Identifying patient subgroups who benefit most from a treatment: using administrative claims data to uncover treatment heterogeneity

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 = 6320) or LDX (n = 6394) 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.

Keywords::

• Comparative effectiveness
• Stratified medicine
• Patient subgroups
• Attention deficit hyperactivity disorder
• Methylphenidate
• Amphetamine

Transparency

Declaration of funding

This study was funded by Shire Development LLC., Wayne, PA, USA.

Declaration of financial/other interests

J.E.S., H.Y., K.P., K.A.B., J.X., and E.Q.W. have disclosed that they are employees of Analysis Group, Inc., a company that received funding from Shire Development LLC to conduct this study. M.H.E., J.S., and P.H. have disclosed that they are employees of Shire Development LLC. Shire develops and markets psychiatric drugs including treatments for ADHD.

Acknowledgments

No assistance in the preparation of this article is to be declared.