title: Use of latent growth curve models for assessing the effects of darbepoetin alfa on hemoglobin and fatigue.
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.
authors.affiliation: Center for Health Outcomes Research, United BioSource Corporation, 20 Bloomsbury Square, London WC1A 2NS, UK. donald.stull@unitedbiosource.com
authors.forename: Donald E
authors.initials: DE
authors.lastname: Stull
authors.forename: Margaret K
authors.initials: MK
authors.lastname: Vernon
authors.forename: Jason C
authors.initials: JC
authors.lastname: Legg
authors.forename: Hema N
authors.initials: HN
authors.lastname: Viswanathan
authors.forename: Diane
authors.initials: D
authors.lastname: Fairclough
authors.forename: Dennis A
authors.initials: DA
authors.lastname: Revicki
mesh_terms: D000740:Anemia / Q000139:chemically induced / Q000188:drug therapy*; D000970:Antineoplastic Agents / Q000009:adverse effects*; D019540:Area Under Curve; D000068256:Darbepoetin alfa; D004921:Erythropoietin / Q000031:analogs & derivatives* / Q000627:therapeutic use; D005221:Fatigue / Q000139:chemically induced / Q000188:drug therapy* / Q000209:etiology; D005260:Female; D006305:Health Status Indicators; D006397:Hematinics / Q000627:therapeutic use*; D006454:Hemoglobins / Q000187:drug effects*; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D009369:Neoplasms / Q000150:complications / Q000188:drug therapy*; D012044:Regression Analysis; D013223:Statistics as Topic
chemical_list: D000970:Antineoplastic Agents; D006397:Hematinics; D006454:Hemoglobins; D004921:Erythropoietin; D000068256:Darbepoetin alfa