Characterizing Imbalance in the Tails of the Propensity Score Distribution.

Understanding characteristics of patients with propensity scores in the tails of the propensity score (PS) distribution has relevance for inverse-probability-of-treatment-weighted and PS-based estimation in observational studies. Here we outline a method for identifying variables most responsible for extreme propensity scores. The approach is illustrated in 3 scenarios: 1) a plasmode simulation of adult patients in the National Ambulatory Medical Care Survey (2011-2015) and 2) timing of dexamethasone initiation and 3) timing of remdesivir initiation in patients hospitalized for coronavirus disease 2019 from February 2020 through January 2021. PS models were fitted using relevant baseline covariates, and tails of the PS distribution were defined using asymmetric first and 99th percentiles. After fitting of the PS model in each original data set, values of each key covariate were permuted and model-agnostic variable importance measures were examined. Visualization and variable importance techniques were helpful in identifying variables most responsible for extreme propensity scores and may help identify individual characteristics that might make patients inappropriate for inclusion in a study (e.g., off-label use). Subsetting or restricting the study sample based on variables identified using this approach may help investigators avoid the need for trimming or overlap weights in studies.

Influence of Incomplete Death Information on Cumulative Risk Estimates in United States Claims Data.

Administrative claims databases often do not capture date or fact of death, so studies using these data may inappropriately treat death as a censoring event-equivalent to other withdrawal reasons-rather than a competing event. We examined 1-, 3-, and 5-year inverse-probability-of-treatment-weighted cumulative risks of a composite cardiovascular outcome among 34,527 initiators of telmisartan (exposure) and ramipril (referent) ages ≥55 in Optum claims from 2003 to 2020. Differences in cumulative risks of the cardiovascular endpoint due to censoring of death (cause-specific), as compared to treating death as a competing event (sub-distribution), increased with greater follow-up time and older age, where event and mortality risks were higher. Among ramipril users (selected results), 5-year cause-specific and sub-distribution cumulative risk estimates per 100, respectively, were 16.4 (95% CI 15.3, 17.5) and 16.2 (95% CI 15.1, 17.3) among ages 55-64 (difference=0.2) and were 43.2 (95% CI 41.3, 45.2) and 39.7 (95% CI 37.9, 41.4) among ages ≥75 (difference=3.6). Plasmode simulation results demonstrated the differences in cause-specific versus sub-distribution cumulative risks to increase with increasing mortality rate. We suggest researchers consider the cohort's baseline mortality risk when deciding whether real-world data with incomplete death information can be used without concern.

Impact of age at ivacaftor initiation on pulmonary outcomes among people with cystic fibrosis.

BACKGROUND: Ivacaftor (IVA) improves lung function and other extrapulmonary outcomes in people with cystic fibrosis (CF). However, the effect of initiating IVA at earlier versus later ages has not been studied. METHODS: We conducted an observational cohort study of people in the US CF Foundation Patient Registry aged ≥6 years with ≥1 CF transmembrane conductance regulator-gating mutation to compare the effects of initiating IVA at earlier ages on per cent predicted forced expiratory volume in 1 s (ppFEV1) and pulmonary exacerbation (PEx) outcomes. People with CF were grouped by age at IVA initiation (ages 6-10, 11-15, 16-20 and 21-25 years) to perform three analyses of younger versus older IVA initiation (6-10 vs 11-15, 11-15 vs 16-20 and 16-20 vs 21-25 years). For each analysis, baseline characteristics assessed over 1-year periods at the same age prior to IVA initiation were balanced by standardised mortality/morbidity ratio (SMR) weighting. For each analysis, outcomes were compared over a 5-year outcome assessment period when both groups were in the same age range and receiving IVA. FINDINGS: Baseline characteristics were well balanced between younger and older IVA initiator groups after SMR weighting. In the outcome assessment period, younger IVA initiators had significantly higher mean ppFEV1 than older initiators across all comparisons, and those initiating IVA between ages 6-10 and 11-15 years had significantly lower PEx rates. INTERPRETATION: Study findings showed the importance of early IVA initiation in people with CF.

Long-term impact of ivacaftor on mortality rate and health outcomes in people with cystic fibrosis.

BACKGROUND: Ivacaftor (IVA) has been shown to improve lung function and other clinical outcomes in people with cystic fibrosis (CF). A decade of real-world IVA availability has enabled the examination of long-term outcomes with this treatment. This retrospective, longitudinal cohort study investigated the impact of IVA on mortality rate and health outcomes among people with CF in the US. METHODS: Data from the US CF Foundation Patient Registry from January 2010 to December 2019 were analysed. The IVA-treated cohort included people with a CF transmembrane conductance regulator (CFTR) gating mutation (excluding R117H); age-matched comparator cohort included people with a F508del and a minimal function CFTR mutation who had no prior CFTR modulator treatment. Baseline characteristics were balanced between cohorts using standardised mortality ratio weighting generated from propensity scores. Outcomes of interest were overall survival, lung transplant, percent predicted forced expiratory volume in 1 s (ppFEV1), body mass index (BMI), pulmonary exacerbations (PEx), outpatient visits and hospitalisations. FINDINGS: Over a maximum follow-up of 7.9 years, the IVA-treated cohort (N=736) had lower rates of mortality (hazard ratio [HR] (95% CI): 0.22 (0.09 to 0.45)), lung transplant (HR: 0.11 (95% CI 0.02 to 0.28)), PEx (rate ratio: 0.49 (95% CI 0.42 to 0.55)) and all-cause hospitalisations (rate ratio: 0.50 (95% CI 0.43 to 0.56)) as well as better lung function (mean difference in ppFEV1: 8.46 (95% CI 7.34 to 9.75)) and higher BMI/BMI z-scores (mean difference 1.20 (95% CI 0.92 to 1.71) kg/m2 and 0.27 (95% CI 0.25 to 0.40), respectively) than the comparator cohort (N=733). INTERPRETATION: Our analysis suggests that IVA provides sustained clinical benefits in people with CF over a follow-up period of approximately 8 years. These findings reinforce the existing real-world evidence that IVA can slow disease progression and decrease the healthcare burden of CF over the long term.

Comparing PCSK9 Monoclonal Antibody Treatment Strategies Following Myocardial Infarction Using Negative Control Outcomes: A Target Trial Emulation Study.

BACKGROUND: Initiation of proprotein convertase subtilisin/kexin type 9 monoclonal antibody (PCSK9 mAb) for lipid-lowering following myocardial infarction (MI) is likely affected by patients' prognostic factors, potentially leading to bias when comparing real-world treatment effects. METHODS: Using target-trial emulation, we assessed potential confounding when comparing two treatment strategies post-MI: initiation of PCSK9 mAb within 1 year and no initiation of PCSK9 mAb. We identified MI hospitalizations during July 2015-June 2020 for patients aged ≥18 years in Optum's de-identified Clinformatics Data Mart (CDM) and MarketScan, and those aged ≥66 in the US Medicare claims database. We estimated a 3-year counterfactual cumulative risk and risk difference (RD) for 10 negative control outcomes using the clone-censor-weight approach to address time-varying confounding and immortal person-time. RESULTS: PCSK9 mAb initiation within 1-year post-MI was low (0.7% in MarketScan and 0.4% in both CDM and Medicare databases). In CDM, there was a lower risk for cancer (RD = -3.6% [95% CI: -4.3%, -2.9%]), decubitus ulcer (RD = -7.7% [95% CI: -11.8%, -3.7%]), fracture (RD = -8.1% [95% CI: -9.6%, -6.6%]), influenza vaccine (RD = -9.3% [95% CI: -17.5%, -1.1%]), and visual test (RD = -0.6% [95% CI: -0.7%, -0.6%]) under the PCSK9 mAb initiation versus no initiation strategy. Similar differences persisted in the MarketScan and Medicare databases. In each database, ezetimibe and low-density lipoprotein testing were unbalanced between treatment strategies. CONCLUSION: A comparative effectiveness study of these treatments using the current approach would likely bias results due to the low number of PCSK9 mAb initiators.

Comparative effectiveness of ZUMA-5 (axi-cel) vs SCHOLAR-5 external control in relapsed/refractory follicular lymphoma.

In the pivotal ZUMA-5 trial, axicabtagene ciloleucel (axi-cel; an autologous anti-CD19 chimeric antigen receptor T-cell therapy) demonstrated high rates of durable response in relapsed/refractory (r/r) follicular lymphoma (FL) patients. Here, outcomes from ZUMA-5 are compared with the international SCHOLAR-5 cohort, which applied key ZUMA-5 trial eligibility criteria simulating randomized controlled trial conditions. SCHOLAR-5 data were extracted from institutions in 5 countries, and from 1 historical clinical trial, for r/r FL patients who initiated a third or higher line of therapy after July 2014. Patient characteristics were balanced through propensity scoring on prespecified prognostic factors using standardized mortality ratio (SMR) weighting. Time-to-event outcomes were evaluated using weighted Kaplan-Meier analysis. Overall response rate (ORR) and complete response (CR) rate were compared using weighted odds ratios. The 143 ScHOLAR-5 patients reduced to an effective sample of 85 patients after SMR weighting vs 86 patients in ZUMA-5. Median follow-up time was 25.4 and 23.3 months for SCHOLAR-5 and ZUMA-5. Median overall survival (OS) and progression-free survival (PFS) in SCHOLAR-5 were 59.8 months and 12.7 months and not reached in ZUMA-5. Hazard ratios for OS and PFS were 0.42 (95% confidence interval [CI], 0.21-0.83) and 0.30 (95% CI, 0.18-0.49). The ORR and CR rate were 49.9% and 29.9% in SCHOLAR-5 and 94.2% and 79.1% in ZUMA-5, for odds ratios of 16.2 (95% CI, 5.6-46.9) and 8.9 (95% CI, 4.3-18.3). Compared with available therapies, axi-cel demonstrated an improvement in meaningful clinical endpoints, suggesting axi-cel addresses an important unmet need for r/r FL patients. This trial was registered at www.clinicaltrials.gov as #NCT03105336.

Staging and clean room: Constructs designed to facilitate transparency and reduce bias in comparative analyses of real-world data.

PURPOSE: We describe constructs designed to protect the integrity of the results from comparative analyses using real-world data (RWD): staging and clean room. METHODS: Staging involves performing sequential preliminary analyses and evaluating the population size available and potential bias before conducting comparative analyses. A clean room involves restricted access to data and preliminary results, policies governing exploratory analyses and protocol deviations, and audit trail. These constructs are intended to allow decisions about protocol deviations, such as changes to design or model specification, to be made without knowledge of how they might affect subsequent analyses. We describe an example for implementing staging with a clean room. RESULTS: Stage 1 may involve selecting a data source, developing and registering a protocol, establishing a clean room, and applying inclusion/exclusion criteria. Stage 2 may involve attempting to achieve covariate balance, often through propensity score models. Stage 3 may involve evaluating the presence of residual confounding using negative control outcomes. After each stage, check points may be implemented when a team of statisticians, epidemiologists and clinicians masked to how their decisions may affect study outcomes, reviews the results. This review team may be tasked with making recommendations for protocol deviations to address study precision or bias. They may recommend proceeding to the next stage, conducting additional analyses to address bias, or terminating the study. Stage 4 may involve conducting the comparative analyses. CONCLUSIONS: The staging and clean room constructs are intended to protect the integrity and enhance confidence in the results of analyses of RWD.

A Per-Protocol Analysis Using Inverse-Probability-of-Censoring Weights in a Randomized Trial of Initial Protease Inhibitor Versus Nonnucleoside Reverse Transcriptase Inhibitor Regimens in Children.

Protocol adherence may influence measured treatment effectiveness in randomized controlled trials. Using data from a multicenter trial (Europe and the Americas, 2002-2009) of children with human immunodeficiency virus type 1 who had been randomized to receive initial protease inhibitor (PI) versus nonnucleoside reverse transcriptase inhibitor (NNRTI) antiretroviral therapy regimens, we generated time-to-event intention-to-treat (ITT) estimates of treatment effectiveness, applied inverse-probability-of-censoring weights to generate per-protocol efficacy estimates, and compared shifts from ITT to per-protocol estimates across and within treatment arms. In ITT analyses, 263 participants experienced 4-year treatment failure probabilities of 41.3% for PIs and 39.5% for NNRTIs (risk difference = 1.8% (95% confidence interval (CI): -10.1, 13.7); hazard ratio = 1.09 (95% CI: 0.74, 1.60)). In per-protocol analyses, failure probabilities were 35.6% for PIs and 29.2% for NNRTIs (risk difference = 6.4% (95% CI: -6.7, 19.4); hazard ratio = 1.30 (95% CI: 0.80, 2.12)). Within-arm shifts in failure probabilities from ITT to per-protocol analyses were 5.7% for PIs and 10.3% for NNRTIs. Protocol nonadherence was nondifferential across arms, suggesting that possibly better NNRTI efficacy may have been masked by differences in within-arm shifts deriving from differential regimen forgiveness, residual confounding, or chance. A per-protocol approach using inverse-probability-of-censoring weights facilitated evaluation of relationships among adherence, efficacy, and forgiveness applicable to pediatric oral antiretroviral regimens.

Epidemiology of Community-Acquired Acute Kidney Injury Among US Veterans.

RATIONALE & OBJECTIVE: Community-acquired acute kidney injury (CA-AKI) develops outside of the hospital and is the most common form of AKI globally. National estimates of CA-AKI in the United States are absent due to limited availability of laboratory data. This study leverages national data from the Veterans Health Administration (VA) to estimate incidence and risk factors of CA-AKI. STUDY DESIGN: Retrospective cohort study using national VA administrative and laboratory data to assess cumulative CA-AKI incidence. SETTING & PARTICIPANTS: VA primary care patients in 2013-2017 with recorded outpatient serum creatinine (Scr) and no history of chronic kidney disease≥stage 5. PREDICTOR: Sociodemographics, comorbidities, medication use, and health care utilization. OUTCOME: Annual incidence of CA-AKI defined as a≥1.5-fold relative increase in Scr on either a subsequent outpatient Scr or inpatient Scr obtained within ≤24 hours of admission. ANALYTICAL APPROACH: We calculated the relative change in Scr within 12 months of an outpatient Scr value. A Cox model was used to estimate the association between CA-AKI and baseline characteristics, accounting for repeated measurements. RESULTS: Of approximately 2.5 million eligible veterans each year, the cumulative incidence of CA-AKI was approximately 2% annually. Only 27% of CA-AKI was detected at hospital admission. In adjusted analyses, high health care utilization, chronic illness, cancer, rural location, female sex, and use of renin-angiotensin aldosterone system inhibitors or diuretics were associated with increased CA-AKI risk (all, HR>1.20). LIMITATIONS: Limited generalizability of results outside a veteran population, lack of a standardized definition for CA-AKI, and possibility of surveillance bias and misclassification. CONCLUSIONS: CA-AKI affects 1 of every 50 US veterans annually. With less than a third of CA-AKI observed in the inpatient hospital setting, reliance on inpatient evaluation of AKI suggests significant underrecognition and missed opportunities to prevent and manage the long-term consequences of AKI.

Effectiveness of Remdesivir Treatment Protocols Among Patients Hospitalized with COVID-19: A Target Trial Emulation.

BACKGROUND: Remdesivir is recommended for certain hospitalized patients with COVID-19. However, these recommendations are based on evidence from small randomized trials, early observational studies, or expert opinion. Further investigation is needed to better inform treatment guidelines with regard to the effectiveness of remdesivir among these patients. METHODS: We emulated a randomized target trial using chargemaster data from 333 US hospitals from 1 May 2020 to 31 December 2021. We compared three treatment protocols: remdesivir within 2 days of hospital admission, no remdesivir within the first 2 days of admission, and no remdesivir ever. We used baseline comorbidities recorded from encounters up to 12 months before admission and identified the use of in-hospital medications, procedures, and oxygen supplementation from charges. We estimated the cumulative incidence of mortality or mechanical ventilation/extracorporeal membrane oxygenation with an inverse probability of censoring weighted estimator. We conducted analyses in the total population as well as in subgroups stratified by level of oxygen supplementation. RESULTS: A total of 274,319 adult patients met the eligibility criteria for the study. Thirty-day in-hospital mortality risk differences for patients adhering to the early remdesivir protocol were -3.1% (95% confidence interval = -3.5%, -2.7%) compared to no early remdesivir and -3.7% (95% confidence interval -4.2%, -3.2%) compared to never remdesivir, with the strongest effect in patients needing high-flow oxygen. For mechanical ventilation/extracorporeal membrane oxygenation, risk differences were minimal. CONCLUSIONS: We estimate that, among hospitalized patients with COVID-19, remdesivir treatment within 2 days of admission reduced 30-day in-hospital mortality, particularly for patients receiving supplemental oxygen on the day of admission.

G-estimation of structural nested mean models for interval-censored data using pseudo-observations.

Two large-scale randomized clinical trials compared fenofibrate and placebo in diabetic patients with pre-existing retinopathy (FIELD study) or risk factors (ACCORD trial) on an intention-to-treat basis and reported a significant reduction in the progression of diabetic retinopathy in the fenofibrate arms. However, their analyses involved complications due to intercurrent events, that is, treatment-switching and interval-censoring. This article addresses these problems involved in estimation of causal effects of long-term use of fibrates in a cohort study that followed patients with type 2 diabetes for 8 years. We propose structural nested mean models (SNMMs) of time-varying treatment effects and pseudo-observation estimators for interval-censored data. The first estimator for SNMMs uses a nonparametric maximum likelihood estimator (MLE) as a pseudo-observation, while the second estimator is based on MLE under a parametric piecewise exponential distribution. Through numerical studies with real and simulated datasets, the pseudo-observations estimators of causal effects using the nonparametric Wellner-Zhan estimator perform well even under dependent interval-censoring. Its application to the diabetes study revealed that the use of fibrates in the first 4 years reduced the risk of diabetic retinopathy but did not support its efficacy beyond 4 years.

Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review.

PURPOSE: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. METHODS: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. RESULTS: Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. CONCLUSIONS: Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.

Azithromycin use increases the risk of sudden cardiac death in patients with hemodialysis-dependent kidney failure.

Azithromycin is an antibiotic with QT-prolonging potential commonly prescribed to individuals receiving hemodialysis. Hemodialysis patients have a high prevalence of clinical conditions, such as structural heart disease, that can enhance the pro-arrhythmic effects azithromycin, but were excluded from prior investigations evaluating the cardiac safety of azithromycin. Using data from the United States Renal Data System (2007-2017), we conducted two cohort studies to examine the cardiac safety of azithromycin relative to amoxicillin-based antibiotics (amoxicillin, amoxicillin/clavulanic acid) and levofloxacin (a fluoroquinolone antibiotic known to prolong the QT-interval) in the hemodialysis population. The primary outcome was five-day sudden cardiac death. Using inverse probability of treatment weighted survival models, we estimated hazard ratios, risk differences, and 95% confidence intervals. The azithromycin vs. amoxicillin-based antibiotic cohort included 282,899 patients and 725,431 treatment episodes (381,306 azithromycin and 344,125 amoxicillin-based episodes). Azithromycin vs. amoxicillin-based antibiotic treatment was associated with higher relative and absolute risks of sudden cardiac death, weighted hazard ratio of 1.70 (95% Confidence Interval, 1.36 to 2.11) and weighted risk difference per 100,000 treatment episodes of 25.0 (15.5 to 36.5). The azithromycin vs. levofloxacin cohort included 245,143 patients and 554,557 treatment episodes (387,382 azithromycin and 167,175 levofloxacin episodes). Azithromycin vs. levofloxacin treatment was associated with lower relative and absolute risks of sudden cardiac death, weighted hazard ratio of 0.79 (0.64 to 0.96) and weighted risk difference per 100,000 treatment episodes of -18.9 (-35.5 to -3.8). Thus, when selecting among azithromycin, levofloxacin, and amoxicillin-based antibiotics, clinicians should weigh the relative antimicrobial benefits of these drugs against their potential cardiac risks.

Proton pump inhibitors may enhance the risk of citalopram- and escitalopram-associated sudden cardiac death among patients receiving hemodialysis.

PURPOSE: Polypharmacy is common in the hemodialysis population and increases the likelihood that patients will be exposed to clinically significant drug-drug interactions. Concurrent use of proton pump inhibitors (PPIs) with citalopram or escitalopram may potentiate the QT-prolonging effects of these selective serotonin reuptake inhibitors through pharmacodynamic and/or pharmacokinetic interactions. METHODS: We conducted a retrospective cohort study using data from the U.S. Renal Data System (2007-2017) and a new-user design to examine the differential risk of sudden cardiac death (SCD) associated with citalopram/escitalopram initiation vs. sertraline initiation in the presence and absence of PPI use among adults receiving hemodialysis. We studied 72 559 patients:14 983 (21%) citalopram/escitalopram initiators using a PPI; 26 503 (36%) citalopram/escitalopram initiators not using a PPI;10 779 (15%) sertraline initiators using a PPI; and 20 294 (28%) sertraline initiators not using a PPI (referent). The outcome of interest was 1-year SCD. We used inverse probability of treatment weighted survival models to estimate weighted hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Compared with sertraline initiators not using a PPI, citalopram/escitalopram initiators using a PPI had the numerically highest risk of SCD (HR [95% CI] = 1.31 [1.11-1.54]), followed by citalopram/escitalopram initiators not using a PPI (HR [95% CI] = 1.22 [1.06-1.41]). Sertraline initiators using a PPI had a similar risk of SCD compared with those not using a PPI (HR [95% CI] = 1.03 [0.85-1.26]). CONCLUSIONS: Existing PPI use may elevate the risk of SCD associated with citalopram or escitalopram initiation among hemodialysis patients.

Visualizations throughout pharmacoepidemiology study planning, implementation, and reporting.

Transparency is increasingly promoted to instill trust in nonrandomized studies using real-world data. Graphics and data visualizations support transparency by aiding communication and understanding, and can inform study design and analysis decisions. However, other than graphical representation of a study design and flow diagrams (e.g., a Consolidated Standards of Reporting Trials [CONSORT] like diagram), specific standards on how to maximize validity and transparency with visualization are needed. This paper provides guidance on how to use visualizations throughout the life cycle of a pharmacoepidemiology study-from initial study design to final report-to facilitate rationalized and transparent decision-making about study design and implementation, and clear communication of study findings. Our intent is to help researchers align their practices with current consensus statements on transparency.

Use of negative control outcomes to assess the comparability of patients initiating lipid-lowering therapies.

PURPOSE: Clinical trials have demonstrated efficacy of proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) in reducing risk of cardiovascular disease events, but effectiveness in routine clinical care has not been well-studied. We used negative control outcomes to assess potential confounding in an observational study of PCSK9i versus ezetimibe or high-intensity statin. METHODS: Using commercial claims, we identified U.S. adults initiating PCSK9i, ezetimibe, or high-intensity statin in 2015-2018, with other lipid-lowering therapy (LLT) use in the year prior (LLT cohort) or atherosclerotic cardiovascular disease (ASCVD) in the past 90 days (ASCVD cohort). We compared initiators of PCSK9i to ezetimibe and high-intensity statin by estimating one-year risks of negative control outcomes influenced by frailty or health-seeking behaviors. Inverse probability of treatment and censoring weighted estimators of risk differences (RDs) were used to evaluate residual confounding after controlling for covariates. RESULTS: PCSK9i initiators had lower one-year risks of negative control outcomes associated with frailty, such as decubitus ulcer in the ASCVD cohort (PCSK9i vs. high-intensity statin RD = -3.5%, 95% confidence interval (CI): -4.6%, -2.5%; PCSK9i vs. ezetimibe RD = -1.3%, 95% CI: -2.1%, -0.6%), with similar but attenuated associations in the LLT cohort. Lower risks of accidents and fractures were also observed for PCSK9i, varying by cohort. Risks were similar for outcomes associated with health-seeking behaviors, although trended higher for PCSK9i in the ASCVD cohort. CONCLUSIONS: Observed associations suggest lower frailty and potentially greater health-seeking behaviors among PCSK9i initiators, particularly those with a recent ASCVD diagnosis, with the potential to bias real-world analyses of treatment effectiveness.

Informing Healthcare Decisions with Observational Research Assessing Causal Effect. An Official American Thoracic Society Research Statement.

Rationale: Decisions in medicine are made on the basis of knowledge and reasoning, often in shared conversations with patients and families in consideration of clinical practice guideline recommendations, individual preferences, and individual goals. Observational studies can provide valuable knowledge to inform guidelines, decisions, and policy.Objectives: The American Thoracic Society (ATS) created a multidisciplinary ad hoc committee to develop a research statement to clarify the role of observational studies-alongside randomized controlled trials (RCTs)-in informing clinical decisions in pulmonary, critical care, and sleep medicine.Methods: The committee examined the strengths of observational studies assessing causal effects, how they complement RCTs, factors that impact observational study quality, perceptions of observational research, and, finally, the practicalities of incorporating observational research into ATS clinical practice guidelines.Measurements and Main Results: There are strengths and weakness of observational studies as well as RCTs. Observational studies can provide evidence in representative and diverse patient populations. Quality observational studies should be sought in the development of ATS clinical practice guidelines, and medical decision-making in general, when 1) no RCTs are identified or RCTs are appraised as being of low- or very low-quality (replacement); 2) RCTs are of moderate quality because of indirectness, imprecision, or inconsistency, and observational studies mitigate the reason that RCT evidence was downgraded (complementary); or 3) RCTs do not provide evidence for outcomes that a guideline committee considers essential for decision-making (e.g., rare or long-term outcomes; "sequential").Conclusions: Observational studies should be considered in developing clinical practice guidelines and in making clinical decisions.

G-estimation of structural nested mean models for competing risks data using pseudo-observations.

This article provides methods of causal inference for competing risks data. The methods are formulated as structural nested mean models of causal effects directly related to the cumulative incidence function or subdistribution hazard, which reflect the survival experience of a subject in the presence of competing risks. The effect measures include causal risk differences, causal risk ratios, causal subdistribution hazard ratios, and causal effects of time-varying exposures. Inference is implemented by g-estimation using pseudo-observations, a technique to handle censoring. The finite-sample performance of the proposed estimators in simulated datasets and application to time-varying exposures in a cohort study of type 2 diabetes are also presented.

Estimating the Effectiveness of Rotavirus Vaccine Schedules.

BACKGROUND: Important questions exist regarding the comparative effectiveness of alternative childhood vaccine schedules; however, optimal approaches to studying this complex issue are unclear. METHODS: We applied methods for studying dynamic treatment regimens to estimate the comparative effectiveness of different rotavirus vaccine (RV) schedules for preventing acute gastroenteritis-related emergency department (ED) visits or hospitalization. We studied the effectiveness of six separate protocols: one- and two-dose monovalent rotavirus vaccine (RV1); one-, two-, and three-dose pentavalent rotavirus vaccine (RV5); and no RV vaccine. We used data on all infants to estimate the counterfactual cumulative risk for each protocol. Infants were censored when vaccine receipt deviated from the protocol. Inverse probability of censoring-weighted estimation addressed potentially informative censoring by protocol deviations. A nonparametric group-based bootstrap procedure provided statistical inference. RESULTS: The method yielded similar 2-year effectiveness estimates for the full-series protocols; weighted risk difference estimates comparing unvaccinated children to those adherent to either full-series (two-dose RV1, three-dose RV5) corresponded to four fewer hospitalizations and 12 fewer ED visits over the 2-year period per 1,000 children. We observed dose-response relationships, such that additional doses further reduced risk of acute gastroenteritis. Under a theoretical intervention to fully vaccinate all children, the 2-year risk differences comparing full to observed adherence were 0.04% (95% CI = 0.03%, 0.05%) for hospitalizations and 0.17% (95% CI = 0.14%, 0.19%) for ED visits. CONCLUSIONS: The proposed approach can generate important evidence about the consequences of delaying or skipping vaccine doses, and the impact of interventions to improve vaccine schedule adherence.

Mortality in US Hemodialysis Patients Following Exposure to Wildfire Smoke.

BACKGROUND: Wildfires are increasingly a significant source of fine particulate matter (PM2.5), which has been linked to adverse health effects and increased mortality. ESKD patients are potentially susceptible to this environmental stressor. METHODS: We conducted a retrospective time-series analysis of the association between daily exposure to wildfire PM2.5 and mortality in 253 counties near a major wildfire between 2008 and 2012. Using quasi-Poisson regression models, we estimated rate ratios (RRs) for all-cause mortality on the day of exposure and up to 30 days following exposure, adjusted for background PM2.5, day of week, seasonality, and heat. We stratified the analysis by causes of death (cardiac, vascular, infectious, or other) and place of death (clinical or nonclinical setting) for differential PM2.5 exposure and outcome classification. RESULTS: We found 48,454 deaths matched to the 253 counties. A 10-µg/m3 increase in wildfire PM2.5 associated with a 4% increase in all-cause mortality on the same day (RR, 1.04; 95% confidence interval [95% CI], 1.01 to 1.07) and 7% increase cumulatively over 30 days following exposure (RR, 1.07; 95% CI, 1.01 to 1.12). Risk was elevated following exposure for deaths occurring in nonclinical settings (RR, 1.07; 95% CI, 1.02 to 1.12), suggesting modification of exposure by place of death. "Other" deaths (those not attributed to cardiac, vascular, or infectious causes) accounted for the largest portion of deaths and had a strong same-day effect (RR, 1.08; 95% CI, 1.03 to 1.12) and cumulative effect over the 30-day period. On days with a wildfire PM2.5 contribution >10 µg/m3, exposure accounted for 8.4% of mortality. CONCLUSIONS: Wildfire smoke exposure was positively associated with all-cause mortality among patients receiving in-center hemodialysis.