ArticleFatigue : biomedicine, health & behavior2021
Prediction of evening fatigue severity in outpatients receiving chemotherapy: less may be more.
Article in Fatigue : biomedicine, health & behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review.Health and quality of life outcomes · 2025Article
- Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.JCO clinical cancer informatics · 2024Article
- Machine Learning Approaches to Predict Symptoms in People With Cancer: Systematic Review.JMIR cancer · 2024Review
- Ecological Momentary Assessment to Explore Fatigue, Mood, and Physical Activity Levels in People Receiving Peritoneal Dialysis.Kidney international reports · 2024Article
- Predicting patient reported outcome measures: a scoping review for the artificial intelligence-guided patient preference predictor.Frontiers in artificial intelligence · 2024Article
- Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023Article
- [Tiredness, fatigue and exhaustion: all the same or manifestations of a continuum?-Food for thought].Somnologie : Schlafforschung und Schlafmedizin = Somnology : sleep research and sleep medicine · 2022Review
- Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundFatigue is the most common and debilitating symptom experienced by oncology patients undergoing chemotherapy. Little is known about patient characteristics that predict changes in fatigue severity over time. PURPOSE: To predict the severity of evening fatigue in the week following the administration of chemotherapy using machine learning approaches.
methodsOutpatients with breast, gastrointestinal, gynecological, or lung cancer (
resultsRandom forest (RF) models provided the best fit across all models. For the RF model using individual LFS item scores, two of the 13 individual LFS items (i.e., "worn out", "exhausted") were the strongest predictors.
conclusionThis study is the first to use machine learning techniques to predict evening fatigue severity in the week following chemotherapy from fatigue scores obtained in the week prior to chemotherapy. 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 evening fatigue severity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.