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Effectiveness of Intraindividual Variability in Detecting Subtle Cognitive Performance Deficits in Breast Cancer Patients

Published online by Cambridge University Press:  08 June 2018

Barbara Collins ,
Gerard Widmann  and
Giorgio A. Tasca
Barbara Collins*
Affiliation:
The Ottawa Hospital – Civic Campus, Ottawa, Ontario, Canada The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
Gerard Widmann
Affiliation:
The Ottawa Hospital – Civic Campus, Ottawa, Ontario, Canada Adler University, Chicago, Illinois
Giorgio A. Tasca
Affiliation:
The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
*
Correspondence and reprint requests to: Barbara Collins, The Ottawa Hospital Research Institute, 725 Parkdale Avenue, Ottawa, ON, Canada, K1Y 4E9. E-mail: [email protected]
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Abstract

Objectives: The purpose of this study was to determine if intraindividual variability would be more sensitive than speed or accuracy in detecting subtle cancer-related cognitive disturbance. Methods: Data were from a previous study in which 60 breast cancer (BC) patients underwent neuropsychological assessment before commencement of chemotherapy and again following each chemotherapy cycle. Sixty healthy controls were tested at equivalent intervals. Hierarchical linear modeling was used to compare the BC and control groups in terms of accuracy, mean reaction time, and intraindividual variability in reaction time on a computerized continuous performance test with three conditions: a simple reaction time task, a “1-back” task, and a “2-back” task. Results: An increase in accuracy and response speed over sessions was noted on some tasks in the sample as a whole but there were no differences in these parameters between the BC patients and the controls on any condition. There was a significant group difference in change in intraindividual variability across sessions (i.e., a “group × session interaction”), albeit only on the most complex “2-back” task. Intraindividual variability declined in the control group (i.e., consistency improved with practice) but this practice effect was significantly attenuated in the BC patients. There was no main effect of group on the “2-back” task. Conclusions: Results support our hypothesis that intraindividual variability is a more sensitive indicator of subtle cognitive disturbance than conventional speed or accuracy measures and may have potential in the assessment of mild cognitive impairment in patients with non-central nervous system cancers. (JINS, 2018, 24, 1–11)

Keywords

OncologyChemotherapyCognitive functionExecutive functionReaction timeIntraindividual variabilityNeuropsychological testing
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 7 , August 2018 , pp. 724 - 734
Copyright
Copyright © The International Neuropsychological Society 2018 

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References

REFERENCES

Askren, M.K., Jung, M., Berman, M.G., Zhang, M., Therrien, B., Peltier, S., & Cimprich, B. (2014). Neuromarkers of fatigue and cognitive complaints following chemotherapy for breast cancer: A prospective fMRI investigation. Breast Cancer Research and Treatment, 147, 445–455. doi: 10.1007/s10549-014-3092-6 Google Scholar
Bernstein, L.J., Catton, P.A., & Tannock, I.F. (2014). Intra-individual variability in women with breast cancer. Journal of the International Neuropsychological Society, 20, 380–390. doi: 10.1017/s1355617714000125 Google Scholar
Bernstein, L.J., McCreath, G.A., Komeylian, Z., & Rich, J.B. (2017). Cognitive impairment in breast cancer survivors treated with chemotherapy depends on control group type and cognitive domains assessed: A mutli-level meta-analysis. Neuroscience and Biobehavioral Reviews, 83, 417–428. doi: 10.106/j.neubiorev.2017.10.028 Google Scholar
Bruhn, P., & Parsons, O.A. (1977). Reaction time variability in epileptic and brain-damaged patients. Cortex 1977, 13, 373–384. doi.org/ 10.1016/S00-10-9452(77)80018-X Google Scholar
Burton, C.L., Strauss, E., Hultsch, D.F., & Hunter, M.A. (2009). The relationship between everyday problem solving and inconsistency in reaction time in older adults. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 16, 607–632. doi: 10.1080/13825580903167283 Google Scholar
Castellanos, F.X., Sonuga-Barke, E.J.S., Scheres, A., Di Martino, A., Hyde, C., & Walters, J.R. (2005). Varieties of attention-deficit/hyperactivity disorder-related intraindividual variability. Biological Psychiatry, 57, 1416–1423. doi: 10.1016/j.biopsych.2004.12.005 Google Scholar
Collins, B., Mackenzie, J., Tasca, G.A., Scherling, C., & Smith, A. (2013). Cognitive effects of chemotherapy in breast cancer patients: A dose-response study. Psychooncology, 22, 1517–1527. doi: 10.1002/pon.3163 Google Scholar
De Ruiter, M.B., & Schagen, S. (2013). Functional MRI studies in non-CNS cancers. Brain Imaging and Behavior, 7, 388–408. doi: 10.1007/s11682-013-9249-9 Google Scholar
Debess, J., Riis, J.Ø., Engebjerg, M.C., & Ewertz, M. (2010). Cognitive function after adjuvant treatment for early breast cancer: A population-based longitudinal study. Breast Cancer Research and Treatment, 121, 91–100. doi: 10.1007/s10549-010-0756-8 Google Scholar
Deprez, S., Billiet, T., Sunaert, S., & Leemans, A. (2013). Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: A review. Brain Imaging and Behavior, 7, 409–435. doi: 10.1007/s11682-012-9220-1 Google Scholar
Duchek, J.M., Balota, D.A., Tse, C.-S., Holtzman, D.M., Fagan, A.M., & Goate, A.M. (2009). The utility of intraindividual variability in selective attention tasks as an early marker for Alzheimer’s disease. Neuropsychology, 23, 746–758. doi: 10.1037/a0016583 Google Scholar
Duijts, S.F.A., van Egmond, M.P., Spelten, E., van Muijen, P., Anema, J.R., & van der Beek, A.J. (2014). Physical and psychosocial problems in cancer survivors beyond return to work: A systematic review. Psychooncology, 23, 481–492. doi: 10.1002/pon.3467 Google Scholar
Fauser, M., Löhle, M., Ebersbach, G., Odin, P., Fuchs, G., Jost, W.H., & Storch, A. (2015). Intraindividual variability of nonmotor fluctuations in advanced Parkinson’s disease. Journal of Parkinson’s Disease, 5, 737–741. doi: 10.3233/JPD-150656 Google Scholar
Fitch, M.I., Armstrong, J., & Tsang, S. (2008). Patients’ experiences with cognitive changes after chemotherapy. Canadian Oncology Nursing Journal, 18, 180–192. doi: 10.5737/1181912x184180185 Google Scholar
Flehmig, H.C., Steinborn, M., Langner, R., Scholz, A., & Westhoff, K. (2007). Assessing intraindividual variability in sustained attention: Reliability, relation to speed and accuracy, and practice effects. Psychology Science, 49, 132–149.Google Scholar
Gelman, A., & Loken, E. (2013). The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time. In. 14.11.2013 ed. Technical report, Department of Statistics, Columbia University. Retrieved from http://www.stat.columbia.edu/~gelman/research/unpublished/p_hacking.pdf Google Scholar
Golay, P., Fagot, D., & Lecerf, T. (2013). Against coefficient of variation for estimation of intraindividual variability with accuracy measures. Tutorials in Quantitative Methods for Psychology, 9, 6–14.Google Scholar
Gualtieri, C.T., & Johnson, L.G. (2006). Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Archives of Clinical Neuropsychology, 21, 623–643. doi: 10.1016/j.acn.2006.05.007 Google Scholar
Haynes, B.I., Bauermeister, S., & Bunce, D. (2017). A systematic review of longitudinal associations between reaction time intraindividual variability and age-related cognitive decline or impairment, dementia, and mortality. Journal of the International Neuropsychological Society, 23, 431–455. doi: 10.1017/S1355617717000236 Google Scholar
Hermelink, K., Küchenhoff, H., Untch, M., Bauerfeind, I., Lux, M.P., Bühner, M., & Münzel, K. (2010). Two different sides of ‘chemobrain’: Determinants and nondeterminants of self-perceived cognitive dysfunction in a prospective, randomized, multicenter study. Psychooncology, 19, 1321–1328. doi: 10.1002/pon.1695 Google Scholar
Hill, B.D., Rohling, M.L., Boettcher, A.C., & Meyers, J.E. (2013). Cognitive intra-individual variability has a positive association with traumatic brain injury severity and suboptimal effort. Archives of Clinical Neuropsychology, 28, 640–648. doi: 10.1093/arclin/act045 Google Scholar
Hodgson, K.D., Hutchinson, A.D., Wilson, C.J., & Nettelbeck, T. (2013). A meta-analysis of the effects of chemotherapy on cognition in patients with cancer. Cancer Treatment Reviews, 39, 297–304. doi: 10.1016/j.ctrv.2012.11.001 Google Scholar
Hultsch, D.F., MacDonald, S.W.S., & Dixon, R.A. (2002). Variability in reaction time performance of younger and older adults. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 57B, 101–115. doi.org/ 10.1093/geronb/57.2.P101 Google Scholar
Hultsch, D.F., MacDonald, S.W.S., Hunter, M.A., Levy-Bencheton, J., & Strauss, E. (2000). Intraindividual variability in cognitive performance in older adults: Comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology, 14, 588–598. doi: 10.1037//0894-4105.14.4.588 Google Scholar
Hutchinson, A.D., Hosking, J.R., Kichenadasse, G., Mattiske, J.K., & Wilson, C. (2012). Objective and subjective cognitive impairment following chemotherapy for cancer: A systematic review. Cancer Treatment Reviews, 38, 926–934. doi: 10.1016/j.ctrv.2012.05.002 Google Scholar
Jackson, J.D., Balota, D.A., Duchek, J.M., & Head, D. (2012). White matter integrity and reaction time intraindividual variability in healthy aging and early-stage Alzheimer disease. Neuropsychologia, 50, 357–366. doi: 10.1016/j.neuropsychologia.2011.11.024 Google Scholar
Janelsins, M.C., Heckler, C.E., Peppone, L.J., Kamen, C., Mustian, K.M., Mohile, S.G., & Morrow, G.R. (2017). Cognitive complaints in survivors of breast cancer after chemotherapy compared with age-matched controls: An analysis from a nationwide, multicenter, prospective longitudinal study. Journal of Clinical Oncology, 35, 506–514. doi:10.1200/JCO.2016.68.5826 Google Scholar
Kesler, S.R., Kent, J.S., & O’Hara, R. (2011). Prefrontal cortex and executive function impairments in primary breast cancer. Archives of Neurology, 68, 1447–1453. doi: 10.1001/archneurol.2011.245 Google Scholar
Li, S.-C., Aggen, S.H., Nesselroade, J.R., & Baltes, P.B. (2001). Short-term fluctuations in elderly people’s sensorimotor functioning predict text and spatial memory performance: The MacArthur Successful Aging Studies. Gerontology, 47, 100–116. doi: 10.1159/000052782 Google Scholar
Morgan, E.E., Woods, S.P., Delano-Wood, L., Bondi, M.W., & Grant, I. (2011). Intraindividual variability in HIV infection: Evidence for greater neurocognitive dispersion in older HIV seropositive adults. Neuropsychology, 25, 645–654. doi: 10.1037/a0023792 Google Scholar
Ono, M., Ogilvie, J.M., Wilson, J.S., Green, H.J., Chambers, S.K., Ownsworth, T., &Shum, D.H.K. (2015). A meta-analysis of cognitive impairment and decline associated with adjuvant chemotherapy in women with breast cancer. Frontiers in Oncology, 5, 59. doi: 10.3389/fonc.2015.00059 Google Scholar
Pullens, M.J.J., De Vries, J., & Roukema, J.A. (2010). Subjective cognitive dysfunction in breast cancer patients: A systematic review. Psychooncology, 19, 1127–1138. doi: 10.1002/pon.1673 Google Scholar
Runowicz, C.D., Leach, C.R., Henry, N.L., Henry, K.S., Mackey, H.T., Cowens-Alvarado, R.L., & Ganz, P.A. (2016). American Cancer Society/American Society of Clinical Oncology Breast Cancer Survivorship Care Guideline. Journal of Clinical Oncology, 34, 611–635. doi: 10.1200/JCO.2015.64.3809 Google Scholar
Singer, J.D., & Willett, J.B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press.Google Scholar
Stuss, D.T., Murphy, K.J., Binns, M.A., & Alexander, M.P. (2003). Staying on the job: The frontal lobes control individual performance variability. Brain, 126, 2363–2380. doi: 10.1093/brain/awg237 Google Scholar
Wagner, L.I., Sweet, J., Butt, Z., Lai, J., & Cella, D. (2009). Measuring patient self-reported cognitive function: Development of the Functional Assessment of Cancer Therapy--Cognitive Function instrument. Journal of Supportive Oncology, 7, W32–W39.Google Scholar
Wojtowicz, M., Berrigan, L.I., & Fisk, J.D. (2012). Intra-individual variability as a measure of information processing difficulties in multiple sclerosis. International Journal of MS Care, 14, 77–83.Google Scholar
Yao, C., Rich, J.B., Tannock, I.F., Seruga, B., Tirona, K., & Bernstein, L.J. (2016). Pretreatment differences in intraindividual variability in reaction time between women diagnosed with breast cancer and healthy controls. Journal of the International Neuropsychological Society, 22, 530–539. doi: 10.1017/S1355617716000126 Google Scholar
Yao, C., Rich, J.B., Tirona, K., & Bernstein, L.J. (2017). Intraindividual variability in reaction time before and after neoadjuvant chemotherapy in women diagnosed with breast cancer. Psychooncology, 26, 2261–2268. doi: 10.1002/pon.4351 Google Scholar
Zahn, T.P., Jacobsen, L.K., Gordon, C.T., McKenna, K., Frazier, J.A., & Rapoport, J.L. (1998). Attention deficits in childhood-onset schizophrenia: Reaction time studies. Journal of Abnormal Psychology, 107, 97–108. http://dx.doi.org/10.1037/0021-843X.107.1.97 Google Scholar
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