Literature DB >> 20060499

Use of latent growth curve models for assessing the effects of darbepoetin alfa on hemoglobin and fatigue.

Donald E Stull1, Margaret K Vernon, Jason C Legg, Hema N Viswanathan, Diane Fairclough, Dennis A Revicki.   

Abstract

BACKGROUND: The relationship between darbepoetin alfa and fatigue in chemotherapy-induced anemia (CIA) patients is complex because of patients receiving transfusions and the mediating effect of hemoglobin. Latent growth models (LGMs) were used to examine simultaneously relationships among drug exposure, fatigue outcomes, covariates, and mediating factors.
METHODS: Data from four CIA studies (AMG 20010145: small cell lung cancer, n=547; AMG 980297: lung cancer, n=288; AMG 20000161: lymphoproliferative malignancies, n=339; AMG 20030232: non-myeloid malignancies, n=320) were analyzed separately. Patients reported fatigue using the FACT-Fatigue. The effect of darbepoetin alfa on FACT-F changes mediated through hemoglobin changes was examined with LGMs controlling for transfusions, age, sex, baseline ECOG performance status, and health status (EQ-5D VAS). Model fit was assessed using multiple indices including the comparative fit index (CFI).
RESULTS: Darbepoetin alfa increased hemoglobin levels which were associated with decreases in fatigue. Increases in hemoglobin were statistically significantly (p<0.05) related to decreases in fatigue in the studies (AMG 20030145: beta=0.28; AMG 980297: beta=0.46; AMG 20000161: beta=0.59; and AMG 20030232: beta=0.39). Darbepoetin alfa statistically significantly increased hemoglobin (AMG 20010145:beta=0.50, AMG 980297:beta=0.53, AMG 20000161:beta=0.47, and AMG 20030232:beta=0.30) while controlling for covariates. Model fit was acceptable (CFI> or =0.89) in all studies.
CONCLUSIONS: Results indicate LGMs may be a valuable statistical method for modeling complex relationships among clinical and patient reported outcomes. A statistically significant effect of darbepoetin alfa on fatigue change through hemoglobin change occurred across four studies, after modeling the effects of transfusions, age, sex, EQ-5D VAS and ECOG. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20060499     DOI: 10.1016/j.cct.2009.12.006

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.226


  5 in total

Review 1.  Content validity of patient-reported outcome measures: perspectives from a PROMIS meeting.

Authors:  Susan Magasi; Gery Ryan; Dennis Revicki; William Lenderking; Ron D Hays; Meryl Brod; Claire Snyder; Maarten Boers; David Cella
Journal:  Qual Life Res       Date:  2011-08-25       Impact factor: 4.147

Review 2.  Erythropoietin or darbepoetin for patients with cancer.

Authors:  Thomy Tonia; Annette Mettler; Nadège Robert; Guido Schwarzer; Jerome Seidenfeld; Olaf Weingart; Chris Hyde; Andreas Engert; Julia Bohlius
Journal:  Cochrane Database Syst Rev       Date:  2012-12-12

3.  Synchronization of administrations of chemotherapy and erythropoiesis-stimulating agents and frequency of associated healthcare visits.

Authors:  Jerrold W Hill; Sanatan Shreay; November McGarvey; Ajita P De; Gregory P Hess; Patricia K Corey-Lisle
Journal:  Support Care Cancer       Date:  2013-06-12       Impact factor: 3.603

Review 4.  Erythropoietin and cancer: the unintended consequences of anemia correction.

Authors:  Nataša Debeljak; Peter Solár; Arthur J Sytkowski
Journal:  Front Immunol       Date:  2014-11-11       Impact factor: 7.561

5.  Assessing Changes in Chronic Spontaneous/Idiopathic Urticaria: Comparisons of Patient-Reported Outcomes Using Latent Growth Modeling.

Authors:  Donald E Stull; Doreen McBride; Katherine Houghton; Andrew Y Finlay; Ari Gnanasakthy; Maria-Magdalena Balp
Journal:  Adv Ther       Date:  2016-01-30       Impact factor: 3.845

  5 in total

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