The long-term effects of dapagliflozin in chronic kidney disease: a time-to-event analysis.

BACKGROUND AND HYPOTHESIS: Chronic kidney disease (CKD) presents a significant clinical and economic burden to healthcare systems worldwide, which increases considerably with progression towards kidney failure. The DAPA-CKD trial demonstrated that patients with or without type 2 diabetes (T2D) who were treated with dapagliflozin experienced slower progression of CKD versus placebo. Understanding the effect of long-term treatment with dapagliflozin on the timing of kidney failure beyond trial follow-up can assist informed decision-making by healthcare providers and patients. The study objective was therefore to extrapolate the outcome-based clinical benefits of treatment with dapagliflozin in patients with CKD via a time-to-event analysis using trial data. METHODS: Patient-level data from the DAPA-CKD trial were used to parameterise a closed cohort-level partitioned survival model that predicted time-to-event for key trial endpoints (kidney failure, all-cause mortality, sustained decline in kidney function, and hospitalisation for heart failure). Data were pooled with a subpopulation of the DECLARE-TIMI 58 trial to create a combined CKD population spanning a range of CKD stages; a parallel survival analysis was conducted in this population. RESULTS: In the DAPA-CKD and pooled CKD populations, treatment with dapagliflozin delayed time to first event for kidney failure, all-cause mortality, sustained decline in kidney function, and hospitalisation for heart failure. Attenuation of CKD progression was predicted to slow the time to kidney failure by 6.6 years (dapagliflozin: 25.2, 95%CI: 19.0-31.5; standard therapy: 18.5, 95%CI: 14.7-23.4) in the DAPA-CKD population. A similar result was observed in the pooled CKD population with an estimated delay of 6.3 years (dapagliflozin: 36.0, 95%CI: 31.9-38.3; standard therapy: 29.6, 95%CI: 25.5-34.7). CONCLUSION: Treatment with dapagliflozin over a lifetime time horizon may considerably delay the mean time to adverse clinical outcomes for patients who would go on to experience them, including those at modest risk of progression.

Associations between the EQ-5D-5L and exacerbations of chronic obstructive pulmonary disease in the ETHOS trial.

PURPOSE: Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with deteriorating health and health-related quality of life (HRQoL) among people with COPD during and after events. HRQoL data are key to evaluating treatment cost-effectiveness and informing reimbursement decisions in COPD. EuroQoL 5-dimension 5-level (EQ-5D-5L) utility scores, based on various HRQoL measures, are used in economic evaluations of pharmacotherapy. These analyses estimated associations between EQ-5D-5L utility scores and exacerbations (new and previous) in patients with moderate-to-very severe COPD. METHODS: Longitudinal mixed models for repeated measures (MMRM), adjusted for time and treatment, were conducted using data from the ETHOS study (NCT02465567); models regressed EQ-5D-5L on current and past exacerbations that occurred during the study, adjusting for other patient reported outcomes and clinical factors. RESULTS: Based on the simplest covariate adjusted model (adjusted for current exacerbations and number of previous exacerbations during the study), a current moderate exacerbation was associated with an EQ-5D-5L disutility of 0.055 (95% confidence interval: 0.048, 0.062) with an additional disutility of 0.035 (0.014, 0.055) if the exacerbation was severe. After resolving, each prior exacerbation was associated with a disutility that persisted for the remainder of the study (moderate exacerbation, 0.014 [0.011, 0.016]; further disutility for severe exacerbation, 0.011 [0.003, 0.018]). CONCLUSION: An EQ-5D-5L disutility of 0.090 was associated with a current severe exacerbation in ETHOS. Our findings suggest incorporating the effects of current, recently resolved, and cumulative exacerbations into economic models when estimating benefits and costs of COPD pharmacotherapy, as exacerbations have both acute and persistent effects.

A first step towards best practice recommendations for the design and statistical analyses of pragmatic clinical trials: A modified Delphi approach.

AIM: Pragmatic clinical trials (PCTs) are randomized trials implemented through routine clinical practice, where design parameters of traditional randomized controlled trials are modified to increase generalizability. However, this may introduce statistical challenges. We aimed to identify these challenges and discuss possible solutions leading to best practice recommendations for the design and analysis of PCTs. METHODS: A modified Delphi method was used to reach consensus among a panel of 11 experts in clinical trials and statistics. Statistical issues were identified in a focused literature review and aggregated with insights and possible solutions from experts collected through a series of survey iterations. Issues were ranked according to their importance. RESULTS: Twenty-seven articles were included and combined with experts' insight to generate a list of issues categorized into participants, recruiting sites, randomization, blinding and intervention, outcome (selection and measurement) and data analysis. Consensus was reached about the most important issues: risk of participants' attrition, heterogeneity of "usual care" across sites, absence of blinding, use of a subjective endpoint and data analysis aligned with the trial estimand. Potential issues should be anticipated and preferably be addressed in the trial protocol. The experts provided solutions regarding data collection and data analysis, which were considered of equal importance. DISCUSSION: A set of important statistical issues in PCTs was identified and approaches were suggested to anticipate and/or minimize these through data analysis. Any impact of choosing a pragmatic design feature should be gauged in the light of the trial estimand.

Relationship between risk, cumulative burden of exacerbations and mortality in patients with COPD: modelling analysis using data from the ETHOS study.

BACKGROUND: The major drivers of cost-effectiveness for chronic obstructive pulmonary disease (COPD) therapies are the occurrence of exacerbations and deaths. Exacerbations, including acute and long-term events, can cause worsening of COPD and lead to an increased risk of further exacerbations, and ultimately may elevate the risk of death. In contrast to this, health economic models are based on COPD severity progression. In this post hoc analysis of the ETHOS study, we focus on the progression of COPD due to exacerbations and deaths. METHODS: We fitted semi-parametric and fully parametric multi-state Markov models with the following five progressive states: State 1, no exacerbation; State 2, 1 moderate exacerbation; State 3, ≥ 2 moderate exacerbations; State 4, ≥ 1 severe exacerbations; State 5, death. The models only allowed a patient to transition to a worsened health state, and transitions did not necessarily have to be to the next adjacent state. We used the multi-state models to analyse data from ETHOS, a phase III, 52-week study assessing the efficacy and safety of triple therapy with budesonide/glycopyrronium/formoterol fumarate dihydrate in moderate-to-very severe COPD. RESULTS: The Weibull multi-state Markov model showed good fit of the data. In line with clinical evidence, we found a higher mortality risk after a severe exacerbation (11.4-fold relative ratio increase [95% CI, 7.7-17.0], 6.4-fold increase [95% CI, 3.8-10.8] and 5.4-fold increase [95% CI, 2.9-10.3] relative to no exacerbations, 1 moderate exacerbation or ≥ 2 moderate exacerbations, respectively). One moderate exacerbation increased mortality risk 1.8-fold (95% CI, 1.1-2.9) vs no exacerbations. We also found a higher risk of severe exacerbation and mortality following ≥ 2 moderate exacerbations. CONCLUSION: Multi-state modelling of patients with COPD in ETHOS found an acute and chronic effect of severe exacerbations on mortality risk. Risk was also increased after a moderate exacerbation. Clinical management with effective pharmacotherapies should be optimised to avoid even moderate exacerbations. Modelling with exacerbations could be an alternative to current COPD models focused on disease progression. TRIAL REGISTRATION: NCT02465567.

Comparison of Parametric Survival Extrapolation Approaches Incorporating General Population Mortality for Adequate Health Technology Assessment of New Oncology Drugs.

OBJECTIVES: Survival extrapolation of trial outcomes is required for health economic evaluation. Generally, all-cause mortality (ACM) is modeled using standard parametric distributions, often without distinguishing disease-specific/excess mortality and general population background mortality (GPM). Recent National Institute for Health and Care Excellence guidance (Technical Support Document 21) recommends adding GPM hazards to disease-specific/excess mortality hazards in the log-likelihood function ("internal additive hazards"). This article compares alternative extrapolation approaches with and without GPM adjustment. METHODS: Survival extrapolations using the internal additive hazards approach (1) are compared to no GPM adjustment (2), applying GPM hazards once ACM hazards drop below GPM hazards (3), adding GPM hazards to ACM hazards (4), and proportional hazards for ACM versus GPM hazards (5). The fit, face validity, mean predicted life-years, and corresponding uncertainty measures are assessed for the active versus control arms of immature and mature (30- and 75-month follow-up) multiple myeloma data and mature (64-month follow-up) breast cancer data. RESULTS: The 5 approaches yielded considerably different outcomes. Incremental mean predicted life-years vary most in the immature multiple myeloma data set. The lognormal distribution (best statistical fit for approaches 1-4) produces survival increments of 3.5 (95% credible interval: 1.4-5.3), 8.5 (3.1-13.0), 3.5 (1.3-5.4), 2.9 (1.1-4.5), and 1.6 (0.4-2.8) years for approaches 1 to 5, respectively. Approach 1 had the highest face validity for all data sets. Uncertainty over parametric distributions was comparable for GPM-adjusted approaches 1, 3, and 4, and much larger for approach 2. CONCLUSION: This study highlights the importance of GPM adjustment, and particularly of incorporating GPM hazards in the log-likelihood function of standard parametric distributions.

Assessing the Influence of Subsequent Immunotherapy on Overall Survival in Patients with Unresectable Stage III Non-Small Cell Lung Cancer from the PACIFIC Study.

BACKGROUND: Historically, the standard of care for patients with unresectable, Stage III non-small cell lung cancer had been concurrent chemoradiotherapy. However, outcomes had been poor, with approximately 15% to 32% of patients alive at 5 years. In the placebo-controlled Phase III A PACIFIC trial, consolidation treatment with durvalumab after concurrent chemoradiotherapy significantly improved overall survival (OS) and progression-free survival in patients with unresectable, Stage III non-small cell lung cancer, establishing this regimen as a new standard of care in this setting. In the PACIFIC trial, crossover between treatment arms (durvalumab or placebo) was not permitted. However, after discontinuation from study treatment, patients from both arms of PACIFIC could switch to subsequent anticancer therapy, including durvalumab and other immunotherapies, which is known to influence standard intention-to-treat analysis of OS, potentially underestimating the effect of an experimental drug. Moreover, the introduction of immunotherapies has demonstrated marked improvements in the postprogression, metastatic non-small cell lung cancer setting. OBJECTIVE: To examine the influence of subsequent immunotherapy on OS in the PACIFIC trial. METHODS: Both a Rank Preserving Structural Failure Time Model (RPSFTM) and modified 2-stage method were used. RPSFTM assumes that a patient's survival time with no immunotherapy (counterfactual survival time) is equal to the observed time influenced by immunotherapy, multiplied by an acceleration factor, plus the time not influenced. The modified 2-stage method estimates the effect of immunotherapy by comparing postsubsequent-treatment-initiation survival times between patients with and without subsequent immunotherapy. In both models, OS was adjusted to reflect a hypothetical scenario in which no patients received subsequent immunotherapy. RPSFTM was also used for scenarios in which subsequent immunotherapy was received by increasing proportions of placebo patients but none of the durvalumab patients. RESULTS: In the intention-to-treat analysis (3-year follow-up), durvalumab improved OS versus placebo (stratified hazard ratio = 0.69; 95% CI, 0.55-0.86). Overall, 10% and 27% of durvalumab and placebo patients, respectively, received subsequent immunotherapy. With subsequent immunotherapy removed from both arms, estimated hazard ratio was 0.66 (95% CI, 0.53-0.84) with RPSFTM and 0.68 (95% CI, 0.54-0.85) with the modified 2-stage method. With subsequent immunotherapy removed from the durvalumab arm only (RPSFTM), estimated hazard ratio increased as the proportion of placebo patients receiving subsequent immunotherapy increased, up to 0.75 (95% CI, 0.60-0.94) maximum (assuming all placebo patients with subsequent treatment received immunotherapy). CONCLUSIONS: Results were consistent with the intention-to-treat analysis, supporting the conclusion that durvalumab after chemoradiotherapy provides substantial OS benefit in patients with Stage III, unresectable non-small cell lung cancer. ClinicalTrials.gov identifier: NCT02125461 (Curr Ther Res Clin Exp. 2021; 82:XXX-XXX).

Extrapolating Survival Data Using Historical Trial-Based a Priori Distributions.

OBJECTIVES: To show how clinical trial data can be extrapolated using historical trial data-based a priori distributions. METHODS: Extrapolations based on 30-month pivotal multiple myeloma trial data were compared with 75-month data from the same trial. The 30-month data represent a typical decision-making scenario where early results from a clinical trial are extrapolated. Mature historical trial data with the same comparator as in the pivotal trial were incorporated in 2 stages. First, the parametric distribution selection was based on the historical trial data. Second, the shape parameter estimate of the historical trial was used to define an informative a priori distribution for the shape of the 30-month pivotal trial data. The method was compared with standard approaches, fitting parametric distributions to the 30-month data with noninformative prior. The predicted survival of each method was compared with the observed survival (ΔAUC) in the 75-month trial data. RESULTS: The Weibull had the best fit to the historical trial and the log-normal to the 30-month pivotal trial data. The ΔAUC of the Weibull with informative priors was considerably smaller compared with the standard Weibull. Also, the predicted median survival based on the Weibull with informative priors was more accurate (melphalan and prednisone [MP] 40 months, and bortezomib [V] combined with MP [VMP] 62 months) than based on the standard Weibull (MP 45 months and VMP 72 months) when compared with the observed median (MP 41.3 months and VMP 56.4 months). CONCLUSIONS: Extrapolation of clinical trial data is improved by using historical trial data-based informative a priori distributions.

Structured Benefit-risk assessment: a review of key publications and initiatives on frameworks and methodologies.

Introduction The conduct of structured benefit-risk assessment (BRA) of pharmaceutical products is a key area of interest for regulatory agencies and the pharmaceutical industry. However, the acceptance of a standardized approach and implementation are slow. Statisticians play major roles in these organizations, and have a great opportunity to be involved and drive the shaping of future BRA. Method We performed a literature search of recent reviews and initiatives assessing BRA methodologies, and grouped them to assist those new to BRA in learning, understanding, and choosing methodologies. We summarized the key points and discussed the impact of this emerging field on various stakeholders, particularly statisticians in the pharmaceutical industry. Results We provide introductory, essential, special interest, and further information and initiatives materials that direct readers to the most relevant materials, which were published between 2000 and 2013. Based on recommendations in these materials we supply a toolkit of advocated BRA methodologies. Discussion Despite initiatives promoting these methodologies, there are still barriers, one of which being the lack of a consensus on the most appropriate methodologies among stakeholders. However, this opens up opportunities, for statisticians in the pharmaceutical industry especially, to champion appropriate BRA methodology use throughout the pharmaceutical product lifecycle. Conclusions This article may serve as a starting point for discussions and to reach a mutual consensus for methodology selection in a particular situation. Regulators and pharmaceutical industry should continue to collaborate to develop and take forward BRA methodologies, and by clear communication develop a mutual understanding of the key issues. Copyright © 2015 John Wiley & Sons, Ltd.

Improved estimation of overall survival and progression-free survival for state transition modeling.

Aim: National Institute for Health and Care Excellence guidance (Technical Support Document 19) highlights a key challenge of state transition models (STMs) being their difficulty in achieving a satisfactory fit to the observed within-trial endpoints. Fitting poorly to data over the trial period can then have implications for long-term extrapolations. A novel estimation approach is defined in which the predicted overall survival (OS) and progression-free survival (PFS) extrapolations from an STM are optimized to provide closer estimates of the within-trial endpoints. Materials & methods: An STM was fitted to the SQUIRE trial data in non-small-cell lung cancer (obtained from Project Data Sphere). Two methods were used: a standard approach whereby the maximum likelihood was utilized for the individual transitions and the best-fitting parametric model selected based on AIC/BIC, and a novel approach in which parameters were optimized by minimizing the area between the STM-predicted OS and PFS curves and the corresponding OS and PFS Kaplan-Meier curves. Sensitivity analyses were conducted to assess uncertainty. Results: The novel approach resulted in closer estimations to the OS and PFS Kaplan-Meier for all combinations of parametric distributions analyzed compared with the standard approach. Though the uncertainty associated with the novel approach was slightly larger, it provided better estimates to the restricted mean survival time in 10 of the 12 parametric distributions analyzed. Conclusion: A novel approach is defined which provides an alternative STM estimation method enabling improved fits to modeled endpoints, which can easily be extended to more complex model structures.

Using 30-day modified rankin scale score to predict 90-day score in patients with intracranial hemorrhage: Derivation and validation of prediction model.

Whether 30-day modified Rankin Scale (mRS) scores can predict 90-day scores is unclear. This study derived and validated a model to predict ordinal 90-day mRS score in an intracerebral hemorrhage (ICH) population using 30-day mRS values and routinely available baseline variables. Adults enrolled in the Antihypertensive Treatment of Acute Cerebral Hemorrhage-2 (ATACH-2) trial between May 2011 and September 2015 with acute ICH, who were alive at 30 days and had mRS scores reported at both 30 and 90 days were included in this post-hoc analysis. A proportional odds regression model for predicting ordinal 90-day mRS scores was developed and internally validated using bootstrapping. Variables in the model included: mRS score at 30 days, age (years), hematoma volume (cm3), hematoma location (deep [basal ganglia, thalamus], lobar, or infratentorial), presence of intraventricular hemorrhage (IVH), baseline Glasgow Coma Scale (GCS) score, and National Institutes of Health Stroke Scale (NIHSS) score at randomization. We assessed model fit, calibration, discrimination, and agreement (ordinal, dichotomized functional independence), and EuroQol-5D ([EQ-5D] utility weighted) between predicted and observed 90-day mRS. A total of 898/1000 participants were included. Following bootstrap internal validation, our model (calibration slope = 0.967) had an optimism-corrected c-index of 0.884 (95% CI = 0.873-0.896) and R2 = 0.712 for 90-day mRS score. The weighted ĸ for agreement between observed and predicted ordinal 90-day mRS score was 0.811 (95% CI = 0.787-0.834). Agreement between observed and predicted functional independence (mRS score of 0-2) at 90 days was 74.3% (95% CI = 69.9-78.7%). The mean ± SD absolute difference between predicted and observed EQ-5D-weighted mRS score was negligible (0.005 ± 0.145). This tool allows practitioners and researchers to utilize clinically available information along with the mRS score 30 days after ICH to reliably predict the mRS score at 90 days.

AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: The RAVEN cohort study.

OBJECTIVES: Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. METHODS: Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. RESULTS: Over 4.5 million AZD1222 recipients were matched (mean follow-up ∼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the 'fit' (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). CONCLUSIONS: Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed.

Progression-free survival with fulvestrant 500 mg and alternative endocrine therapies as second-line treatment for advanced breast cancer: a network meta-analysis with parametric survival models.

BACKGROUND: Ouwens et al. and Jansen have presented methods for (network) meta-analysis of survival data by using a multidimensional treatment effect as an alternative to the synthesis of constant hazards ratios, which allow for a better fit to the data and the expected survival of competing interventions for cost-effectiveness analysis. However, results may be sensitive to the assumed underlying survival function. OBJECTIVE: To estimate the expected progression-free survival (PFS) for fulvestrant 500 mg versus alternative hormonal therapies for postmenopausal women with advanced breast cancer who relapsed previously by means of a network meta-analysis of currently available randomized controlled trials using alternative underlying survival functions. METHODS: Eleven randomized controlled trials were included that evaluated fulvestrant 500 mg (n = 3), fulvestrant 250 mg (n = 5), fulvestrant 250 mg loading dose (n = 3), anastrozole 1 mg (n = 3), megestrol acetate (n = 4), letrozole 2.5 mg (n = 3), letrozole 0.5 mg (n = 3), and exemestane (n = 2). PFS percentages and numbers at risk were derived from Kaplan-Meier curves and combined by means of Bayesian network meta-analysis on the basis of the difference in the shape and scale parameters of the Weibull, log-normal, and log-logistic parametric survival functions. RESULTS: The log-normal distribution provided the best fit, suggesting that the proportional hazard assumption was not valid. Based on the difference in expected PFS, it was found that fulvestrant 500 mg is more efficacious than fulvestrant 250 mg, megestrol acetate, and anastrozole (-5.73 months; 95% credible interval [CrI]-10.67,-1.67). Expected PFS for fulvestrant 500 mg ranged from 10.87 (95% CrI 9.21, 13.07) to 17.02 (95% CrI 13.33, 22.02) months for the Weibull versus log-logistic distribution. CONCLUSIONS: Fulvestrant 500 mg is expected to be more efficacious than fulvestrant 250 mg, megestrol acetate, and anastrozole 1 mg and at least as efficacious as exemestane and letrozole 2.5 mg in terms of PFS among postmenopausal women with advanced breast cancer after failure on endocrine therapy. The findings were not sensitive to the distribution, although the expected PFS varied substantially, emphasizing the importance of performing sensitivity analyses.

Network meta-interpolation: Effect modification adjustment in network meta-analysis using subgroup analyses.

Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this paper, we propose Network Meta-Interpolation (NMI): a method using subgroup analyses to adjust for EM that does not assume SEM. NMI balances effect modifiers across studies by turning treatment effect (TE) estimates at the subgroup- and study level into TE and standard errors at EM values common to all studies. In an extensive simulation study, we simulate two evidence networks consisting of four treatments, and assess the impact of departure from the SEM assumption, variable EM correlation across trials, trial sample size and network size. NMI was compared to standard NMA, network meta-regression (NMR) and Multilevel NMR (ML-NMR) in terms of estimation accuracy and credible interval (CrI) coverage. In the base case non-SEM dataset, NMI achieved the highest estimation accuracy with root mean squared error (RMSE) of 0.228, followed by standard NMA (0.241), ML-NMR (0.447) and NMR (0.541). In the SEM dataset, NMI was again the most accurate method with RMSE of 0.222, followed by ML-NMR (0.255). CrI coverage followed a similar pattern. NMI's dominance in terms of estimation accuracy and CrI coverage appeared to be consistent across all scenarios. NMI represents an effective option for NMA in the presence of study imbalance and available subgroup data.

EXAcerbations of COPD and their OutcomeS on CardioVascular diseases (EXACOS-CV) Programme: protocol of multicountry observational cohort studies.

INTRODUCTION: In patients with chronic obstructive pulmonary disease (COPD), the risk of certain cardiovascular (CV) events is increased by threefold to fivefold in the year following acute exacerbation of COPD (AECOPD), compared with a non-exacerbation period. While the effect of severe AECOPD is well established, the relationship of moderate exacerbation or prior exacerbation to elevated risk of CV events is less clear. We will conduct cohort studies in multiple countries to further characterise the association between AECOPD and CV events. METHODS AND ANALYSIS: Retrospective longitudinal cohort studies will be conducted within routinely collected electronic healthcare records or claims databases. The study cohorts will include patients meeting inclusion criteria for COPD between 1 January 2014 and 31 December 2018. Moderate exacerbation is defined as an outpatient visit and/or medication dispensation/prescription for exacerbation; severe exacerbation is defined as hospitalisation for COPD. The primary outcomes of interest are the time to (1) first hospitalisation for a CV event (including acute coronary syndrome, heart failure, arrhythmias or cerebral ischaemia) since cohort entry or (2) death. Time-dependent Cox proportional hazards models will compare the hazard of a CV event between exposed periods following exacerbation (split into these periods: 1-7, 8-14, 15-30, 31-180 and 181-365 days) and the unexposed reference time period, adjusted on time-fixed and time-varying confounders. ETHICS AND DISSEMINATION: Studies have been approved in Canada, Japan, the Netherlands, Spain and the UK, where an institutional review board is mandated. For each study, the results will be published in peer-reviewed journals.

Cost-effectiveness of ticagrelor plus aspirin versus aspirin in acute ischaemic stroke or transient ischaemic attack: an economic evaluation of the THALES trial.

Objective: THALES demonstrated that ticagrelor plus aspirin reduced the risk of stroke or death but increased bleeding versus aspirin during the 30 days following a mild-to-moderate acute non-cardioembolic ischaemic stroke (AIS) or high-risk transient ischaemic attack (TIA). There are no cost-effectiveness analyses supporting this combination in Europe. To address this, a cost-effectiveness analysis was performed. Methods: Cost-effectiveness was evaluated using a decision tree and Markov model with a short-term and long-term (30-year) horizon. Stroke, mortality, bleeding and EuroQol-5 Dimension (EQ-5D) data from THALES were used to estimate short-term outcomes. Model transitions were based on stroke severity (disabling stroke was defined as modified Rankin Scale >2). Healthcare resource utilisation and EQ-5D data beyond 30 days were based on SOCRATES, another trial in AIS/TIA that compared ticagrelor with aspirin. Long-term costs, survival and disutilities were based on published literature. Unit costs were derived from national databases and discounted at 3% annually from a Swedish healthcare perspective. Results: One-month treatment with ticagrelor plus aspirin resulted in 12 fewer strokes, 4 additional major bleeds and cost savings of €95 000 per 1000 patients versus aspirin from a Swedish healthcare perspective. This translated into increased quality-adjusted life-years (0.04) and reduced societal costs (-€1358) per patient over a lifetime horizon. Key drivers of cost-effectiveness were number of patients experiencing subsequent disabling stroke and degree of disability. Findings were robust over a range of input assumptions. Conclusion: One month of treatment with ticagrelor plus aspirin is likely to improve outcomes and reduce costs versus aspirin in mild-to-moderate AIS or high-risk TIA. Trial registration number: NCT03354429.

COVID-19 vaccine booster doses provide increased protection against COVID-19 hospitalization compared with previously vaccinated individuals: Interim findings from the REFORCO-Brazil real-world effectiveness study during Delta and Omicron.

BACKGROUND: Although COVID-19 booster vaccination is widely recommended, there is limited long-term, population-level, real-world evidence on the magnitude of improved protection against severe COVID-19 conferred by boosting with monovalent COVID-19 vaccines developed against ancestral SARS-CoV-2, especially in low- or middle-income countries. We present interim results from the first large-scale assessment of the relative vaccine effectiveness (rVE) of first and second booster doses against severe COVID-19 in a low-/middle-income country. METHODS: REFORCO-Brazil is an ongoing, test-negative case-control study (NCT05697705) utilizing Brazil national severe acute respiratory syndrome (SARS) surveillance and vaccination data. In SARS hospitalizations from August 1, 2021 to July 31, 2022, we matched test-positive (via SARS-CoV-2 antigen/reverse transcription polymerase chain reaction [RT-PCR]) cases and test-negative case-controls (via RT-PCR) based on admission date, preceding vaccinations, and age. We evaluated the rVEs of four monovalent COVID-19 vaccines (AZD1222, Ad26.COV2.S, CoronaVac, and BNT162b2) as second boosters compared with any first boosters received ≥4 months previously, and as first boosters compared with primary-series vaccinations completed ≥4 months previously. RESULTS: The overall rVE of second boosters, from 5668 (2238 test-positive) evaluated hospitalizations, was 24.7 % (95 % confidence interval [CI]: 12.6-35.1); the overall rVE of first boosters, from 30,272 (12,063 test-positive) hospitalizations, was 46.8 % (95 % CI: 43.3-50.0). The rVEs of AZD1222 and BNT162b2 were similar: 29.4 % (95 % CI: 8.6-45.5) and 25.5 % (95 % CI: 4.2-42.2), respectively, for second boosters; and 42.5 % (95 % CI: 28.0-54.0) and 50.8 % (95 % CI: 47.5-54.0), respectively, for first boosters. In general, rVEs were higher in elderly (≥80 years) and immunocompromised/high-risk individuals. CONCLUSIONS: Our results support the use of AZD1222 and other adenoviral/mRNA vaccine boosters to maintain protection against COVID-19 hospitalization from Omicron subvariants, including in elderly and immunocompromised individuals at increased risk of accelerated waning or severe outcomes.

The Role of Expert Opinion in Projecting Long-Term Survival Outcomes Beyond the Horizon of a Clinical Trial.

INTRODUCTION: Clinical trials often have short follow-ups, and long-term outcomes such as survival must be extrapolated. Current extrapolation methods often produce a wide range of survival values. To minimize uncertainty in projections, we developed a novel method that incorporates formally elicited expert opinion in a Bayesian analysis and used it to extrapolate survival in the placebo arm of DAPA-CKD, a phase 3 trial of dapagliflozin in patients with chronic kidney disease (NCT03036150). METHODS: A summary of mortality data from 13 studies that included DAPA-CKD-like populations and training on elicitation were provided to six experts. An elicitation survey was used to gather the experts' 10- and 20-year survival estimates for patients in the placebo arm of DAPA-CKD. These estimates were combined with DAPA-CKD mortality and general population mortality (GPM) data in a Bayesian analysis to extrapolate long-term survival using seven parametric distributions. Results were compared with those from standard frequentist approaches (with and without GPM data) that do not incorporate expert opinion. RESULTS: The group expert-elicited estimate for 20-year survival was 31% (lower estimate, 10%; upper estimate, 40%). In the Bayesian analysis, the 20-year extrapolated survival across the seven distributions was 14.9-39.1%, a range that was 2.4- and 1.6-fold smaller than those produced by the frequentist methods (0.0-56.9% without and 0.0-39.2% with GPM data). CONCLUSIONS: Using expert opinion in a Bayesian analysis provided a robust method for extrapolating long-term survival in the placebo arm of DAPA-CKD. The method could be applied to other populations with limited survival data.

Mortality risk reduction with budesonide/glycopyrrolate/formoterol fumarate versus fluticasone furoate/umeclidinium/vilanterol in COPD: a matching-adjusted indirect comparison based on ETHOS and IMPACT.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. While two approved fixed-dose inhaled corticosteroid/long-acting muscarinic antagonist (LAMA)/long-acting ß2-agonist (LABA) triple therapies reduce all-cause mortality (ACM) versus dual LAMA/LABA therapy in patients with COPD, head-to-head studies have not compared the effects of these therapies on ACM. We compared ACM in adults with moderate-to-very severe COPD receiving budesonide/glycopyrrolate/formoterol fumarate (BGF) in ETHOS versus fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) in IMPACT using a matching-adjusted indirect comparison (MAIC). METHODS: A systematic literature review identified two studies (ETHOS [NCT02465567]; IMPACT [NCT02164513]) of ≥52 weeks reporting ACM as an efficacy endpoint in patients receiving triple therapy. As ETHOS and IMPACT lack a common comparator, an unanchored MAIC compared ACM between licensed doses of BGF (320/18/9.6 µg) from ETHOS and FF/UMEC/VI (100/62.5/25 µg) from IMPACT in patients with moderate-to-very severe COPD. Using on- and off-treatment data from the final retrieved datasets of the intention-to-treat populations, BGF data were adjusted according to aggregate FF/UMEC/VI data using 11 baseline covariates; a supplementary unadjusted indirect treatment comparison was also conducted. P-values for these post-hoc analyses are not adjusted for Type I error. RESULTS: ACM over 52 weeks was statistically significantly reduced by 39% for BGF versus FF/UMEC/VI in the MAIC (hazard ratio [HR] [95% CI]: 0.61 [0.38, 0.95], p = 0.030) and unadjusted analysis (HR [95% CI]: 0.61 [0.41, 0.92], p = 0.019). CONCLUSION: In this MAIC, which adjusted for population heterogeneity between ETHOS and IMPACT, ACM was significantly reduced with BGF versus FF/UMEC/VI in patients with moderate-to-very severe COPD.

Chronic obstructive pulmonary disease (known as COPD) is a leading cause of death worldwide, being responsible for over 3 million deaths in 2019. People living with COPD are more likely to die. Importantly, a sudden worsening of COPD symptoms (known as an exacerbation) is associated with a higher chance of death from heart-related and breathing-related problems. Therefore, reducing risk of death is an important treatment goal for COPD. Of the three medications approved for treating COPD that combine three drugs in a single-inhaler device, there are two­referred to generically as budesonide/glycopyrrolate/formoterol fumarate (BGF) and fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI)­that can reduce the risk of death in people living with COPD compared with treatments that combine two drugs. However, no studies have directly compared the risk of death in people living with COPD treated with these medicines. We compared the risk of death in people living with moderate-to-very severe COPD who received either BGF during a clinical trial called ETHOS or FF/UMEC/VI during a clinical trial called IMPACT. To make this comparison, we used a method called "matching-adjusted indirect comparison", which used specific features (such as sex, breathing difficulty, and whether they were current smokers) to match patients from the two studies to ensure similar groups were examined. Our analysis showed a 39% decrease in the chance of death in patients who received BGF compared with patients who received FF/UMEC/VI. This finding may be important for doctors to improve patient health and reduce the risk of death in people living with COPD.

Definitions, acceptability, limitations, and guidance in the use and reporting of surrogate end points in trials: a scoping review.

OBJECTIVE: To synthesize the current literature on the use of surrogate end points, including definitions, acceptability, and limitations of surrogate end points and guidance for their design/reporting, into trial reporting items. STUDY DESIGN AND SETTING: Literature was identified through searching bibliographic databases (until March 1, 2022) and gray literature sources (until May 27, 2022). Data were thematically analyzed into four categories: (1) definitions, (2) acceptability, (3) limitations and challenges, and (4) guidance, and synthesized into reporting guidance items. RESULTS: After screening, 90 documents were included: 79% (n = 71) had data on definitions, 77% (n = 69) on acceptability, 72% (n = 65) on limitations and challenges, and 61% (n = 55) on guidance. Data were synthesized into 17 potential trial reporting items: explicit statements on the use of surrogate end point(s) and justification for their use (items 1-6); methodological considerations, including whether sample size calculations were informed by surrogate validity (items 7-9); reporting of results for composite outcomes containing a surrogate end point (item 10); discussion and interpretation of findings (items 11-14); plans for confirmatory studies, collecting data on the surrogate end point and target outcome, and data sharing (items 15-16); and informing trial participants about using surrogate end points (item 17). CONCLUSION: The review identified and synthesized items on the use of surrogate end points in trials; these will inform the development of the Standard Protocol Items: Recommendations for Interventional Trials-SURROGATE and Consolidated Standards of Reporting Trials-SURROGATE extensions.

Protection against COVID-19 hospitalisation conferred by primary-series vaccination with AZD1222 in non-boosted individuals: first vaccine effectiveness results of the European COVIDRIVE study and meta-regression analysis.

Background: Vaccine effectiveness (VE) studies with long-term follow-up are needed to understand durability of protection against severe COVID-19 outcomes conferred by primary-series vaccination in individuals not receiving boosters. COVIDRIVE is a European public-private partnership evaluating brand-specific vaccine effectiveness (VE). We report a prespecified interim analysis of primary-series AZD1222 (ChAdOx1 nCoV-19) VE. Methods: Seven Study Contributors in Europe collected data on individuals aged ≥18 years who were hospitalised with severe acute respiratory infection (June 1st, 2021-September 5th, 2022) and eligible for COVID-19 vaccination prior to hospitalisation. In this test-negative case-control study, individuals were defined as test-positive cases or test-negative controls (SARS-CoV-2 RT-PCR) and were either fully vaccinated (two AZD1222 doses, 4-12 weeks apart, completed ≥14 days prior to symptom onset; no booster doses) or unvaccinated (no COVID-19 vaccine prior to hospitalisation). The primary objective was to estimate AZD1222 VE against COVID-19 hospitalisation. A literature review and meta-regression were conducted to contextualise findings on durability of protection. Findings: 761 individuals were included during the 15-month analysis period. Overall AZD1222 VE estimate was 72.8% (95% CI, 53.4-84.1). VE was 93.8% (48.6-99.3) in participants who received second AZD1222 doses ≤8 weeks prior to hospitalisation, with spline-based VE estimates demonstrating protection (VE ≥ 50%) 30 weeks post-second dose. Meta-regression analysis (data from seven publications) showed consistent results, with ≥80% protection against COVID-19 hospitalisation through ∼43 weeks post-second dose, with some degree of waning. Interpretation: Primary-series AZD1222 vaccination confers protection against COVID-19 hospitalisation with enduring levels of VE through ≥6 months. Funding: AstraZeneca.