Cognitive Function in Adults with Acute Myeloid Leukemia Treated with Chemotherapy: A Systematic Review

Abstract

Background:

Chemotherapy is essential for treating acute myeloid leukemia (AML). Prior studies concluded that survivors of cancer who were treated with chemotherapy experience cognitive impairment. Therefore, it is important to understand cognitive function in survivors of AML.

Objective:

To explore distributions and correlates of cognitive function; and prediction of cognitive function on other outcomes in adults with AML who were treated with chemotherapy.

Methods:

A health science librarian systematically searched PubMed, CINAHL, PsycINFO, and Embase databases. Two reviewers independently conducted the title, abstract, and full-text screening. Data were extracted and synthesized based on the aims of the review.

Results:

A total of 10 articles were included. Findings indicate that up to 62.2% of adults with AML experienced impaired cognitive function after starting chemotherapy. Three studies found cognitive function remained stable over time. Education and cytokines were potential correlates of cognitive function. Worse cognitive function may predict lower physical performance and higher mortality, although the results were inconsistent across studies.

Conclusion:

Impaired cognitive function was observed in adults with AML who were treated with chemotherapy. However, no study used a validated subjective cognitive function-specific patient-reported questionnaire and previous studies focusing on cognitive function included relatively young samples. Hence, further research on cognitive function in older adults with AML is needed.

Implication for practice:

Due to the high prevalence of cognitive impairment identified, it is important to screen cognitive function in adults with AML who are planning to receive chemotherapy to intervene and provide support earlier.

Introduction

Cognitive impairment has been reported in survivors of cancer and involves deficits in memory, attention, executive function, and processing speed.^{1, 2} With these deficits, survivors of cancer may experience social isolation,³ decreased working capacity,³ lower quality of life (QOL),⁴ and increased mortality risk.⁵ According to Lange and colleagues,² cognitive impairment may result from various factors, such as aging, cancer itself, genes and biomarkers, and toxicities of specific cancer treatments. Regardless of causality, decrements in cognitive function in survivors of cancer is known as cancer-related cognitive impairment (CRCI).⁶

CRCI—which has been colloquially labeled as “chemobrain” or “chemo fog”—has been reported in survivors of cancer undergoing anticancer therapy, during or after treatment completion,^{7, 8} and during long-term survivorship.⁹ Existing research focuses primarily on survivors of cancer with a solid tumor diagnosis, such as breast cancer.¹⁰ Prior studies of hematological cancers focused on pediatric populations with acute lymphoblastic leukemia or primary central nervous system lymphoma.¹¹

For survivors with a diagnosis of acute myeloid leukemia (AML), chemotherapy is a standard treatment.¹² In the United States, AML is the most common acute leukemia, with over 20 050 new cases anticipated in 2022.¹³ AML is especially common in older adults as the median age at diagnosis of 68 years.¹⁴ Because a large percentage of adults with AML receive chemotherapy and are older, it is important to understand the CRCI in this population. Furthermore, because radiation and surgery are rarely employed in adults with AML, cognitive impairment in this population after therapy may be due either to chemotherapy, the existential trauma of the diagnosis, biologic consequences of the leukemia, and aging.

The objectives of this systematic review were to 1) describe cognitive function at pre-, during, or post-chemotherapy; 2) identify potential correlates of cognitive function; and 3) explore how cognitive function predicts other outcomes in adults with AML.

Methods

This review was guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses.¹⁵ The review protocol is registered in PROSPERO (protocol # CRD 42020170338).

Search Strategy

The PubMed, CINAHL Plus with Full Text (EBSCOhost), APA PsycInfo (EBSCOhost), and Embase databases were searched by a health science librarian (JLC) on November 17, 2021. The search included a combination of key words and subject headings for AML, chemotherapy, and CRCI (Appendix I). No date restrictions and limitations were set except for the Embase database. During the Embase database search, we limited the search by including only articles as the publication type. All articles were imported into EndNote; after removing duplicates, the articles were then imported into Covidence for screening.

Data Extraction and Synthesis

Three authors (YNC, SB, and ALB) independently screened the title/abstract and full-text articles to identify studies for inclusion. Discrepancies were resolved by a third author. The inclusion criteria were: 1) full-text articles published in English, 2) included participants ≥18 years old, 3) reported cognitive function in adults with AML or a mixed sample of adults with AML or myelodysplastic syndromes (MDS) who were treated with chemotherapy, and 4) research studies with observational or experimental designs. We considered the studies eligible if they included participants with MDS because those with high-risk MDS have an increased risk of progressing to AML and may be considered for intensive chemotherapy or stem cell transplant.¹⁶ In addition, we included all chemotherapy regimens and dosage if they were identified as AML chemotherapy by the studies. For cognitive function outcome, we included overall cognitive function and cognitive domains results from the studies assessed using patient-reported questionnaires, objective neuropsychological assessments, or neuroimaging on adults with AML. Studies including survivors who received chemotherapy and those who did not receive chemotherapy but did not separately report cognitive function in participants who received chemotherapy were excluded.

Data were extracted using an Excel template created by the authors (YNC and SB) and included purpose, study design, sample size and characteristics, measure tool and time points, main findings, strengths and weaknesses, and implications. Findings were synthesized based on the aims of this review.

Quality Assessment

Instead of using the Mixed Methods Appraisal Tool (MMAT) registered in the PROSPERO, one author (YNC) assessed the quality of the included articles using the Joanna Briggs Institute (JBI) Systematic Reviews Critical Appraisal Tools.¹⁷ Specifically, for articles using longitudinal or cohort study design, we used the Checklist for Cohort Studies. For articles using cross-sectional design, we used the Checklist for Analytical Cross-Sectional Studies. Each item was assessed using “Yes”, “No”, “Unclear”, or “Not Applicable.” We did not exclude any articles based on the quality assessment results.

Results

The initial search identified 1,114 articles. After excluding duplicates and screening title/abstract, 44 articles were identified. After full-text screening, 10 articles were retained in the final synthesis (see Figure).

Figure.

PRISMA Flowchart of Study Selection Process

Study Characteristics and Study Quality

The 10 articles, from eight independent studies, were published between 2009 and 2021 across six countries (Table 1). Four were prospective longitudinal,^18–21 four were prospective cohort,^22–25 and two were cross-sectional.^{26, 27} For studies used repeated assessments over time, and intervals ranged from a month to a couple cycles of chemotherapy, with total study duration up to over 12 months. In the five studies for which cognitive function was not the main outcome, cognitive function was measured exclusively at baseline.^23–27 The majority of studies focused on geriatric assessment.^{19, 22–24, 26} Three studies had cognitive function as the main outcome.^{20, 21, 27}

Table 1.

Characteristics of the Included Studies (n=10)

First Author (Year)	Design	n	Treatment	Male (%)	Age in Years, Mean(SD)/Median	Length of Study
Alibhai (2009)18	L	20	CT	55	70 (NS)	12m
Jouzier (2021)22	C	397	Intensive CT	57	69 (NS)	>12m
Klepin (2011)26a	CS	54	Intensive CT	59	71 (6)	N/A
Klepin (2013)23a	C	74	Intensive CT	54	70 (6) or 69	?
Klepin (2016)19a	L	49	Intensive CT	57	69	≈3–4m
Kotb (2019)27	CS	45b	CT	NS	NS	N/A
Meyers (2005)20	L	54c	CT	56	60 (NS)	1m
Modzelewski (2011)21	L	20	Intensive CT	45	38 (12)	6m
Molga (2020)24	C	98c	CT & non-CT	63	77	?
Oliva (2011)25	C	113	CT & non-CT	51	72 (6)	12m

^aThe articles were from the same study.

^bThe sample included other malignant hematological disease and only presented the number of adults with AML.

^cThe sample included adults with myelodysplastic syndromes.

Abbreviations: ≈, approximately; ?, not able to determine; C, cohort; CS, cross-sectional; CT, chemotherapy; L, longitudinal; m, months; N/A, not applicable; non-CT, non-chemotherapy; NS, non-specified; SD, standard deviation.

All articles focused on recruiting a single group of participants with exposure of AML or MDS treatment (ie. chemotherapy or supportive care). The majority of the articles (70%) pre-identified and managed confounding factors by using statistical methods or publishing normative data. The quality of the included articles, appraised using the JBI Systematic Reviews Critical Appraisal Tools, can be found in Table 2.

Table 2.

Quality Assessment of the Included Studies (n=10)

First Author (Year)	Alibhai (2009)18	Jouzier (2021)22	Klepin (2011)26	Klepin (2013)23	Klepin (2016)19	Kotb (2019)27	Meyers (2005)20	Modzelewski (2011)21	Molga, (2020)24	Oliva (2011)25
Were the two groups similar and recruited from the same population?	Y	Y	-	Y	Y	-	Y	Y	Y	Y
Were the exposures measured similarly to assign people to both exposed and unexposed groups?	N/A	N/A	-	N/A	N/A	-	N/A	N/A	N/A	N/A
Was the exposure measured in a valid and reliable way?	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A
Were confounding factors identified?	N	Y	Y	Y	Y	N	Y	Y	N	Y
Were strategies to deal with confounding factors stated?	N	Y	Y	Y	Y	N	Y	Y	N	Y
Were the groups/participants free of the outcome at the start of the study (or at the moment of exposure)?	N/A	N/A	-	N/A	N/A	-	N/A	N/A	N/A	N/A
Were the outcomes measured in a valid and reliable way?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Was the follow up time reported and sufficient to be long enough for outcomes to occur?	Y	Y	-	U	Y	-	Y	Y	U	Y
Was follow up complete, and if not, were the reasons to loss to follow up described and explored?	Y	Y	-	Y	Y	-	Y	Y	Y	Y
Were strategies to address incomplete follow up utilized?	N	Y	-	Y	N	-	N	N	Y	Y
Was appropriate statistical analysis used?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Were the criteria for inclusion in the sample clearly defined?	-	-	Y	-	-	Y	-	-	-	-
Were the study subjects and the setting described in detail?	-	-	Y	-	-	Y	-	-	-	-
Were objective, standard criteria used for measurement of the condition?	-	-	Y	-	-	Y	-	-	-	-

Abbreviations: Y, yes; N, no; N/A, not applicable; U, unclear.

Sample Characteristics

Study sample sizes ranged between 20 and 397. Two studies included participants with a diagnosis of MDS^{20, 24} and one recruited participants with other types of malignant hematological disease.²⁷ Most studies included participants with intensive chemotherapy only.^{19, 21–23, 26} Two studies also included participants who were treated with supportive care or immunomodulatory agents (for MDS), which did not include chemotherapy.^{24, 25} Across studies, similar numbers of men and women were included; participant mean age ranged from 38–72 years, and median age ranged from 69–77 years. For studies reporting race, White was predominant (95.9%–96.3%).^{19, 23, 26} For studies reporting education level, college degree or above was predominant (51.4%–57.5%).^{19, 23, 26}

Main Findings

Change in cognitive function across chemotherapy continuum

Various approaches (patient-reported questionnaires, neuropsychological assessments, and neuroimaging) were used across studies to measure cognitive function (Table 3). Two studies reported subjective or perceived cognitive function while eight studies reported neuropsychological assessment and one study used additional neuroimaging to capture objective data. Of studies with subjective measures, all assessed cognitive function using the EORTC QLQ-C30 two-items cognitive function subscale with an aim to explore QOL among an AML population and reported mean or median cognitive function scores.^{18, 25} Specifically, one longitudinal study further examined the change of cognitive function over time and found a stable cognitive function across the treatment continuum up to 12 months.¹⁸

Table 3.

Main Cognition Outcome of the Included Studies (n=10)

First Author (Year)	Measures	Assessment Timepoints	Reported Format / Time Point	Change Overtime	Correlates Tested
Cognition assessed more than once
Alibhai (2009)18	2 items	pre-CT, 1m, 4m, 6m, 9m, 12m	mean score / all time points	Stable (no p-value)	remission status at 6m
Jouzier (2021)22	MMSE (<26 CI)	at dx, 3rd cycle re-ICT, 6th cycle re-ICT, end-CCT	mean score / at dx P of CI at dx: 16%	NS	gender, performance status, age, grade 3–4 toxicity during induction, time of induction, lomustine during induction and postinduction therapy
Klepin (2016)19	3MS (<77 CI)	pre-ICT, post-ICT	mean score / all time points P of CI: ≈> 20%→≈< 20%	NS	-
Meyers (2005)20	Digit Span, Digit Symbol, HVLT, COWA-verbal fluency, TMT, GPT	pre-CT, 1m	mean score / pre-CT P of impaired domains- attention: 7%→8% psychomotor speed: 8%→13% total recall: 44%→58% immediate recognition: 7%→25% delayed recall: 41%→58% verbal fluency: 17%→25% visual scanning: 28%→38% executive function: 29%→46% dexterity: 37%→54%	P of impaired dexterity: S↑ P of other impaired domains: NS	age, education, hemoglobin, fatigue, cytokines
Modzelewski (2011)21	SPECT, ICARS, BI, TMT, 9HPT, DRS, Digit Span, GBVLT	at dx, pre-CCT, 2nd cycle CCT, during CCT, post-CCT, 6m	mean score / all time points P of normal test score: 100%	SPECT at dx vs. pre-CCT vs. 2nd cycle CCT: NS R’t hand dexterity: S↑ during CCT–post-CCT L’t hand dexterity: S↓ 2nd cycle CCT–during CCT & S↑ post-CCT–6m attention: S↑ post-CCT–6m working memory: S↑ post-CCT–6m & S↑ at dx–pre-CCT verbal memory: S↑ at dx–6m global efficiency: S↑ at dx–6m	-
Cognition assessed once
Klepin (2011)26	3MS (<80 CI)	within 5d of initial hospitalization	mean score P of CI: 31.5%	N/A	cytogenetics
Klepin (2013)23	3MS (<77 CI)	within 5d of initial hospitalization	median score P of CI: 28.8%	N/A	-
Kotb (2019)27	MOCA (<26 CI)	6m–2y post-CT	mean score of each domain P of CI: 62.2%	N/A	-
Molga (2020)24	MMSE (<24 CI)	pre-treatment	N/A	N/A	-
Oliva (2011)25	2 items	at dx	IC group median score	N/A	treatment

Note: 2 items= cognitive function domain from the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), ≈ approximately, ↑ increased, ↓ decreased, S significant, L’t=left, R’t=right

Abbreviations: 3MS, Modified Mini-Mental State Examination; 9HPT, Nine Hole Peg Test; BI, Barthel Index; CCT, consolidation chemotherapy; CF, cognitive function; CI, cognitive impairment; COWA, Controlled Oral Word Association; CT, chemotherapy; d, days; DRS, Mattis Dementia Rating Scale; dx, diagnosis; GBVLT, Grober and Buschke Verbal Learning test; GPT, Grooved Pegboard Test; HVLT, Hopkins Verbal Learning Test; IC, intensive chemotherapy; ICARS, International Cooperative Ataxia Rating Scale; ICT, induction chemotherapy; m, months; MMSE, Mini-Mental State Exam; MOCA, Montreal Cognitive Assessment; N/A, not applicable; NS, non-specified; p, prevalence; SPECT, single-photon emission computerized tomography; TMT, Trial Making Test; y, years.

Among the eight studies using objective assessment tools, two used the Mini-Mental State Exam (MMSE), three used the Modified Mini-Mental State Examination (3MS), one used the Montreal Cognitive Assessment (MOCA), and two used a battery of neuropsychological assessments. For the six studies using the MMSE, 3MS, and MOCA to assess overall cognitive function, two longitudinal studies assessed the change of cognitive function using the MMSE and 3MS, respectively, from diagnosis of AML up to the end of consolidation chemotherapy and found that cognitive function remained stable over time (p=.55; p=.72).^{19, 22} In addition to reporting mean or median score, a specific cut-off score for cognitive impairment was defined and the prevalence of cognitive impairment was further identified. Three articles from the same study included the 3MS as part of the geriatric assessment and found the prevalence of cognitive impairment ranged from above 20% to 31.5% prior to induction chemotherapy/within 5 days of initial hospitalization for AML^{19, 23, 26} and less than 20% after induction chemotherapy.¹⁹ One study conducted the assessment using the MMSE at AML diagnosis and reported 16% of participants had cognitive impairment.²² A cross-sectional study assessed cognitive function at six months to two years after chemotherapy using the MOCA and observed 62.2% prevalence of cognitive impairment.²⁷ These studies concluded that although cognitive function remained stable over time, the prevalence of cognitive function was 16%–31.5% at the initiation of chemotherapy and up to 62.2% after starting chemotherapy.

CRCI shows impairment in different cognitive domains; therefore, researchers in two studies used batteries of neuropsychological assessments to better understand how each domain is impacted.^{20, 21} Specifically, in one study, mixed results were identified in severity of impairment related to hand dexterity, attention, working memory, verbal memory, and global efficiency between time points across the treatment continuum.²¹ However, the other study identified a non-significant increase in prevalence of impairment related to attention, psychomotor speed, total recall, immediate recognition, delayed recall, verbal fluency, visual scanning, and executive function between pre- and post-induction chemotherapy²⁰ and a significant increase in prevalence of impaired dexterity.²⁰ Unfortunately, with only two studies using batteries of neuropsychological assessment with a follow-up time frame between one and six months, we had limited evidence for drawing a powerful conclusion on how chemotherapy impacts domains of cognitive function in the AML population. These findings highlight the necessity for using batteries of neuropsychological assessments in future CRCI research.

Neuroimaging is an evolving method to understand cognitive function. In addition to the neuropsychological assessments, one study further used single-photon emission computerized tomography (SPECT) to measure brain perfusion and indicated non-significant differences between pre-chemotherapy and post-chemotherapy.²¹ However, with this single study, we are hesitant to draw conclusions.

Potential correlates of cognitive function

The following potential correlates were tested across studies:

Age.

The relationship between age and cognitive function was tested in two studies and both reported non-significant findings.^{20, 22} Specifically, one study found that age did not correlate with the change of cognitive function over time.²² Another study found a non-significant relationship between age and cognitive function.²⁰

Gender.

One study observed no significant difference in the change of cognitive function over time between gender.²²

Education.

One study found a significant positive association between years of education and cognitive function.²⁰

Biomarkers.

One study examined the relationship between biomarkers and cognitive function and reported mixed findings.²⁰ For cytogenetics, the study found a significant negative association between IL-6 and executive function, and a positive association between IL-8 and memory at pre-chemotherapy.²⁰ Yet, no significant relationship was found between hemoglobin and cognitive function at pre-chemotherapy.²⁰

Disease characteristics.

Relationships between disease characteristics and cognitive function was assessed in two studies that included: cytogenetics (favorable to intermediate vs. unfavorable),²⁶ and remission status at 6 months (p=.88);¹⁸ however, no significant relationships were identified.

Chemotherapy regimens.

Comparisons in cognitive function across different AML chemotherapy regimens were made in two studies; both generated no significant findings.^{22, 25} One cross-sectional study reported no difference in cognitive function at AML diagnosis between patients receiving intensive and palliative treatment (p=.52).²⁵ Similarly, the other longitudinal study reported that with or without lomustine during induction and post-induction chemotherapy did not associate with the change in cognitive function over time (p=.61).²²

Time of induction.

Jouzier and colleagues²² further tested the relationship with time of induction and also discovered non-significant findings.

Fatigue.

In one study, no significant relationship between fatigue and cognitive function was found prior to starting chemotherapy.²⁰

Functional status.

Jouzier and colleagues²² reported a 16% and 34% of cognitive impairment in participants with the Eastern Cooperative Oncology Group (ECOG) performance status 0–1 and those with the ECOG performance status 2, respectively (no p-value tested). This same study also found a non-significant relationship between the ECOG performance status and the change of cognitive function over time.²²

To summarize, only education and cytokines were identified to significantly correlate with cognitive function. However, these findings were only reported in one study. In contrast, age, gender, hemoglobin, cytogenetics, remission status, treatment regimens, hemoglobin, fatigue, and functional status were not significantly associated with cognitive function.

Prediction of cognitive function on other outcomes

Cohort studies with a focus on geriatric assessments examined the prediction of cognitive function on disease status, treatment plan, symptoms, and physical performance among adults with AML. One study found that cognitive function at initiation of chemotherapy had non-significant effect on remission (3MS>77 vs. 3MS<77= 67% vs. 57%, p=.41).²³ Another study reported that participants with cognitive impairment at pre-chemotherapy completed significant fewer cycles of azacitidine chemotherapy than those without cognitive impairment at pre-chemotherapy (MMSE<24 vs. MMSE≥24: 3.5 ± 2.1 vs. 10.9 ± 7.9; p=.03).²⁴ Using six cycles of azacytidine chemotherapy as a cut-off point, this same study also found a significant higher percentage of participants with cognitive impairment at pre-chemotherapy were not able to complete the six cycles than those without cognitive impairment at pre-chemotherapy (MMSE<24 vs. MMSE≥24: 75% vs. 24%, p=.05).²⁴

Another cohort study identified that cognitive function at diagnosis did not predict the occurrence of grade 3–4 toxicities during induction chemotherapy (MMSE≥26 vs. MMSE<26: no toxicities number= 83.3% vs. 16.7% & toxicities number= 78.7% vs. 21.4%, p=.31).²² In terms of the prediction on physical performance, one longitudinal study identified a significant positive relationship between baseline cognitive function and the improvement of physical performance from pre- to post-induction chemotherapy, after adjusting for cytogenetic risk, depression, balance, and performance status (p=.05).¹⁹ Also, this same study reported that participants with cognitive impairment (3MS<77) at both pre- and post-induction chemotherapy had more decrease in physical performance (Short Physical Performance Battery: 8.0±1.7 vs. 3.6±1.7, p=.07) compared to those without cognitive impairment (Short Physical Performance Battery: 8.4±0.7 vs. 6.9±0.7, p=0.12).¹⁹ However, all these findings were tested in only one study. We are therefore unable to surmise a definitive conclusion about the prediction of cognitive function on disease, treatment plan, symptoms, and physical performance.

Findings about the prediction of cognitive function on mortality were tested in one study.²³ Klepin and colleagues²³ found a non-significant higher percentage of 30-day mortality (within 30 days since starting induction chemotherapy) in participants with cognitive impairment than those who did not have cognitive impairment (3MS<77: 23.8%, [95%CI=8.2–47.2] vs. 3MS≥77: 9.6%, [95%CI=3.0–21.0], p=.14). However, this same study also discovered a significant positive relationship between cognitive impairment and risk of death after adjusting for covariates (HR 2.5, [95%CI=1.2–5.5]).²³ The prediction of cognitive function on survival was mixed across three studies.^22–24 Klepin and colleagues²³ discovered that participants with cognitive impairment within 5 days of initial hospitalization had a significantly lower median overall survival than those without cognitive impairment (3MS<77: 5.2 months vs. 3MS≥77: 15.6 months, p=.002). However, Jouzier and colleagues²² found that there was non-significant prediction of cognitive function at diagnosis on both overall survival (MMSE≥26 vs. MMSE<26: median overall survival= 26 months [95%CI=22.4–31.2] vs. 21 months [95%CI=13.1–36.8], p=.67) and event free survival (MMSE≥26 vs. MMSE<26: median event free survival=16 months [95%CI=12.5–19] vs. 13 months [95%CI=9.7–22.5], p=.81). Similarly, another study also identified that there was no significant difference in survival between participants who received azacytidine chemotherapy with and without cognitive impairment (12 months vs. 19 months, p=1).²⁴ Although these longitudinal or cohort studies with a focus on geriatric assessments emphasize on a comprehensive domains of aging, such as functional status, mobility, nutrition, and cognition; these exploratory findings reinforce the importance of understanding cognition in this patient population because of its potential prediction on multiple aspects of adults with AML.

Discussion

We found in our systematic review that, in extant AML research, cognitive function was studied as one of the components of QOL and as an important factor of geriatric assessment. Our review concluded that up to 62.2% of adults with AML experienced cognitive impairment; however, stable cognitive function after initiating chemotherapy was identified when measured either using patient-reported questionnaires or objective assessments.

Although chemotherapy is a standard treatment for adults with AML, we identified limited research focusing on the impact of AML chemotherapy on CRCI. Of the two studies including patient-reported questionnaire, both used the EORTC QLQ-C30 cognitive function subscale.^{18, 25} However, considering the EORTC QLQ-C30 is a QOL measure, and the cognitive function subscale only measures two cognitive domains,²⁸ it might not be sensitive enough to capture changes in cognitive function following chemotherapy. Additionally, EORTC QLQ-C30 provides different information about cognitive function compared to neuropsychological assessments. Consequently, we identified a gap in researchers’ understanding of perceived cognitive function as reported via cognitive function-specific self-reported questionnaires. Perceived cognitive function is critically important²⁹ to facilitate early recognition of declines in cognitive function³⁰ and increase clinicians’ ability to detect CRCI.³¹ Hence, these findings highlight a necessity for researchers to understand CRCI in the AML population and use cognitive function-specific patient-reported measures.

Objective assessments were widely used in CRCI studies. The MMSE and 3MS (which was expanded from the MMSE)³² were the most used objective assessment in our review, specifically in studies focusing on geriatric assessment.^{19,22–24,26} However, the MMSE may not be sensitive enough to detect cognitive changes in cancer populations³¹ because it is a screening measure of cognitive function and thus provides limited information. Although batteries of neuropsychological assessments and neuroimaging are recommended by the International Cancer and Cognition Task Force,^1,33 only two studies used them.^20,21 With this small number of studies, we were unable to conclude how chemotherapy impacts cognition domains in adults with AML. To address this gap, we highlight a need for researchers to use batteries of neuropsychological assessment to understand CRCI in AML.

Understanding the correlates of cognitive function will enable early identification and intervention. Lower education correlated with worse cognitive function,²⁰ which was consistent with findings of a prior study of lymphoma survivors.³⁴ Although aging may contribute to a lower cognitive function in some domains, our review found no relationship between age and cognitive function.^20,22 One study included in our review found no relationship between fatigue and cognitive function,²⁰ which was different from the results of a prior study reporting fatigue as a predictor of decreased cognitive function in survivors of cancer.³⁵ This inconsistency might be due to the measures used: Meyers, Albitar, and Estey²⁰ used a battery of neuropsychological assessments, while Oh³⁵ used the MMSE and a patient-reported questionnaire. The differences between patient-reported cognitive function and neuropsychological assessments have been identified in prior research. Specifically, O’Farrell, Smith, and Collins³⁶ found that patient-reported cognitive function was negatively associated with anxiety and fatigue, while objective cognitive function measured by a battery of neuropsychological assessments was not. In addition, survivors of cancer with a low hemoglobin level may experience symptoms (i.e. fatigue, dizziness, headache) which might contribute to cognitive decline.³⁷ However, no significant relationship was found between hemoglobin level and cognitive function in our review.²⁰ Researchers proposed that inflammation is a possible etiology of CRCI.² A prior study also identified a significant negative relationship between cytokines (IL-1β, TNF-α and IL-4) and cognitive function.³⁸ However, the identified cytokines were different from the ones identified in our review.²⁰ Finally, no psychological correlates were tested. A recent systematic review of 19 studies focusing on survivors of breast cancer concluded that survivors with higher levels of psychological distress indicated worse cognitive function.³⁹ Therefore, the relationship between emotional distress and cognitive function should be further studied in AML survivors. To summarize, the small number of studies testing each correlate and their inconsistent use of cognitive function measures limits the power of our findings. The lack of strong evidence reinforces the importance of using cognitive function-specific measures and further testing the correlates in future studies.

Limited studies included in our review found that worse cognitive function contributes to poorer outcomes in adults with AML. In our review, one study found worse cognitive function causes an early cessation of azacytidine therapy.²⁴ Azacytidine, one of the hypomethylating agents, was prescribed in combination with Venetoclax to treat AML survivors who are precluded from intensive chemotherapy.⁴⁰ This treatment plan includes daily oral medication, Venetoclax, which requires AML survivors to adhere to their treatment protocol. Unfortunately, prior research found that poor cognitive function may lead to a nonadherence to oral cancer treatment over time.⁴¹ Another study reported that adults with AML experiencing worse cognitive function have poorer chances of survival.²³ This finding aligned with prior studies, which indicated a significant positive relationship between decreased cognitive function and mortality in community-dwelling older adults.⁴² Studies focusing on other cancer diagnosis found that survivors of cancer with CRCI may experience social isolation,³ poor working capacity,³ and decreased QOL.⁴ Considering differences in patients’ characteristics, how CRCI impacts survivors of cancer may vary. For example, Boykoff, Moieni, and Subramanian⁴³ found that the symptoms of CRCI made survivors of breast cancer easily distractible and decreased work efficiency, forcing them to switch to jobs with lighter workloads. However, survivors of breast cancer have a median age of diagnosis of 62 years,⁴⁴ while AML is 68 years, which is over standard retirement age.¹⁴ Hence, work capacity might not be the focus in the AML population. Instead, AML survivors may be more focused on other tasks, so researchers cannot assume that CRCI has the same impact in AML survivors as it does in different cancer populations. A research gap exists, and qualitative studies are needed to understand experiences of older adults with AML with CRCI.

Our review included ten articles reporting cognitive function; because we did not restrict to CRCI studies, we obtained a broader understanding of current cognitive function study in AML population. However, the sample sizes were varied across studies and some major findings were only tested in a single study, which made it hard to draw conclusions on the cognitive function in this population. In addition, the three studies on CRCI were not representative of the general AML population because the age of their samples (mean age: 38–60 years) were younger than the median age of diagnosis (68 years)^{20, 21} and did not focus exclusively on AML survivors.^{20, 27} Due to these weaknesses in the sample ages and diagnosis, we know little about CRCI in older adults with AML. Thus, older adults should be recruited in future CRCI research in the AML population.

This review is not without limitation. First, no gray literature was searched. Therefore, unpublished reports and conference proceedings related to CRCI in AML survivors were missed during the searching process. Second, due to the limited research about CRCI in hematological malignancies, studies recruited samples with a MDS, or AML diagnosis were included in the review. The results we captured might not be the experiences of AML survivors exclusively.

Conclusion

Our review provided a thorough understanding of current research on cognitive function in adults with AML who were treated with chemotherapy. Cognitive function may impact survivors in different aspects. However, stable cognitive function was identified after initiating chemotherapy. Furthermore, some potential correlates of cognitive function—education and cytokines—were identified.

Our review identified several CRCI research gaps in the AML population. First, a lack of using cognitive function-specific measures limited the power of findings related to understanding experiences and correlates of CRCI. Second, there is no research exploring how CRCI impacts adults with AML. Lastly, CRCI studies included a variety of diagnoses and relatively younger samples. Therefore, future researchers should use patient-reported questionnaires and objective assessments (such as a battery of neuropsychological assessments) to explore CRCI and correlates in adults with AML—in particular, older adults. Furthermore, given the emergence of newer treatments for AML in older adults, there will be more choices in therapies and the risks of CRCI with such therapies (both new and old treatments) need to be consistently defined in order to empower patients to choose according to their goals. Finally, considering differences in patients’ characteristics (ie. Age), how CRCI impacts survivors of cancer may vary. It is also crucial to use a qualitative approach to explore how CRCI impacts this patient population. Once a preliminary understanding is obtained, quantitative studies with fully powered sample sizes and intervention development can be further conducted. By doing so, we will have an in-depth and comprehensive understanding of CRCI in adults with AML.