Introduction: Limited studies report anxiety and depression prevalence and their correlations with prognosis in acute myeloid leukemia (AML). Even worse, their risk factors for AML remained unclear. This study aimed to investigate the prevalence, risk factors, and prognostic value of anxiety and depression in AML patients. Methods: Totally, 132 de novo AML patients, 60 non-malignant hematological disease patients (as disease controls), and 60 healthy controls were enrolled. Anxiety and depression status were evaluated by the Hospital Anxiety and Depression Scale (HADS) in all participants. Results: HADS-anxiety score (8.2 ± 3.2 vs. 6.1 ± 2.9 vs. 4.7 ± 2.8), anxiety rate (48.5% vs. 25.0% vs. 10.0%), HADS-depression score (7.8 ± 3.0 vs. 5.8 ± 3.0 vs. 4.0 ± 2.8), and depression rate (43.2% vs. 23.3% vs. 8.3%) were highest in AML patients, followed by disease controls, and the lowest in healthy controls (all p < 0.001). Multivariate logistic regression analysis identified that factors independently associated with anxiety included male (p = 0.002, odds ratio [OR] = 0.240), smoking (p = 0.043, OR = 2.474), education duration (p = 0.024, OR = 0.889), and NCCN high-risk stratification (p = 0.008, OR = 2.347), while those independently associated with depression were age (p = 0.005, OR = 1.055), single/divorced/widowed status (p = 0.014, OR = 3.149), NCCN high-risk stratification (p = 0.002, OR = 3.077), and white blood cell (WBC) (p < 0.001, OR = 1.062). Additionally, depression was correlated with shorter accumulating event-free survival (p = 0.012) and overall survival (p = 0.041) in AML patients, whereas anxiety was not. Conclusions: Anxiety and depression are prevalent, among which depression is associated with poor survival profile, but anxiety is not; moreover, age, male, education, single/divorced/widowed status, smoking, NCCN high-risk stratification, and WBC were independent related factors of anxiety and depression in AML patients.

Acute myeloid leukemia (AML) is a hematological malignancy characterized by the uncontrolled clonal proliferation of hematopoietic progenitor cells [1, 2]. It mainly occurs in elderly persons exceeding 60 years old, with an incidence of 4.3 cases per 100,000 population per year and a high mortality rate [3‒5]. Although the management of AML has achieved certain advancement during the few past decades, only approximately 40–45% of young and 10–20% of old AML patients could be cured by the current standard chemotherapy with or without hematopoietic stem cell transplantation (HSCT), resulting in a poor overall prognosis of AML [6‒9]. Apart from unsatisfying prognosis, disease progression, chemotherapy-related side effects, and fear of recurrence might cause anxiety or depression in AML patients, especially those with heavy disease burdens [10, 11].

Anxiety and depression are the most common psychiatric conditions in patients with malignancies, which influence life quality and the patient’s adherence to treatment [12, 13]. More importantly, it is proposed that anxiety or depressive symptoms are correlated with worse survival in malignancies as well [14‒16]. In aspects of AML, very limited studies explore the relation of anxiety and depression to its prognosis: a study suggests that both anxiety and depression predict poor survival profiles in AML patients [10]; another study shows that anxiety and depression may correlate with shorter overall survival (OS) in refractory or relapsed AML patients [11]. In fact, although these previous studies display the correlation of anxiety or depression with prognosis, few were performed to investigate the risk factors of anxiety and depression in AML patients. Therefore, the present study aimed to explore the prevalence of anxiety and depression, their related factors, as well as their association with event-free survival (EFS) and OS in AML patients.

Participants

This study consecutively included 132 newly diagnosed AML patients who were treated in our hospital from February 2016 to December 2019. All enrolled patients were identified by the following enrollment criteria: (i) diagnosed as AML according to the World Health Organization (WHO) classification of AML [17]; (ii) aged over 18 years; (iii) able to accomplish the assessment of the Hospital Anxiety and Depression Scale (HADS); (iv) willing to accept regular follow-up. The main exclusion criteria were (i) history of documented psychiatric disorders; (ii) severe cognitive impairment (mini-mental state examination score ≤10); (iii) concomitant with uncontrolled diseases that seriously affect mental health such as stroke; (iv) history of other cancers or malignancies; (v) lactating or pregnant patients. Besides, during the same period, 60 patients with non-malignant hematological disease (such as purpura and anemia, as disease controls) as well as 60 healthy subjects were also included in this study as disease controls and health controls, respectively. Meanwhile, to match the age and sex of AML, the age of disease controls and healthy controls was limited within 45–70 years, and the sex ratio of male versus female in disease controls and healthy controls was set at 3:2. This study was approved by the Institutional Review Board of Southern University of Science and Technology Hospital (approval No. 20151219). The participants provided written informed consent. The statutory guardians of the participants provided written informed consent under circumstances of illiteracy.

Collection of Clinical Data

For AML patients, clinical characteristics were collected, including demographic characteristics, underlying diseases, French-American-British (FAB) classification, risk stratification, cytogenetics, genetic mutations, biochemical indexes, and induction treatment complete response (CR). The risk stratification was classified according to the criterion issued by the National Comprehensive Cancer Network (NCCN) [18].

Evaluation of Anxiety and Depression

HADS was assessed on the day of discharge from the hospital for AML and after enrollment for disease controls and healthy controls. The HADS for anxiety (HADS-A) subscale and the HADS for depression (HADS-D) subscale were, respectively, applied to assess the anxiety status and depression status of all participants [19]. In order to promote the accessibility and universality of this study, the HADS questionnaires were completed by patients themselves, and this was not the intended use of the questionnaire. The HADS questionnaire contained 7 questions for assessing anxiety and 7 questions for assessing depression. Each question could be scored as 0–3. Both the HADS-A subscale and the HADS-D subscale had a maximum score of 21. In the current study, the HADS-A score >7 was considered anxiety; similarly, the HADS-D score >7 was considered depression (suspected anxiety/depression (HADS-A/D score 8–10) and definite anxiety/depression (HADS-A/D score >10) were combined) [19]. The HADS questionnaire used in the current study is shown in online supplementary material (for all online suppl. material, see https://doi.org/10.1159/000536457).

Assessment of Survival Data

AML patients were followed up until withdrawal from the study, death, or the end of this study (April 30, 2021). The median follow-up duration was 32.0 months, and the range was 2.0–60.0 months. In addition, disease status was recorded to calculate EFS and OS. EFS was defined as the time from the beginning of induction treatment to treatment failure (defined as failure to achieve CR), relapse from CR, or death. OS was defined as the time from the beginning of induction treatment to death [20].

Statistical Analysis

Statistical description and statistical inference were fulfilled using SPSS 22.0 (IBM Corp., Armonk, NY, USA), and figures were generated using GraphPad Prism 7.02 software (GraphPad Software Inc., San Diego, CA, USA). Kolmogorov-Smirnov test was used for normality assessment. Comparisons of three groups were analyzed by one-way analysis of variance (ANOVA) and χ2 test, and multiple comparisons were adjusted by the Bonferroni method. Univariate and multivariate logistic regression analysis was carried out to evaluate the factors related to anxiety and depression. The parameters in the univariate model were all included in the multivariate model with forward stepwise mode. The validity of the prediction models was evaluated using receiver operating characteristic (ROC) analysis. Kaplan-Meier curves and log-rank tests were used to elucidate the correlation of anxiety and depression with accumulating EFS and OS. Additionally, adjusted Kaplan-Meyer curves were plotted using R 3.3.2, adjusting for the factors of the multivariate logistic regression analyses for anxiety and depression, respectively. Statistical significance was concluded if there was a p value <0.05 in the analysis.

Clinical Characteristics of AML Patients

The clinical characteristics of AML patients are shown in Table 1, which could be briefly described as follows. The mean age of AML patients was 58.5 ± 12.2 years, with 81 (61.4%) males and 51 (38.6%) females. The median education duration was 9.0 (interquartile range [IQR]: 6.0–12.0) years. The number of single/divorced/widowed and married patients was 46 (34.8%) and 86 (65.2%), respectively. Concerning the underlying diseases, 43 (32.6%), 28 (21.2%), and 18 (13.6%) patients had hypertension, hyperlipidemia, and diabetes mellitus, respectively. Regarding FAB classification, 10 (7.6%), 40 (30.3%), 35 (26.5%), and 47 (35.6%) patients were classified as having M1, M2, M4, M5 subtypes, respectively. There were 21 (15.9%) patients at favorable NCCN risk stratification, 71 (53.8%) patients at intermediate NCCN risk stratification, and 40 (30.3%) patients at poor NCCN risk stratification. Furthermore, there were 98 (74.2%) patients who achieved CR after induction therapy.

Table 1.

Clinical characteristics

ItemsAML (N = 132)
Demographic characteristics 
 Age, years, mean ± SD 58.5±12.2 
 Gender, n (%) 
  Male 81 (61.4) 
  Female 51 (38.6) 
 Education duration, years, median (IQR) 9.0 (6.0–12.0) 
 Marry status, n (%) 
  Single/divorced/widowed 46 (34.8) 
  Married 86 (65.2) 
 Employment status before treatment, n (%) 
  Unemployed 86 (65.2) 
  Employed 46 (34.8) 
 Smoking, n (%) 46 (34.8) 
 Drinking, n (%) 45 (34.1) 
Underlying diseases, n (%) 
 Hypertension 43 (32.6) 
 Hyperlipidemia 28 (21.2) 
 Diabetes mellitus 18 (13.6) 
FAB classification, n (%) 
 M1 10 (7.6) 
 M2 40 (30.3) 
 M4 35 (26.5) 
 M5 47 (35.6) 
NCCN risk stratification, n (%) 
 Favorable 21 (15.9) 
 Intermediate 71 (53.8) 
 Poor 40 (30.3) 
Cytogenetics, n (%) 
 Normal karyotype 60 (45.5) 
 Complex karyotype 18 (13.6) 
 Monosomal karyotype 8 (6.1) 
 Inv (16) or t (16; 16) 7 (5.3) 
 +8 6 (4.5) 
 −7 or 7q− 5 (3.8) 
 t (9; 11) 4 (3.0) 
 t (8; 21) 1 (0.8) 
 −5 or 5q− 1 (0.8) 
 Others non-defined 30 (22.7) 
Genetic mutations, n (%) 
 NPM1 mutation 37 (28.0) 
 FLT3-ITD mutation 30 (22.7) 
 WT1 mutation 18 (13.6) 
 Isolated biallelic CEBPA mutation 11 (8.3) 
Biochemical indexes 
 WBC, ×109/L, median (IQR) 16.5 (8.3–28.1) 
 BM blasts, %, median (IQR) 74.5 (60.3–83.8) 
Induction treatment CR, n (%) 98 (74.2) 
ItemsAML (N = 132)
Demographic characteristics 
 Age, years, mean ± SD 58.5±12.2 
 Gender, n (%) 
  Male 81 (61.4) 
  Female 51 (38.6) 
 Education duration, years, median (IQR) 9.0 (6.0–12.0) 
 Marry status, n (%) 
  Single/divorced/widowed 46 (34.8) 
  Married 86 (65.2) 
 Employment status before treatment, n (%) 
  Unemployed 86 (65.2) 
  Employed 46 (34.8) 
 Smoking, n (%) 46 (34.8) 
 Drinking, n (%) 45 (34.1) 
Underlying diseases, n (%) 
 Hypertension 43 (32.6) 
 Hyperlipidemia 28 (21.2) 
 Diabetes mellitus 18 (13.6) 
FAB classification, n (%) 
 M1 10 (7.6) 
 M2 40 (30.3) 
 M4 35 (26.5) 
 M5 47 (35.6) 
NCCN risk stratification, n (%) 
 Favorable 21 (15.9) 
 Intermediate 71 (53.8) 
 Poor 40 (30.3) 
Cytogenetics, n (%) 
 Normal karyotype 60 (45.5) 
 Complex karyotype 18 (13.6) 
 Monosomal karyotype 8 (6.1) 
 Inv (16) or t (16; 16) 7 (5.3) 
 +8 6 (4.5) 
 −7 or 7q− 5 (3.8) 
 t (9; 11) 4 (3.0) 
 t (8; 21) 1 (0.8) 
 −5 or 5q− 1 (0.8) 
 Others non-defined 30 (22.7) 
Genetic mutations, n (%) 
 NPM1 mutation 37 (28.0) 
 FLT3-ITD mutation 30 (22.7) 
 WT1 mutation 18 (13.6) 
 Isolated biallelic CEBPA mutation 11 (8.3) 
Biochemical indexes 
 WBC, ×109/L, median (IQR) 16.5 (8.3–28.1) 
 BM blasts, %, median (IQR) 74.5 (60.3–83.8) 
Induction treatment CR, n (%) 98 (74.2) 

AML, acute myeloid leukemia; SD, standard deviation; IQR, interquartile range; FAB, French-American-British; NPM1, nucleophosmin 1; FLT3-ITD, the internal tandem duplication (ITD) representing the most common type of FMS-like tyrosine kinase 3 (FLT3) mutation; WT1, Wilms’ tumor 1; CEBPA, CCAAT/enhancer binding protein alpha; WBC, white blood cell; BM, bone marrow; CR, complete response; NCCN, National Comprehensive Cancer Network.

Comparison of Anxiety and Depression among AML Patients, Disease Controls, and Healthy Controls

The HADS-A score was highest in the AML patients, the second highest in the disease controls, and the lowest in the healthy controls ([8.2 ± 3.2] vs. [6.1 ± 2.9] vs. [4.7 ± 2.8]) (p < 0.001) (Fig. 1a). Meanwhile, the anxiety rate was the most prevalent in the AML patients, followed by the disease controls, and the minimum in the healthy controls (48.5% vs. 25.0% vs. 10.0%) (p < 0.001) (Fig. 1b).

Fig. 1.

Comparison of anxiety and depression. Comparison of HADS-A score (a), anxiety rate (b), HADS-D score (c), depression rate (d) among AML patients, non-malignant hematological disease patients, and healthy controls. HADS, Hospital Anxiety and Depression Scale; AML, acute myeloid leukemia.

Fig. 1.

Comparison of anxiety and depression. Comparison of HADS-A score (a), anxiety rate (b), HADS-D score (c), depression rate (d) among AML patients, non-malignant hematological disease patients, and healthy controls. HADS, Hospital Anxiety and Depression Scale; AML, acute myeloid leukemia.

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Besides, the HADS-D score was the top in the AML patients, the second top in the disease controls, and the lowest in the healthy controls ([7.8 ± 3.0] vs. [5.8 ± 3.0] vs. [4.0 ± 2.8]) (p < 0.001) (Fig. 1c). In addition, the depression rate was highest in the AML patients, followed by the disease controls, and the least in the healthy controls (43.2% vs. 23.3% vs. 8.3%) (p < 0.001) (Fig. 1d).

Anxiety-Related Factors in AML Patients

The univariate logistic regression analysis illustrated that diabetes mellitus (p = 0.012), higher NCCN risk stratification (p = 0.012), and no induction treatment CR (p = 0.030) were correlated with higher risk of anxiety, while males (p = 0.010) were associated with lower risk of anxiety. Besides, multivariate logistic regression analysis presented that smoking (p = 0.043, hazard ratio [HR]: 2.474) and higher NCCN risk stratification (p = 0.008, HR: 2.347) were independently associated with higher risk of anxiety; meanwhile, it suggested that male (p = 0.002, HR: 0.240) and education duration (p = 0.024, HR: 0.889) were independently correlated with lower risk of anxiety (Table 2). Moreover, the receiver operating characteristic (ROC) curve showed that a combination of the above independent factors had a certain capability of discriminating anxiety AML patients from non-anxiety AML patients (area under curve: 0.749, 95% confidence interval [CI]: 0.667–0.831). The sensitivity and specificity at the best cut-off point were 0.779 and 0.609, respectively (Fig. 2).

Table 2.

Analysis of anxiety-related factors in AML patients

Itemsp valueOR95% CI
lowerupper
Univariate logistic regression analysis 
 Age 0.121 1.023 0.994 1.053 
 Male 0.010 0.388 0.188 0.798 
 Smoking 0.325 1.435 0.699 2.944 
 Drinking 0.301 0.682 0.330 1.409 
 Hypertension 0.125 1.781 0.853 3.719 
 Hyperlipidemia 0.304 1.556 0.670 3.610 
 Diabetes mellitus 0.012 4.480 1.389 14.451 
 Education duration 0.106 0.928 0.847 1.016 
 Single/divorced/widowed 0.178 1.642 0.798 3.380 
 Unemployed 0.401 1.362 0.663 2.798 
 FAB classification 
  M1 Reference    
  M2 0.205 2.500 0.606 10.321 
  M4 0.740 0.783 0.185 3.319 
  M5 0.608 1.437 0.359 5.762 
 Higher risk stratification* 0.012 2.014 1.167 3.474 
 WBC 0.053 1.023 1.000 1.047 
 BM blasts 0.085 1.021 0.997 1.046 
 No induction treatment CR 0.030 2.444 1.088 5.490 
Forward stepwise multivariate logistic regression analysis 
 Male 0.002 0.240 0.100 0.580 
 Smoking 0.043 2.474 1.031 5.938 
 Diabetes mellitus 0.073 3.137 0.900 10.935 
 Education duration 0.024 0.889 0.802 0.984 
 Higher risk stratification* 0.008 2.347 1.248 4.414 
Itemsp valueOR95% CI
lowerupper
Univariate logistic regression analysis 
 Age 0.121 1.023 0.994 1.053 
 Male 0.010 0.388 0.188 0.798 
 Smoking 0.325 1.435 0.699 2.944 
 Drinking 0.301 0.682 0.330 1.409 
 Hypertension 0.125 1.781 0.853 3.719 
 Hyperlipidemia 0.304 1.556 0.670 3.610 
 Diabetes mellitus 0.012 4.480 1.389 14.451 
 Education duration 0.106 0.928 0.847 1.016 
 Single/divorced/widowed 0.178 1.642 0.798 3.380 
 Unemployed 0.401 1.362 0.663 2.798 
 FAB classification 
  M1 Reference    
  M2 0.205 2.500 0.606 10.321 
  M4 0.740 0.783 0.185 3.319 
  M5 0.608 1.437 0.359 5.762 
 Higher risk stratification* 0.012 2.014 1.167 3.474 
 WBC 0.053 1.023 1.000 1.047 
 BM blasts 0.085 1.021 0.997 1.046 
 No induction treatment CR 0.030 2.444 1.088 5.490 
Forward stepwise multivariate logistic regression analysis 
 Male 0.002 0.240 0.100 0.580 
 Smoking 0.043 2.474 1.031 5.938 
 Diabetes mellitus 0.073 3.137 0.900 10.935 
 Education duration 0.024 0.889 0.802 0.984 
 Higher risk stratification* 0.008 2.347 1.248 4.414 

AML, acute myeloid leukemia; OR, odds ratio; CI, confidence interval; FAB, French-American-British; WBC, white blood cell; BM, bone marrow; CR, complete response.

*Risk stratification was based on the guidelines from the National Comprehensive Cancer Network (NCCN).

Fig. 2.

Capability of anxiety-related independent factors for discriminating anxiety from non-anxiety in AML patients. AUC, area under curve; CI, confidence interval; AML, acute myeloid leukemia.

Fig. 2.

Capability of anxiety-related independent factors for discriminating anxiety from non-anxiety in AML patients. AUC, area under curve; CI, confidence interval; AML, acute myeloid leukemia.

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Depression-Related Factors in AML Patients

Age (p = 0.002), diabetes mellitus (p = 0.036), single/divorced/widowed status (p = 0.025), M2 subtype of FAB classification (p = 0.048), higher NCCN risk stratification (p = 0.005), white blood cell (WBC) (p < 0.001), and no induction treatment CR (p = 0.004) were all correlated with higher risk of depression. Additionally, multivariate logistic regression analysis showed that age (p = 0.005, HR: 1.055), single/divorced/widowed status (p = 0.014, HR: 3.149), higher NCCN risk stratification (p = 0.002, HR: 3.077), and WBC (p < 0.001, HR: 1.062) were independently associated with higher risk of depression (Table 3). The ROC curve also suggested that a combination of the above independent factors had a good ability of distinguishing depression AML patients from non-depression AML patients (area under curve: 0.848, 95% CI: 0.780–0.917). The sensitivity and specificity at the best cut-off point were 0.773 and 0.842, respectively (Fig. 3).

Table 3.

Analysis of depression-related factors in AML patients

Itemsp valueOR95% CI
lowerupper
Univariate logistic regression analysis 
 Age 0.002 1.053 1.020 1.087 
 Male 0.153 0.596 0.293 1.211 
 Smoking 0.431 1.336 0.650 2.747 
 Drinking 0.596 0.821 0.395 1.704 
 Hypertension 0.200 1.616 0.776 3.367 
 Hyperlipidemia 0.096 2.049 0.880 4.772 
 Diabetes mellitus 0.036 3.067 1.074 8.759 
 Education duration 0.114 0.928 0.846 1.018 
 Single/divorced/widowed 0.025 2.306 1.111 4.788 
 Unemployed 0.156 1.708 0.815 3.580 
 FAB classification 
  M1 Reference    
  M2 0.048 5.412 1.017 28.791 
  M4 0.848 1.185 0.208 6.744 
  M5 0.090 4.174 0.800 21.770 
 Higher risk stratification* 0.005 2.220 1.267 3.891 
 WBC <0.001 1.058 1.028 1.088 
 BM blasts 0.182 1.017 0.992 1.041 
 No induction treatment CR 0.004 3.300 1.460 7.461 
Forward stepwise multivariate logistic regression analysis 
 Age 0.005 1.055 1.016 1.096 
 Single/divorced/widowed 0.014 3.149 1.259 7.876 
 Higher risk stratification* 0.002 3.077 1.498 6.321 
 WBC <0.001 1.062 1.027 1.097 
Itemsp valueOR95% CI
lowerupper
Univariate logistic regression analysis 
 Age 0.002 1.053 1.020 1.087 
 Male 0.153 0.596 0.293 1.211 
 Smoking 0.431 1.336 0.650 2.747 
 Drinking 0.596 0.821 0.395 1.704 
 Hypertension 0.200 1.616 0.776 3.367 
 Hyperlipidemia 0.096 2.049 0.880 4.772 
 Diabetes mellitus 0.036 3.067 1.074 8.759 
 Education duration 0.114 0.928 0.846 1.018 
 Single/divorced/widowed 0.025 2.306 1.111 4.788 
 Unemployed 0.156 1.708 0.815 3.580 
 FAB classification 
  M1 Reference    
  M2 0.048 5.412 1.017 28.791 
  M4 0.848 1.185 0.208 6.744 
  M5 0.090 4.174 0.800 21.770 
 Higher risk stratification* 0.005 2.220 1.267 3.891 
 WBC <0.001 1.058 1.028 1.088 
 BM blasts 0.182 1.017 0.992 1.041 
 No induction treatment CR 0.004 3.300 1.460 7.461 
Forward stepwise multivariate logistic regression analysis 
 Age 0.005 1.055 1.016 1.096 
 Single/divorced/widowed 0.014 3.149 1.259 7.876 
 Higher risk stratification* 0.002 3.077 1.498 6.321 
 WBC <0.001 1.062 1.027 1.097 

AML, acute myeloid leukemia; OR, odds ratio; CI, confidence interval; FAB, French-American-British; WBC, white blood cell; BM, bone marrow; CR, complete response.

*Risk stratification was based on the guidelines from the National Comprehensive Cancer Network (NCCN).

Fig. 3.

Capability of depression-related independent factors for separating depression from non-depression in AML patients. AUC, area under curve; CI, confidence interval; AML, acute myeloid leukemia.

Fig. 3.

Capability of depression-related independent factors for separating depression from non-depression in AML patients. AUC, area under curve; CI, confidence interval; AML, acute myeloid leukemia.

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Correlation of Anxiety and Depression with Prognosis in AML Patients

No correlation was found in anxiety with accumulating EFS (p = 0.168, HR [95% CI] = 1.380 [0.868–2.195]). The median (95% CI) EFS was 27.0 (21.1–32.9) months in anxiety cohort and 33.3 (26.1–39.9) months in no anxiety cohort (Fig. 4a). Anxiety was also not associated with OS (p = 0.099, HR [95% CI] = 1.730 [0.890–3.364]). The median (95% CI) OS was 51.0 (43.2–58.8) months in anxiety cohort and not reached in no anxiety cohort (Fig. 4b).

Fig. 4.

Association of anxiety and depression with accumulating EFS and OS in AML patients. Correlation of anxiety with accumulating EFS (a) and accumulating OS (b), as well as correlation of depression with accumulating EFS (c) and accumulating OS (d) in AML patients. EFS, event-free survival; OS, overall survival; AML, acute myeloid leukemia.

Fig. 4.

Association of anxiety and depression with accumulating EFS and OS in AML patients. Correlation of anxiety with accumulating EFS (a) and accumulating OS (b), as well as correlation of depression with accumulating EFS (c) and accumulating OS (d) in AML patients. EFS, event-free survival; OS, overall survival; AML, acute myeloid leukemia.

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In terms of depression, it was correlated with shorter accumulating EFS (p = 0.012, HR [95% CI] = 1.790 [1.126–2.847]). The median (95% CI) EFS was 27.0 (21.8–32.2) months in depression cohort and 34.0 (23.8–44.2) months in no depression cohort (Fig. 4c). Depression was also associated with shorter accumulating OS (p = 0.041, HR [95% CI] = 1.960 [1.010–3.804]). The median (95% CI) OS was 48.0 (39.3–57.6) months in depression cohort and not reached in no depression cohort (Fig. 4d). Nevertheless, after adjusted by their respective independent factors, anxiety or depression were not associated with accumulating EFS or OS (all p > 0.05) (Fig. 5a–d).

Fig. 5.

Association of anxiety and depression with accumulating EFS and OS in AML patients after adjustment by their respective independent factors. Association of anxiety with accumulating EFS (a) and accumulating OS (b) after adjustment by smoking, NCCN high-risk stratification, male, and education duration. Association of depression with accumulating EFS (c) and accumulating OS (d) after adjustment by age, single/divorced/widowed status, NCCN high-risk stratification, and WBC.

Fig. 5.

Association of anxiety and depression with accumulating EFS and OS in AML patients after adjustment by their respective independent factors. Association of anxiety with accumulating EFS (a) and accumulating OS (b) after adjustment by smoking, NCCN high-risk stratification, male, and education duration. Association of depression with accumulating EFS (c) and accumulating OS (d) after adjustment by age, single/divorced/widowed status, NCCN high-risk stratification, and WBC.

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Regarding the prevalence of anxiety or depression in patients with the hematological disease, it is reported that the HADS-anxiety, HADS-depression score, anxiety prevalence, and depression prevalence were elevated in AML patients than in healthy controls [10]. Meanwhile, compared with the community sample of older individuals, older hematological malignancy patients show more prevalence of depression [21]. In our study, the prevalence of anxiety and depression was 48.5% and 43.2%, respectively, in AML patients, which was similar to previous studies [10, 11]. Meanwhile, both anxiety and depression were more prevalent in AML patients compared with disease controls and healthy controls. One possible reason could be that AML patients had to face uncomfortable feelings brought by disease symptoms (such as anemia, fever, bleeding, osteoarthritis pain) or financial burden, resulting in a higher prevalence of anxiety and depression in AML patients [22].

Except for the above-mentioned data, according to preceding studies, multiple risk factors for anxiety and depression have been identified in leukemia [11, 23]; however, these studies only collect regional data or focus on children. To further evaluate anxiety and depression risk factors in patients from various regions, this study was performed, which observed that in AML patients, smoking and high-risk stratification were independently associated with elevated risk of anxiety; meanwhile, male and education duration were independently correlated with decreased risk of anxiety. Besides, age, single/divorced/widowed, high-risk stratification, and WBC were independently associated with higher risk of depression. Possible explanations could be elucidated as follows: (1) smoking: we hypothesized that many smokers were vulnerable to mental illness and had heavier mental and financial burden [24]; (2) high-risk stratification: higher risk stratification meant patients would have to receive more intensive therapies, which might accelerate physical deconditioning; (3) male: adolescent girls and women would face physical and psychological problems caused by endocrine disorders, while this issue would not disturb men in AML patients [25, 26]; (4) education: patients with higher education might have obtained more knowledge, which was important for the understanding and management of anxiety [27]; (5) age: AML patients with older age might have comorbidities after treatment, while their illness might progress due to attenuated body functionality; besides, older adults tend to strongly react to loneliness and isolation due to lacking psychological companion. [28]; (6) single/divorced/widowed status: single/divorced/widowed status might have resulted in psychological conditions, such as loneliness and despair for the absence of social support and concern, and further causing depression [29]; (7) WBC: high WBC presented an unfavorable prognosis for AML treatment outcome, and a worse prognosis could mean a higher risk of depression in AML patients [30, 31].

In terms of the influence of anxiety and depression on survival profile in hematological malignancy, one study shows that EFS is shorter in anxiety patients and OS is worse in both anxiety and depression patients, compared with non-anxiety and non-depression AML patients [10]. Another study discloses that EuroQol Five Dimensions Questionnaire indices (which contain anxiety and depression as a central dimension) are associated with OS in AML patients treated with azacitidine [32, 33]. Our study found that depression was correlated with shorter accumulating EFS and OS in AML patients, which could be explained by the fact that (1) depression could be a long-term disorder in humans, which would induce the recurrence and progression of the disease, subsequently causing poor survival in AML patients, including EFS and OS [34‒36]; (2) patients with depression might have lower adherence to treatment, thus directly causing a worse prognosis [10]. However, after adjustment by the respective independent correlative factors, anxiety or depression were not associated with EFS or OS. Therefore, the prognostic value of anxiety and depression in AML patients warranted further investigation.

Although several findings were shown, there still existed several limitations. First, low statistical power might be caused because of small sample size; second, anxiety and depression were evaluated by AML patients themselves according to HADS questionnaire, causing subjective bias; third, the follow-up period is not long enough; hence, investigation on the association of anxiety and depression with long-term prognosis should be conducted in studies with a longer follow-up duration (for instance, a median follow-up duration of 5 years); fourthly, several characteristics could not be traced, such as red blood cell and platelet transfusion dependence, and the association of anxiety and depression with these characteristics could be further investigated.

In conclusion, anxiety and depression are commonly existed in AML patients with age, male, education, single/divorced/widowed status, smoking, NCCN high-risk stratification, and WBC as their independent related factors. Besides, depression instead of anxiety associates with poor survival profile. The current study may provide potential evidence for managing anxiety and depression in AML patients, thus promoting their psychological health and outcomes.

This study was approved by the Institutional Review Board of Southern University of Science and Technology Hospital (approval No. 20151219). The participants provided written informed consent. The statutory guardians of the participants provided written informed consent under circumstances of illiteracy.

The authors declare that they have no conflict of interest.

This study was supported by the National Key Clinical Specialist Construction Programs of China (2012-649).

Tao Zhong contributed to the conception and the design of the study. Dan Xu and Wenchao Li were responsible for the acquisition and analysis of the data. Wenchao Li contributed to the interpretation of the data, manuscript drafting, and critical revisions. All authors approved the final manuscript to be published.

Additional Information

Tao Zhong and Dan Xu contributed equally to this work.

Data are not publicly available due to ethical reasons. Further inquiries can be directed to the corresponding author.

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