Application of latent growth and growth mixture modeling to identify and
characterize differential responders to treatment for COPD.
Author(s): Stull DE, Wiklund I, Gale R, Capkun-Niggli G, Houghton K, Jones P.
Affiliation(s): RTI Health Solutions, The Pavilion, Towers Business Park, Wilmslow Road,
Didsbury, Manchester, M20 2LS, UK. dstull@rti.org
Publication date & source: 2011, Contemp Clin Trials. , 32(6):818-28
OBJECTIVE: To explore the utility of applying growth mixture models (GMMs) in
secondary analyses of clinical trials to identify sources of variability in data
reported by patients with COPD.
METHODS: Analyses were performed on data from two 6-month clinical trials
comparing indacaterol and open-label tiotropium or blinded salmeterol and the
first six months of a 12-month trial comparing indacaterol and blinded
formoterol. Latent growth model (LGM) analyses were conducted to explore the
response of the SGRQ Symptoms score from baseline to six months and GMM analyses
were evaluated as a method to identify latent classes of differential responders.
RESULTS: Variability in SGRQ Symptom scores was found suggesting subsets of
patients with differential response to treatment. GMM analyses found subsets of
non-responders in all trials. When the responders were analyzed separately from
non-responders, there were increased treatment effects (e.g., symptoms score
improvement over six months for whole groups: indacaterol=8-12 units,
tiotropium=7 units, salmeterol=9 units, formoterol=11 units. Responder subgroup
improvement: indacaterol=9-21 units, tiotropium=7 units, salmeterol=10 units,
formoterol=20 units). Responders had significantly different baseline SGRQ
Symptom scores, smoking history, age, and mMRC dyspnea scores than
non-responders.
CONCLUSIONS: Patients with COPD represent a heterogeneous population in terms of
their reporting of symptoms and response to treatment. GMM analyses are able to
identify sub-groups of responders and non-responders. Application of this
methodology could be of value on other endpoints in COPD and in other disease
areas.
|