• Inger Utne, Borghild Løyland, Ellen Karine Grov, Hege Lund Rasmussen, Ann Helen Torstveit, Bruce A Cooper, Judy Mastick, Melissa Mazor, Melisa Wong, Steven M Paul, Yvette P Conley, Thierry Jahan, Christine Ritchie, Jon D Levine, and Christine Miaskowski.
• Department of Nursing and Health Promotion, Faculty of Health Sciences, OsloMet - Oslo Metropolitan University, Oslo, Norway.
• Eur J Oncol Nurs. 2018 Oct 1; 36: 32-39.

PurposeWhile attentional function is an extremely important patient outcome for older adults, research on changes in function in this group is extremely limited. The purposes of this study were to: identify subgroups of older patients (i.e., latent growth classes) based on changes in their level of self-reported attentional function; determine which demographic and clinical characteristics were associated with subgroup membership; and determine if these subgroups differed on quality of life (QOL) outcomes.MethodsOlder oncology outpatients (n = 365) who were assessed for changes in attention and working memory using the Attentional Function Index a total of six times over two cycles of chemotherapy (CTX). QOL was assessed using the Medical Outcomes Study-Short Form 12 and the QOL-Patient Version Scale. Latent profile analysis (LPA) was used to identify subgroups of older adults with distinct attentional function profiles.ResultsThree distinct attentional functional profiles were identified (i.e., low, moderate, and high attentional function). Compared to the high class, older adults in the low and moderate attentional function classes had lower functional status scores, a worse comorbidity profile and were more likely to be diagnosed with depression. In addition, QOL scores followed an expected pattern (low class < moderate class < high attentional function class).ConclusionsThree distinct attentional function profiles were identified among a relatively large sample of older adults undergoing CTX. The phenotypic characteristics associated with membership in the low and moderate latent classes can be used by clinicians to identify high risk patients.Copyright © 2018 Elsevier Ltd. All rights reserved.

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