Using generalized estimating equations and extensions in randomized trials with missing longitudinal patient reported outcome data

UNSTRUCTURED Background: Adherence constitutes a great challenge for disease management, particularly when treating chronically ill patients facing an extensive, complex and long-term therapy. Earlier studies emphasize the relevance of adherence for improving therapy benefits. Besides the positive impact of increased patient support, the use of mobile health applications has gained importance in disease management. Objective: We aimed to develop a software application providing innovative features to simplify the contact between patients and treating physicians in order to overcome adherence barriers, to implement risk management plans and to collect patient reported outcome data. Methods: A novel software application ensuring data security was developed. Various innovative modules have been implemented, enabling bidirectional communication between treating physicians and patients, supporting therapy monitoring and management and allowing the collection of large sets of anonymous patient data. Results: The PatientConcept app is freely available for download and is tested since 2016, with more than 1800 generated patient IDs and 279 patients documenting health data according to risk management plans online in 2017. The impact on adherence issues is currently tested in larger patient populations. Conclusion: This innovative app provides a feasible and cost-optimized possibility to intensify and simplify the communication between patients and their treating physicians across indications, thus promising an exceptional benefit to both. It may not only support chronically ill patients in managing their daily life and improving adherence, but can also facilitate the implementation of risk management plans through automated monitoring, thus supporting physicians in their daily routine. Furthermore, patient reported outcome data can be collected. Importantly, a secure ID-associated data management ensures patient anonymity complying with highest data safety standards.

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GEECORR: A SAS macro for regression models of correlated binary responses and within-cluster correlation using generalized estimating equations

Computer Methods and Programs in Biomedicine ◽

10.1016/j.cmpb.2021.106276 ◽

2021 ◽

pp. 106276

Author(s):

Tracie L. Shing ◽

John S. Preisser ◽

Richard C. Zink

Keyword(s):

Generalized Estimating Equations ◽

Regression Models ◽

Estimating Equations ◽

Binary Responses ◽

Sas Macro ◽

Correlated Binary Responses ◽

Cluster Correlation ◽

Generalized Estimating

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Scope and heterogeneity of outcomes reported in randomized trials in patients receiving peritoneal dialysis

Clinical Kidney Journal ◽

10.1093/ckj/sfaa224 ◽

2020 ◽

Author(s):

Karine E Manera ◽

David W Johnson ◽

Yeoungjee Cho ◽

Benedicte Sautenet ◽

Jenny Shen ◽

...

Keyword(s):

Peritoneal Dialysis ◽

Patient Reported Outcomes ◽

Randomized Trials ◽

Primary Outcome ◽

Median Number ◽

Patient Reported Outcome ◽

Patient Reported ◽

Inform Decision Making ◽

Solute Clearance

Abstract Background Randomized trials can provide evidence to inform decision-making but this may be limited if the outcomes of importance to patients and clinicians are omitted or reported inconsistently. We aimed to assess the scope and heterogeneity of outcomes reported in trials in peritoneal dialysis (PD). Methods We searched the Cochrane Kidney and Transplant Specialized Register for randomized trials in PD. We extracted all reported outcome domains and measurements and analyzed their frequency and characteristics. Results From 128 reports of 120 included trials, 80 different outcome domains were reported. Overall, 39 (49%) domains were surrogate, 23 (29%) patient-reported and 18 (22%) clinical. The five most commonly reported domains were PD-related infection [59 (49%) trials], dialysis solute clearance [51 (42%)], kidney function [45 (38%)], protein metabolism [44 (37%)] and inflammatory markers/oxidative stress [42 (35%)]. Quality of life was reported infrequently (4% of trials). Only 14 (12%) trials included a patient-reported outcome as a primary outcome. The median number of outcome measures (defined as a different measurement, aggregation and metric) was 22 (interquartile range 13–37) per trial. PD-related infection was the most frequently reported clinical outcome as well as the most frequently stated primary outcome. A total of 383 different measures for infection were used, with 66 used more than once. Conclusions Trials in PD include important clinical outcomes such as infection, but these are measured and reported inconsistently. Patient-reported outcomes are infrequently reported and nearly half of the domains were surrogate. Standardized outcomes for PD trials are required to improve efficiency and relevance.

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