Psychiatric disorders and infections are both common comorbidities among patients with cancer. However, little is known about the role of precancer psychiatric disorders on the subsequent risk of sepsis as a complication of infections among patients with cancer. We conducted a cohort study of 362,500 patients with newly diagnosed cancer during 2006–2014 in Sweden. We used flexible parametric models to calculate the HRs of sepsis after cancer diagnosis in relation to precancer psychiatric disorders and the analyses were performed in two models. In model 1, analyses were adjusted for sex, age at cancer diagnosis, calendar period, region of residence, and type of cancer. In model 2, further adjustments were made for marital status, educational level, cancer stage, infection history, and Charlson Comorbidity Index score. During a median follow-up of 2.6 years, we identified 872 cases of sepsis among patients with cancer with precancer psychiatric disorders (incidence rate, IR, 14.8 per 1,000 person-years) and 12,133 cases among patients with cancer without such disorders (IR, 11.6 per 1000 person-years), leading to a statistically significant association between precancer psychiatric disorders and sepsis in both the simplified (HR, 1.31; 95% CI, 1.22–1.40) and full (HR, 1.26; 95% CI, 1.18–1.35) models. The positive association was consistently noted among patients with different demographic factors or cancer characteristics, for most cancer types, and during the entire follow-up after cancer diagnosis. Collectively, preexisting psychiatric disorders were associated with an increased risk of sepsis after cancer diagnosis, suggesting a need of heightened clinical awareness in this patient group.

Significance:

These results call for extended prevention and surveillance of sepsis among patients with cancer with psychiatric comorbidities.

Sepsis is a common complication of cancer and its treatment. Patients with cancer have a nearly ten times higher risk of sepsis, compared with individuals without cancer (1, 2). Sepsis is associated with markedly elevated healthcare use and medical costs as well as increased mortality (1–3). It is therefore important to identify risk factors for sepsis among patients with cancer, ideally during the entire disease course (from diagnosis until later survivorship), with the aim to improve cancer survival and reduce healthcare cost. Psychiatric disorders, especially depression, anxiety, and adjustment disorders are also common comorbidities among patients with cancer (4) and have a wide spectrum of effects on physical health, including modulating the risk of infections (5–7). One potential pathway that links together psychiatric disorders with infections is psychological stress, which is known to play an important role in the onset, maintenance, and aggravation of psychiatric disorders (8) as well as in modulating immune function (9, 10). Disparities in healthcare access in relation to psychiatric disorders and differential risk behaviors among patients with psychiatric disorders might be additional or alternative mechanisms linking together psychiatric disorders with infection, especially severe infections (6, 11, 12). Although recent studies have suggested that depression and other stress-related disorders are associated with severe infections in the general population (13, 14), whether a similar association exists among patients with cancer, a high-risk group for infections, remains unknown. To this end, we assessed the risk of subsequent sepsis, as a complication of infections, among cancer patients with precancer psychiatric disorders, in contrast to cancer patients without such disorders.

Study cohort

We identified 362,500 patients (age ≥30) with a newly diagnosed cancer from January 1, 2006 to December 31, 2014 in Sweden, based on the Swedish Cancer Register, which has been available since 1958 with a nearly 100% coverage of the entire country. From the Cancer Register, we obtained information on date of diagnosis and cancer type. Since 2004, the register has also collected relatively complete information on cancer stage at the time of diagnosis, except for hematologic malignancy and central nervous system (CNS) tumors. According to the 10th Swedish Revision of the International Classification of Diseases (ICD-10) codes, we further classified cancers into eight groups, including prostate cancer, breast cancer, colorectal cancer, lung cancer, non–melanoma skin cancer, CNS tumor, hematologic malignancies, and other cancers (Supplementary Table S1). We used the personal identification numbers uniquely assigned to all Swedish residents to follow these patients from date of diagnosis, until a diagnosis of sepsis, emigration out of Sweden, death, or December 31 2014, whichever occurred first, through cross-linkages to the Swedish Patient Register (for ascertainment of sepsis), Migration Register, and Causes of Death Register. The Swedish Patient Register includes discharge records from inpatient care (100% complete for the country since 1987) and outpatient based-specialist care (>80% complete for the entire country since 2001). Because we aimed to study the association of psychiatric disorders with sepsis subsequent to a cancer diagnosis, patients with cancer that had a diagnosis of sepsis before cancer diagnosis were excluded (N = 6,498), leaving 356,002 in the final analysis (98%; Supplementary Fig. S1).

Precancer psychiatric disorders

Through the Swedish Patient Register, we identified clinical diagnoses of psychiatric disorders among the cancer patients between January 1, 2001 and the date of cancer diagnosis. Psychiatric disorders were defined through any first inpatient or outpatient hospital visit with a main diagnosis concerning the ICD-10 codes F10-F99. Patients with cancer that had a clinical diagnosis of psychiatric disorders before cancer diagnosis were defined as exposed to psychiatric disorders, whereas the other patients with cancer served as the unexposed group (i.e., reference). We further classified psychiatric disorders as substance abuse (ICD-10: F10–F16/F18–F19), depression (ICD-10: F32–F33), anxiety (ICD-10: F40–F41), stress reaction and adjustment disorder (ICD-10: F43), somatoform/conversion disorder (ICD-10: F44–F45), and other psychiatric disorders.

Sepsis

A clinical diagnosis of sepsis was defined as any first inpatient or outpatient hospital visit with a main diagnosis concerning sepsis, according to the Patient Register. The ICD-10 codes used to define sepsis are listed in Supplementary Table S2 (15, 16).

Covariables

We collected information about region of residence, marital status, and educational level from the Swedish Longitudinal Integration Database for Health Insurance and Labor Market. We calculated Charlson Comorbidity Index score (17) within the five years prior to cancer diagnosis for all patients according to the Patient Register. Cancer stage was ascertained by the TNM or FIGO information from the Cancer Register, including limited-stage localized (T-localized/N0/M0 or FIGO 0, I), advanced-stage localized (T-advanced/N0/M0 or FIGO II), regional spread (any T/N+/M0 or FIGO III), advanced (any T/any N/M+ or FIGO IV), and unknown stage (detailed information is available from https://www.encr.eu/sites/default/files/pdf/extentofdisease.pdf; refs. 18–20). We used information on cancer subtypes, including lymphoma, myeloma, leukemia, myelodysplastic syndrome, and myeloproliferative neoplasms for hematological malignancy, instead of stage. Unknown was used as the cancer stage for CNS tumors. As the risk of sepsis might differ between patients with and without a history of severe infection before cancer diagnosis, we also obtained information on history of inpatient care due to infection within the three months before cancer diagnosis through the Patient Register. ICD-10 codes used to identify infections are listed in Supplementary Table S2 (21, 22).

Statistical analysis

We first described the characteristics of patients with cancer, including sex, age at diagnosis, calendar period of diagnosis (2006–2010 or 2011–2014), region of residence (Southern Sweden, Central Sweden, or Northern Sweden), marital status (single, married or cohabiting, or divorced or widowed), educational level (>12 years, 9–12 years, <9 years, or unknown), type of cancer, cancer stage, infection history, and Charlson Comorbidity Index score (0, 1, or ≥2). We calculated the unadjusted incidence rates (IR) of sepsis among patients with or without precancer psychiatric disorders during the entire follow-up, using number of cases divided by accumulated person-years at risk. To demonstrate the temporal pattern of absolute rate of sepsis along with time since cancer diagnosis, we first fitted a flexible parametric survival model to estimate hazards of sepsis among these two groups of patients, allowing the hazards to change over time (i.e., nonproportional hazards). We then used flexible parametric survival models to estimate the HRs and their corresponding 95% confidence intervals (CI) for sepsis, after adjusting for other covariates. We first performed models that allow for nonproportional hazards for the effect of exposure, that is, the HRs were allowed to change over time since cohort entry. Because we observed constant HRs over time, we also performed proportional hazards models to estimate average HRs for the entire follow-up period. Time since cohort entry was used as the underlying time scale in all analyses and the analyses were performed in two models. In model 1, analyses were adjusted for sex, age at cancer diagnosis, calendar period, region of residence, and type of cancer, as potential confounders. In model 2, we further adjusted for covariables that might both confound and mediate the studied association, including marital status, educational level, cancer stage, infection history, and Charlson Comorbidity Index score. We hypothesized that while sex, age, calendar period, region of residence, and type of cancer might be potential confounders for the association of psychiatric disorders with sepsis, marital status, educational level, cancer stage, infection history and Charlson Comorbidity Index score might instead serve as potential mediators linking together precancer psychiatric disorders with sepsis after cancer diagnosis. A detailed description of the statistical models is provided in the Supplementary Methods.

The association of precancer psychiatric disorders with sepsis might vary between patients with different sociodemographic and clinical characteristics, that is, patient characteristics might interact with the effect of precancer psychiatric disorders on sepsis. For instance, the risk of sepsis following a cancer diagnosis might differ by sex, age, socioeconomic status, disease severity, susceptibility to infection, and general health status. We therefore performed additional analyses to assess the interactions between precancer psychiatric disorders and sex, age, calendar period, region of residence, marital status, educational level, cancer stage, infection history, or Charlson Comorbidity Index score. The differences between subgroup-specific HRs were assessed by introducing interaction terms to the flexible parametric models and the corresponding statistical significance was assessed by likelihood ratio tests. As the association might also vary for different cancer types and individual psychiatric disorders, we also separately analyzed patients with different cancers, as well as for different individual psychiatric disorders. The differences between group-specific HRs were assessed by introducing interaction terms to the flexible parametric models and the corresponding statistical significance was assessed by likelihood ratio tests. As the association might also vary for different cancer types and individual psychiatric disorders, we also separately analyzed patients with different cancers, as well as for different individual psychiatric disorders. We found in a previous study that the risk of psychiatric disorders started to increase quickly from approximately one year before cancer diagnosis (23), which might be attributable to the experience of psychological distress in relation to the emerging cancer symptoms or the clinical evaluation of a potential cancer (24), or simply the cancer-related inflammation (25). In another sensitivity analysis, we restricted the definition of precancer psychiatric disorders to the ones diagnosed more than one year before cancer diagnosis.

Analyses were performed using statistical software (SAS, version 9.4; SAS Institute and Stata, version 15.1; StataCorp LP). P < 0.05 was used to indicate statistical significance. The study was approved by the Regional Ethical Review Board in Stockholm, Sweden.

We identified 22,609 patients with cancer with a diagnosis of psychiatric disorders before cancer diagnosis, and 333,393 patients without such a diagnosis. The median age at diagnosis was 64 for patients with cancer with precancer psychiatric disorders and 68 for patients with cancer without such comorbidities. Among patients with precancer psychiatric disorders, 50% were male; among patients without pre-cancer psychiatric disorders, 54% were male.

Compared to patients without psychiatric disorders, patients with psychiatric disorders were in general more likely to be female, diagnosed with cancer at a younger age and at a later calendar period, non-cohabitating, and have a higher prevalence of infection history and a higher Charlson Comorbidity Index score (Table 1).

Table 1.

Baseline characteristics of the study participants in a cohort study of 356,002 cancer patients that were diagnosed during 2006–2014 in Sweden.

CharacteristicsCancer patients without psychiatric disorders at the time of diagnosisCancer patients with psychiatric disorders at the time of diagnosis
No. of patients 333,393 22,609 
Male (%) 181,215 (54.4%) 11,301 (50.0%) 
Median age at diagnosis, years 68 64 
Calendar period 
 2006–2010 184,545 (55.4%) 10,308 (45.6%) 
 2011–2014 148,848 (44.6%) 12,301 (54.4%) 
Region of residence 
 Southern Sweden 148,890 (44.7%) 10,253 (45.3%) 
 Central Sweden 131,482 (39.4%) 9,489 (42.0%) 
 Northern Sweden 53,021 (15.9%) 2,867 (12.7%) 
Marital status 
 Single 43,493 (13.0%) 5,509 (24.4%) 
 Married or cohabiting 187,366 (56.2%) 8,211 (36.3%) 
 Divorced or widowed 102,534 (30.8%) 8,889 (39.3%) 
Education 
 >12 years 78,688 (23.6%) 5,070 (22.4%) 
 9–12 years 157,692 (47.3%) 12,408 (54.9%) 
 <9 years 93,247 (28.0%) 4,911 (21.7%) 
 Unknown 3,766 (1.1%) 220 (1.0%) 
Cancer stagea 
 Limited-stage localized 94,567 (28.4%) 6,708 (29.7%) 
 Advanced-stage localized 20,369 (6.1%) 1,399 (6.2%) 
 Regional spread 34,693 (10.4%) 2,739 (12.1%) 
 Advanced 35,003 (10.5%) 2,617 (11.6%) 
 Unknown 122,782 (36.8%) 7,501 (33.2%) 
 Not applicable 25,979 (7.8%) 1,645 (7.3%) 
Infection historyb 4,830 (1.4%) 483 (2.1%) 
Charlson Comorbidity Index score 
 0 281,792 (84.5%) 18,299 (80.9%) 
 1 41,533 (12.5%) 3,406 (15.1%) 
 ≥2 10,068 (3.0%) 904 (4.0%) 
CharacteristicsCancer patients without psychiatric disorders at the time of diagnosisCancer patients with psychiatric disorders at the time of diagnosis
No. of patients 333,393 22,609 
Male (%) 181,215 (54.4%) 11,301 (50.0%) 
Median age at diagnosis, years 68 64 
Calendar period 
 2006–2010 184,545 (55.4%) 10,308 (45.6%) 
 2011–2014 148,848 (44.6%) 12,301 (54.4%) 
Region of residence 
 Southern Sweden 148,890 (44.7%) 10,253 (45.3%) 
 Central Sweden 131,482 (39.4%) 9,489 (42.0%) 
 Northern Sweden 53,021 (15.9%) 2,867 (12.7%) 
Marital status 
 Single 43,493 (13.0%) 5,509 (24.4%) 
 Married or cohabiting 187,366 (56.2%) 8,211 (36.3%) 
 Divorced or widowed 102,534 (30.8%) 8,889 (39.3%) 
Education 
 >12 years 78,688 (23.6%) 5,070 (22.4%) 
 9–12 years 157,692 (47.3%) 12,408 (54.9%) 
 <9 years 93,247 (28.0%) 4,911 (21.7%) 
 Unknown 3,766 (1.1%) 220 (1.0%) 
Cancer stagea 
 Limited-stage localized 94,567 (28.4%) 6,708 (29.7%) 
 Advanced-stage localized 20,369 (6.1%) 1,399 (6.2%) 
 Regional spread 34,693 (10.4%) 2,739 (12.1%) 
 Advanced 35,003 (10.5%) 2,617 (11.6%) 
 Unknown 122,782 (36.8%) 7,501 (33.2%) 
 Not applicable 25,979 (7.8%) 1,645 (7.3%) 
Infection historyb 4,830 (1.4%) 483 (2.1%) 
Charlson Comorbidity Index score 
 0 281,792 (84.5%) 18,299 (80.9%) 
 1 41,533 (12.5%) 3,406 (15.1%) 
 ≥2 10,068 (3.0%) 904 (4.0%) 

aPatients with missing or unknown TNM stage and patients with CNS tumors were classified as ‘Unknown.’ Patients with hematologic malignancy were classified as “not applicable,” including 3,273 patients with leukemia, 1,450 patients with myelodysplastic syndrome, 3,108 patients with myeloproliferative neoplasm, 4,299 patients with myeloma, and 15,494 patients with lymphoma.

bInfection history was defined as history of inpatient care due to infection within the three months before cancer diagnosis through the Patient Register.

During a median follow-up of 2.6 years, a total of 13,005 cases of sepsis were identified. Among these cases, 11,104 (85.4%) were ascertained through inpatient care, whereas 1,901 (14.6%) through outpatient care. We identified 872 incident cases of sepsis among patients with cancer with precancer psychiatric disorders (IR, 14.8 per 1000 person-years) and 12,133 cases among patients with cancer without precancer psychiatric disorders (IR, 11.6 per 1,000 person-years; Table 2). Patients with precancer psychiatric disorders had constantly higher hazard of sepsis, compared with patients without precancer psychiatric disorders, during the entire follow-up apart from the very brief time period immediately after cancer diagnosis (Fig. 1A). Compared with the reference, we found an increased rate of sepsis among patients with cancer with precancer psychiatric disorders. The increased rate was noted immediately after cancer diagnosis and persisted until the end of follow-up (Fig. 1B). Because of the constant HRs noted during the entire follow-up, all HRs presented below are derived from models assuming proportional hazards for effect of precancer psychiatric disorders. The increased rate was similar in both the simpler (HR, 1.31; 95% CI, 1.22–1.40) and full (HR, 1.26; 95% CI, 1.18–1.35) models. The increased rate did not vary greatly by sex, calendar period of diagnosis, region of residence, educational level, infection history, or Charlson Comorbidity Index score, but was slightly greater among younger patients, non-cohabitating patients, and patients with lower stage cancer (Table 2).

Table 2.

Incidence rates (per 1000 person-years) and hazard ratios of sepsis among patients with cancer with psychiatric disorders compared with patients with cancer without psychiatric disorders, a cohort study in Sweden, 2006–2014.

Patients with cancer without psychiatric disorders at the time of diagnosisPatients with cancer with psychiatric disorders at the time of diagnosis
CharacteristicsNo. of patients with sepsisCrude IRHR (95% CI)No. of patients with sepsisCrude IRModel 1a HR (95% CI)PModel 2b HR (95% CI)P
Overall 12,133 11.6 1.0 872 14.8 1.31 (1.22–1.40)  1.26 (1.18–1.35)  
Sex       0.56  0.39 
 Male 7,534 13.3 1.0 492 17.5 1.29 (1.17–1.41)  1.23 (1.12–1.35)  
 Female 4,599 9.6 1.0 380 12.3 1.34 (1.21–1.49)  1.31 (1.18–1.45)  
Age, years       0.03  0.01 
 ≤54 1,401 7.5 1.0 205 12.3 1.53 (1.32–1.77)  1.50 (1.30–1.74)  
 55–64 2,552 9.3 1.0 266 14.2 1.38 (1.22–1.57)  1.31 (1.16–1.49)  
 65–74 3,940 12.1 1.0 251 16.5 1.27 (1.12–1.44)  1.23 (1.08–1.40)  
 75–84 3,194 15.7 1.0 115 16.8 1.05 (0.87–1.26)  0.99 (0.82–1.19)  
 ≥85 1,046 18.5 1.0 35 22.4 1.21 (0.87–1.70)  1.18 (0.84–1.65)  
Calendar period       0.40  0.81 
 2006–2010 8,551 10.7 1.0 520 12.9 1.28 (1.17–1.40)  1.23 (1.12–1.34)  
 2011–2014 3,582 14.6 1.0 352 19.0 1.36 (1.22–1.52)  1.31 (1.18–1.47)  
Region of residence       0.06  0.08 
 Southern Sweden 5,242 11.2 1.0 410 15.1 1.39 (1.26–1.54)  1.33 (1.20–1.47)  
 Central Sweden 4,762 11.5 1.0 362 14.7 1.31 (1.18–1.46)  1.26 (1.14–1.41)  
 Northern Sweden 2,129 13.1 1.0 100 13.9 1.07 (0.87–1.31)  1.04 (0.85–1.27)  
Marital status       –  0.004 
 Single 1,368 10.0 1.0 232 16.6 –  1.56 (1.36–1.79)  
 Married or cohabiting 7,025 11.3 1.0 303 13.1 –  1.16 (1.04–1.31)  
 Divorced or widowed 3,740 12.9 1.0 337 15.5 –  1.20 (1.08–1.35)  
Education       –  0.64 
 >12 years 2,443 9.1 1.0 168 11.7 –  1.25 (1.07–1.46)  
 9–12 years 5,672 11.3 1.0 479 14.9 –  1.29 (1.18–1.42)  
 <9 years 3,837 14.4 1.0 217 18.4 –  1.23 (1.07–1.41)  
 Unknown 181 20.0 1.0 15.3 –  0.86 (0.42–1.75)  
Cancer stagec       –  0.02 
 Limited-stage localized 2,154 6.3 1.0 179 8.7 –  1.39 (1.19–1.61)  
 Advanced-stage localized 803 12.5 1.0 63 18.2 –  1.41 (1.09–1.82)  
 Regional spread 1,550 15.9 1.0 130 20.5 –  1.28 (1.07–1.53)  
 Advanced 1,516 38.1 1.0 105 44.1 –  1.10 (0.90–1.34)  
 Unknown 3,800 8.9 1.0 274 12.6 –  1.38 (1.22–1.56)  
 Not applicable 2,310 30.6 1.0 121 28.4 –  0.99 (0.82–1.19)  
Infection historyd       –  0.98 
 Yes 308 33.4 1.0 35 43.5 –  1.26 (1.18–1.35)  
 No 11825 11.4 1.0 837 14.4 –  1.26 (0.89–1.78)  
Charlson Comorbidity Index score       –  0.96 
 0 9600 10.4 1.0 648 13.0 –  1.27 (1.17–1.37)  
 1 1910 17.9 1.0 160 21.5 –  1.25 (1.06–1.47)  
 ≥2 623 30.3 1.0 64 38.7 –  1.23 (0.95–1.59)  
Patients with cancer without psychiatric disorders at the time of diagnosisPatients with cancer with psychiatric disorders at the time of diagnosis
CharacteristicsNo. of patients with sepsisCrude IRHR (95% CI)No. of patients with sepsisCrude IRModel 1a HR (95% CI)PModel 2b HR (95% CI)P
Overall 12,133 11.6 1.0 872 14.8 1.31 (1.22–1.40)  1.26 (1.18–1.35)  
Sex       0.56  0.39 
 Male 7,534 13.3 1.0 492 17.5 1.29 (1.17–1.41)  1.23 (1.12–1.35)  
 Female 4,599 9.6 1.0 380 12.3 1.34 (1.21–1.49)  1.31 (1.18–1.45)  
Age, years       0.03  0.01 
 ≤54 1,401 7.5 1.0 205 12.3 1.53 (1.32–1.77)  1.50 (1.30–1.74)  
 55–64 2,552 9.3 1.0 266 14.2 1.38 (1.22–1.57)  1.31 (1.16–1.49)  
 65–74 3,940 12.1 1.0 251 16.5 1.27 (1.12–1.44)  1.23 (1.08–1.40)  
 75–84 3,194 15.7 1.0 115 16.8 1.05 (0.87–1.26)  0.99 (0.82–1.19)  
 ≥85 1,046 18.5 1.0 35 22.4 1.21 (0.87–1.70)  1.18 (0.84–1.65)  
Calendar period       0.40  0.81 
 2006–2010 8,551 10.7 1.0 520 12.9 1.28 (1.17–1.40)  1.23 (1.12–1.34)  
 2011–2014 3,582 14.6 1.0 352 19.0 1.36 (1.22–1.52)  1.31 (1.18–1.47)  
Region of residence       0.06  0.08 
 Southern Sweden 5,242 11.2 1.0 410 15.1 1.39 (1.26–1.54)  1.33 (1.20–1.47)  
 Central Sweden 4,762 11.5 1.0 362 14.7 1.31 (1.18–1.46)  1.26 (1.14–1.41)  
 Northern Sweden 2,129 13.1 1.0 100 13.9 1.07 (0.87–1.31)  1.04 (0.85–1.27)  
Marital status       –  0.004 
 Single 1,368 10.0 1.0 232 16.6 –  1.56 (1.36–1.79)  
 Married or cohabiting 7,025 11.3 1.0 303 13.1 –  1.16 (1.04–1.31)  
 Divorced or widowed 3,740 12.9 1.0 337 15.5 –  1.20 (1.08–1.35)  
Education       –  0.64 
 >12 years 2,443 9.1 1.0 168 11.7 –  1.25 (1.07–1.46)  
 9–12 years 5,672 11.3 1.0 479 14.9 –  1.29 (1.18–1.42)  
 <9 years 3,837 14.4 1.0 217 18.4 –  1.23 (1.07–1.41)  
 Unknown 181 20.0 1.0 15.3 –  0.86 (0.42–1.75)  
Cancer stagec       –  0.02 
 Limited-stage localized 2,154 6.3 1.0 179 8.7 –  1.39 (1.19–1.61)  
 Advanced-stage localized 803 12.5 1.0 63 18.2 –  1.41 (1.09–1.82)  
 Regional spread 1,550 15.9 1.0 130 20.5 –  1.28 (1.07–1.53)  
 Advanced 1,516 38.1 1.0 105 44.1 –  1.10 (0.90–1.34)  
 Unknown 3,800 8.9 1.0 274 12.6 –  1.38 (1.22–1.56)  
 Not applicable 2,310 30.6 1.0 121 28.4 –  0.99 (0.82–1.19)  
Infection historyd       –  0.98 
 Yes 308 33.4 1.0 35 43.5 –  1.26 (1.18–1.35)  
 No 11825 11.4 1.0 837 14.4 –  1.26 (0.89–1.78)  
Charlson Comorbidity Index score       –  0.96 
 0 9600 10.4 1.0 648 13.0 –  1.27 (1.17–1.37)  
 1 1910 17.9 1.0 160 21.5 –  1.25 (1.06–1.47)  
 ≥2 623 30.3 1.0 64 38.7 –  1.23 (0.95–1.59)  

Abbreviation: CI, confidence interval.

aModel 1 was adjusted for sex, age, calendar period, region of residence, and type of cancer. The effect of type of cancer was allowed to vary over time (nonproportional hazards), and the effects of other covariates were assumed to be time-fixed (proportional hazards) in all analyses.

bModel 2 was adjusted for sex, age, calendar period, marital status, educational level, region of residence, type of cancer, cancer stage, infection history, and Charlson Comorbidity Index score. The effect of type of cancer was allowed to vary over time (nonproportional hazards), and the effects of other covariates were assumed to be time-fixed (proportional hazards) in all analyses.

cPatients with missing or unknown TNM stage and patients with CNS tumors were classified as ‘Unknown.’ Patients with hematologic malignancy were classified as “not applicable,” including 3,273 patients with leukemia, 1,450 patients with myelodysplastic syndrome, 3,108 patients with myeloproliferative neoplasm, 4,299 patients with myeloma, and 15,494 patients with lymphoma.

dInfection history was defined as history of inpatient care due to infection within the three months before cancer diagnosis through the Patient Register.

Figure 1.

Hazards and HRs of sepsis among patients with cancer with precancer psychiatric disorders compared with patients with cancer without precancer psychiatric disorders, a cohort study in Sweden, 2006–2014. A, Hazards of sepsis among patients with cancer with and without precancer psychiatric disorders. Hazards were estimated from flexible parametric survival models. B, HRs and 95% confidence intervals of sepsis among patients with cancer with precancer psychiatric disorders compared with patients with cancer without precancer psychiatric disorders. HRs were estimated from flexible parametric survival models, allowing the effect of psychiatric disorders and type of cancer on sepsis to vary over time. A spline with 5 df (4 intermediate knots and 2 knots at each boundary, placed at quintiles of distribution of events) was used for the baseline rate, while a spline with 3 df was used for the time-varying effect. Model 1 was adjusted for sex, age, calendar period, region of residence, and type of cancer. Model 2 was adjusted for sex, age, calendar period, marital status, educational level, region of residence, type of cancer, cancer stage, infection history, and Charlson Comorbidity Index score.

Figure 1.

Hazards and HRs of sepsis among patients with cancer with precancer psychiatric disorders compared with patients with cancer without precancer psychiatric disorders, a cohort study in Sweden, 2006–2014. A, Hazards of sepsis among patients with cancer with and without precancer psychiatric disorders. Hazards were estimated from flexible parametric survival models. B, HRs and 95% confidence intervals of sepsis among patients with cancer with precancer psychiatric disorders compared with patients with cancer without precancer psychiatric disorders. HRs were estimated from flexible parametric survival models, allowing the effect of psychiatric disorders and type of cancer on sepsis to vary over time. A spline with 5 df (4 intermediate knots and 2 knots at each boundary, placed at quintiles of distribution of events) was used for the baseline rate, while a spline with 3 df was used for the time-varying effect. Model 1 was adjusted for sex, age, calendar period, region of residence, and type of cancer. Model 2 was adjusted for sex, age, calendar period, marital status, educational level, region of residence, type of cancer, cancer stage, infection history, and Charlson Comorbidity Index score.

Close modal

Largely similar results were found for all major cancer types, except hematologic malignancy and non-melanoma skin cancer (Table 3). The strongest associations were observed for breast cancer, prostate cancer, and the group of other cancers. Similar results were also found for most individual psychiatric disorders studied, with the strongest association noted for substance abuse, followed by depression and other psychiatric disorders (Table 4). When restricting the definition of precancer psychiatric disorders to psychiatric disorders diagnosed more than one year before cancer diagnosis, a similar overall association and temporal pattern of the association were noted (Supplementary Fig. S2).

Table 3.

HRs and 95% CI of sepsis among cancer patients with psychiatric disorders compared to cancer patients without psychiatric disorders, analysis by common cancer types.

Patients with cancer without psychiatric disorders at the time of diagnosisPatients with cancer with psychiatric disorders at the time of diagnosis
CharacteristicsNo. of patients with sepsisCrude IRHR (95% CI)No. of patients with sepsisCrude IRModel 1a HR (95% CI)Model 2b HR (95% CI)
Overall 12,133 11.6 1.0 872 14.8 1.31 (1.22–1.40) 1.26 (1.18–1.35) 
Prostate 2,087 7.9 1.0 113 9.9 1.41 (1.17–1.70) 1.31 (1.08–1.58) 
Breast 1,034 5.8 1.0 104 8.9 1.48 (1.21–1.82) 1.36 (1.11–1.67) 
Colorectal 1,564 14.3 1.0 90 17.1 1.20 (0.97–1.46) 1.19 (0.96–1.47) 
Lung 780 27.7 1.0 76 33.5 1.17 (0.92–1.49) 1.19 (0.93–1.51) 
Non-melanoma skin 550 8.5 1.0 19 7.0 1.02 (0.65–1.62) 0.94 (0.59–1.48) 
CNS 189 8.3 1.0 14 7.3 1.08 (0.63–1.87) 1.12 (0.64–1.94) 
Hematological 2,310 30.6 1.0 121 28.4 0.95 (0.79–1.15) 0.98 (0.81–1.17) 
Other 3,619 11.9 1.0 335 17.2 1.51 (1.35–1.69) 1.42 (1.26–1.59) 
Patients with cancer without psychiatric disorders at the time of diagnosisPatients with cancer with psychiatric disorders at the time of diagnosis
CharacteristicsNo. of patients with sepsisCrude IRHR (95% CI)No. of patients with sepsisCrude IRModel 1a HR (95% CI)Model 2b HR (95% CI)
Overall 12,133 11.6 1.0 872 14.8 1.31 (1.22–1.40) 1.26 (1.18–1.35) 
Prostate 2,087 7.9 1.0 113 9.9 1.41 (1.17–1.70) 1.31 (1.08–1.58) 
Breast 1,034 5.8 1.0 104 8.9 1.48 (1.21–1.82) 1.36 (1.11–1.67) 
Colorectal 1,564 14.3 1.0 90 17.1 1.20 (0.97–1.46) 1.19 (0.96–1.47) 
Lung 780 27.7 1.0 76 33.5 1.17 (0.92–1.49) 1.19 (0.93–1.51) 
Non-melanoma skin 550 8.5 1.0 19 7.0 1.02 (0.65–1.62) 0.94 (0.59–1.48) 
CNS 189 8.3 1.0 14 7.3 1.08 (0.63–1.87) 1.12 (0.64–1.94) 
Hematological 2,310 30.6 1.0 121 28.4 0.95 (0.79–1.15) 0.98 (0.81–1.17) 
Other 3,619 11.9 1.0 335 17.2 1.51 (1.35–1.69) 1.42 (1.26–1.59) 

Abbreviation: CI, confidence interval.

aModel 1 was adjusted for sex, age, calendar period, and region of residence, and the effects of all covariates were assumed to be time-fixed (proportional hazards) in all analyses.

bModel 2 was adjusted for sex, age, calendar period, marital status, educational level, region of residence, cancer stage, infection history, and Charlson Comorbidity Index score, and the effects of all covariates were assumed to be time-fixed (proportional hazards) in all analyses.

Table 4.

HRs and 95% CI of sepsis among patients with cancer with psychiatric disorders compared with patients with cancer without psychiatric disorders, analysis by specific psychiatric disorders.

CharacteristicsNo. of patients with sepsisCrude IRModel 1a HR (95% CI)Model 2b HR (95% CI)
Reference 12,133 11.6 1.0 1.0 
Depression 225 14.8 1.33 (1.17–1.52) 1.30 (1.14–1.48) 
Anxiety 126 13.4 1.25 (1.05–1.49) 1.22 (1.02–1.45) 
Stress reaction and adjustment disorder 63 10.2 1.06 (0.82–1.35) 1.02 (0.80–1.31) 
Substance abuse 240 19.2 1.49 (1.31–1.70) 1.40 (1.23–1.59) 
Somatoform/conversion disorder 33 12.1 1.09 (0.77–1.53) 1.08 (0.76–1.51) 
Other 185 14.2 1.30 (1.12–1.50) 1.26 (1.09–1.46) 
CharacteristicsNo. of patients with sepsisCrude IRModel 1a HR (95% CI)Model 2b HR (95% CI)
Reference 12,133 11.6 1.0 1.0 
Depression 225 14.8 1.33 (1.17–1.52) 1.30 (1.14–1.48) 
Anxiety 126 13.4 1.25 (1.05–1.49) 1.22 (1.02–1.45) 
Stress reaction and adjustment disorder 63 10.2 1.06 (0.82–1.35) 1.02 (0.80–1.31) 
Substance abuse 240 19.2 1.49 (1.31–1.70) 1.40 (1.23–1.59) 
Somatoform/conversion disorder 33 12.1 1.09 (0.77–1.53) 1.08 (0.76–1.51) 
Other 185 14.2 1.30 (1.12–1.50) 1.26 (1.09–1.46) 

Abbreviation: CI, confidence interval.

aModel 1 was adjusted for sex, age, calendar period, region of residence, and type of cancer. The effect of type of cancer was allowed to vary over time (nonproportional hazards), and the effects of other covariates were assumed to be time-fixed (proportional hazards) in all analyses.

bModel 2 was adjusted for sex, age, calendar period, marital status, educational level, region of residence, type of cancer, cancer stage, infection history, and Charlson Comorbidity Index score. The effect of type of cancer was allowed to vary over time (nonproportional hazards), and the effects of other covariates were assumed to be time-fixed (proportional hazards) in all analyses.

On the basis of a large national cohort, we found that preexisting psychiatric disorders before cancer diagnosis were associated with a higher subsequent rate of sepsis among patients with cancer. Such an association was noted immediately after cancer diagnosis and persisted up to nine years after cancer diagnosis. The association did not differ greatly by sex, calendar period, region of residence, educational level, infection history, or Charlson Comorbidity Index score, but was slightly stronger among patients diagnosed at younger age, non-cohabitating patients, and patients with a lower stage cancer.

Sepsis is a common complication among patients with cancer due to immunosuppression caused by intensive cancer treatment, the hospital setting, or factors associated with the underlying malignancy itself (26). Sepsis is known to be associated with longer hospital stay and higher medical cost (26). Despite intensive care, sepsis further leads to higher mortality among patients with cancer (26, 27). Psychiatric disorders are also common concomitants of cancer (4) and have been suggested to play a significant role in somatic illnesses, including severe infections and sepsis (5–7, 13, 14). The potential role of psychiatric disorders on sepsis among patients with cancer has however rarely been investigated. Our results provide therefore new knowledge to substantiate an elevated risk of sepsis in relation to psychiatric disorders among patients with cancer, a high-risk population for sepsis. Such knowledge could provide evidence for early prevention and intervention for vulnerable individuals, and subsequently improve prognosis of patients with cancer and optimize the use of medical resources. In this study, we focused on psychiatric disorders before cancer diagnosis as the exposure. However, increased risk of newly onset psychiatric disorders after cancer diagnosis has also been reported. Whether and how postcancer psychiatric disorders influence the risk of sepsis among patients with cancer remains therefore to be examined, taking into full consideration of cancer treatment and progression.

A link between psychiatric disorders and sepsis is plausible. One potential pathway is psychological distress, which is a known correlate of psychiatric disorders and modulates immune responses through the hypothalamic–pituitary–adrenal axis and sympathetic nervous system (9, 10). Mounting in vivo and in vitro evidence has supported that psychologic distress downregulates immune responses by suppressing antibody production and inhibiting T-cell responses (28, 29). Recent studies also indicated that psychological distress stimulates systemic low-grade inflammation by elevating plasma levels of IL6 and C-reactive protein (30, 31). Another potential pathway is the inequalities to health care among patients with psychiatric disorders in general, compared to individuals without such disorders. For instance, patients with psychiatric disorders tend to have less healthcare access in general, despite greater access to psychiatric care (6, 11). Delayed diagnosis and treatment for infections might therefore have contributed to the increased risk of sepsis among cancer patients with psychiatric comorbidities. Similarly, a lower degree of compliance to medical treatment among patients with psychiatric disorders (6, 11) might be an additional explanation. Finally, the noted association might also be attributable to differential behavioral factors between patients with and without psychiatric disorders. For instance, patients with substance abuse are more likely to experience infections through unsafe injection and sexual risk behaviors (12).

There was an increased risk of sepsis in relation to precancer psychiatric disorders among patients with most cancer types but not hematologic malignancy or non-melanoma skin cancer. The different results might be attributable to the different underlying diseases and their treatments. For instance, prophylactic use of antibiotics among patients with hematologic malignancy, who are highly susceptible to infections, might have contributed to the null association. The lack of association among patients with non-melanoma skin cancer might on the other hand be due to the general low likelihood of systemic treatment in this patient group.

A major strength of our study is the nationwide cohort design with large sample size and long and complete follow-up. Together with the prospectively and independently collected information on psychiatric disorders and sepsis, these strengths greatly reduced concerns about selection and information biases. The possibility to adjust for a handful of potential confounders was another strength of the study.

Our study also has limitations. One limitation of this study is the lack of information on cancer treatment. Cancer treatment, including surgery, chemotherapy, and radiotherapy, is generally invasive or intensive, and could increase the risk of sepsis through potential pathogen contamination or immunosuppression. Lack of treatment information therefore prevented us from assessing the role of specific cancer treatment on the association between precancer psychiatric disorders and sepsis. Because patients with cancer with psychiatric disorders might be more likely to receive less invasive and intensive treatment compared with cancer patients without psychiatric disorders (32), the noted association could have been an underestimate of the real association because of the possible lower rate of treatment-related sepsis among the exposed group. Another limitation of this study is the lack of data on lifestyle factors (e.g., smoking, nutrition, physical activity) that may also impact risk of sepsis, because individuals with psychiatric disorders have generally more unhealthy lifestyles compared to individuals without such disorders (33). Similar results observed among patients with different Charlson Comorbidity Index scores, which could be regarded as a proxy of overall health status, might partly alleviate such concern.

In conclusion, preexisting psychiatric disorders before cancer diagnosis were associated with an increased risk of sepsis among cancer patients. Our findings call for extended prevention and surveillance of sepsis among cancer patients with psychiatric comorbidities.

Q. Liu reports grants from Chinese Scholarship Council during the conduct of the study. T.M.-L. Andersson is involved in an ongoing public-private real-world evidence collaboration between Karolinska Institutet and Janssen Pharmaceuticals, however, the current project is not related to this collaboration. F. Fang reports grants from Swedish Cancer Society, grants from Swedish Research Council for Health, Working Life and Welfare, and grants from Karolinska Institutet during the conduct of the study. No potential conflicts of interest were disclosed by the other authors.

Q. Liu: Conceptualization, formal analysis, methodology, writing-original draft, writing-review and editing. H. Song: Conceptualization, methodology, writing-review and editing. T.M.-L. Andersson: Conceptualization, formal analysis, supervision, methodology, writing-review and editing. P.K.E. Magnusson: Supervision, writing-review and editing. J. Zhu: Methodology, writing-review and editing. K.E. Smedby: Conceptualization, resources, supervision, methodology, writing-review and editing. F. Fang: Conceptualization, supervision, funding acquisition, methodology, writing-review and editing.

This study was supported by the Swedish Cancer Society (no. CAN 2017/322), the Swedish Research Council for Health, Working Life and Welfare (no. 2017-00531), the China Scholarship Council (no. 201700260291), and the Karolinska Institutet (Senior Researcher Award and Strategic Research Area in Epidemiology).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Danai
PA
,
Moss
M
,
Mannino
DM
,
Martin
GS
. 
The epidemiology of sepsis in patients with malignancy
.
Chest
2006
;
129
:
1432
40
.
2.
Moore
JX
,
Akinyemiju
T
,
Bartolucci
A
,
Wang
HE
,
Waterbor
J
,
Griffin
R
. 
A prospective study of cancer survivors and risk of sepsis within the REGARDS cohort
.
Cancer Epidemiol
2018
;
55
:
30
8
.
3.
Angus
DC
,
Linde-Zwirble
WT
,
Lidicker
J
,
Clermont
G
,
Carcillo
J
,
Pinsky
MR
. 
Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care
.
Crit Care Med
2001
;
29
:
1303
10
.
4.
Mitchell
AJ
,
Chan
M
,
Bhatti
H
,
Halton
M
,
Grassi
L
,
Johansen
C
, et al
Prevalence of depression, anxiety, and adjustment disorder in oncological, haematological, and palliative-care settings: a meta-analysis of 94 interview-based studies
.
Lancet Oncol
2011
;
12
:
160
74
.
5.
M
DEH
,
Correll
CU
,
Bobes
J
,
Cetkovich-Bakmas
M
,
Cohen
D
,
Asai
I
, et al
Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care
.
World Psychiatry J
2011
;
10
:
52
77
.
6.
De Hert
M
,
Cohen
D
,
Bobes
J
,
Cetkovich-Bakmas
M
,
Leucht
S
,
Ndetei
DM
, et al
Physical illness in patients with severe mental disorders. II. Barriers to care, monitoring and treatment guidelines, plus recommendations at the system and individual level
.
World Psychiatry
2011
;
10
:
138
51
.
7.
IN
O
,
Hoegh
C
,
Eien
N
,
Bi
N
,
I
M
. 
Comorbidity of physical disorders among patients with severe mental illness with and without substance use disorders: a systematic review and meta-analysis
.
J Dual Diagn
2019
;
15
:
192
206
.
8.
Tost
H
,
Champagne
FA
,
Meyer-Lindenberg
A
. 
Environmental influence in the brain, human welfare and mental health
.
Nat Neurosci
2015
;
18
:
1421
31
.
9.
Glaser
R
,
Kiecolt-Glaser
JK
. 
Stress-induced immune dysfunction: implications for health
.
Nat Rev Immunol
2005
;
5
:
243
51
.
10.
Dhabhar
FS
. 
Effects of stress on immune function: the good, the bad, and the beautiful
.
Immunol Res
2014
;
58
:
193
210
.
11.
Lawrence
D
,
Kisely
S
. 
Inequalities in healthcare provision for people with severe mental illness
.
J Psychopharmacol
2010
;
24
:
61
8
.
12.
Thepthien
B
,
Altaf
L
,
Chuchareon
P
,
Srivanichakron
S
. 
Substance abuse in early adolescents and HIV preventive behaviors: findings from a school-based cross-sectional survey for the period from 2009 to 2013, Bangkok Thailand
.
AIDS Care
2016
;
28
:
1327
31
.
13.
Andersson
NW
,
Goodwin
RD
,
Okkels
N
,
Gustafsson
LN
,
Taha
F
,
Cole
SW
, et al
Depression and the risk of severe infections: prospective analyses on a nationwide representative sample
.
Int J Epidemiol
2016
;
45
:
131
9
.
14.
Song
H
,
Fall
K
,
Fang
F
,
Erlendsdóttir
H
,
Lu
D
,
Mataix-Cols
D
, et al
Stress related disorders and subsequent risk of life threatening infections: population based sibling controlled cohort study
.
BMJ
2019
;
367
:
l5784
.
15.
Fang
F
,
Chen
H
,
Wirdefeldt
K
,
Ronnevi
LO
,
Al-Chalabi
A
,
Peters
TL
, et al
Infection of the central nervous system, sepsis and amyotrophic lateral sclerosis
.
PLoS One
2011
;
6
:
e29749
.
16.
Fang
F
,
Wirdefeldt
K
,
Jacks
A
,
Kamel
F
,
Ye
W
,
Chen
H
. 
CNS infections, sepsis and risk of Parkinson's disease
.
Int J Epidemiol
2012
;
41
:
1042
9
.
17.
Charlson
ME
,
Pompei
P
,
Ales
KL
,
MacKenzie
CR
. 
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation
.
J Chronic Dis
1987
;
40
:
373
83
.
18.
Zhu
J
,
Sjolander
A
,
Fall
K
,
Valdimarsdottir
U
,
Fang
F
. 
Mental disorders around cancer diagnosis and increased hospital admission rate - a nationwide cohort study of Swedish cancer patients
.
BMC Cancer
2018
;
18
:
322
.
19.
Zhu
J
,
Fang
F
,
Sjolander
A
,
Fall
K
,
Adami
HO
,
Valdimarsdottir
U
. 
First-onset mental disorders after cancer diagnosis and cancer-specific mortality: a nationwide cohort study
.
Ann Oncol
2017
;
28
:
1964
9
.
20.
ENCR RECOMMENDATIONS: Condensed TNM for Coding the Extent of Disease
; 
2002
. Available at: https://www.encr.eu/sites/default/files/pdf/extentofdisease.pdf.
21.
Brand
JS
,
Colzani
E
,
Johansson
ALV
,
Giesecke
J
,
Clements
M
,
Bergh
J
, et al
Infection-related hospitalizations in breast cancer patients: Risk and impact on prognosis
.
J Infect
2016
;
72
:
650
8
.
22.
Sorup
S
,
Villumsen
M
,
Ravn
H
,
Benn
CS
,
Sørensen
TIA
,
Aaby
P
, et al
Smallpox vaccination and all-cause infectious disease hospitalization: a Danish register-based cohort study
.
Int J Epidemiol
2011
;
40
:
955
63
.
23.
Lu
D
,
Andersson
TM
,
Fall
K
,
Hultman
CM
,
Czene
K
,
Valdimarsdóttir
U
, et al
Clinical diagnosis of mental disorders immediately before and after cancer diagnosis: a nationwide matched cohort study in Sweden
.
JAMA Oncol
2016
;
2
:
1188
96
.
24.
Brett
J
,
Bankhead
C
,
Henderson
B
,
Watson
E
,
Austoker
J
. 
The psychological impact of mammographic screening. A systematic review
.
Psychooncology
2005
;
14
:
917
38
.
25.
Walker
AK
,
Chang
A
,
Ziegler
AI
,
Dhillon
HM
,
Vardy
JL
,
Sloan
EK
. 
Low dose aspirin blocks breast cancer-induced cognitive impairment in mice
.
PLoS One
2018
;
13
:
e0208593
.
26.
Williams
MD
,
Braun
LA
,
Cooper
LM
,
Johnston
J
,
Weiss
RV
,
Qualy
RL
, et al
Hospitalized cancer patients with severe sepsis: analysis of incidence, mortality, and associated costs of care
.
Crit Care
2004
;
8
:
R291
8
.
27.
Abou Dagher
G
,
El Khuri
C
,
Chehadeh
AA
,
Chami
A
,
Bachir
R
,
Zebian
D
, et al
Are patients with cancer with sepsis and bacteraemia at a higher risk of mortality? A retrospective chart review of patients presenting to a tertiary care centre in Lebanon
.
BMJ Open
2017
;
7
:
e013502
.
28.
Rabin
BS
.
Stress, immune function, and health: the connection
.
New York, NY
:
Wiley-Liss & Sons Inc
; 
1999
.
29.
Glaser
R
,
Rabin
B
,
Chesney
M
,
Cohen
S
,
Natelson
B
. 
Stress-induced immunomodulation: implications for infectious diseases?
JAMA
1999
;
281
:
2268
70
.
30.
Rohleder
N
. 
Stimulation of systemic low-grade inflammation by psychosocial stress
.
Psychosom Med
2014
;
76
:
181
9
.
31.
Gouin
JP
,
Glaser
R
,
Malarkey
WB
,
Beversdorf
D
,
Kiecolt-Glaser
J
. 
Chronic stress, daily stressors, and circulating inflammatory markers
.
Health Psychol
2012
;
31
:
264
8
.
32.
Wasterlid
T
,
Mohammadi
M
,
Smedby
KE
,
Glimelius
I
,
Jerkeman
M
,
Bottai
M
, et al
Impact of comorbidity on disease characteristics, treatment intent and outcome in diffuse large B-cell lymphoma: a Swedish lymphoma register study
.
J Intern Med
2019
;
285
:
455
68
.
33.
Penninx
BW
,
Milaneschi
Y
,
Lamers
F
,
Vogelzangs
N
. 
Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile
.
BMC Med
2013
;
11
:
129
.