer with low-dose computed tomography (CT) reduced lung cancer-specific and all-cause mortality compared with chest radiography. It is uncertain whether these results apply to a nationally representative target population.

OBJECTIVE: To extend inferences about the effects of lung cancer screening strategies from the NLST to a nationally representative target population of NLST-eligible US adults.

DESIGN, SETTING, AND PARTICIPANTS: This comparative effectiveness study included NLST data from US adults at 33 participating centers enrolled between August 2002 and April 2004 with follow-up through 2009 along with National Health Interview Survey (NHIS) cross-sectional household interview survey data from 2010. Eligible participants were adults aged 55 to 74 years, and were current or former smokers with at least 30 pack-years of smoking (former smokers were required to have quit within the last 15 years). Transportability analyses combined baseline covariate, treatment, and outcome data from the NLST with covariate data from the NHIS and reweighted the trial data to the target population. Data were analyzed from March 2020 to May 2023.

INTERVENTIONS: Low-dose CT or chest radiography screening with a screening assessment at baseline, then yearly for 2 more years.

MAIN OUTCOMES AND MEASURES: For the outcomes of lung-cancer specific and all-cause death, mortality rates, rate differences, and ratios were calculated at a median (25th percentile and 75th percentile) follow-up of 5.5 (5.2-5.9) years for lung cancer-specific mortality and 6.5 (6.1-6.9) years for all-cause mortality.

RESULTS: The transportability analysis included 51 274 NLST participants and 685 NHIS participants representing the target population (of approximately 5 700 000 individuals after survey-weighting). Compared with the target population, NLST participants were younger (median [25th percentile and 75th percentile] age, 60 [57 to 65] years vs 63 [58 to 67] years), had fewer comorbidities (eg, heart disease, 6551 of 51 274 [12.8%] vs 1 025 951 of 5 739 532 [17.9%]), and were more educated (bachelor's degree or higher, 16 349 of 51 274 [31.9%] vs 859 812 of 5 739 532 [15.0%]). In the target population, for lung cancer-specific mortality, the estimated relative rate reduction was 18% (95% CI, 1% to 33%) and the estimated absolute rate reduction with low-dose CT vs chest radiography was 71 deaths per 100 000 person-years (95% CI, 4 to 138 deaths per 100 000 person-years); for all-cause mortality the estimated relative rate reduction was 6% (95% CI, -2% to 12%). In the NLST, for lung cancer-specific mortality, the estimated relative rate reduction was 21% (95% CI, 9% to 32%) and the estimated absolute rate reduction was 67 deaths per 100 000 person-years (95% CI, 27 to 106 deaths per 100 000 person-years); for all-cause mortality, the estimated relative rate reduction was 7% (95% CI, 0% to 12%).

CONCLUSIONS AND RELEVANCE: Estimates of the comparative effectiveness of low-dose CT screening compared with chest radiography in a nationally representative target population were similar to those from unweighted NLST analyses, particularly on the relative scale. Increased uncertainty around effect estimates for the target population reflects large differences in the observed characteristics of trial participants and the target population.

When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with certain characteristics in order to improve trial economy or support inferences about subgroups of clusters, may preclude simple random sampling from the cohort into the trial, and thus interfere with the goal of producing generalizable inferences about the target population. We describe a nested trial design where the randomized clusters are embedded within a cohort of trial-eligible clusters from the target population and where clusters are selected for inclusion in the trial with known sampling probabilities that may depend on cluster characteristics (e.g., allowing clusters to be chosen to facilitate trial conduct or to examine hypotheses related to their characteristics). We develop and evaluate methods for analyzing data from this design to generalize causal inferences to the target population underlying the cohort. We present identification and estimation results for the expectation of the average potential outcome and for the average treatment effect, in the entire target population of clusters and in its non-randomized subset. In simulation studies, we show that all the estimators have low bias but markedly different precision. Cluster randomized trials where clusters are selected for inclusion with known sampling probabilities that depend on cluster characteristics, combined with efficient estimation methods, can precisely quantify treatment effects in the target population, while addressing objectives of trial conduct that require oversampling clusters on the basis of their characteristics.

Epidemiologists are attempting to address research questions of increasing complexity by developing novel methods for combining information from diverse sources. Cole et al. (Am J Epidemiol. 2022;XXX(XX):XXXX-XXXX) provide two examples of combining information to draw inferences about a population proportion. In this commentary, we consider combining information to learn about a target population as an epidemiological activity and distinguish it from more conventional meta-analyses. We examine possible rationales for combining information and discuss broad methodological considerations, with an emphasis on aspects of study design, including the selection among candidate data sources and the sampling of observations from these sources.

BACKGROUND: Vaccine hesitancy persists alongside concerns about the safety of coronavirus disease 2019 (COVID-19) vaccines. We aimed to examine the effect of COVID-19 vaccination on risk of death among US veterans.

METHODS: We conducted a target trial emulation to estimate and compare risk of death up to 60 days under two COVID-19 vaccination strategies: vaccination within 7 days of enrollment versus no vaccination through follow-up. The study cohort included individuals aged ≥18 years enrolled in the Veterans Health Administration system and eligible to receive a COVID-19 vaccination according to guideline recommendations from 1 March 2021 through 1 July 2021. The outcomes of interest included deaths from any cause and excluding a COVID-19 diagnosis. Observations were cloned to both treatment strategies, censored, and weighted to estimate per-protocol effects.

RESULTS: We included 3 158 507 veterans. Under the vaccination strategy, 364 993 received vaccine within 7 days. At 60 days, there were 156 deaths per 100 000 veterans under the vaccination strategy versus 185 deaths under the no vaccination strategy, corresponding to an absolute risk difference of -25.9 (95% confidence limit [CL], -59.5 to 2.7) and relative risk of 0.86 (95% CL, .7 to 1.0). When those with a COVID-19 infection in the first 60 days were censored, the absolute risk difference was -20.6 (95% CL, -53.4 to 16.0) with a relative risk of 0.88 (95% CL, .7 to 1.1).

CONCLUSIONS: Vaccination against COVID-19 was associated with a lower but not statistically significantly different risk of death in the first 60 days. These results agree with prior scientific knowledge suggesting vaccination is safe with the potential for substantial health benefits.

BACKGROUND AND AIMS: Declines in cardiovascular mortality have stagnated in the USA since 2011. There is growing concern that these patterns reflect worsening cardiovascular health in younger adults. However, little is known about how the burden of acute cardiovascular hospitalizations and mortality has changed in this population. Changes in cardiovascular hospitalizations and mortality among adults aged 25-64 years were evaluated, overall and by community-level income.

METHODS: Using the National Inpatient Sample, age-standardized annual hospitalization and in-hospital mortality rates for acute myocardial infarction (AMI), heart failure, and ischaemic stroke were determined among adults aged 25-64 years. Quasi-Poisson and quasi-binominal regression models were fitted to compare outcomes between individuals residing in low- and higher-income communities.

RESULTS: Between 2008 and 2019, age-standardized hospitalization rates for AMI increased among younger adults from 155.0 (95% confidence interval: 154.6, 155.4) per 100 000 to 160.7 (160.3, 161.1) per 100 000 (absolute change +5.7 [5.0, 6.3], P < .001). Heart failure hospitalizations also increased (165.3 [164.8, 165.7] to 225.3 [224.8, 225.8], absolute change +60.0 (59.3, 60.6), P < .001), as ischaemic stroke hospitalizations (76.3 [76.1, 76.7] to 108.1 [107.8, 108.5], absolute change +31.7 (31.2, 32.2), P < .001). Across all conditions, hospitalizations rates were significantly higher among younger adults residing in low-income compared with higher-income communities, and disparities did not narrow between groups. In-hospital mortality decreased for all conditions over the study period.

CONCLUSIONS: There was an alarming increase in cardiovascular hospitalizations among younger adults in the USA from 2008 to 2019, and disparities between those residing in low- and higher-income communities did not narrow.

BACKGROUND: Recent advances in heart failure (HF) care have sought to shift management from inpatient to outpatient and observation settings. We evaluated the association among HF treatment in the (1) inpatient; (2) observation; (3) emergency department (ED); and (4) outpatient settings with 30-day mortality, hospitalizations and cost.

METHODS: Using 100% Medicare inpatient, outpatient and Part B files from 2011-2018, 1,534,708 unique patient encounters in which intravenous (IV) diuretics were received for a primary diagnosis of HF were identified. Encounters were sorted into mutually exclusive settings: (1) inpatient; (2) observation; (3) ED; or (4) outpatient IV diuretic clinic. The primary outcome was 30-day all-cause mortality. Secondary outcomes included 30-day hospitalization and total 30-day costs. Multivariable logistic and linear regression were used to examine the association between treatment location and the primary and secondary outcomes.

RESULTS: Patients treated in observation and outpatient settings had lower 30-day mortality rates (observation OR 0.67, 95% CI 0.66-0.69; P < 0.001; outpatient OR 0.53, 95% CI 0.51-0.55; P < 0.001) compared to those treated in inpatient settings. Observation and outpatient treatment were also associated with decreased 30-day total cost compared to inpatient treatment. Observation relative cost -$5528.77, 95% CI -$5613.63 to -$5443.92; outpatient relative cost -$7005.95; 95% CI -$7103.94 to -$6907.96). Patients treated in the emergency department and discharged had increased mortality rates (OR 1.15, 95% CI 1.13-1.17; P < 0.001) and increased rates of hospitalization (OR 1.72, 95% CI 1.70-1.73; P < 0.001) compared to patients treated as inpatients.

CONCLUSIONS: Medicare beneficiaries who received IV diuresis for acute HF in the outpatient and observation settings had lower mortality rates and decreased costs of care compared to patients treated as inpatients. Outpatient and observation management of acute decompensated HF, when available, is a safe and cost-effective strategy in certain populations of patients with HF.

BACKGROUND: Lower-limb amputation rates in patients with chronic limb-threatening ischemia vary across the United States, with marked disparities in amputation rates by gender, race, and income status. We evaluated the association of patient, hospital, and geographic characteristics with the intensity of vascular care received the year before a major lower-limb amputation and how intensity of care associates with outcomes after amputation.

METHODS: Using Medicare claims data (2016-2019), beneficiaries diagnosed with chronic limb-threatening ischemia who underwent a major lower-limb amputation were identified. We examined patient, hospital, and geographic characteristics associated with the intensity of vascular care received the year before amputation. Secondary objectives evaluated all-cause mortality and adverse events following amputation.

RESULTS: Of 33 036 total Medicare beneficiaries undergoing major amputation, 7885 (23.9%) were due to chronic limb-threatening ischemia; of these, 4988 (63.3%) received low-intensity and 2897 (36.7%) received high-intensity vascular care. Mean age, 76.6 years; women, 38.9%; Black adults, 24.5%; and of low income, 35.2%. After multivariable adjustment, those of low income (odds ratio, 0.65 [95% CI, 0.58-0.72]; P<0.001), and to a lesser extent, men (odds ratio, 0.89 [95% CI, 0.81-0.98]; P=0.019), and those who received care at a safety-net hospital (odds ratio, 0.87 [95% CI, 0.78-0.97]; P=0.012) were most likely to receive low intensity of care before amputation. High-intensity care was associated with a lower risk of all-cause mortality 2 years following amputation (hazard ratio, 0.79 [95% CI, 0.74-0.85]; P<0.001).

CONCLUSIONS: Patients who were of low-income status, and to a lesser extent, men, or those cared for at safety-net hospitals were most likely to receive low-intensity vascular care. Low-intensity care was associated with worse long-term event-free survival. These data emphasize the continued disparities that exist in contemporary vascular practice.