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.

Comparative analysis of tabelecleucel and current treatment in patients with Epstein-Barr virus-positive post-transplant lymphoproliferative disease following hematopoietic cell transplant or solid organ transplant.

Aims: With recent European Union marketing authorization, tabelecleucel is the first off-the-shelf, allogeneic Epstein-Barr virus (EBV)-specific T-cell immunotherapy approved for the treatment of relapsed/refractory EBV-positive post-transplant lymphoproliferative disease (EBV+ PTLD). In the absence of a control arm, real-world evidence can provide a comparative benchmark for single-arm studies in ultra-rare populations. This study assessed the treatment effect of tabelecleucel in the single-arm phase 3 ALLELE study (NCT03394365) versus a treatment group from a multinational, multicenter retrospective chart review study (RS002) of patients with EBV+ PTLD.Methods: In ALLELE, patients had disease relapsed/refractory to rituximab ± chemotherapy and received tabelecleucel 2x106 cells/kg on days 1, 8, and 15 in 35-day cycles. Patients in RS002 had disease relapsed/refractory to rituximab ± chemotherapy and received next line of systemic therapy between January 2000 and December 2018. Propensity score-based standardized mortality/morbidity ratio weighting was used to achieve balance between treatment and comparator arms. Kaplan-Meier estimators and Cox regression models were used to compare overall survival (OS) in the re-weighted sample.Results: 30 patients (n = 14 hematopoietic cell transplant [HCT], n = 16 solid organ transplant [SOT]) from ALLELE (data cutoff: November 2021) and 84 patients (n = 36 HCT, n = 48 SOT) from RS002 (data lock: January 2021) were included. Median time from diagnosis to first tabelecleucel dose (ALLELE) or start date of next line of systemic therapy (RS002) was 3.6 months. Tabelecleucel was associated with a substantial OS benefit compared with current treatment, with an unadjusted HR of 0.47 (95% CI 0.25-0.88) and adjusted HR of 0.37 (95% CI 0.20-0.71) when using the start date of the next line of therapy as the index date. Sensitivity analyses yielded consistent results.Conclusions: In this study of real-world data, tabelecleucel was associated with an OS benefit among patients with R/R EBV+ PTLD for whom there is high unmet need.

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 aged ≥66 in US Medicare claims database. We estimated 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 vs. 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.

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.

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.

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.

Impact of the COVID-19 Pandemic on Pediatric Preventive Health Care Among North Carolina Children Enrolled in Medicaid.

BACKGROUND: Children enrolled in private insurance had reduced preventive health care during the coronavirus disease 2019 (COVID-19) pandemic. However, the impact of the pandemic on children enrolled in Medicaid has been minimally described. METHODS: We used an administrative claims database from North Carolina Medicaid to evaluate the rates of well-child visits and immunization administration for children ≤14 months of age, and used a quasi-Poisson regression model to estimate the rate ratio (RR) of each outcome during the pandemic period (3/15/2020 through 3/15/2021) compared with the pre-pandemic period (3/15/2019 through 3/14/2020). RESULTS: We included 83 442 children during the pre-pandemic period and 96 634 children during the pandemic period. During the pre-pandemic period, 405 295 well-child visits and 715 100 immunization administrations were billed; during the pandemic period, 287 285 well-child visits and 457 144 immunization administrations were billed. The rates of well-child visits (RR 0.64; 95% CI, 0.64-0.64) and vaccine administration (RR 0.55; 95% CI, 0.55-0.55) were lower during the pandemic compared with the pre-pandemic period. CONCLUSIONS: The rates of well-child visits and immunization administrations among North Carolina children enrolled in public insurance substantially decreased during the first year of the COVID-19 pandemic.

Trends in Pediatric Emergency and Inpatient Healthcare Use for Mental and Behavioral Health Among North Carolinians During the Early COVID-19 Pandemic.

BACKGROUND: Widespread school closures and health care avoidance during the COVID-19 pandemic led to disruptions in access to pediatric mental health care. METHODS: We conducted a retrospective study of emergency and inpatient administrative claims from privately insured children aged 6-20 years in North Carolina between January 2019 and December 2020. We compared rates of emergency department (ED) visits (per 100 000 person-days) and risks of hospitalizations (per 100 000 persons) with diagnosis codes in each category (mental/behavioral health; suicidal ideation, suicide attempt, and intentional self-harm [SI/SA/ISH]; and social issues) across 3 time periods (pre-pandemic, lockdown, and reopening). We calculated the proportion and 95% confidence intervals (CI) of total ED visits and total hospitalizations attributable to mental/behavioral health and SI/SA/ISH across the 3 time periods. RESULTS: Rates of all categories of ED visits decreased from pre-pandemic to the lockdown period; from pre-pandemic to the reopening period, mental/behavioral health visits decreased but rates of SI/SA/ISH visits were unchanged. The proportion of ED visits attributable to mental/behavioral health increased from 3.5% (95% CI 3.2%-3.7%) pre-pandemic to 4.0% (95% CI 3.7%-4.3%) during reopening, and the proportion of SI/SA/ISH diagnoses increased from 1.6% (95% CI 1.4%-1.8%) pre-pandemic to 2.4% (95% CI 2.1%-2.7%) during the reopening period. Emergency care use for social issues and hospital admissions for mental/behavioral health and SI/SA/ISH diagnoses were unchanged across the study periods. CONCLUSIONS: In the early pandemic, pediatric mental health care and acute suicidal crises accounted for increased proportions of emergency care. During pandemic recovery, understanding the populations most impacted and increasing access to preventative mental health care is critical.

Effects of Adjusting for Instrumental Variables on the Bias and Precision of Propensity Score Weighted Estimators: Analysis Under Complete, Near, and No Positivity Violations.

Purpose: To demonstrate that using an instrumental variable (IV) with monotonicity reduces the accuracy of propensity score (PS) weighted estimators for the average treatment effect (ATE). Methods: Monotonicity in the relationship between a binary IV and a binary treatment variable is an important assumption to identify the ATE for compliers who would only take treatment when encouraged by the IV. We perform theoretical and numerical investigations to study the impact of using the IV that satisfies monotonicity on the PS of treatment in terms of the positivity assumption, which requires that the PS be strictly between 0 and 1, and the accuracy of PS weighted estimators. Two versions of monotonicity that result in one-sided or two-sided noncompliance are considered. Results: The PS adjusting for the IV always violates the positivity assumption when noncompliance occurs in one direction (one-sided noncompliance) and is more extreme than without the IV under two-sided noncompliance. These results are valid if the probability of being encouraged to get treatment and the compliance score, the probability of being a complier, are strictly between 0 and 1. Conclusion: Using a binary IV with monotonicity as a covariate for the PS model makes the estimated PSs unnecessarily extreme, reducing the accuracy of the PS weighted estimators.

Cardiovascular Safety in Postmenopausal Women and Men With Osteoporosis Treated With Denosumab and Zoledronic Acid: A Post-Authorization Safety Study.

Osteoporosis and cardiovascular disease are common in older adults. Treatment of osteoporosis reduces the burden of debilitating fractures; however, it is important to understand the benefit versus risk of treatment. This study evaluates the risk of stroke (ischemic or hemorrhagic) and myocardial infarction (MI) among postmenopausal women and men initiating osteoporosis treatment with denosumab (receptor activator of nuclear factor κB ligand [RANKL] inhibitor) or zoledronic acid (bisphosphonate) between October 2010 and June 2019. A retrospective cohort study employing the new user/active comparator design was conducted. Analyses were conducted separately in two national US commercial databases, MarketScan® and Optum® for reproducibility. Inverse probability of treatment and censoring weighting was employed to control for confounding and informative censoring. Cumulative risks at 6-month, 12-month, and 36-month time points were calculated and adjusted risk ratios and differences (with 95% confidence intervals [CIs]) were estimated. In MarketScan® and Optum® databases, 96,611 and 73,127 patients met all study eligibility criteria, respectively. At 36 months, the risk ratio estimates (zoledronic acid referent group) were 1.22 (95% CI, 0.77-1.66) and 0.97 (95% CI, 0.63-1.32) for MI and 1.00 (95% CI, 0.61-1.40) and 0.87 (95% CI, 0.56-1.17) for stroke in MarketScan and Optum, respectively. Most of the treatment associations across the other time periods and outcomes also had 95% CIs including the null value. In these large samples of real-world US patients, no increased risk in MI and stroke were identified for up to 36 months of treatment in denosumab users compared with zoledronic acid users. © 2023 Amgen. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

In-Person Instruction and Educational Outcomes of K-8 Students During the COVID-19 Pandemic.

OBJECTIVES: Quantify the relationship between district policy permitting in-person instruction and educational outcomes during the 2020 to 2021 academic year for kindergarten through eighth grade students. METHODS: An ecological, repeated cross-sectional analysis of grade-level proficiency of students enrolled in public school districts in North Carolina (n = 115 school districts) was conducted. Univariate and multivariate analyses were performed to evaluate the association between the proportion of the school year a district spent in-person and 2020 to 2021 end-of-year student proficiency in the district. We then fit a multivariable linear regression model, weighted by district size, and adjusted for district-level 2018 to 2019 proficiency and district-level factors (rural or urban, area deprivation). RESULTS: Compared to 2018 to 2019, there was a 12.1% decrease (95% confidence interval [CI]: 16.8-19.3) in mathematics and an 18.1% decrease (95% CI: 10.8-13.4) in reading proficiency across the state at the end of 2020 to 2021. Compared to a district that remained entirely remote for the 2020 to 2021 school year, a district offering full in-person instruction had 12% (95% CI: 11%-12.9%) and 4.1% (95% CI: 3.5%-4.8%) more students achieve grade-level proficiency in mathematics and reading, respectively. In-person instruction was associated with greater increases in mathematics proficiency than reading, and greater increases in elementary-level students' proficiency than middle school-level. CONCLUSIONS: The proportion of students achieving grade-level proficiency in 2020 to 2021 fell below prepandemic levels at each evaluated time point in the academic year. Increased time spent in-person by a school district was associated with an increased proportion of students achieving grade-level end-of-grade proficiency in both mathematics and reading.

Utilization and Impact of Symptomatic and Exposure SARS-CoV-2 Testing in K-12 Schools.

OBJECTIVES: The Centers for Disease Control and Prevention recommend that schools can offer severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic (on-demand) testing for students and staff with coronavirus disease 2019 symptoms or exposures. Data related to the uptake, implementation, and effect of school-associated on-demand diagnostic testing have not been described. METHODS: The Rapid Acceleration of Diagnostics Underserved Populations Return to School program provided resources to researchers to implement on-demand SARS-CoV-2 testing in schools. This study describes the strategies used and uptake among the different testing programs. Risk of positivity was compared for symptomatic and exposure testing during the δ and ο variant periods. We estimated the number of school absence days saved with school-based diagnostic testing. RESULTS: Of the 16 eligible programs, 7 provided school-based on-demand testing. The number of persons that participated in these testing programs is 8281, with 4134 (49.9%) receiving >1 test during the school year. Risk of positivity was higher for symptomatic testing compared with exposure testing and higher during the ο variant predominant period compared with the δ variant predominant period. Overall, access to testing saved an estimated 13 806 absent school days. CONCLUSIONS: School-based on-demand SARS-CoV-2 testing was used throughout the school year, and nearly half the participants accessed testing on more than 1 occasion. Future studies should work to understand participant preferences around school-based testing and how these strategies can be used both during and outside of pandemics.

Building School-Academic Partnerships to Implement COVID-19 Testing in Underserved Populations.

OBJECTIVE: In April 2021, the US government made substantial investments in students' safe return to school by providing resources for school-based coronavirus disease 2019 (COVID-19) mitigation strategies, including COVID-19 diagnostic testing. However, testing uptake and access among vulnerable children and children with medical complexities remained unclear. METHODS: The Rapid Acceleration of Diagnostics Underserved Populations program was established by the National Institutes of Health to implement and evaluate COVID-19 testing programs in underserved populations. Researchers partnered with schools to implement COVID-19 testing programs. The authors of this study evaluated COVID-19 testing program implementation and enrollment and sought to determine key implementation strategies. A modified Nominal Group Technique was used to survey program leads to identify and rank testing strategies to provide a consensus of high-priority strategies for infectious disease testing in schools for vulnerable children and children with medical complexities. RESULTS: Among the 11 programs responding to the survey, 4 (36%) included prekindergarten and early care education, 8 (73%) worked with socioeconomically disadvantaged populations, and 4 focused on children with developmental disabilities. A total of 81 916 COVID-19 tests were performed. "Adapting testing strategies to meet the needs, preferences, and changing guidelines," "holding regular meetings with school leadership and staff," and "assessing and responding to community needs" were identified as key implementation strategies by program leads. CONCLUSIONS: School-academic partnerships helped provide COVID-19 testing in vulnerable children and children with medical complexities using approaches that met the needs of these populations. Additional work is needed to develop best practices for in-school infectious disease testing in all children.

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.

Controlling for Differential Regression-To-The-Mean via Propensity Scores: A Simulation Study.

Purpose: Regression-to-the-mean (RTM) is a statistical phenomenon that may occur in epidemiologic studies where inclusion in the study cohort is contingent upon experiencing a laboratory/clinical measurement beyond a defined threshold. When differential across treatment groups, RTM could bias the final study estimate. This poses substantial challenges in observational studies that index patients upon experiencing extreme laboratory or clinical values. Our objective was to investigate propensity score-based methods as a tool for mitigating this source of bias via simulation. Methods: We simulated a noninterventional comparative effectiveness study, comparing treatment with romiplostim to standard-of-care therapies for immune thrombocytopenia (ITP), a disease characterized by low platelet counts. Platelet counts were generated from normal distributions according to the underlying ITP severity, a strong confounder of treatment and outcome. Patients were assigned treatment probabilities based upon ITP severity, which created varied levels of differential and non-differential RTM. Treatments were compared via the difference in median platelet counts during 23 weeks of follow-up. We calculated four summary metrics of the platelet counts measured prior to cohort entry and built six propensity score models to adjust for those variables. We adjusted for these summary metrics using inverse probability of treatment weights. Results: Across all simulated scenarios, propensity score adjustment reduced bias and increased precision of the treatment effect estimator. Adjusting for combinations of the summary metrics was most effective at reducing bias. Adjusting for the mean of prior platelet counts or the difference between the cohort-qualifying platelet count and the largest prior count eliminated the most bias when assessed individually. Conclusion: These results suggest that differential RTM could be reasonably addressed by propensity score models with summaries of historical laboratory values. This approach can be easily applied to any comparative effectiveness or safety study, though investigators should carefully consider the best summary metric for their data.

QT-Prolonging Antibiotics, Serum-to-Dialysate Potassium Gradient, and Risk of Sudden Cardiac Death Among Patients Receiving Maintenance Hemodialysis.

Rationale & Objective: Treatment with certain QT interval-prolonging antibiotics is associated with a higher risk of sudden cardiac death among individuals with hemodialysis-dependent kidney failure. Concurrent exposure to large serum-to-dialysate potassium gradients, which promote large potassium shifts, may augment the proarrhythmic effects of these medications. The primary objective of this study was to examine whether the serum-to-dialysate gradient modifies the cardiac safety of azithromycin, and separately, levofloxacin/moxifloxacin. Study Design: Retrospective observational cohort study using a new-user study design. Setting & Population: Adult in-center hemodialysis patients with Medicare coverage in the US Renal Data System (2007-2017). Exposure: Initiation of azithromycin (or levofloxacin/moxifloxacin) as compared to amoxicillin-based antibiotics (exposure). Serum-to-dialysate potassium gradient (effect modifier). Individual patients could contribute multiple study antibiotic treatment episodes to the analyses. Outcomes: Sudden cardiac death (14 days). Analytical Approach: Inverse probability of treatment-weighted survival models to estimate HRs and robust 95% CIs. Results: The azithromycin versus amoxicillin-based antibiotic cohort included 89,379 unique patients with 113,516 azithromycin and 103,493 amoxicillin-based treatment episodes. Azithromycin versus amoxicillin-based antibiotic treatment was associated with a higher risk of sudden cardiac death overall, HR, 1.68; 95% CI, 1.31-2.16. The risk was numerically higher when the baseline serum-to-dialysate potassium gradient was ≥3 mEq/L compared with <3 mEq/L (HR, 2.22; 95% CI, 1.46-3.40 vs HR, 1.43; 95% CI. 1.04-1.96, P interaction = 0.07). Analogous analyses in a respiratory fluoroquinolone (levofloxacin/moxifloxacin) versus amoxicillin-based antibiotic cohort with 79,449 unique patients and 65,959 respiratory fluoroquinolone and 103,776 amoxicillin-based treatment episodes yielded similar results. Limitations: Residual confounding. Conclusions: Although treatment with azithromycin and, separately, respiratory fluoroquinolones were each associated with a heightened risk of sudden cardiac death, this risk was augmented in the setting of larger serum-to-dialysate potassium gradients. Minimizing the potassium gradient may be an approach to reduce the cardiac risk of these antibiotics.

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.

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.