Skip to main content Accessibility help
×
Home
Hostname: page-component-cf9d5c678-ttsf8 Total loading time: 0.228 Render date: 2021-07-27T10:18:10.487Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Actigraphy as an assessment of performance status in patients with advanced lung cancer

Published online by Cambridge University Press:  11 February 2019

Daisuke Fujisawa
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA Keio University School of Medicine, Department of Neuropsychiatry and Palliative Care Center, Tokyo, Japan
Jennifer S. Temel
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA
Joseph A. Greer
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA
Areej El-Jawahri
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA
Lara Traeger
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA
Jamie M. Jacobs
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA
Stacy Cutrono
Affiliation:
Sylvester Comprehensive Cancer Center, Miami University, Miller School of Medicine, Miami, FL
William F. Pirl
Affiliation:
Massachusetts General Hospital, Cancer Center, Boston, MA Dana-Faber Cancer Institute, Psychosocial Oncology and Palliative Care, Boston, MA
Corresponding
E-mail address:

Abstract

Objective

Wearable devices such as a wrist actigraph may have a potential to objectively estimate patients’ functioning and may supplement performance status (PS). This proof-of-concept study aimed to evaluate whether actigraphy data are significantly associated with patients’ functioning and are predictive of their survival in patients with metastatic non-small cell lung cancer.

Method

We collected actigraphy data for a three-day period in ambulatory patients with stage IV non-small cell lung cancer. We computed correlations between actigraphy data (specifically, proportion of time spent immobile while awake) and clinician-rated PS, subjective report of physical activities, quality of life (the Functional Assessment of Cancer Therapy – Trial Outcome Index), and survival.

Result

Actigraphy data (the proportion of time awake spent immobile) were significantly correlated with Functional Assessment of Cancer Therapy – Trial Outcome Index (r = −0.53, p < 0.001) and with the Eastern Cooperative Oncology Group PS (ECOG PS) (r = 0.37, p < 0.001). The proportion of time awake spent immobile was significantly associated with worse survival. For each 10% increase in this measure, the hazard ratio (HR) was 1.48 (95% confidence interval [CI95%] = 1.06, 2.06) for overall mortality, and odds ratio was 2.99 (CI95% = 1.27, 7.05) for six-month mortality. ECOG PS was also associated with worse survival (HR = 2.80, CI95% = 1.34, 5.86). Among patients with ECOG PS 0-1, the percentage of time awake spent immobile was significantly associated with worse survival, HR = 1.93 (CI95% = 1.10, 3.42), whereas ECOG PS did not predict survival.

Significance of Results

Actigraphy may have potential to predict important clinical outcomes, such as quality of life and survival, and may serve to supplement PS. Further validation study is warranted.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Albain, KS, Crowley, JJ, LeBlanc, M, et al. (1991) Survival determinants in extensive-stage non-small-cell lung cancer: The Southwest Oncology Group experience. Journal of Clinical Oncology 9, 1618–26. doi: 10.1200/JCO.1991.9.9.1618CrossRefGoogle ScholarPubMed
Ando, M, Ando, Y, Hasegawa, , et al. (2001) Prognostic value of performance status assessed by patients themselves, nurses, and oncologists in advanced non-small cell lung cancer. British Journal of Cancer 85, 1634–39. doi: 10.1054/bjoc.2001.2162CrossRefGoogle ScholarPubMed
Bansal, A and Joshi, R (2018) Portable out-of-hospital electrocardiography: A review of current technologies. Journal of Arrhythmia 34, 129–38. doi: 10.1002/joa3.12035CrossRefGoogle ScholarPubMed
Beg, MS, Gupta, A, Stewart, T, et al. (2017) Promise of wearable physical activity monitors in oncology practice. Journal of Oncology Practice 13, 8289. doi: 10.1200/JOP.2016.016857CrossRefGoogle ScholarPubMed
Blagden, SP, Charman, SC, Sharples, LD, et al. (2003) Performance status score: Do patients and their oncologists agree? British Journal of Cancer 89, 1022–27. doi: 10.1038/sj.bjc.6601231CrossRefGoogle ScholarPubMed
Boyne, K, Sherry, DD, Gallagher, PR, et al. (2013) Accuracy of computer algorithms and the human eye in scoring actigraphy. Sleeping and Breathing 17, 411–17. doi: 10.1007/s11325-012-0709-zCrossRefGoogle ScholarPubMed
Broderick, JM, Ryan, J, O'Donnell, DM, et al. (2014) A guide to assessing physical activity using accelerometry in cancer patients. Supportive Care in Cancer 22, 1121–30. doi: 10.1007/s00520-013-2102-2CrossRefGoogle ScholarPubMed
Cella, DF, Bonomi, AE, Lloyd, SR, et al. (1995) Reliability and validity of the Functional Assessment of Cancer Therapy-Lung (FACT-L) quality of life instrument. Lung Cancer 12, 199220.CrossRefGoogle ScholarPubMed
Chang, WP, Smith, R, and Lin, CC (2018) Age and rest-activity rhythm as predictors of survival in patients with newly diagnosed lung cancer. Chronobiology International 35, 188–97. doi: 10.1080/07420528.2017.1391278CrossRefGoogle ScholarPubMed
Chasan-Taber, S, Rimm, EB, Stampfer, MJ, et al. (1996) Reproducibility and validity of a self-administered physical activity questionnaire for male health professionals. Epidemiology 7, 8186.CrossRefGoogle ScholarPubMed
Chen, H, Cantor, A, Meyer, J, et al. (2003). Can older cancer patients tolerate chemotherapy? A prospective pilot study. Cancer 97, 1107–14. doi: 10.1002/cncr.11110CrossRefGoogle ScholarPubMed
Colditz, GA, Feskanich, D, Chen, WY, et al. (2003) Physical activity and risk of breast cancer in premenopausal women. British Journal of Cancer 89, 847–51. doi: 10.1038/sj.bjc.6601175CrossRefGoogle ScholarPubMed
Decoster, L, Van Puyvelde, K, Mohile, S, et al. (2015) Screening tools for multidimensional health problems warranting a geriatric assessment in older cancer patients: An update on SIOG recommendations. Annals of Oncology 26, 288300. doi: 10.1093/annonc/mdu210CrossRefGoogle Scholar
Gresham, G, Schrack, J, Gresham, LM, et al. (2018) Wearable activity monitors in oncology trials: Current use of an emerging technology. Contemporary Clinical Trials Communications 64, 1321. doi: 10.1016/j.cct.2017.11.002CrossRefGoogle ScholarPubMed
Innominato, PF, Giacchetti, S, Bjarnason, GA, et al. (2012) Prediction of overall survival through circadian rest-activity monitoring during chemotherapy for metastatic colorectal cancer. International Journal of Cancer 131, 2684–92. doi: 10.1002/ijc.27574CrossRefGoogle ScholarPubMed
Jones, LW, Hornsby, WE, Goetzinger, A, et al. (2012) Prognostic significance of functional capacity and exercise behavior in patients with metastatic non-small cell lung cancer. Lung Cancer 76, 248–52. doi: 10.1016/j.lungcan.2011.10.009CrossRefGoogle ScholarPubMed
Kenis, C, Heeren, P, Bron, D, et al. (2014) Multicenter implementation of geriatric assessment in Belgian patients with cancer: A survey on treating physicians' general experiences and expectations. Journal of Geriatric Oncology 5, 431–38. doi: 10.1016/j.jgo.2014.06.043CrossRefGoogle ScholarPubMed
Levi, F, Dugue, PA, Innominato, P, et al. (2014) Wrist actimetry circadian rhythm as a robust predictor of colorectal cancer patients survival. Chronobiology International 31, 891900. doi: 10.3109/07420528.2014.924523CrossRefGoogle ScholarPubMed
Loprinzi, CL, Laurie, JA, Wieand, HS, et al. (1994) Prospective evaluation of prognostic variables from patient-completed questionnaires. North Central Cancer Treatment Group. Journal of Clinical Oncology 12, 601–07. doi: 10.1200/JCO.1994.12.3.601Google ScholarPubMed
Madsen, MT, Huang, C, and Gogenur, I (2015) Actigraphy for measurements of sleep in relation to oncological treatment of patients with cancer: A systematic review. Sleep Medicine Reviews 20, 7383. doi: 10.1016/j.smrv.2014.07.002CrossRefGoogle ScholarPubMed
Meyerhardt, JA, Giovannucci, EL, Ogino, S, et al. (2009) Physical activity and male colorectal cancer survival. Archives of Internal Medicine 169, 2102–08. doi: 10.1001/archinternmed.2009.412CrossRefGoogle ScholarPubMed
Oken, MM, Creech, RH, Tormey, DC, et al. (1982) Toxicity and response criteria of the Eastern Cooperative Oncology Group. American Journal of Clinical Oncology 5, 649–55.CrossRefGoogle ScholarPubMed
Orr, ST and Aisner, J (1986). Performance status assessment among oncology patients: A review. Cancer Treatment Report 70, 1423–29.Google ScholarPubMed
Paesmans, M, Sculier, JP, Libert, P, et al. (1995) Prognostic factors for survival in advanced non-small-cell lung cancer: Univariate and multivariate analyses including recursive partitioning and amalgamation algorithms in 1,052 patients. The European Lung Cancer Working Party. Journal of Clinical Oncology 13, 1221–30. doi: 10.1200/JCO.1995.13.5.1221CrossRefGoogle ScholarPubMed
Philips Respironics Actiwatch 2. http://www.actigraphy.respironics.com/solutions/actiwatch/actiwatch2.html (last accessed 14 January 2019).Google Scholar
Philips Respironics Actiware Tutorials. http://www.actigraphy.respironics.com/solutions/actiware/tutorials.html (last accessed 14 January 2019).Google Scholar
Sengelov, L, Kamby, C, Geertsen, P, et al. (2000) Predictive factors of response to cisplatin-based chemotherapy and the relation of response to survival in patients with metastatic urothelial cancer. Cancer Chemotherapy and Pharmacology 46, 357–64. doi: 10.1007/s002800000176Google ScholarPubMed
Stotter, A, Reed, MW, Gray, LJ, et al. (2015) Comprehensive geriatric assessment and predicted 3-year survival in treatment planning for frail patients with early breast cancer. British Journal of Surgery 102, 525–33. doi: 10.1002/bjs.9755CrossRefGoogle ScholarPubMed
Tedesco, S, Barton, J, and O'Flynn, B (2017) A review of activity trackers for senior citizens: Research perspectives, commercial landscape and the role of the insurance industry. Sensors (Basel) 17. doi: 10.3390/s17061277Google ScholarPubMed
Wang, DD and Hu, FB (2018) Precision nutrition for prevention and management of type 2 diabetes. Lancet. Diabetes and Endocrinology 6, 416426. doi: 10.1016/S2213-8587(18)30037-8CrossRefGoogle ScholarPubMed
3
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Actigraphy as an assessment of performance status in patients with advanced lung cancer
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Actigraphy as an assessment of performance status in patients with advanced lung cancer
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Actigraphy as an assessment of performance status in patients with advanced lung cancer
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *