Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Apr 11;31(5):253.
doi: 10.1007/s00520-023-07723-5.

Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more

Kord M Kober  1   2   3 , Ritu Roy  4 , Yvette Conley  5 , Anand Dhruva  6 , Marilyn J Hammer  7 , Jon Levine  6 , Adam Olshen  4   8   6 , Christine Miaskowski  9   4
Affiliations

Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more

Kord M Kober et al. Support Care Cancer. .

Abstract

Introduction: Fatigue is the most common and debilitating symptom experienced by cancer patients undergoing chemotherapy (CTX). Prediction of symptom severity can assist clinicians to identify high-risk patients and provide education to decrease symptom severity. The purpose of this study was to predict the severity of morning fatigue in the week following the administration of CTX.

Methods: Outpatients (n = 1217) completed questionnaires 1 week prior to and 1 week following administration of CTX. Morning fatigue was measured using the Lee Fatigue Scale (LFS). Separate prediction models for morning fatigue severity were created using 157 demographic, clinical, symptom, and psychosocial adjustment characteristics and either morning fatigue scores or individual fatigue item scores. Prediction models were created using two regression and five machine learning approaches.

Results: Elastic net models provided the best fit across all models. For the EN model using individual LFS item scores, two of the 13 individual LFS items (i.e., "worn out," "exhausted") were the strongest predictors.

Conclusions: This study is the first to use machine learning techniques to accurately predict the severity of morning fatigue from prior to through the week following the administration of CTX using total and individual item scores from the Lee Fatigue Scale (LFS). Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict morning fatigue severity.

Keywords: Cancer; Chemotherapy; Diurnal variability; Fatigue; Machine learning; Patient reported outcomes; Prediction modeling.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

References

    1. Papadakos JK, Charow RC, Papadakos CJ, Moody LJ, Giuliani ME (2019) Evaluating cancer patient-reported outcome measures: readability and implications for clinical use. Cancer 125(8):1350–1356 - PubMed - DOI
    1. Kotronoulas G, Kearney N, Maguire R, Harrow A, Di Domenico D, Croy S, MacGillivray S (2014) What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. J Clin Oncol 32(14):1480–1501 - PubMed - DOI
    1. Lipscomb J, Reeve BB, Clauser SB, Abrams JS, Bruner DW, Burke LB, Denicoff AM, Ganz PA, Gondek K, Minasian LM, O’Mara AM, Revicki DA, Rock EP, Rowland JH, Sgambati M, Trimble EL (2007) Patient-reported outcomes assessment in cancer trials: taking stock, moving forward. J Clin Oncol 25(32):5133–5140 - PubMed - DOI
    1. Chen J, Ou L, Hollis SJ (2013) A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Serv Res 13:211 - PubMed - PMC - DOI
    1. Basch E, Deal AM, Dueck AC, Scher HI, Kris MG, Hudis C, Schrag D (2017) Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA 318(2):197–198 - PubMed - PMC - DOI

Substances

LinkOut - more resources