Document Detail

Identifying Patient Subgroups Who Benefit Most from a Treatment ─ Using Administrative Claims Data to Uncover Treatment Heterogeneity.
MedLine Citation:
PMID:  22537226     Owner:  NLM     Status:  Publisher    
Abstract Objectives: To illustrate how claims data can be used to 1) develop outcome scores that predict response to a traditional treatment and 2) estimate the economic impact of individualized assignment to a newer treatment based on the outcome score. An example application is based on two treatments for attention deficit hyperactivity disorder (ADHD): osmotic-release oral system methylphenidate (OROS-MPH) and lisdexamfetamine dimesylate (LDX). Methods: Adolescents with ADHD initiating OROS-MPH (N=6,320) or LDX (N=6,394) were selected from the MarketScan claims database. A model was developed for predicting risk of switching/augmentation with OROS-MPH using multiple baseline characteristics. The model was applied to an independent sample to stratify patients by their predicted risk and, within each stratum, risk of switching/augmentation and ADHD-related total costs were compared between OROS-MPH and LDX patients using inverse probability of treatment weighting. Results: The prediction model resulted in substantial stratification, showing risk of switching/augmentation with OROS-MPH ranging from 11.3-42.1%. In the two strata where OROS-MPH had highest risk of switching/augmentation, LDX had significantly lower risk of switching/augmentation than OROS-MPH (by 7.0-8.2%) and lower ADHD-related annual total costs (by $264-$625 per patient). Limitations: The current study has used the risk of switching/augmentation as a proxy measure for treatment efficacy to establish the prediction model, future research using a clinical measure for ADHD symptoms is warranted to verify the findings. Conclusions: Combining multiple patient characteristics into a predicted score for treatment outcomes with a traditional treatment can help identify subgroups of patients who benefit most from a new treatment. In this analysis, ADHD patients with a high predicted score for switching/augmentation with OROS-MPH had a lower rate of switching/augmentation with LDX. Assigning OROS-MPH and LDX treatments based on the predicted scores that are heterogeneous in a patient population may help improve clinical outcomes and the cost-effectiveness of care.
M Haim Erder; James E Signorovitch; Juliana Setyawan; Hongbo Yang; Kejal Parikh; Keith A Betts; Jipan Xie; Paul Hodgkins; Eric Q Wu
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-4-27
Journal Detail:
Title:  Journal of medical economics     Volume:  -     ISSN:  1941-837X     ISO Abbreviation:  -     Publication Date:  2012 Apr 
Date Detail:
Created Date:  2012-4-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9892255     Medline TA:  J Med Econ     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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