scholarly journals Is it time to use real-world data from primary care in Alzheimer’s disease?

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Anna Ponjoan ◽  
Josep Garre-Olmo ◽  
Jordi Blanch ◽  
Ester Fages ◽  
Lia Alves-Cabratosa ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Primary Care ◽  
Alzheimer's Disease ◽  
Real World ◽  
Real World Data ◽  
World Data

scholarly journals Exploring the Feasibility of Using Real-World Data from a Large Clinical Data Research Network to Simulate Clinical Trials of Alzheimer’s Disease

2020 ◽  
Author(s):  
Zhaoyi Chen ◽  
Hansi Zhang ◽  
Yi Guo ◽  
Thomas J George ◽  
Mattia Prosperi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Clinical Data ◽  
Real World ◽  
Large Scale ◽  
Research Network ◽  
Real World Data ◽  
World Data ◽  
Trial Simulation

AbstractClinical trials are essential but often have high financial costs and long execution time. Trial simulation using real world data (RWD) could potentially provide insights on a treatment’s efficacy and safety before running a large-scale trial. In this work, we explored the feasibility of using RWD from a large clinical data research network to simulate a randomized controlled trial of Alzheimer’s disease considering two different scenarios: an one-arm simulation of the standard-of-care control arm; and a two-arm simulation comparing treatment safety between the intervention and control arms with proper patient matching algorithms. We followed original trial’s design and addressed some key questions, including how to translate trial criteria to database queries and establish measures of safety (i.e., serious adverse events) from RWD. Our simulation generated results comparable to the original trial, but also exposed gaps in both trial simulation methodology and the generalizability issue of clinical trials.

Causal AI with Real World Data: Do Statins Protect from Alzheimer's Disease Onset?

2021 ◽  
Author(s):  
Mattia Prosperi ◽  
Shantanu Ghosh ◽  
Zhaoyi Chen ◽  
Marco Salemi ◽  
Tianchen Lyu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Real World ◽  
Disease Onset ◽  
Real World Data ◽  
World Data

scholarly journals Exploring the feasibility of using real-world data from a large clinical data research network to simulate clinical trials of Alzheimer’s disease

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhaoyi Chen ◽  
Hansi Zhang ◽  
Yi Guo ◽  
Thomas J. George ◽  
Mattia Prosperi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Real World ◽  
Comparative Effectiveness ◽  
Research Network ◽  
Real World Data ◽  
World Data ◽  
Trial Simulation ◽  
Simulation Scenario

AbstractIn this study, we explored the feasibility of using real-world data (RWD) from a large clinical research network to simulate real-world clinical trials of Alzheimer’s disease (AD). The target trial (i.e., NCT00478205) is a Phase III double-blind, parallel-group trial that compared the 23 mg donepezil sustained release with the 10 mg donepezil immediate release formulation in patients with moderate to severe AD. We followed the target trial’s study protocol to identify the study population, treatment regimen assignments and outcome assessments, and to set up a number of different simulation scenarios and parameters. We considered two main scenarios: (1) a one-arm simulation: simulating a standard-of-care (SOC) arm that can serve as an external control arm; and (2) a two-arm simulation: simulating both intervention and control arms with proper patient matching algorithms for comparative effectiveness analysis. In the two-arm simulation scenario, we used propensity score matching controlling for baseline characteristics to simulate the randomization process. In the two-arm simulation, higher serious adverse event (SAE) rates were observed in the simulated trials than the rates reported in original trial, and a higher SAE rate was observed in the 23 mg arm than in the 10 mg SOC arm. In the one-arm simulation scenario, similar estimates of SAE rates were observed when proportional sampling was used to control demographic variables. In conclusion, trial simulation using RWD is feasible in this example of AD trial in terms of safety evaluation. Trial simulation using RWD could be a valuable tool for post-market comparative effectiveness studies and for informing future trials’ design. Nevertheless, such an approach may be limited, for example, by the availability of RWD that matches the target trials of interest, and further investigations are warranted.

scholarly journals LDL-cholesterol change and goal attainment following statin intensity titration among Asians in primary care: a retrospective cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Hao Sen Andrew Fang ◽  
Qiao Gao ◽  
Mong Li Lee ◽  
Wynne Hsu ◽  
Ngiap Chuan Tan
Keyword(s):  
Primary Care ◽  
Clinical Trials ◽  
Cohort Study ◽  
Real World ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Goal Attainment ◽  
Real World Data ◽  
World Data ◽  
Asian Patients

Abstract Background Clinical trials have demonstrated that either initiating or up-titrating a statin dose substantially reduce Low-Density Lipoprotein-Cholesterol (LDL-C) levels. However, statin adherence in actual practice tends to be suboptimal, leading to diminished effectiveness. This study aims to use real-world data to determine the effect on LDL-C levels and LDL-C goal attainment rates, when selected statins are titrated in Asian patients. Methods A retrospective cohort study over a 5-year period, from April 2014 to March 2019 was conducted on a cohort of multi-ethnic adult Asian patients with clinical diagnosis of Dyslipidaemia in a primary care clinic in Singapore. The statins were classified into low-intensity (LI), moderate-intensity (MI) and high-intensity (HI) groups according to the 2018 American College of Cardiology and American Heart Association (ACC/AHA) Blood Cholesterol Guidelines. Patients were grouped into “No statin”, “Non-titrators” and “Titrators” cohorts based on prescribing patterns. For the “Titrators” cohort, the mean percentage change in LDL-C and absolute change in LDL-C goal attainment rates were computed for each permutation of statin intensity titration. Results Among the cohort of 11,499 patients, with a total of 266,762 visits, there were 1962 pairs of LDL-C values associated with a statin titration. Initiation of LI, MI and HI statin resulted in a lowering of LDL-C by 21.6% (95%CI = 18.9–24.3%), 28.9% (95%CI = 25.0–32.7%) and 25.2% (95%CI = 12.8–37.7%) respectively. These were comparatively lower than results from clinical trials (30 to 63%). The change of LDL-C levels due to up-titration, down-titration, and discontinuation were − 12.4% to − 28.9%, + 13.2% to + 24.6%, and + 18.1% to + 32.1% respectively. The improvement in LDL-C goal attainment ranged from 26.5% to 47.1% when statin intensity was up-titrated. Conclusion In this study based on real-world data of Asian patients in primary care, it was shown that although statin titration substantially affected LDL-C levels and LDL-C goal attainment rates, the magnitude was lower than results reported from clinical trials. These results should be taken into consideration and provide further insight to clinicians when making statin adjustment recommendations in order to achieve LDL-C targets in clinical practice, particularly for Asian populations.

scholarly journals Incremental Healthcare Utilization and Cost Burden of Comorbid Insomnia in Alzheimer’s Disease Patients

2021 ◽  
pp. 1-12
Author(s):  
Zaina P. Qureshi ◽  
Ellen Thiel ◽  
James Nelson ◽  
Rezaul Khandker
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthcare Utilization ◽  
Real World ◽  
Healthcare Costs ◽  
Real World Data ◽  
Skilled Nursing ◽  
Comorbid Insomnia ◽  
Comorbidity Burden

Background: Insomnia is associated with worsened clinical outcomes among Alzheimer’s disease dementia (AD) patients, increased caregiver burden, and healthcare utilization. Objective: This study aimed to characterize the incremental healthcare burden of insomnia in AD using real-world data. Methods: A retrospective observational study was conducted on AD patients selected from the IBM® MarketScan Commercial and Medicare Supplemental Databases. AD patients with claims-based evidence of insomnia were direct matched to a non-insomnia cohort based on demographic factors. Healthcare utilization and associated costs were assessed for a 12-month follow-up period. Results: A total of 3,500 insomnia AD patients and 9,884 non-insomnia AD patients were analyzed. The insomnia cohort had a higher comorbidity burden at baseline (mean score on Charlson Comorbidity Index 2.5 versus 2.2, p <  0.001) and higher proportions of patients with baseline diagnoses for other conditions including depression: 40%, insomnia cohort versus 25%, non-insomnia (p <  0.001). AD patients with insomnia were more likely to have a claim for inpatient hospitalizations (39.8%versus 32.3%), emergency room services (56.4%versus 48.0%), and skilled-nursing services (42.6%versus 31.9%) (all p <  0.05). Mean total annual healthcare costs during the 12-month follow-up period were significantly higher among AD patients with insomnia as compared to those without. (Mean costs: $37,356 versus $27,990, p <  0.001). Conclusion: AD patients with comorbid insomnia are more likely to use higher-cost healthcare services such as inpatient hospitalization, and skilled nursing, and have higher total healthcare costs. This real-world analysis provides evidence that AD disease management should consider proper treatment of comorbid insomnia due to the incremental burden and cost implications.

scholarly journals Impact of Comorbidities and Commonly Used Drugs on Mortality in COPD – Real-World Data from a Primary Care Setting

2020 ◽  
Vol Volume 15 ◽  
pp. 235-245 ◽  
Author(s):  
Jens Ellingsen ◽  
Gunnar Johansson ◽  
Kjell Larsson ◽  
Karin Lisspers ◽  
Andrei Malinovschi ◽  
...  
Keyword(s):  
Primary Care ◽  
Real World ◽  
Care Setting ◽  
Primary Care Setting ◽  
Real World Data ◽  
World Data
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