Application of latent growth and growth mixture modeling to identify and characterize differential responders to treatment for COPD

Stull, Donald E.; Gale, Rupert; Capkun-Niggli, Gorana; Houghton, Katherine; Jones, Paul

doi:10.1016/j.cct.2011.06.004

Cited by 25 publications

(33 citation statements)

References 26 publications

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“…As heterogeneity in response to treatment is common in clinical trials, 39,40 we further sought to identify homogenous subgroups of patients who respond differently to the intervention.…”

Section: Discussionmentioning

confidence: 99%

“…Trends in change in BP during the course of the 8‐week intervention period were examined by means of latent class growth modeling (LCGM) using Mplus version 7.1 (Muthén & Muthén, 1998–2010, Los Angeles, CA). As heterogeneity in response to treatment is common in clinical trials, we further sought to identify homogenous subgroups of patients who respond differently to the intervention.…”

Section: Methodsmentioning

confidence: 99%

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Improved Blood Pressure Control Using an Interactive Mobile Phone Support System

Bengtsson

Kjellgren

Hallberg

et al. 2015

J of Clinical Hypertension

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This explorative, longitudinal study evaluated the effect of the daily use of a mobile phone‐based self‐management support system for hypertension in reducing blood pressure (BP) among 50 primary care patients with hypertension over 8 weeks. The self‐management system comprises modules for (1) self‐reports of BP, pulse, lifestyle, symptoms, and well‐being; (2) delivery of reminders and encouragements; and (3) graphical feedback of self‐reports. Daily use of the support system significantly reduced BP (systolic BP −7 mm Hg, diastolic BP −4.9 mm Hg) between baseline and week 8, with daily improvements leveling off as the study progressed. Three homogenous subsets of patients were identified who, despite different initial BP levels, showed similar decreases in BP during the study, indicating that patients benefited irrespective of baseline BP. In showing significant reductions in BP, our results suggest that the self‐management support system may be a useful tool in clinical practice to help patients self‐manage their hypertension.

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“…As heterogeneity in response to treatment is common in clinical trials, 39,40 we further sought to identify homogenous subgroups of patients who respond differently to the intervention.…”

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Improved Blood Pressure Control Using an Interactive Mobile Phone Support System

Bengtsson

Kjellgren

Hallberg

et al. 2015

J of Clinical Hypertension

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“…Despite these efforts, differential treatment response can still exist; that is, not all patients in treatment groups respond in the same way or to the same extent. This can disguise true treatment effects and potentially mask the value of products for particular patients by increasing the mean response where there is a class of hyperresponders or, conversely, decreasing the mean response where there is a class of hypo-or nonresponders [5]. That is, some patients in active treatment groups may show no response, or deterioration, and when their results are analyzed together with the results of responsive patients, the overall treatment effect is dampened.…”

Section: Introductionmentioning

confidence: 99%

“…However, as discussed above, this assumption may be untenable in some circumstances for any number of reasons (e.g., different genotypes, differences in health care use outside the trial protocol, differences in concomitant medication use, and differences in family or social support). Differences between individuals can result in qualitatively and quantitatively different slopes of change over time [4,5].…”

Section: Introductionmentioning

confidence: 99%

Identifying Differential Responders and Their Characteristics in Clinical Trials: Innovative Methods for Analyzing Longitudinal Data

Stull¹,

Houghton²

2013

Value in Health

Self Cite

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“…Therefore, there are two types of HTE: 1) the latent class variable in GMM divides individuals into groups with different growth curves; and 2) coefficient estimates vary across latent classes. Donald Stull et al apply GMM to identify and characterize differential responders to treatment for COPD [44]. In comparison of LGM and GMM focusing on longitudinal data, Luke & Muthen discuss factor mixture modeling as a method for cross-sectional studies when heterogeneous populations arise in a similar fashion as in GMM [45].…”

Section: Reviewmentioning

confidence: 99%

From concepts, theory, and evidence of heterogeneity of treatment effects to methodological approaches: a primer

Willke

Zheng

Subedi

et al. 2012

BMC Med Res Methodol

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Implicit in the growing interest in patient-centered outcomes research is a growing need for better evidence regarding how responses to a given intervention or treatment may vary across patients, referred to as heterogeneity of treatment effect (HTE). A variety of methods are available for exploring HTE, each associated with unique strengths and limitations. This paper reviews a selected set of methodological approaches to understanding HTE, focusing largely but not exclusively on their uses with randomized trial data. It is oriented for the “intermediate” outcomes researcher, who may already be familiar with some methods, but would value a systematic overview of both more and less familiar methods with attention to when and why they may be used. Drawing from the biomedical, statistical, epidemiological and econometrics literature, we describe the steps involved in choosing an HTE approach, focusing on whether the intent of the analysis is for exploratory, initial testing, or confirmatory testing purposes. We also map HTE methodological approaches to data considerations as well as the strengths and limitations of each approach. Methods reviewed include formal subgroup analysis, meta-analysis and meta-regression, various types of predictive risk modeling including classification and regression tree analysis, series of n-of-1 trials, latent growth and growth mixture models, quantile regression, and selected non-parametric methods. In addition to an overview of each HTE method, examples and references are provided for further reading.By guiding the selection of the methods and analysis, this review is meant to better enable outcomes researchers to understand and explore aspects of HTE in the context of patient-centered outcomes research.

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Application of latent growth and growth mixture modeling to identify and characterize differential responders to treatment for COPD

Cited by 25 publications

References 26 publications

Improved Blood Pressure Control Using an Interactive Mobile Phone Support System

Improved Blood Pressure Control Using an Interactive Mobile Phone Support System

Identifying Differential Responders and Their Characteristics in Clinical Trials: Innovative Methods for Analyzing Longitudinal Data

From concepts, theory, and evidence of heterogeneity of treatment effects to methodological approaches: a primer

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