urc mondor

Unité de Recherche Clinique Henri Mondor

Four Distinct Health Profiles in Older Patients With Cancer: Latent Class Analysis of the Prospective ELCAPA Cohort.

Ferrat E, Audureau E, Paillaud E, Liuu E, Tournigand C, Lagrange J-L, Canoui-Poitrine F, Caillet P, Bastuji-Garin S J Gerontol A Biol Sci Med Sci. 2016;71(12):1653-1660.

<p><b>BACKGROUND: </b>Several studies have evaluated the independent prognostic value of impairments in single geriatric-assessment (GA) components in elderly cancer patients. None identified homogeneous subgroups. Our aims were to identify such subgroups based on combinations of GA components and to assess their associations with treatment decisions, admission, and death.</p><p><b>METHODS: </b>We prospectively included 1,021 patients aged ≥70 years who had solid or hematologic malignancies and who underwent a GA in one of two French teaching hospitals. Two geriatricians independently selected candidate GA parameters for latent class analysis, which was then performed on the 821 cases without missing data. Age, gender, tumor site, metastatic status, and inpatient versus outpatient status were used as active covariates and predictors of class membership. Outcomes were cancer treatment decisions, overall 1-year mortality, and 6-month unscheduled admissions. Sensitivity analyses were performed on the overall population of 1,021 patients and on 375 newly enrolled patients.</p><p><b>RESULTS: </b>We identified four classes: relatively healthy (LC1, 28%), malnourished (LC2, 36%), cognitive and mood impaired (LC3, 15%), and globally impaired (LC4, 21%). Tumor site, metastatic status, age, and in/outpatient status independently predicted class membership (p < .001). In adjusted pairwise comparisons, compared to LC1, the three other LCs were associated with higher risks of palliative treatment, death, and unscheduled admission (p ≤ .05). LC4 was associated with 1-year mortality and palliative treatment compared to LC2 and LC3 (p ≤ .05).</p><p><b>CONCLUSION: </b>We identified four health profiles that may help physicians select cancer treatments and geriatric interventions. Researchers may find these profiles useful for stratifying patients in clinical trials.</p>

MeSH terms: Aged; Decision Making; Female; France; Geriatric Assessment; Hospitalization; Humans; Male; Neoplasms; Prognosis; Prospective Studies; Risk Assessment
DOI: 10.1093/gerona/glw052