Literature DB >> 32383398

Incidence of and sociological risk factors for suicide death in patients with leukemia: A population-based study.

Jin Yang1,2, Qingqing Liu1,2, Fanfan Zhao1,2, Xiaojie Feng1,2, Rahel Elishilia Kaaya1,2, Jun Lyu1,2.   

Abstract

OBJECTIVES: Suicide is closely related to sociological factors, but sociological analyses of suicide risk in leukemia are lacking. This study is the first to use the Surveillance, Epidemiology, and End Results Program (SEER) database to analyze sociological risk factors for suicide death in leukemia patients.
METHODS: A retrospective search of the SEER database was conducted. Logistic regression was used to identify independent risk factors for suicide death. Variables significant in the univariate logistic regression models were subsequently analyzed using multivariate regression.
RESULTS: The death rate was highest in California (1.73%). Suicide mortality was more common during the 1970s and 1980s, after which it trended downward. Young age at diagnosis (18-34 vs. >64 years: odds ratio [OR] = 1.537, 95% confidence interval [CI] = 1.007-2.347; 35-64 vs. >64 years: OR = 1.610, 95% CI = 1.309-1.979), being male (OR = 1.518, 95% CI = 1.230-1.873), and living where a high proportion of people have at least a bachelor's degree (>50% vs. <20%: OR = 8.115, 95% CI = 5.053-13.034) significantly increased suicide death risk.
CONCLUSION: Our findings could increase clinician awareness of and appropriate support for leukemia patients at risk of death by suicide.

Entities:  

Keywords:  Incidence; SEER database; death by suicide; leukemia; population-based; regression; sociological risk factors

Mesh:

Year:  2020        PMID: 32383398      PMCID: PMC7221221          DOI: 10.1177/0300060520922463

Source DB:  PubMed          Journal:  J Int Med Res        ISSN: 0300-0605            Impact factor:   1.671


Introduction

Death by suicide is a global problem that can occur throughout the life span and represents a serious healthcare burden.[1] Globally, almost 800,000 people die each year from suicide (one death every 40 seconds), accounting for 1.5% of deaths worldwide.[2] The healthcare burden is even greater when suicidal ideation and attempted suicide are included.[3] Cancer poses a major threat to human life, and being diagnosed with cancer is associated with increased risks of suicidal ideation and attempted suicide.[4] The suicide rate is reportedly almost twice as high in cancer patients as in the general population.[5,6] In addition, about 70% of suicide deaths among patients older than 60 years are related to medical conditions, and the incidence is particularly high in cancer patients.[7-12] Anxiety, comorbidities (e.g. depression, patient stress, high levels of hopelessness[13-15]), psychosocial conditions and decreased quality of life owing to adverse drug reactions are the leading causes of suicide in cancer patients. Increasing attention is being paid to sociological factors associated with suicide, and research on the association between cancer and sociological factors is growing. Caleyachetty et al.[16] found that exposure to a greater number of social risk factors increases the risk of death from all cancers combined, tobacco-related cancers and lung cancer in US adults. Another study found that women who had been socially isolated before diagnosis had a 66% increased risk of subsequent all-cause mortality and a triple risk of breast cancer mortality compared with socially integrated women.[17] Leukemia constitutes a group of life-threatening blood and bone marrow malignancies.[18] Leukemia cells proliferate and accumulate in bone marrow and other hematopoietic tissues owing to uncontrolled proliferation, differentiation disorders and blocked apoptosis, and infiltrate other non-hematopoietic tissues and organs, while inhibiting normal hematopoietic function. The Surveillance, Epidemiology, and End Results Program (SEER) database includes 18 registries that cover 30% of the US population and records demographic, clinical and outcome information for all cancers diagnosed in representative geographic regions of the USA.[19,20] It is therefore a potentially useful resource for identifying suicide deaths. The sociological risk factors examined in this study mainly relate to social environment, economics, education and other factors, rather than tumor size and stage, which are more clinically focused factors. Death by suicide is closely related to sociological factors (e.g. psychological, family, social life, interpersonal relationships and spiritual factors), but there are no previous sociological analyses of suicide risk in leukemia. Therefore, this study is the first to use the SEER database to analyze sociological risk factors for suicide death in leukemia patients.

Methods

Patients

A retrospective search of the SEER database was performed for cases diagnosed between 1973 and 2015; the database was accessed using SEER*Stat software (Surveillance Research Program, National Cancer Institute SEER*Stat software (seer.cancer.gov/seerstat) version 8.3.4). We searched the SEER database for records using International Classification of Diseases for Oncology (ICD-O-3) codes. We searched for patients older than 18 years, and excluded cases with no diagnosis, microscopic confirmation, autopsy findings only, or incomplete variables. The use of data from the SEER database does not require informed patient consent because all of these publicly available data are anonymized and de-identified prior to release. The SEER database can be accessed free of charge, and this study was exempted from obtaining informed consent by the institutional research committee of the First Affiliated Hospital of Xi’an Jiaotong University.

Statistical analysis

Patients were divided into the following two groups: suicide death and other causes of death. Logistic regression was used to identify independent risk factors for death by suicide. Variables that were statistically significant in the univariate logistic regression models were subsequently also analyzed using multivariate logistic regression models. All statistical tests were two-sided, with P < 0.05 considered to indicate statistical significance. All statistical analyses were performed using SPSS version 24.0 (IBM Corp., Chicago, IL, USA) and R (version 3.5.0) software (www.r-project.org).

Results

Patient characteristics

The application of our selection criteria identified 142,107 eligible patients, of whom 400 died by suicide. Most patients in the present cohort were aged >64 years, male, white and married. There were more suicide deaths in the groups living at a medium poverty level (71.0%), that comprised 20% to 50% of residents with at least a bachelor’s degree, had <10% who were unemployed, had a median household income of USD 50,001–100,000, and comprised <20% current smokers. The baseline demographics for the two groups are shown in Table 1.
Table 1.

Characteristics of patients.

Suicide death [n (%)]Other causes of death [n (%)]
Total400141,707
Age at diagnosis (years)
 18–3424 (6.0)6,346 (4.5)
 35–64152 (38.0)39,934 (28.2)
 >64224 (56.0)95,427 (67.3)
Sex
 Female129 (32.3)59,775 (42.2)
 Male271 (67.8)81,932 (57.8)
Race
 White351 (87.8)123,453 (87.1)
 Black31 (7.8)11,152 (7.9)
 Other18 (4.4)7,102 (5.0)
Marital status at diagnosis
 Married (including common law)240 (60.0)82,527 (58.2)
 Unmarried or domestic partner53 (13.3)17,052 (12.0)
 Divorced/separated/widowed107 (26.7)42,128 (29.8)
Poverty level
 Low75 (18.8)28,451 (20.0)
 Medium284 (71.0)92,920 (65.6)
 High41 (10.2)20,336 (14.4)
At least bachelor’s degree
 <20%39 (9.8)21,308 (15.0)
 20% to 50%282 (70.5)115,453 (81.5)
 >50%79 (19.7)4,946 (3.5)
Unemployed
 <10%361 (90.2)119,054 (84.0)
 ≥10%39 (9.8)22,653 (16.0)
Median (yearly) household income (USD)
 10,000–50,00063 (15.8)31,718 (22.4)
 50,001–100,000320 (80.0)105,876 (74.7)
 >100,00017 (4.2)4,113 (2.9)
Current smoker
 <20%317 (79.2)92,403 (65.2)
 ≥20%83 (20.8)49,304 (34.8)
Characteristics of patients.

Differences in suicide mortality rates by decade and state

The death rate from suicide was highest in California, at 1.73‰, followed by Washington, Michigan, and Georgia, at 0.22‰, 0.15‰ and 0.14‰, respectively. Suicide mortality was more common during the 1970s and 1980s, after which it trended downward (Figure 1).
Figure 1.

Differences in rate of suicide mortality by decade.

Differences in rate of suicide mortality by decade.

Risk factors for suicide death

Univariate logistic regression showed that age at diagnosis, sex, having at least a bachelor’s degree, being unemployed, median household income and current smoking status were significant contributors to the risk of death by suicide (all P < 0.05). We included these factors in the multivariate logistic regression, which showed that age at diagnosis (18–34 vs. >64 years: odds ratio [OR] = 1.537, 95% confidence interval [CI] = 1.007–2.347, P = 0.046; 35–64 vs. >64 years: OR = 1.610, 95% CI = 1.309–1.979, P < 0.001), sex (male vs. female: OR = 1.518, 95% CI = 1.230–1.873, P < 0.001), and the proportion of residents having at least a bachelor’s degree (>50% vs. <20%: OR = 8.115, 95% CI = 5.053–13.034, P < 0.001) significantly affected the risk of suicide death. Having a higher median household income (>USD 100,000 vs. USD 10,000–50,000: OR = 0.294, 95% CI = 0.152–0.567, P < 0.001) and being a current smoker (≥20% vs. <20%: OR = 0.564, 95% CI = 0.409–0.778, P < 0.001) seemed to exert protective effects (Table 2).
Table 2.

Univariate and multivariate logistic regression analysis results.

VariableUnivariate analysis
Multivariate analysis
OR95% CIP-valueOR95% CIP-value
Age at diagnosis (years)
 18–341.6111.057–2.456 0.027 1.5371.007–2.347 0.046
 35–641.6221.319–1.993 <0.001 1.6101.309–1.979 <0.001
 >64Reference
Sex
 FemaleReference
 Male1.5331.242–1.891 <0.001 1.5181.230–1.873 <0.001
Race
 WhiteReference
 Black1.1220.698–1.8030.635
 Other1.0970.613–1.9620.756
Marital status at diagnosis
 Married (including common law)Reference
 Unmarried or domestic partner1.0690.793–1.4400.662
 Divorced/separated/widowed0.8730.695–1.0970.245
Poverty level
 LowReference
 Medium1.1590.899–1.4960.255
 High0.7650.522–1.1200.168
At least bachelor’s degree
 <20%Reference
 20% to 50%1.3350.954–1.8660.0921.1260.757–1.6740.559
 >50%8.7275.939–12.823 <0.001 8.1155.053–13.034 <0.001
Unemployed
 <10%1.7611.265–2.452 0.001 1.3780.942–2.0160.099
 ≥10%Reference
Median (yearly) household income (USD)
 10,000–50,000ReferenceReference
 50,001–100,0001.5221.161–1.994 0.002 0.7040.469–1.0560.090
 >100,0002.0811.217–3.559 0.007 0.2940.152–0.567 <0.001
Current smoker
 <20%Reference
 ≥20%0.4910.385–0.625 <0.001 0.5640.409–0.778 <0.001

OR: odds ratio; CI: confidence interval.

Univariate and multivariate logistic regression analysis results. OR: odds ratio; CI: confidence interval.

Stratified analysis of different current smoker groups

We conducted a stratified analysis of current smokers. In the group of people that comprised <20% current smokers, being younger at the time of diagnosis (18–34 vs. >64 years: OR = 1.656, 95% CI = 1.051–2.610, P = 0.030; 35–64 vs. >64 years: OR = 1.633, 95% CI = 1.294–2.061, P < 0.001) and having at least a bachelor’s degree (>50% vs. <20%: OR = 8.612, 95% CI = 3.017–24.580, P < 0.001) significantly increased the risk of suicide death. Having a higher median household income (>USD 100,000 vs. USD 10,000–50,000: OR = 0.290, 95% CI = 0.115–0.733, P = 0.009) was a protective factor. In the group of people comprising ≥20% current smokers, being younger at diagnosis (35–64 vs. >64 years: OR = 1.628, 95% CI = 1.028–2.579, P = 0.038) and being male (vs. female: OR = 4.508, 95% CI = 2.399–8.471, P < 0.001) significantly increased the risk of suicide death, whereas being black (vs. white: OR = 0.271, 95% CI = 0.083–0.884, P = 0.030) was a protective factor (Table 3).
Table 3.

Multivariate logistic regression analysis results for current smoker groups.

VariableCurrent smoker <20%
Current smoker ≥20%
OR95% CIP-valueOR95% CIP-value
Age at diagnosis (years)
 18–341.6561.051–2.610 0.030 1.1080.325–3.7760.870
 35–641.6331.294–2.061 <0.001 1.6281.028–2.579 0.038
 >64Reference
Sex
 FemaleReference
 Male4.5082.399–8.471 <0.001
Race
 WhiteReference
 Black0.2710.083–0.884 0.030
 Other
Marital status at diagnosis
 Married (including common law)Reference
 Unmarried or domestic partner
 Divorced/separated/widowed
Poverty level
 LowReference
 Medium
 High
At least bachelor’s degree
 <20%Reference
 20% to 50%1.2230.444–3.3700.697
 >50%8.6123.017–24.580 <0.001
Unemployed
 <10%
 ≥10%Reference
Median (yearly) household income (USD)
 10,000–50,000ReferenceReference
 50,001–100,0000.6930.321–0.7330.351
 >100,0000.2900.115–0.733 0.009

OR: odds ratio; CI: confidence interval.

Multivariate logistic regression analysis results for current smoker groups. OR: odds ratio; CI: confidence interval.

Discussion

This study is the first to use the SEER database to analyze the sociological risk factors for suicide death in leukemia patients from 1973 to 2015. We found that younger age at time of diagnosis, being male and living where a higher proportion of people have at least a bachelor’s degree significantly increased the risk of suicide death. Death by suicide is a major public health problem.[6] Suicidal ideation can be triggered by genetic, psychological or neurobiological factors, and some cancer patients—especially those in an advanced stage—have a strong wish to die.[21-23] Kam et al.[24] found that the incidence of suicide was more than three times as high in patients with head and neck cancer compared with the general US population. Klaassen et al.[25] found that suicide in patients with genitourinary malignancies poses a public health problem, especially among males, older people and those with aggressive disease. Bowden et al.[7] found that being female, white and aged ≤39 years or 70 to 79 years were factors strongly associated with an increased risk of suicide in patients with gastric cancer. However, there are few reports on the association between leukemia and suicide risk. This is the first study to use the SEER database to analyze the sociological risk factors for suicide death in leukemia patients. The findings indicate that being younger at diagnosis, being male, and having at least a bachelor’s degree significantly increased the risk of suicide death. Age has always been a risk factor for death by suicide, and patients of different ages exhibit different psychological responses during treatment.[26] One study of medical students, house staff and faculty physicians showed that younger patients are more likely to have anxiety than older patients.[27] We found that age at diagnosis was a risk factor for death by suicide among leukemia patients. This suggests that young patients should receive cancer-related psychological education as soon as possible, and they should communicate with their family and medical workers to avoid excessive psychological stress levels. We also found that sex was a risk factor for suicide. Being male conferred an increased suicide death risk, which is consistent with the finding that males in the general population are more likely to die by suicide.[28] Another study showed that suicidal ideation was significantly more common in males.[29] Healthcare professionals should pay more attention to communicating with male patients to help them avoid death by suicide caused by factors such as excessive psychological stress, fear of the reactions of parents and friends, and fear of social discrimination.[5] One of our most interesting findings was that highly educated patients (those with at least a bachelor’s degree) are significantly more likely to die from suicide. Levels of psychological distress are increasing among students in higher education institutions.[30] Suicidal behavior in college students is related to various factors, such as psychopathology, stressful life events and personality traits,[31] and the rapid growth of higher education and the high expectations students must meet have increased the amount of psychological pressure that they experience.[32] The number of years of potential life lost by suicide death and the associated socioeconomic burden are enormous.[33-35] It is clear that there is a need to investigate these apparent effects of academic qualifications to develop effective prevention strategies in this population. The death rate from suicide was highest in California, followed by Washington, Michigan, and Georgia. This may be because these states, particularly California, have a more developed economy, higher living standards, higher levels of education and higher levels of psychological stress. We found that being a current smoker seemed to have a protective effect. We conducted a stratified analysis after dividing smokers into two groups according to their proportion. Age at diagnosis remained a risk factor for suicide death. The risk of suicide death was significantly higher in the group comprising <20% current smokers, in that having at least a bachelor’s degree (>50% vs. <20%), and in the group comprising ≥20% current smokers who were male. The World Health Organization has shown that suicide is now the fourth most important health problem after cerebrovascular disease, chronic obstructive pulmonary disease and severe depression, and so is an important issue that affects public health, family happiness and social harmony.[36] Suicide in hospitalized patients also causes serious harm and is a source of substantial psychological stress for medical staff.[37] Improving hospital safety, security and management; outpatient monitoring; and training medical staff in patient suicide assessments and prevention are particularly important for preventing suicide among leukemia patients. There were several study limitations: (1) the retrospective design is an inherent limitation, (2) we were unable to obtain SEER data on various potentially important factors such as anxiety, depression and pain, (3) the cause of death recorded in the database may have been biased by misclassification, (4) these results do not include individuals who attempt suicide, (5) some of the individuals with leukemia also had secondary cancers or metastatic cancers. Emotional distress may be cumulative and so may be strongly related to suicide, and (6) these findings likely cannot be generalized to minority populations, as the sample comprises predominately older, Caucasian males.

Conclusion

We found that younger age at diagnosis, being male and having at least a bachelor’s degree significantly increased the risk of suicide death. It is crucial to identify and treat people at risk of death by suicide as early as possible. More attention should be paid to sociological risk factors. Clinicians, caregivers and family members should be more aware of suicidal tendency in leukemia patients to provide timely treatment and psychological counselling.
  33 in total

1.  Mental health outcomes in elderly men with prostate cancer.

Authors:  Praful Ravi; Pierre I Karakiewicz; Florian Roghmann; Giorgio Gandaglia; Toni K Choueiri; Mani Menon; Rana R McKay; Paul L Nguyen; Jesse D Sammon; Shyam Sukumar; Briony Varda; Steven L Chang; Adam S Kibel; Maxine Sun; Quoc-Dien Trinh
Journal:  Urol Oncol       Date:  2014-08-19       Impact factor: 3.498

Review 2.  The psychology and neurobiology of suicidal behavior.

Authors:  Thomas E Joiner; Jessica S Brown; LaRicka R Wingate
Journal:  Annu Rev Psychol       Date:  2005       Impact factor: 24.137

Review 3.  Demographic and clinical factors associated with suicide in gastric cancer in the United States.

Authors:  Mallory B Bowden; Nathaniel J Walsh; Andrew J Jones; Asif M Talukder; Andrew G Lawson; Edward J Kruse
Journal:  J Gastrointest Oncol       Date:  2017-10

4.  Psychological distress and risk for suicidal behavior among university students in contemporary China.

Authors:  Fang Tang; Majella Byrne; Ping Qin
Journal:  J Affect Disord       Date:  2017-12-06       Impact factor: 4.839

Review 5.  Leukemia.

Authors:  Gunnar Juliusson; Rachael Hough
Journal:  Prog Tumor Res       Date:  2016-09-05

6.  Suicidal death within a year of a cancer diagnosis: A population-based study.

Authors:  Anas M Saad; Mohamed M Gad; Muneer J Al-Husseini; Mohamad A AlKhayat; Ahmad Rachid; Ahmad Samir Alfaar; Hesham M Hamoda
Journal:  Cancer       Date:  2019-01-07       Impact factor: 6.860

7.  Sex Differences in Mental Health Outcomes of Suicide Exposure.

Authors:  Judy van de Venne; Julie Cerel; Melinda Moore; Myfanwy Maple
Journal:  Arch Suicide Res       Date:  2019-06-10

8.  Depression and suicide ideas of cancer patients and influencing factors in South Korea.

Authors:  Su Jin Lee; Jong Hyock Park; Bo Young Park; So Young Kim; Il Hak Lee; Jong Heun Kim; Dai Ha Koh; Chang-Hoon Kim; Jae Hyun Park; Myong Sei Sohn
Journal:  Asian Pac J Cancer Prev       Date:  2014

9.  All-cause and cause-specific death rates by educational status for two million people in two American Cancer Society cohorts, 1959-1996.

Authors:  Kyle Steenland; Jane Henley; Michael Thun
Journal:  Am J Epidemiol       Date:  2002-07-01       Impact factor: 4.897

10.  Are there specific health-related factors that can accentuate the risk of suicide among men with prostate cancer?

Authors:  Abraraw Lehuluante; Per Fransson
Journal:  Support Care Cancer       Date:  2014-02-11       Impact factor: 3.603

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