Framework for the Synthesis of Non-Randomised Studies and Randomised Controlled Trials: A Guidance on Conducting a Systematic Review and Meta-Analysis for Healthcare Decision Making

Introduction: High-quality randomised controlled trials (RCTs) provide the most reliable evidence on the comparative efficacy of new medicines. However, non-randomised studies (NRS) are increasingly recognised as a source of insights into the real-world performance of novel therapeutic products, particularly when traditional RCTs are impractical or lack generalisability. This means there is a growing need for synthesising evidence from RCTs and NRS in healthcare decision making, particularly given recent developments such as innovative study designs, digital technologies and linked databases across countries. Crucially, however, no formal framework exists to guide the integration of these data types. Objectives and Methods: To address this gap, we used a mixed methods approach (review of existing guidance, methodological papers, Delphi survey) to develop guidance for researchers and healthcare decision-makers on when and how to best combine evidence from NRS and RCTs to improve transparency and build confidence in the resulting summary effect estimates. Results: Our framework comprises seven steps on guiding the integration and interpretation of evidence from NRS and RCTs and we offer recommendations on the most appropriate statistical approaches based on three main analytical scenarios in healthcare decision making (specifically, ‘high-bar evidence’ when RCTs are the preferred source of evidence, ‘medium,’ and ‘low’ when NRS is the main source of inference). Conclusion: Our framework augments existing guidance on assessing the quality of NRS and their compatibility with RCTs for evidence synthesis, while also highlighting potential challenges in implementing it. This manuscript received endorsement from the International Society for Pharmacoepidemiology

Effectiveness and safety of edoxaban versus warfarin in patients with nonvalvular atrial fibrillation: a systematic review and meta-analysis of observational studies

Background: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia type. Patients with AF are often administered anticoagulants to reduce the risk of ischemic stroke due to an irregular heartbeat. We evaluated the efficacy and safety of edoxaban versus warfarin in patients with nonvalvular AF by conducting an updated meta-analysis of real-world studies.Methods: In this comprehensive meta-analysis, we searched two databases, PubMed and EMBASE, and included retrospective cohort observational studies that compared edoxaban with warfarin in patients with nonvalvular AF from 1 January 2009, to 30 September 2023. The effectiveness and safety outcomes were ischemic stroke and major bleeding, respectively. In the final analysis, six retrospective observational studies involving 87,236 patients treated with warfarin and 40,933 patients treated with edoxaban were included. To analyze the data, we used a random-effects model to calculate the hazard ratio (HR).Results: Patients treated with edoxaban had a significantly lower risk of ischemic stroke [hazard ratio (HR) = 0.66; 95% confidence interval (CI) = 0.61–0.70; p < 0.0001] and major bleeding (HR = 0.58; 95% CI = 0.49–0.69; p < 0.0001) than those treated with warfarin. The sensitivity analysis results for ischemic stroke and major bleeding were as follows: HR = 0.66; 95% CI = 0.61–0.70; p < 0.0001 and HR = 0.58; 95% CI = 0.49–0.69; p < 0.0001, respectively.Conclusion: Our findings revealed that edoxaban performed better than warfarin against major bleeding and ischemic stroke

Drug Expenditure, Price, and Utilization in US Medicaid: A Trend Analysis for New Multiple Myeloma Medications from 2016 to 2022

Introduction: Multiple myeloma (MM) is the most common plasma cell tumor type. In late 2015, the FDA approved three new medications for MM. These medications were ixazomib, daratumumab, and elotuzumab. However, their utilization, reimbursement, and price in the Medicaid program have not been analyzed before. Methods: A retrospective drug utilization study using the national Medicaid pharmacy claims data from 2016 to 2022 in the US. The primary metrics of analysis were utilization (number of prescriptions), reimbursement (total spending), and price (reimbursement per prescription). Results: The overall Medicaid utilization of MM medications increased from 1671 prescriptions in 2016 to 34,583 prescriptions in 2022 (1970% increase). Moreover, the overall Medicaid reimbursement for the new MM medications increased from USD 9,250,000 in 2016 to over USD 214,449,000 in 2022 (2218% increase). Daratumumab had much higher utilization, reimbursement, and market shares than its competitors. Ixazomib was the most expensive medication compared to daratumumab and elotuzumab. Conclusion: The results of this study demonstrate that CMS utilization and spending on MM medications have significantly grown since 2016. Daratumumab has by far the highest utilization, spending, and market share. The utilization of and spending on specific pharmaceuticals are clearly impacted by policy and clinical guideline recommendations

Smoking is associated with an increased risk of dementia: a meta-analysis of prospective cohort studies with investigation of potential effect modifiers.

Previous studies showed inconsistent results on the association of smoking with all-cause dementia and vascular dementia (VaD), and are limited by inclusion of a small number of studies and unexplained heterogeneity. Our review aimed to assess the risk of all-cause dementia, Alzheimer's disease (AD) and VaD associated with smoking, and to identify potential effect modifiers.The PubMed, Embase, Cochrane Library and Psychinfo databases were searched to identify studies that provided risk estimates on smoking and incidence of dementia. A random-effects model was used to yield pooled results. Thirty-seven studies were included. Compared with never smokers, current smokers showed an increased risk of all-cause dementia (risk ratio (RR) 1.30, 95% confidence interval (CI) 1.18-1.45), AD (RR 1.40, 95% CI 1.13-1.73) and VaD (RR 1.38, 95% CI 1.15-1.66). For all-cause dementia, the risk increased by 34% for every 20 cigarettes per day (RR 1.34, 95% CI 1.25-1.43). Former smokers did not show an increased risk of all-cause dementia (RR 1.01, 95% CI 0.96-1.06), AD (RR 1.04, 95% CI 0.96-1.13) and VaD (RR 0.97, 95% CI 0.83-1.13). Subgroup analyses indicated that (1) the significantly increased risk of AD from current smoking was seen only in apolipoprotein E ε4 noncarriers; (2) current smokers aged 65 to 75 years at baseline showed increased risk of all-cause dementia and AD compared to those aged over 75 or under 65 years; and (3) sex, race, study location and diagnostic criteria difference in risk of dementia was not found.Smokers show an increased risk of dementia, and smoking cessation decreases the risk to that of never smokers. The increased risk of AD from smoking is more pronounced in apolipoprotein E ε4 noncarriers. Survival bias and competing risk reduce the risk of dementia from smoking at extreme age

LogRR of A) all-cause dementia and B) Alzheimer’s disease by the mean age at baseline.

<p>Each circle represents an individual study. The area of circle is proportional to the inverse variance of logrr. RR, risk ratio.</p

Meta-analysis for ever smoking and risk of A) all-cause dementia, B) Alzheimer’s disease and C) vascular dementia.

<p>Meta-analysis for ever smoking and risk of A) all-cause dementia, B) Alzheimer’s disease and C) vascular dementia.</p

Characteristics of 37 included studies regarding smoking and risk of dementia.

<p>APOE ε4, apolipoprotein E ε4; NA, not available; BMI, body mass index; IGT, impaired glucose tolerance; NINCDS-ADRDA, DSM-III-R, Diagnostic and Statistical Manual of Mental Disorders, third edition Revised; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, fourth edition; NINDS-AIREN, National Institute of Neurological Disorders and Stroke-Association Internationale pour la Recherche et l'Enseignement en Neurosciences; GMS-AGECAT, Geriatric Mental State-the Automated Geriatric Examination for Computer Assisted Taxonomy; ICD-8, International Classification of Diseases, Eighth Revision; ADDTC core criteria, Alzheimer’s Disease Diagnostic and Treatment Centers core criteria.</p><p>¹ Value refers to mean age of participants at baseline.</p><p>² Value is expressed as maximum.</p><p>³ Dementia was determined by a battery of neuropsychological measures and a standardized neurological examination.</p><p>⁴ The term “other” in the “Adjustment factors” column refers to all the confounders except age, sex, education, APOE ε4, BMI, diabetes, alcohol and hypertension.</p><p>⁵ Value refers to sample size at baseline.</p><p>⁶ The risk estimates were available just for former smoking and the risk of all-cause dementia and AD.</p><p>Characteristics of 37 included studies regarding smoking and risk of dementia.</p

Meta-analysis for current smoking and risk of A) all-cause dementia, B) Alzheimer’s disease and C) vascular dementia.

<p>Meta-analysis for current smoking and risk of A) all-cause dementia, B) Alzheimer’s disease and C) vascular dementia.</p

The linear dose–response relationship plot between current smoking and all-cause dementia.

<p>The solid line represents the linear trend and lines with short dashes represent its’ 95% confidence interval.</p