Skip to main content

Advertisement

Log in

Novel computerized neurocognitive test battery is sensitive to cancer-related cognitive deficits in survivors

  • Published:
Journal of Cancer Survivorship Aims and scope Submit manuscript

Abstract

Purpose

There is increasing interest in developing new methods to improve sensitivity in detecting subtle cognitive deficits associated with cancer and its treatments. The current study aimed to evaluate the ability of a novel computerized battery of cognitive neuroscience–based tests to discriminate between cognitive performance in breast cancer survivors and controls.

Methods

Breast cancer survivors (N = 174) and age-matched non-cancer controls (N = 183) completed the Enformia Cogsuite Battery of cognitive assessments, comprised of 7 computerized tests of multiple cognitive domains. Primary outcome measures included accuracy, reaction times (RT), and coefficients of variation (CV) for each task, as well as global scores of accuracy, RT, and CV aggregated across tests.

Results

Linear regressions adjusting for age, education, and remote vs. in-office administration showed that compared to non-cancer controls, survivors had significantly lower performance on measures of attention, executive function, working memory, verbal ability, visuospatial ability, and motor function. Survivors had significantly greater CV on measures of attention, working memory, and processing speed, and significantly slower RT on measures of verbal fluency.

Conclusions

The Cogsuite battery demonstrates sensitivity to cancer-related cognitive dysfunction across multiple domains, and is capable of identifying specific cognitive processes that may be affected in survivors.

Implications for Cancer Survivors

The sensitivity of these tasks to subtle cognitive deficits has advantages for initial diagnosis of cancer-related cognitive dysfunction, as well as detecting changes in survivors’ cognitive function over time. The remote delivery of the battery may help overcome barriers associated with in-office administration and increase access to neurocognitive evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.

Code availability

Not applicable.

References

  1. Koppelmans V, Breteler MMB, Boogerd W, Seynaeve C, Gundy C, Schagen S. Neuropsychological performance in survivors of breast cancer more than 20 years after adjuvant chemotherapy. J Clin Oncol. 2012;30(10):1080–6.

  2. Ahles TA, Root JC, Ryan EL. Cancer- and cancer treatment-associated cognitive changes: an update on the state of the science. J Clin Oncol. 2012;30:3675–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Vardy J, Wefel JS, Ahles TA, Tannock IF, Schagen SB. Cancer and cancer-therapy related cognitive dysfunction: an international perspective from the Venice cognitive workshop. Ann Oncol. 2007;19:623–9. https://doi.org/10.1093/annonc/mdm500.

    Article  PubMed  Google Scholar 

  4. Ahles TA, Root JC. Cognitive effects of cancer and cancer treatments. Annu Rev Clin Psychol. 2018;14:425–51. https://doi.org/10.1146/annurev-clinpsy-050817-084903.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Horowitz TS, Suls J, Treviño M. A call for a neuroscience approach to cancer-related cognitive impairment. Trends Neurosci. 2018;41:493–6. https://doi.org/10.1016/j.tins.2018.05.001.

    Article  CAS  PubMed  Google Scholar 

  6. Patel SK, Meier AM, Fernandez N, Lo TTY, Moore C, Delgado N. Convergent and criterion validity of the CogState computerized brief battery cognitive assessment in women with and without breast cancer. Clin Neuropsychol. 2017;31:1375–86. https://doi.org/10.1080/13854046.2016.1275819.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Heitzer AM, Ashford JM, Harel BT, Schembri A, Swain MA, Wallace J, et al. Computerized assessment of cognitive impairment among children undergoing radiation therapy for medulloblastoma. J Neurooncol. 2019;141:403–11. https://doi.org/10.1007/s11060-018-03046-2.

    Article  PubMed  Google Scholar 

  8. Feenstra HEM, Murre JMJ, Vermeulen IE, Kieffer JM, Schagen SB. Reliability and validity of a self-administered tool for online neuropsychological testing: the Amsterdam Cognition Scan. J Clin Exp Neuropsychol. 2018;40:253–73. https://doi.org/10.1080/13803395.2017.1339017.

    Article  PubMed  Google Scholar 

  9. Root JC, Ryan E, Barnett G, Andreotti C, Bolutayo K, Ahles TA. Learning and memory performance in a cohort of clinically referred breast cancer survivors: the role of attention versus forgetting in patient-reported memory complaints: memory performance in breast cancer survivors. Psychooncology. 2015;24:548–55. https://doi.org/10.1002/pon.3615.

    Article  PubMed  Google Scholar 

  10. Root JC, Andreotti C, Tsu L, Ellmore TM, Ahles TA. Learning and memory performance in breast cancer survivors 2 to 6 years post-treatment: the role of encoding versus forgetting. J Cancer Surviv. 2016;10:593–9. https://doi.org/10.1007/s11764-015-0505-4.

    Article  PubMed  Google Scholar 

  11. Gaynor AM, Ahles TA, Ryan E, Schofield E, Li Y, Patel SK, et al. Initial encoding deficits with intact memory retention in older long-term breast cancer survivors. 2021. J Cancer Surviv. https://doi.org/10.1007/s11764-021-01086-8.

  12. Fan J, McCandliss BD, Sommer T, Raz A, Posner MI. Testing the efficiency and independence of attentional networks. J Cogn Neurosci. 2002;14:340–7. https://doi.org/10.1162/089892902317361886.

    Article  PubMed  Google Scholar 

  13. Bernstein LJ, Catton PA, Tannock IF. Intra-individual variability in women with breast cancer. Journal of the International Neuropsychological Society 2014;20. https://doi.org/10.1017/S1355617714000125.

  14. Verbruggen F, Aron AR, Band GP, Beste C, Bissett PG, Brockett AT, et al. A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task. Elife. 2019;8:e46323. https://doi.org/10.7554/eLife.46323.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kam JWY, Boyd LA, Hsu CL, Liu-Ambrose T, Handy TC, Lim HJ, et al. Altered neural activation during prepotent response inhibition in breast cancer survivors treated with chemotherapy: an fMRI study. Brain Imaging Behav. 2016;10:840–8. https://doi.org/10.1007/s11682-015-9464-7.

    Article  PubMed  Google Scholar 

  16. Scherling C, Collins B, MacKenzie J, Bielajew C, Smith A. Prechemotherapy differences in response inhibition in breast cancer patients compared to controls: a functional magnetic resonance imaging study. J Clin Exp Neuropsychol. 2012;34:543–60. https://doi.org/10.1080/13803395.2012.666227.

    Article  PubMed  Google Scholar 

  17. Chao HH, Uchio E, Zhang S, Hu S, Bednarski SR, Luo X, et al. Effects of androgen deprivation on brain function in prostate cancer patients - a prospective observational cohort analysis. BMC Cancer. 2012;12:371. https://doi.org/10.1186/1471-2407-12-371.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. McDonald BC, Conroy SK, Ahles TA. Alterations in brain activation during working memory processing associated with breast cancer and treatment: a prospective functional MRI study. J Clin Oncol. 2012;30:2500–8.

    Article  PubMed  PubMed Central  Google Scholar 

  19. McDonald BC, Conroy SK, Ahles TA, West JD, Saykin AJ. Gray matter reduction associated with systemic chemotherapy for breast cancer: a prospective MRI study. Breast Cancer Res Treat. 2010;123:819–28. https://doi.org/10.1007/s10549-010-1088-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Inagaki M, Yoshikawa E, Matsuoka Y, Sugawara Y, Nakano T, Akechi T, et al. Smaller regional volumes of brain gray and white matter demonstrated in breast cancer survivors exposed to adjuvant chemotherapy. Cancer. 2007;109:146–56.

    Article  PubMed  Google Scholar 

  21. McDonald BC, Conroy SK, Smith DJ, West JD, Saykin AJ. Frontal gray matter reduction after breast cancer chemotherapy and association with executive symptoms: a replication and extension study. Brain Behav Immun. 2013;30(Suppl):S117-125. https://doi.org/10.1016/j.bbi.2012.05.007.

    Article  PubMed  Google Scholar 

  22. Deprez S, Amant F, Yigit R, Porke K, Verhoeven J, den Stock JV, et al. Chemotherapy-induced structural changes in cerebral white matter and its correlation with impaired cognitive functioning in breast cancer patients. Hum Brain Mapp. 2011;32:480–93. https://doi.org/10.1002/hbm.21033.

    Article  PubMed  Google Scholar 

  23. McDonald BC, Saykin AJ. Alterations in brain structure related to breast cancer and its treatment: chemotherapy and other considerations. Brain Imaging Behav. 2013;7:374–87. https://doi.org/10.1007/s11682-013-9256-x.

    Article  PubMed  Google Scholar 

  24. Owen AM, McMillan KM, Laird AR, Bullmore E. N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp. 2005;25:46–59. https://doi.org/10.1002/hbm.20131.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Luxton J, Brinkman TM, Kimberg C, Robison LL, Hudson MM, Krull KR. Utility of the N-back task in survivors of childhood acute lymphoblastic leukemia. J Clin Exp Neuropsychol. 2014;36:944–55. https://doi.org/10.1080/13803395.2014.957168.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jim SL, Phillips KM, Chait S. Meta-analysis of cognitive functioning in breast cancer survivors previously treated with standard-dose chemotherapy. J Clin Oncol. 2012;30:3578–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. McGinty HL, Phillips KM, Jim HSL, Cessna JM, Asvat Y, Cases MG, et al. Cognitive functioning in men receiving androgen deprivation therapy for prostate cancer: a systematic review and meta-analysis. Support Care Cancer. 2014;22:2271–80. https://doi.org/10.1007/s00520-014-2285-1.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Cherrier MM, Higano CS. Impact of androgen deprivation therapy on mood, cognition, and risk for AD. Urologic Oncology: Seminars and Original Investigations. 2020;38:53–61. https://doi.org/10.1016/j.urolonc.2019.01.021.

    Article  PubMed  Google Scholar 

  29. Shepard RN, Metzler J. Mental rotation of three-dimensional objects. Science. 1971;171:701–3. https://doi.org/10.1126/science.171.3972.701.

    Article  CAS  PubMed  Google Scholar 

  30. Mm C, Pr B, Al S, Cs H. Changes in neuronal activation patterns in response to androgen deprivation therapy: a pilot study. BMC Cancer 2010;10. https://doi.org/10.1186/1471-2407-10-1.

  31. Ahles TA, Li Y, McDonald BC, Schwartz GN, Kaufman PA, Tsongalis GJ, et al. Longitudinal assessment of cognitive changes associated with adjuvant treatment for breast cancer: the impact of APOE and smoking: cognition and breast cancer treatment. Psychooncology. 2014;23:1382–90. https://doi.org/10.1002/pon.3545.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Hedayati E, Schedin A, Nyman H, Alinaghizadeh H, Albertsson M. The effects of breast cancer diagnosis and surgery on cognitive functions. Acta Oncol. 2011;50:1027–36. https://doi.org/10.3109/0284186X.2011.572911.

    Article  PubMed  Google Scholar 

  33. Phillips KM, Jim HS, Small BJ, Laronga C, Andrykowski MA, Jacobsen PB. Cognitive functioning after cancer treatment. Cancer. 2012;118:1925–32. https://doi.org/10.1002/cncr.26432.

    Article  PubMed  Google Scholar 

  34. Robinson LM, Fitts SS, Kraft GH. Laterality of performance in fingertapping rate and grip strength by hemisphere of stroke and gender. Arch Phys Med Rehabil. 1990;71:695–8.

    CAS  PubMed  Google Scholar 

  35. Zhai F, Liu J, Su N, Han F, Zhou L, Ni J, et al. Disrupted white matter integrity and network connectivity are related to poor motor performance. Sci Rep. 2020;10:18369. https://doi.org/10.1038/s41598-020-75617-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Suzumura S, Kanada Y, Osawa A, Sugioka J, Maeda N, Nagahama T, et al. Assessment of finger motor function that reflects the severity of cognitive function. Fujita Med J. 2021;7:122–9. https://doi.org/10.20407/fmj.2020-013.

    Article  PubMed  Google Scholar 

  37. van Dam FSAM, Boogerd W, Schagen SB, Muller MJ, Droogleeverfortuyn ME, Wall EVD, et al. Impairment of cognitive function in women receiving adjuvant treatment for high-risk breast cancer: high-dose versus standard-dose chemotherapy. JNCI: Journal of the National Cancer Institute. 1998;90:210–8. https://doi.org/10.1093/jnci/90.3.210.

    Article  CAS  PubMed  Google Scholar 

  38. Schagen SB, van Dam FSAM, Muller MJ, Boogerd W, Lindeboom J, Bruning PF. Cognitive deficits after postoperative adjuvant chemotherapy for breast carcinoma. Cancer. 1999;85:640–50. https://doi.org/10.1002/(SICI)1097-0142(19990201)85:3%3c640::AID-CNCR14%3e3.0.CO;2-G.

    Article  CAS  PubMed  Google Scholar 

  39. Lange M, Joly F, Vardy J, Ahles T, Dubois M, Tron L, et al. Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors. Ann Oncol. 2019;30:1925–40. https://doi.org/10.1093/annonc/mdz410.

    Article  CAS  PubMed  Google Scholar 

  40. Enformia. Cogsuite. Enformia Inc. n.d. Retrieved September 3, 2021 from https://www.enformia.com/.

  41. Box GEP, Cox DR. An analysis of transformations. J Roy Stat Soc: Ser B (Methodol). 1964;26:211–43. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x.

    Article  Google Scholar 

  42. Hultsch DF, MacDonald SWS, Dixon RA. Variability in reaction time performance of younger and older adults. J Gerontol B Psychol Sci Soc Sci. 2002;57:P101-115. https://doi.org/10.1093/geronb/57.2.p101.

    Article  PubMed  Google Scholar 

  43. Venables WN, Ripley BD, Venables WN. Modern applied statistics with S. 4th ed. New York: Springer; 2002.

    Book  Google Scholar 

  44. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2020)

  45. IBM Spss Statistics. Armonk. NY: IBM Corp; 2020.

    Google Scholar 

  46. Ehrenstein JK, van Zon SKR, Duijts SFA, van Dijk BAC, Dorland HF, Schagen SB, et al. Type of cancer treatment and cognitive symptoms in working cancer survivors: an 18-month follow-up study. J Cancer Surviv. 2020;14:158–67. https://doi.org/10.1007/s11764-019-00839-w.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Dijkshoorn ABC, van Stralen HE, Sloots M, Schagen SB, Visser-Meily JMA, Schepers VPM. Prevalence of cognitive impairment and change in patients with breast cancer: a systematic review of longitudinal studies. Psychooncology. 2021;30:635–48. https://doi.org/10.1002/pon.5623.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Joly F, Giffard B, Rigal O, De Ruiter MB, Small BJ, Dubois M, et al. Impact of cancer and its treatments on cognitive function: advances in research from the Paris International Cognition and Cancer Task Force Symposium and Update Since 2012. J Pain Symptom Manage. 2015;50:830–41. https://doi.org/10.1016/j.jpainsymman.2015.06.019.

    Article  PubMed  Google Scholar 

  49. Schagen SB. Late effects of adjuvant chemotherapy on cognitive function: a follow-up study in breast cancer patients. Ann Oncol. 2002;13:1387–97. https://doi.org/10.1093/annonc/mdf241.

    Article  CAS  PubMed  Google Scholar 

  50. Dykiert D, Der G, Starr JM, Deary IJ. Age differences in intra-individual variability in simple and choice reaction time: systematic review and meta-analysis. PLoS ONE. 2012;7:e45759. https://doi.org/10.1371/journal.pone.0045759.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. LaPlume AA, Anderson ND, McKetton L, Levine B, Troyer AK. When I’m 64: age-related variability in over 40,000 online cognitive test takers. J Gerontol B Psychol Sci Soc Sci. 2022;77:104–17. https://doi.org/10.1093/geronb/gbab143.

    Article  PubMed  Google Scholar 

  52. Bielak AAM, Hultsch DF, Strauss E, Macdonald SWS, Hunter MA. Intraindividual variability in reaction time predicts cognitive outcomes 5 years later. Neuropsychology. 2010;24:731–41. https://doi.org/10.1037/a0019802.

    Article  PubMed  Google Scholar 

  53. Bunce D, Anstey KJ, Christensen H, Dear K, Wen W, Sachdev P. White matter hyperintensities and within-person variability in community-dwelling adults aged 60–64 years. Neuropsychologia. 2007;45:2009–15. https://doi.org/10.1016/j.neuropsychologia.2007.02.006.

    Article  PubMed  Google Scholar 

  54. Bahmani Z, Clark K, Merrikhi Y, Mueller A, Pettine W, Isabel Vanegas M, et al. Prefrontal contributions to attention and working memory. Curr Top Behav Neurosci. 2019;41:129–53. https://doi.org/10.1007/7854_2018_74.

    Article  PubMed  Google Scholar 

  55. Crawford JR, Sutherland D, Garthwaite PH. On the reliability and standard errors of measurement of contrast measures from the D-KEFS. J Int Neuropsychol Soc. 2008;14:1069–73. https://doi.org/10.1017/S1355617708081228.

    Article  PubMed  Google Scholar 

  56. MacLeod JW, Lawrence MA, McConnell MM, Eskes GA, Klein RM, Shore DI. Appraising the ANT: psychometric and theoretical considerations of the attention network test. Neuropsychology. 2010;24:637–51. https://doi.org/10.1037/a0019803.

    Article  PubMed  Google Scholar 

  57. Wang Y-F, Cui Q, Liu F, Huo Y-J, Lu F-M, Chen H, et al. A new method for computing attention network scores and relationships between attention networks. PLoS ONE. 2014;9:e89733. https://doi.org/10.1371/journal.pone.0089733.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Fan J, Gu X, Guise KG, Liu X, Fossella J, Wang H, et al. Testing the behavioral interaction and integration of attentional networks. Brain Cogn. 2009;70:209–20. https://doi.org/10.1016/j.bandc.2009.02.002.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Manly JJ, Jacobs DM, Touradji P, Small SA, Stern Y. Reading level attenuates differences in neuropsychological test performance between African American and White elders. J Int Neuropsychol Soc. 2002;8:341–8. https://doi.org/10.1017/S1355617702813157.

    Article  PubMed  Google Scholar 

  60. Manly JJ, Tang M-X, Schupf N, Stern Y, Vonsattel J-PG, Mayeux R. Frequency and course of mild cognitive impairment in a multiethnic community. Annals of Neurology. 2008;63:494–506. https://doi.org/10.1002/ana.21326.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Zahodne L, Manly J, Narkhede A, Griffith E, Decarli C, Schupf N, et al. Structural MRI predictors of late-life cognition differ across African Americans, Hispanics, and Whites. Current Alzheimer Research. 2015;12:632–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. McEwen BS. In pursuit of resilience: stress, epigenetics, and brain plasticity: In pursuit of resilience. Ann NY Acad Sci. 2016;1373:56–64. https://doi.org/10.1111/nyas.13020.

    Article  PubMed  Google Scholar 

  63. Chattarji S, Tomar A, Suvrathan A, Ghosh S, Rahman MM. Neighborhood matters: divergent patterns of stress-induced plasticity across the brain. Nat Neurosci. 2015;18:1364–75. https://doi.org/10.1038/nn.4115.

    Article  CAS  PubMed  Google Scholar 

  64. Menning S, de Ruiter MB, Veltman DJ, Koppelmans V, Kirschbaum C, Boogerd W, et al. Multimodal MRI and cognitive function in patients with breast cancer prior to adjuvant treatment - The role of fatigue. NeuroImage: Clinical. 2015;7:547–54. https://doi.org/10.1016/j.nicl.2015.02.005.

    Article  PubMed  Google Scholar 

  65. Pullens MJJ, De Vries J, Roukema JA. Subjective cognitive dysfunction in breast cancer patients: a systematic review. Psychooncology. 2010;19:1127–38. https://doi.org/10.1002/pon.1673.

    Article  PubMed  Google Scholar 

  66. Asher A. Cognitive dysfunction among cancer survivors. Am J Phys Med Rehabil. 2011;90:S16-26. https://doi.org/10.1097/PHM.0b013e31820be463.

    Article  PubMed  Google Scholar 

  67. Morrison GE, Simone CM, Ng NF, Hardy JL. Reliability and validity of the NeuroCognitive Performance Test, a web-based neuropsychological assessment. Frontiers in Psychology 2015;6.

  68. Bauer RM, Iverson GL, Cernich AN, Binder LM, Ruff RM, Naugle RI. Computerized neuropsychological assessment devices: joint position paper of the American Academy of Clinical Neuropsychology and the National Academy of Neuropsychology. Arch Clin Neuropsychol. 2012;27:362–73. https://doi.org/10.1093/arclin/acs027.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Wojcik CM, Beier M, Costello K, DeLuca J, Feinstein A, Goverover Y, et al. Computerized neuropsychological assessment devices in multiple sclerosis: a systematic review. Mult Scler. 2019;25:1848–69. https://doi.org/10.1177/1352458519879094.

  70. Maruff P, Collie A, Darby D, Weaver-Cargin J, Masters C, Currie J. Subtle Memory Decline over 12 Months in Mild Cognitive Impairment. Dement Geriatr Cogn Disord. 2004;18:342–8. https://doi.org/10.1159/000080229.

    Article  CAS  PubMed  Google Scholar 

  71. Friedman TW, Yelland GW, Robinson SR. Subtle cognitive impairment in elders with mini-mental state examination scores within the ‘normal’ range. Int J Geriatr Psychiatry. 2012;27:463–71. https://doi.org/10.1002/gps.2736.

    Article  PubMed  Google Scholar 

  72. Snyder PJ, Jackson CE, Petersen RC, Khachaturian AS, Kaye J, Albert MS, et al. Assessment of cognition in mild cognitive impairment: a comparative study. Alzheimer’s & Dementia. 2011;7:338–55. https://doi.org/10.1016/j.jalz.2011.03.009.

    Article  Google Scholar 

  73. Weissberger GH, Strong JV, Stefanidis KB, Summers MJ, Bondi MW, Stricker NH. Diagnostic accuracy of memory measures in Alzheimer’s dementia and mild cognitive impairment: a systematic review and meta-analysis. Neuropsychol Rev. 2017;27:354–88. https://doi.org/10.1007/s11065-017-9360-6.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Hoogland J, van Wanrooij LL, Boel JA, Goldman JG, Stebbins GT, Dalrymple-Alford JC, et al. Detecting mild cognitive deficits in Parkinson’s disease: comparison of neuropsychological tests. Mov Disord. 2018;33:1750–9. https://doi.org/10.1002/mds.110.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work was supported by grants from the National Cancer Institute at the National Institutes of Health (SBIR grant # HHSN261201600024C, P30 CA008748).

Author information

Authors and Affiliations

Authors

Contributions

AMG: data curation, formal analysis, writing—original draft, writing—review and editing, and visualization. AA: data curation, writing—review and editing, and visualization. DJ: conceptualization, funding acquisition, resources, investigation, data curation, and writing—review and editing. LS: formal analysis and writing—review and editing. YL: formal analysis and writing—review and editing. TAA: conceptualization, investigation, and writing—review and editing. JCR: conceptualization, funding acquisition, resources, investigation, data curation, and writing—review and editing.

Corresponding author

Correspondence to Alexandra M. Gaynor.

Ethics declarations

Ethics approval

This study involving human participants was performed in accordance with the ethical standards of the institution and national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study protocol was approved by the ethics committee and the Institutional Review Boards at Memorial Sloan Kettering Cancer Center and City of Hope National Medical Center.

Consent to participate

Informed consent was obtained from all participants in this study.

Consent for publication

Not applicable.

Conflict of interest

Duane Jung is the CEO of the Enformia, Inc., the publisher of the Cogsuite battery. All other authors certify that they have no conflicts of interest to disclose.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (JPG 933 kb)

Supplementary file2 (JPG 611 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gaynor, A.M., Ahsan, A., Jung, D. et al. Novel computerized neurocognitive test battery is sensitive to cancer-related cognitive deficits in survivors. J Cancer Surviv 18, 466–478 (2024). https://doi.org/10.1007/s11764-022-01232-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11764-022-01232-w

Keywords

Navigation