Longitudinal Analysis of Depression and Anxiety Symptoms as Independent Predictors of Neurocognitive Function in Primary Brain Tumor Patients

Tibbs, M.D.; Huynh‐Le, Minh‐Phuong; Reyes, Anny; Macari, Anna Christina; Karunamuni, Roshan; Tringale, Kathryn R.; Burkeen, J.; Marshall, Deborah; Xu, Ronghui; McDonald, Carrie R.; Hattangadi‐Gluth, Jona A.

doi:10.1016/j.ijrobp.2020.07.002

Cited by 33 publications

(17 citation statements)

References 41 publications

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“…We further excluded 106 publications based on the exclusion criteria. Finally, 23 studies describing the development of prediction models were included, of which 16 ( Gregor et al, 1996 ; Blay et al, 1998 ; Klein et al, 2002 ; Kaleita et al, 2004 ; van Beek et al, 2007 ; Wang et al, 2010 ; Starke et al, 2011 ; Gondi et al, 2012 ; Kangas et al, 2012 ; Chapman et al, 2016 ; Wong et al, 2019 ; Dutz et al, 2020 ; Gui et al, 2020 ; Tibbs et al, 2020 ; Langegård et al, 2021 ; Zamanipoor Najafabadi et al, 2021 ) studies included patients with primary and 7 ( Wolfson et al, 2011 ; Gondi et al, 2013 ; Nakazaki and Kano, 2013 ; Chen et al, 2017 ; Yamamoto et al, 2017 ; Gui et al, 2019 ; Brown et al, 2020 ) with metastatic brain tumors. No external validation studies were identified.…”

Section: Resultsmentioning

confidence: 99%

Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients With Primary or Secondary Brain Tumors: A Systematic Review

et al. 2022

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PurposeAlthough an increasing body of literature suggests a relationship between brain irradiation and deterioration of neurocognitive function, it remains as the standard therapeutic and prophylactic modality in patients with brain tumors. This review was aimed to abstract and evaluate the prediction models for radiation-induced neurocognitive decline in patients with primary or secondary brain tumors.MethodsMEDLINE was searched on October 31, 2021 for publications containing relevant truncation and MeSH terms related to “radiotherapy,” “brain,” “prediction model,” and “neurocognitive impairments.” Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool.ResultsOf 3,580 studies reviewed, 23 prediction models were identified. Age, tumor location, education level, baseline neurocognitive score, and radiation dose to the hippocampus were the most common predictors in the models. The Hopkins verbal learning (n = 7) and the trail making tests (n = 4) were the most frequent outcome assessment tools. All studies used regression (n = 14 linear, n = 8 logistic, and n = 4 Cox) as machine learning method. All models were judged to have a high risk of bias mainly due to issues in the analysis.ConclusionExisting models have limited quality and are at high risk of bias. Following recommendations are outlined in this review to improve future models: developing cognitive assessment instruments taking into account the peculiar traits of the different brain tumors and radiation modalities; adherence to model development and validation guidelines; careful choice of candidate predictors according to the literature and domain expert consensus; and considering radiation dose to brain substructures as they can provide important information on specific neurocognitive impairments.

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Section: Resultsmentioning

confidence: 99%

Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients With Primary or Secondary Brain Tumors: A Systematic Review

et al. 2022

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“…Lastly, the EQ-5D asks patients to rate their abilities across five domains using a descriptive scale ranging from “I have no problems [with activity]” to “I am unable to do [activity].” The five domains in the scale are mobility (ability to walk), self-care (ability to wash or dress self), usual activities (including work, study, housework, family or leisure activities), pain/ discomfort, and anxiety/depression ( 50 ). Importantly, this scale attempts to capture anxiety and depression, which have been shown to occur in advanced disease, including stage IV cancers ( 37 , 51 ). However, the scale's brevity may prevent providers and researchers to understand specific drivers of poorer QoL.…”

Section: Quality Of Life In Patients With Brain Metastasesmentioning

confidence: 99%

Quality of Life and Role of Palliative and Supportive Care for Patients With Brain Metastases and Caregivers: A Review

Colón

Lim

2022

Front. Neurol.

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Brain metastases (BM) are the most commonly diagnosed secondary brain lesions in adults, influencing these patients' symptoms and treatment courses. With improvements in oncologic treatments, patients with BM are now living longer with their advanced cancers, and issues pertaining to quality of life become more pressing. The American Society of Clinical Oncology has recommended early implementation of palliative care for cancer patients, though incorporation and implementation of palliative and other supportive services in the setting of true multidisciplinary care requires additional attention and research for patients with intracranial metastases. We review the physical, cognitive, and psychosocial challenges patients with BM and their caregivers face during their cancer course as well as the current published research on quality of life metrics relating to this patient population and the diverse roles specialty palliative care, rehabilitation services, and other healthcare providers play in a comprehensive multidisciplinary care model.

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“…We further excluded 106 publications based on the exclusion criteria. Finally, 23 studies describing the development of prediction models were included, of which 16 [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] studies included patients with primary and 7 [35][36][37][38][39][40][41] with metastatic brain tumors. No external validation studies were identi ed.…”

Section: General Characteristics Of Included Studiesmentioning

confidence: 99%

“…Regarding the data source, retrospective cohort was the most popular study design used for nine studies [19,20,23,27,31,33,34,37,39], followed by prospective cohort (seven studies) [21,22,25,26,28,30,38], and prospective trials (seven studies) [24,29,32,35,36,40,41]. The median sample size of the cohorts was 81 (IQR=54-266) and the median incidence of neurocognitive toxicity for studies with binary outcome was 26% (IQR=14%-73%).…”

Section: General Characteristics Of Included Studiesmentioning

confidence: 99%

“…Three studies included the patients who underwent prophylactic cranial irradiation [35,36,40]. Following irradiation techniques were used: intensity modulated radiotherapy (n=4) [28, 30,32,41], stereotactic radiotherapy (n=4) [26,27,38,39], proton beam therapy (n=3) [31,32,34], and gamma knife radiosurgery (n=2) [25,37]. Eleven studies included the patients who were treated with chemotherapy [24, 27, 28, 30-32, 34-36, 40, 41].…”

Section: General Characteristics Of Included Studiesmentioning

confidence: 99%

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Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients with Primary or Secondary Brain Tumors: A Systematic Review

Tohidinezhad

Perri

Zegers

et al. 2021

Preprint

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Purpose: Although an increasing body of literature suggests a relationship between brain irradiation and deterioration of neurocognitive function, it remains as the standard therapeutic and prophylactic modality in patients with brain tumors. This review was aimed to abstract and evaluate the prediction models for radiation-induced neurocognitive decline in patients with primary or secondary brain tumors.Methods: MEDLINE was searched on October 31, 2021 for publications containing relevant truncation and MeSH terms related to “radiotherapy”, “brain”, “prediction model”, and “neurocognitive impairments”. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool.Results: Of 3,580 studies reviewed, 23 prediction models were identified. Age, tumor location, education level, baseline neurocognitive score, and radiation dose to the hippocampus were the most common predictors in the models. The Hopkins verbal learning (n=7) and the trail making tests (n=4) were the most frequent outcome assessment tools. All studies used regression (n=14 linear, n=8 logistic, and n=4 Cox) as machine learning method. All models were judged to have a high risk of bias mainly due to issues in the analysis.Conclusion: Existing models have limited quality and are at high risk of bias. Following recommendations are outlined in this review to improve future models: develop a standardized instrument for neurocognitive assessment in patients with brain tumors; adherence to model development and validation guidelines; careful choice of candidate predictors according to the literature and domain expert consensus; and considering radiation dose to brain substructures as they can provide important information on specific neurocognitive impairments.

show abstract

Longitudinal Analysis of Depression and Anxiety Symptoms as Independent Predictors of Neurocognitive Function in Primary Brain Tumor Patients

Cited by 33 publications

References 41 publications

Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients With Primary or Secondary Brain Tumors: A Systematic Review

Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients With Primary or Secondary Brain Tumors: A Systematic Review

Quality of Life and Role of Palliative and Supportive Care for Patients With Brain Metastases and Caregivers: A Review

Prediction Models for Radiation-Induced Neurocognitive Decline in Adult Patients with Primary or Secondary Brain Tumors: A Systematic Review

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