Assessment and management of cognitive changes in patients with cancer

Parsons, Michael; Dietrich, Jörg

doi:10.1002/cncr.31905

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…If more in-depth cognitive evaluation is required, neuropsychological assessments should be considered. Neuropsychological assessment provides an quantitative as well as qualitative evaluation of factors contributing to cognitive dysfunction, including developmental history, comorbidities, psychiatric syndromes, and polypharmacy [80]. For instance, if there is suspicion of cognitive decline, neuropsychologists are trained to recognize neuropsychological patterns typical of normal aging, Alzheimer's disease and other dementias, psychiatric disorders, and other conditions -which can inform differential diagnosis of CRCD.…”

Section: Neuropsychological Assessmentmentioning

confidence: 99%

Embracing the complexity: Older adults with cancer-related cognitive decline—A Young International Society of Geriatric Oncology position paper

Pergolotti

Battisti

Padgett

et al. 2020

Journal of Geriatric Oncology

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Cancer-related cognitive decline (CRCD) may have particularly significant consequences for older adults, impacting their functional and physical abilities, level of independence, ability to make decisions, treatment adherence, overall quality of life, and ultimately survival. In honor of Dr. Hurria's work we explore and examine multiple types of screening, assessment and nonpharmacologic treatments for CRCD. We then suggest future research and clinical practice questions to holistically appreciate the complexity of older adults with cancer's experiences and fully integrate the team-based approach to best serve this population.

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Section: Neuropsychological Assessmentmentioning

confidence: 99%

Embracing the complexity: Older adults with cancer-related cognitive decline—A Young International Society of Geriatric Oncology position paper

Pergolotti

Battisti

Padgett

et al. 2020

Journal of Geriatric Oncology

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“…End-of-life patients with cancer may have difficulty expressing their symptoms if they can no longer communicate verbally owing to the deterioration of their general condition 10 . When verbal communication with the patient is difficult, experience is required for assessing subjective symptoms known only to the patient 5 .…”

Section: Introductionmentioning

confidence: 99%

Novel method for predicting nonvisible symptoms using machine learning in cancer palliative care

Shimada

Tsuneto

2023

Sci Rep

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End-of-life patients with cancer may find expressing their symptoms difficult if they can no longer communicate verbally because of deteriorating health. In this study, we assessed these symptoms using machine learning, which has excellent predictive capabilities and has recently been applied in healthcare. We performed a retrospective clinical survey involving 213 patients with cancer from August 2015 to August 2016. We divided the reported symptoms into two groups—visible and nonvisible symptoms. We used decision tree analysis, an analytical machine learning method that organizes and analyzes information in the form of a tree diagram to visually represent the information structure. Our machine learning model used patient background data and visible symptoms to predict nonvisible symptoms: pain, dyspnea, fatigue, drowsiness, anxiety, delirium, inadequate informed consent, and spiritual issues. The highest and/or lowest values for prediction accuracy, sensitivity, and specificity were 88.0%/55.5%, 84.9%/3.3%, and 96.7%/24.1%, respectively. This work will facilitate better assessment and management of symptoms in patients with cancer. This study was the first to predict nonvisible symptoms using decision tree analyses for patients with cancer receiving palliative care. Notably, applications based on our results may assess symptoms to the same extent as healthcare professionals.

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“…9 Patients with cancer at the end of life may have di culty expressing their symptoms if they can no longer communicate verbally owing to the deterioration of their general condition. 10 When verbal communication with the patient is di cult, experience is required for assessing subjective symptoms known only to the patient. 5 Additionally, there is often a dearth of palliative care specialists in rural areas.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method to Predict Nonvisible Symptoms Using Machine Learning in Cancer Palliative Care

Shimada

Tsuneto

2022

SSRN Journal

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Assessment and management of cognitive changes in patients with cancer

Abstract: Cancer‐related cognitive impairment has been a contentious issue in the past, but 2 decades of research have improved our understanding of the problem. It is time to move these advances into routine clinical care for cancer patients.

Cited by 10 publications

References 27 publications

Embracing the complexity: Older adults with cancer-related cognitive decline—A Young International Society of Geriatric Oncology position paper

Embracing the complexity: Older adults with cancer-related cognitive decline—A Young International Society of Geriatric Oncology position paper

Novel method for predicting nonvisible symptoms using machine learning in cancer palliative care

A Novel Method to Predict Nonvisible Symptoms Using Machine Learning in Cancer Palliative Care

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