BACKGROUND: Health-related quality of life (HRQOL) heterogeneity among cancer survivors may mask subgroups (classes) with different limitations and long-term outcomes. The authors determined the HRQOL classes that exist among lung cancer survivors, examined transitions among those classes over time, and compared survival outcomes of patients according to the classes present in the initial phase of care. METHODS: Lung cancer survivors in the Cancer Care Outcomes Research and Surveillance Consortium completed EuroQol 5-domain quality-of-life questionnaires 4.8 months (initial phase) and >1 year (survivorship phase) after diagnosis (n = 1396). Latent class analysis and latent transition analysis were used to determine HRQOL classes and transitions across time. Correlates of class membership were tested using multinomial logistic regression. Kaplan-Meier and Cox regression analyses were used to compare survival across class membership. RESULTS: Latent class analysis identified 4 classes at diagnosis and follow-up: 1) poor HRQOL, 2) pain-dominant impairment, 3) mobility/usual activities impairment, and 4) good HRQOL. Probabilities of remaining in the same class were .87, .85, .82, and .73 for classes 4, 1, 3, and 2, respectively. Younger age, lower income, lower education, comorbidities, and a history of depression/emotional problems were associated with a greater likelihood of being in classes 1, 2, or 3 at follow-up. Patients in classes 1 and 3 had significantly lower median survival estimates than patients in class 4 (4.8 years, 3.8 years, and 5.5 years, respectively; P < .001). CONCLUSIONS: Examining the heterogeneity of HRQOL in lung cancer populations allows the identification of classes with different limitations and long-term outcomes and, thus, guides tailored and patient-centered provision of supportive care.
BACKGROUND: Health-related quality of life (HRQOL) heterogeneity among cancer survivors may mask subgroups (classes) with different limitations and long-term outcomes. The authors determined the HRQOL classes that exist among lung cancer survivors, examined transitions among those classes over time, and compared survival outcomes of patients according to the classes present in the initial phase of care. METHODS:Lung cancer survivors in the Cancer Care Outcomes Research and Surveillance Consortium completed EuroQol 5-domain quality-of-life questionnaires 4.8 months (initial phase) and >1 year (survivorship phase) after diagnosis (n = 1396). Latent class analysis and latent transition analysis were used to determine HRQOL classes and transitions across time. Correlates of class membership were tested using multinomial logistic regression. Kaplan-Meier and Cox regression analyses were used to compare survival across class membership. RESULTS: Latent class analysis identified 4 classes at diagnosis and follow-up: 1) poor HRQOL, 2) pain-dominant impairment, 3) mobility/usual activities impairment, and 4) good HRQOL. Probabilities of remaining in the same class were .87, .85, .82, and .73 for classes 4, 1, 3, and 2, respectively. Younger age, lower income, lower education, comorbidities, and a history of depression/emotional problems were associated with a greater likelihood of being in classes 1, 2, or 3 at follow-up. Patients in classes 1 and 3 had significantly lower median survival estimates than patients in class 4 (4.8 years, 3.8 years, and 5.5 years, respectively; P < .001). CONCLUSIONS: Examining the heterogeneity of HRQOL in lung cancer populations allows the identification of classes with different limitations and long-term outcomes and, thus, guides tailored and patient-centered provision of supportive care.
Authors: Janneke P C Grutters; Manuela A Joore; Erwin M Wiegman; Johannes A Langendijk; Dirk de Ruysscher; Monique Hochstenbag; Anita Botterweck; Philippe Lambin; Madelon Pijls-Johannesma Journal: Thorax Date: 2010-10 Impact factor: 9.139
Authors: Dennis G Fryback; Nancy Cross Dunham; Mari Palta; Janel Hanmer; Jennifer Buechner; Dasha Cherepanov; Shani A Herrington; Ron D Hays; Robert M Kaplan; Theodore G Ganiats; David Feeny; Paul Kind Journal: Med Care Date: 2007-12 Impact factor: 2.983
Authors: I-Chan Huang; Constantine Frangakis; Mark J Atkinson; Richard J Willke; Walter L Leite; W Bruce Vogel; Albert W Wu Journal: Health Serv Res Date: 2008-02 Impact factor: 3.402
Authors: Laura C Pinheiro; Xianming Tan; Andrew F Olshan; Stephanie B Wheeler; Katherine E Reeder-Hayes; Cleo A Samuel; Bryce B Reeve Journal: Qual Life Res Date: 2017-02-28 Impact factor: 4.147
Authors: Judith Z Goldfinger; Liliana R Preiss; Richard B Devereux; Mary J Roman; Tabitha P Hendershot; Barbara L Kroner; Kim A Eagle Journal: J Am Coll Cardiol Date: 2017-06-13 Impact factor: 24.094
Authors: Lorra Garey; Lorraine R Reitzel; Julie Neisler; Darla E Kendzor; Michael J Zvolensky; Clayton Neighbors; Daphne C Hernandez; Michael S Businelle Journal: Behav Med Date: 2018-05-14 Impact factor: 3.104