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. Author manuscript; available in PMC: 2020 Nov 1.
Published in final edited form as: Brain Behav Immun. 2020 Aug 11;90:167–173. doi: 10.1016/j.bbi.2020.08.006

Early childhood adversity in adult patients with metastatic lung cancer: Cross-sectional analysis of symptom burden and inflammation

Daniel C McFarland a,*, Christian Nelson a, Andrew H Miller b
PMCID: PMC7544656  NIHMSID: NIHMS1622671  PMID: 32791210

Abstract

Objective:

Psychological and physical symptoms commonly occur in patients with metastatic lung cancer and are associated with reduced quality of life and decreased survival. Previous work has associated these symptoms with inflammation. The experience of Early Childhood Adversity (ECA) is linked to chronic inflammation and may identify adult cancer patients who are at-risk for psychological and physical symptoms. We thus hypothesized that ECA in lung cancer patients would be associated with increased psychological symptoms (distress, anxiety, and depression) and physical symptoms and that this relationship would be explained by inflammation.

Methods:

Patients with metastatic lung cancer (n = 92) were evaluated for ECA using the Risky Families Questionnaire. Concomitant assessments were made of distress (Distress Thermometer and Problem List [DT&PL]), anxiety (Generalized Anxiety Disorder-7), depression (Patient Hospital Questionniare-9), physical symptoms (DT&PL), and inflammation (C-reactive protein [CRP]). Multivariate models were created to explain associations of ECA with depression, anxiety, distress, number of physical problems, and inflammation.

Results:

ECA was associated with distress (r = 0.24, p = .03), anxiety (r = 0.30, p = .004), depression (r = 0.35, p = .001), greater physical problems (r = 0.25, p = .03), younger age (r = −0.29, p = .006), and elevated CRP (r = 0.22, p = .04). Multivariate analyses of outcomes found that depression severity was independently explained by both ECA and inflammation (β = 0.37, p = .001) but not distress or anxiety, while controlling for age and sex. Number of physical problems were also associated with ECA (β = 0.35, p = .004) but not inflammation. The association between ECA and physical problems was not significant after controlling for depression.

Conclusion:

ECA is associated with increased depression and physical symptoms independent of inflammation. Moreover, depression appears to mediate the impact of ECA on physical symptoms. ECA may identify patients at risk for psychological and physical symptoms.

1. Introduction

The prevalence of depression, distress, and anxiety in patients with lung cancer is significant and considered to be among the highest in comparison to other cancer subtypes (Walker et al., 2014). In addition, patients with lung cancer experience high rates of physical symptoms that are associated with psychological symptoms (McFarland et al., 2020). Depression may also contribute to worsened overall survival in patients with cancer and in lung cancer patients in particular (Sullivan et al., 2016; Pinquart and Duberstein, 2010). Depression is also more prominent in advanced disease and the majority of lung cancer is advanced (Grotmol et al., 2018).

We previously reported an association between inflammation as measured by C-reactive protein (CRP) and symptom burden (psychological and physical) experienced by patients with metastatic lung cancer (McFarland et al., 2020, 2019). Associations between inflammation and depression are similarly reported in patients with various cancer types (e.g., breast, lung, gastrointestinal, gynecologic, hematologic) (Jehn et al., 2012; Du et al., 2013; Steel et al., 2007; Breitbart et al., 2014; Lutgendorf et al., 2008; Loh et al., 2020) and in various stages (e.g., early localized versus advanced metastatic) (Jehn et al., 2012; Pertl et al., 2013) and settings (e.g., receiving radiation, systemic treatments, or prior to surgery) (McFarland et al., 2019; Xu et al., 2016; Bower et al., 2009). These findings have been replicated in medically healthy patients and also have bearing on depression treatment effects (Strawbridge et al., 2015; Valkanova et al., 2013). This relationship between inflammation and depression is highly applicable to patients with cancer since rates of co-morbid physical and psychological symptom burden are high and inflammation has been termed the seventh hallmark of cancer (Colotta et al., 2009).

Patients with lung cancer have multiple reasons for increased inflammation which may include smoking, obesity, and medical comorbidities in addition to cancer and its treatments (O’Connor et al., 2009). These factors may help explain some of the variability in physical and psychological symptom burden related to inflammation among patients lung cancer. An additional and important source of chronic inflammation and its long term effects may be Early Childhood Adversity (ECA).

ECA has been characterized by marked elevation in chronic Inflammation represented by CRP, interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in adult survivors of childhood abuse (Kiecolt-Glaser et al., 2011; Fagundes et al., 2013). Along with inflammatory markers, ECA in adults is associated with psychological processes such as chronic stress, poor coping, and behaviors such as alcohol and tobacco use, which may also increase inflammation. There is a graded relationship between ECA and risky behaviors, substance abuse, smoking, smoking-related illness such as COPD, and risk of cancer and specifically lung cancer in adulthood (Cronholm et al., 2015; Anda et al., 2008; Brown et al., 2010; Holman et al., 2016). In addition to cancers, adults who experienced abuse, neglect, or traumatic environments as children are also more likely to develop psychiatric disorders (Nanni et al., 2012). Indeed, ECA or maltreatment is a particularly potent risk factor for depression in adults and may be especially potent when individuals encounter stressful life events, such as cancer (Slavich and Irwin, 2014). Importantly, ECA is associated with greater episodes of recurrent and treatment-resistant depression (Akil et al., 2018). However, the relationship between ECA and anxiety or depression may be related to the same chronic inflammation that appears to be associated with ECA and mood symptoms throughout adulthood (Witek Janusek et al., 2013; Young et al., 1997). This may have particular relevance for patients with lung cancer who are particularly prone to chronic inflammatory states even independently of mood symptoms (Jafri et al., 2013).

Thus, behavioral consequences of ECA appear to be mediated by higher levels of chronic inflammation as an adult. The same inflammatory markers (e.g., IL-6, TNF-α, and CRP) that are increased in patients with ECA20, (Fagundes et al., 2013), are similarly elevated in patients with lung cancer and depression (McFarland et al., 2019; Du et al., 2013). But, the effects of ECA in adulthood are far reaching and likely affect physical symptoms given their close relationship with psychological symptom burden (Hughes et al., 2017). That is, ECA may be associated with physical symptoms experienced by patients with lung cancer who are undergoing various systemic treatments and may be dealing with psychological symptoms. Our group previously found that the number of endorsed physical problems was linked to the presence of ECA in other cancer populations (McFarland et al., 2016, 2017). A multitude of physical symptoms are highly prevalent in patients with advanced disease and lung cancer (LeBlanc et al., 2015). The presence and refractoriness of these symptoms increases in patients with depression (Fitzgerald et al., 2015). Therefore, this study also evaluated the presence of physical symptoms and their relationship with psychological issues and ECA.

The presence of physical and psychological symptoms in cancer settings is associated with reduced survival in addition to poor quality of life (Pinquart and Duberstein, 2010). In fact, the survival implications of depression are most severe in patients with early localized and curable lung cancer (Sullivan et al., 2016). In addition, pro-actively addressing physical symptoms (by screening instead of waiting for the patient to present with symptoms) has been associated with improved survival (Basch et al., 2017). Similarly, remission of depression in patients with lung cancer is associated with survival rates that are similar to patients who were not ever depressed during their cancer trajectory (Sullivan et al., 2016). Early detection and treatment of symptoms appears to have significant benefit in patients with cancer, which may be facilitated by the identification of ECA.

The relationship between ECA and symptom burden (psychological and physical) in patients with lung cancer has not been reported previously. We hypothesized that patients with lung cancer who experienced ECA would report higher psychological and physical symptom burden. We also hypothesized that inflammation would explain these relationships given documented associations between inflammation and ECA in addition to the relationship between inflammation and psychological and physical symptoms. This study evaluated the presence of ECA in patients with metastatic lung cancer along with inflammation, psychological symptoms (distress, anxiety, and depression), and physical symptoms.

2. Methods and materials

2.1. Study design

This study utilized a cross-sectional observational design. Convenience sampling was used to obtain sufficient data for adequate analysis of key variables. Surveys and lab values were collected from patients from May to November 2017 as part of standard clinical practice. The Memorial Sloan Kettering Cancer Center Institutional Review Board (IRB) approved this study as a retrospective analysis. The data that support the findings of this study are available from the corresponding author upon reasonable request.

2.2. Participants

Men and women with histologically confirmed stage IV NSCLC who were undergoing active treatment, spoke English, and had a performance status of Eastern Cooperative Group (ECOG) performance status less than or equal to 2 were included (Oken et al., 1982). Patients with other cancers or not undergoing treatment for their metastatic lung cancer were excluded. Patients had to be on active treatment for at least one month and had to be more than one month from receiving the diagnosis of lung cancer to be included.

2.3. Procedure

Patients filled out the questionnaire containing standardized survey questions and laboratory values (CRP) were obtained the same day that the questionnaires were completed. Patients were given questionnaires during medical oncology visits and encouraged to fill them out by themselves without the help of family members. The questionnaires were filled out using pen and paper and collected by medical oncology staff. Data were entered into a secured database and analyzed at a later date. Available psychological services were provided in the survey, and patients were asked to raise any concerns with clinic staff and, in particular, to tell a staff member if they felt significantly depressed or had suicidal ideation. Delivery of questionnaires did not result in utilization of psychological/psychiatric resources.

2.4. Measures

2.4.1. Patient demographic and medical characteristics

Patient demographic information was obtained from the electronic health record and included age, race/ethnicity, sex, marital status, body mass index (BMI), length of time since diagnosis, type of treatment (e.g., chemotherapy, immunotherapy, targeted therapy), line of treatment (i.e., 1st, 2nd, 3rd or beyond), and whether they were taking an antidepressant medication. A CRP value was obtained by turbidimetric immunoassay in a Clinical Laboratory Improvement Amendments (CLIA) certified lab (Pineiro et al., 2018). This is a reliable immunoassay for serum CRP that involves a potent antibody. Inter- and intra-assay coefficient of variation is reliably less than 5%.

2.4.2. Early childhood adversity

The Risky Families Questionnaire (RFQ) is a measure of ECA that captures elements of abuse, neglect, and chaotic home environment. Its measures have been correlated with inflammatory markers that are also correlated with depression and anxiety in the cancer context (Crosswell et al., 2014; Danese et al., 2007; Taylor et al., 2004). It is a 13 item Likert scale questionnaire designed to calculate risk of anxiety, depression, and suicide as well as aggression conduct disorder, delinquency, and antisocial behavior given early life chaotic home environments (Taylor et al., 2004; Repetti et al., 2002). It contains 13 questions scored from 1 to 5 so that the minimum score is 13 and the maximum score is 65. The questions were anchored by “Not at All” and “Very Often”. There are no accepted cut-points. Participants are asked to think over their family life from age 5 to 15 years and answer the questions. The RFQ contains three subscales as defined by Crosswell and colleagues: 1) Abuse (2 questions, e.g., “How often did a parent or other adult in the household swear at you, insult you, put you down, or act in a way that made you feel threatened?”), Neglect (3 questions, e.g., “How often did a parent or other adult in the household make you feel that you were loved, supported, and cared for?” [reverse coded]), and Chaotic Home Environment (4 questions, “In your childhood, did you live with anyone who was a problem drinker or alcoholic, or who used street drugs?”) (Crosswell et al., 2014). The RFQ has demonstrated internal validity and has been used to predict behavioral symptoms in the setting of increased inflammation (Bower et al., 2011). In our current sample, Cronbach’s alpha was measured at 0.78.

2.4.3. Distress

The Distress Thermometer and Problem List (DT&PL) is a one item measurement that ranges from 0 to 10 and is recommended by the National Comprehensive Cancer Network to screen for psychological distress in order to meet their distress screening guidelines and the Commission on Cancer distress screening mandate (Pirl et al., 2014). A cut-off of > 4 has been accepted by the NCCN to indicate clinically meaningful distress (Holland and Bultz, 2007). The Distress Thermometer has shown strong discriminatory power relative to depression with an area under the curve of 0.87. Similar operating characteristics were seen with variations in age, education, marital status, and stage of disease. A score of 7 was found to be an optimal trade-off between sensitivity (0.81) and specificity (0.85) characteristics for detecting depression, but a cut-off of ≥4 is still recommended by the NCCN and was therefore considered most appropriate in this study (Hegel et al., 2008). There is an accompanying problem list subscale that summates practical, family, emotional, spiritual, and physical issues and is used primarily for clinical purposes but has also been evaluated in the research setting previously (Lester et al., 2015; McFarland et al., 2018a, 2018b, 2018c).

2.4.4. Anxiety

The Generalized Anxiety Disorder-7 (GAD-7) is a seven item measure that scores each question from 0 to 3 for a range of scores from 0 to 21, with higher scores indicating greater anxiety (Spitzer et al., 2006). The internal consistency of the GAD-7 is excellent (Cronbach’s α = 0.92) with a good test-retest reliability (intra-class correlation = 0.83) (Spitzer et al., 2006). It has been evaluated for use as a screening tool for generalized anxiety disorder among cancer patients (Esser et al., 2018). Diagnostic accuracy was assessed against another anxiety screen in patients with cancer and found to have an identical AUC of 0.81 (95% CI: 0.79–0.82) (Esser et al., 2018). While various cut points have been used, a cutoff of ≥ 10 was used to identify cases of anxiety in this population as this cutoff score demonstrates sensitivity of 89% and specificity of 82% (Spitzer et al., 2006).

2.4.5. Depression

The Patient Health Questionnaire-9 (PHQ9) is a nine item measure that scores each question from 0 to 3 for a range of scores from 0 to 27 with higher scores indicating greater depressive symptoms (Kroenke et al., 2001). The diagnostic accuracy was found to be a sensitivity of 0.77 (0.71–0.84) and a specificity of 0.94 (0.90–0.97) for identifying depression (Wittkampf et al., 2007). Cutoff scores ranging from 8 to 11 have demonstrated validity and a lower cutoff score of ≥ 8 may perform well in the cancer setting (Thekkumpurath et al., 2011). However, we used a cutoff of ≥10 to identify cases of depression as this criteria is more commonly used among various populations (Manea et al., 2012). Depression severity using the PHQ9 has been graded as mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27).

2.4.6. Physical problems

The Physical Problem List (PPL) subscale of the DT&PL contains 22 items or physical problems that are answered dichotomously (present/absent) for a range of scores from 0 to 22. Some examples include problems with Appearance, Bathing/dressing, Breathing, Changes in Urination, Constipation, Diarrhea, etc. It has been evaluated prospectively in several cancer settings (McFarland et al., 2018a, 2018b; Robbeson et al., 2018). The PPL forms one part of the Problem List of the DT&PL-the other categories are Practical, Familial, Emotional, and Spiritual problems. Patients endorsed whether a physical symptom had been a problem for them over the past week using the PPL on the DT&PL. The DT&PL has been used widely by cancer institutions to meet the Commission on Cancer distress-screening mandate for accreditation in 2015 (Pirl et al., 2014; Bower et al., 2014).

2.5. Statistical analysis

Descriptive statistics were used to analyze sample demographic and clinical characteristics. Pearson correlation coefficients were used for normally distributed variables and Spearman rank correlations were used for non-normally distributed variables. Independent samples t-tests and analysis of variance (ANOVA) were used to test differences between categorical independent variables and continuous dependent variables. CRP was log transformed in order to correct skewness from 3.750 (SE 0.26) to 0.279 and kurtosis from 16.169 (SE 0.51) to −0.443. Primary analysis of ECA used non-transformed ordinal scale values. We performed regression analyses with ECA as an independent variable and psychological variables (distress, anxiety, and depression) as dependent variables and covariates CRP (logarithmic-transformed) and physical symptoms. Hierarchical linear regression models were built to compare the variance of depression (dependent variable) with the addition of covariates (CRP & physical symptoms). Interaction terms were created between ECA and two covariates-CRP and physical symptoms. Statistical procedures were performed using the SPSS version 24 software (SPSS, Chicago, IL 2013), and all statistical tests were two-tailed with a 5% significance level.

3. Results

Questionnaires were given to 120 patients and returned by 92 patients (76% response rate). Sample characteristics are presented in Table 1. The average age was 65.4 years old and the majority of the patients were female (67%), white (87%), and married/partnered (69%). Most patients had adenocarcinoma of the lung (71%) followed by SCLC (15%), Squamous Cell CA (7.5%) and Not Otherwise Specified (5%). Patients were receiving chemotherapy (40%), immunotherapy (35%), or targeted therapies (23%). The majority were receiving first line treatment (59%) followed by 2nd line (26%) and 3rd line treatment or beyond (14%).

Table 1.

Clinical and demographic characteristics of the cohort.

Total (n = 92)
M (SD)
Age (years) 65.4 (9.2)
Body Mass Index 26.1 (5.3)
Time with Disease (months) 14.7 (14.3)
Early Childhood Adversity (RFQ) (13–65) 23.9 (9.3)
 •Abuse (RFQ) (2–10) 3.2 (2.0)†
 •Neglect (RFQ) (3–15) 5.6 (2.8)†
 •Chaotic Environment (RFQ) (4–20) 7.0 (3.4)†
C Reactive Protein (mg/L) 1.37 (2.5)
Distress Score (DT&PL) (0–10) 3.68 (2.9)
Anxiety (GAD7) (0–21) 3.62 (4.3)
Depression Score (PHQ9) (0–27) 6.0 (4.9)
Physical Problem Symptoms DT&PL (0–22) 4.7 (3.6)
Meets Criteria Screen N (%)
Distress (DT&PL ≥ 4): Yes 30 (38%)
No 48 (61%)
Anxiety (GAD7 ≥ 10): 12 (13%)
  •Yes
 •No 78 (86%)
Depression (PHQ9 ≥ 10): 25 (27%)
  •Yes
 •No 67 (72%)
Gender
 •Female 63 (67%)
 •Male 29 (31%)
Disease Type
Adenocarcinoma 66 (71%)
Squamous 7 (7%)
SCLC 14 (15%)
NOS 5 (5%)
Treatment Type
 •Chemotherapy 34 (40%)
 •Immunotherapy 30 (35%)
 •Targeted Therapy 20 (23%)
 •Missing 9 (9%)
Line of Treatment
 •1st 49 (59%)
 •2nd 22 (26%)
 •3rd or beyond 12 (14%)
 •Missing 10 (10%)
Race/Ethnicity
 •White 79 (85%)
 •Black 7 (7%)
 •Latino 5 (5%)
 •Asian 1 (1%)
Married
 •Yes 64 (69%)
 •No 28 (30%)
Antidepressant
 •Yes 20 (23%)
 •No 73 (77%)
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Note:

*

p < .05

**

p < .01

***

p < .001;

†,

RFQ subscales do not add up to total; DT&PL, Distress Thermometer and Problem List; GAD-7, Generalized Anxiety Disorder 7 item; NOS, Not Otherwise Specified; PHQ-9, Patient Health Questionnaire 9 item; SCLC, Small Cell Lung Cancer

The RFQ subscales measure three distinct areas of ECA: abuse, neglect, and chaotic home environment. Average RFQ score was 23.9 (SD 9.3) and included Abuse 3.2 (SD 2.0), Neglect 5.6 (SD 2.8), and Chaotic Home Environment 7.0 (SD 3.4). The average CRP was 1.37 mg/ml (SD 2.5) and patients reported an average of 4.7 (SD 3.6) physical symptom problems. Screening criteria were met by 30% for distress (DT&PL ≥ 4), 13% for anxiety (GAD7 ≥ 10), and 27% for depression (PHQ9 ≥ 10).

ECA correlated with younger age (r = −0.29, p = .006), higher levels of distress (r = 0.24, p = .03), anxiety (r = 0.30, p = .004), and depression (r = 0.37, p = .001), along with a greater number of physical problems (r = 0.25, p = .03) and elevated CRP (r = 0.22, p = .04) (Table 2). Antidepressant use was associated with higher ECA (27.6 versus 22.9) (t = 2.027, p = .05).

Table 2.

Univariate analyses of clinical and demographic information and their associations with ECA and ECA subscales (Abuse, Neglect, and Chaotic Home Environment).

Early Childhood Adversity (RFQ)
Variable r p
Age −0.29 0.006**
CRP (log transformed) 0.24 0.03*
Distress (DT&PL) 0.24 0.03*
Anxiety (GAD7) 0.30 0.004**
Depression (PHQ9) 0.37 0.001*
Physical Problem List (DT&PL) 0.25 0.03*
F P
Disease Type 1.950 0.13
 •Adenocarcinoma
  •Squamous Cell
  •SCLC
  •NOS
Line of Treatment 0.466 0.71
 •1st
  •2nd
  •3rd and beyond
Treatment Type 0.866 0.42
 ••Chemotherapy
  •Immunotherapy
 Targeted therapy
t P
Sex −1.552 0.13
 •Female
  Male
Race 0.243 0.81
 •White n = 79
  Non-White n = 13
Married 1.934 0.06
 •Yes
  •No
 Antidepressant −2.027 0.05*
 •Yes
  •No
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Note:

*

p < .05

**

p < .01

***

p < .001:

BMI, Body Mass Index; CRP, C-reactive protein; DT&PL, Distress Thermometer and Problem List’ GAD7, Generalized Anxiety Disorder-7; PHQ-9, Patient Health Questionnaire-9.

Of note, receipt of chemotherapy, as opposed to other anticancer treatments, was associated with both depression (F = 5.425, p = .006) and inflammation (F = 9.332, p < .001). Treatments did not significantly affect the number of physical symptoms endorsed.

Multivariate models were created for distress, anxiety, depression, and number of physical symptoms. Depression was explained by ECA (β = 0.37, p < .001) and CRP (β = 0.30, p = 004) while controlling for age and sex (adjusted R2 0.192, p < .001) (Table 3). This model explained 19% of depression variance. Number of physical problems was explained by ECA (β = 0.35, p = .004) in addition to older age (β = 0.26, p = .03) and female sex (β = −0.22, p = .04) (adjusted R2 0.124, p = .007). However, the multivariate models for anxiety and distress were not significant (adjusted R2 0.005, p = .36; adjusted R2 0.063, p = .07, respectively).

Table 3.

Multivariate analysis of depression, anxiety, distress, and number of endorsed physical problems explained by early childhood adversity (measured by the Risky Families Questionnaire) and covariate inflammation (C-reactive protein) while controlling for age and sex.

Depression (PHQ-9)
 Anxiety (GAD-7)
 Distress (DT&PL)
 Physical Symptoms (DT&PL)
Variable Regression Coefficient t value p Regress Coefficient t value p Regression Coefficient t value p Regression Coefficient t value P
Control
Age 0.15 (0.06) 1.407 0.16 0.04 (0.05) 0.376 0.71 0.04 (0.04) 0.298 0.77 0.26 (0.01) 2.272 0.03*
Sex −0.14 (1.05) −1.393 0.16 −0.12 (1.03) −1.079 0.28 −0.30 (0.72) −2.577 0.01 −0.22 (0.23) −2.058 0.04*
Covariate
CRP (lg) 0.30 (0.82) 2.961 0.004** 0.12 (0.80) 1.029 0.31 0.16 (0.57) 1.403 0.17 0.16 (0.18) 1.434 0.16
IV
ECA (RFQ) 0.37 (0.06) 3.490 0.001** 0.18 (0.06) 1.486 0.14 0.18 (0.04) 1.400 0.17 0.35 (0.01) 2.966 0.004**
F 6.112 Adjusted R2 0.192, p < .001 F 1.099 Adjusted R2 0.005, p = .36 F 2.258 Adjusted R2 0.063, p = .07 F 3.825 Adjusted R2 0.124, p = .007
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Note:

*

p < .05

**

p < .01;

CRP, C-reactive protein; DT&PL, Distress Thermometer and Problem List; ECA, Early Childhood Adversity; GAD-7, Generalized Anxiety Disorder 7 item; IV, independent variable; PQH-9, Patient Health Questionnaire-9; RFQ, Risky Families Questionnaire.

The relationship between ECA and depression was still significant when controlled for inflammation (partial correlation r = 0.33, p = .002) and controlled for number of endorsed physical problems (partial correlation, r = 0.27, p = .04). The relationship between ECA and number of physical problems was still significant when controlled for inflammation (partial correlation r = 0.22, p = .05) but was no longer significant when controlled for depression (partial correlation r = 0.008, p = .94). The median number of physical problems was 3.0 (range 0–18) and the most commonly endorsed were fatigue (65%), sleep disturbance (37%), pain (32%), trouble breathing (31%), and itchy dry skin (30%). The relationship between ECA and inflammation is no longer significant when controlled for depression (partial correlation r = 0.10, p = .36).

4. Discussion

This study found that ECA was associated with increased depression and physical symptoms in the setting of metastatic lung cancer independently of inflammation. The primary driver of the associated consequences of ECA appears to be depression, which mediated the relationship between ECA and physical symptoms. This study adds an analysis of the contribution of ECA to the problematic symptom burden that patients experience after diagnosis and during treatment. Interest in early childhood adversity has brought about substantial evidence for its lasting effects into adulthood (Scott et al., 2011). In the cancer setting, most research has focused on ECA as a risk factor for developing cancer through behavioral and stress-related biological causes (Holman et al., 2016). A select few studies have evaluated ECA and its associations with cancer related symptoms once patients are diagnosed with cancer and undergoing treatment. Associations with depressive symptoms have also been noted in breast cancer and hematologic malignancy with elevated ECA (McFarland et al., 2016, 2017). Among cancer types, lung cancer has the highest incidence worldwide and results in abundant physical and psychological symptoms (LeBlanc et al., 2015; Siegel et al., 2019). Despite the effectiveness of patient reported outcomes incorporation into symptom management, psychiatric symptoms, such as depression, remain a challenge for clinicians to address adequately (Giuliani et al., 2016).

It is intriguing that anxiety and distress were not independently associated with ECA as seen in other settings (Witek Janusek et al., 2013). A similar surprise was that ECA was not significantly associated with inflammation or number of physical problems after controlling for depression. This suggests that relationships between ECA and anxiety, distress, or inflammation may be mediated by depression. However, it is possible that independent relationships between these variables may have been obscured by the setting of metastatic lung cancer since levels of inflammation and anxiety are elevated at baseline even when patients are not depressed. A larger study would be needed to verify this hypothesis.

The role of ECA and its association with depression in the lung cancer setting in particular deserves further study. Understanding this underlying association may help clarify the underlying biology of cancer –related depression. As well, incorporation of ECA may help consultant psychiatrists and oncologists identify their at-risk patients. This has particularly relevant implications for patients at diagnosis or shortly thereafter when the survival implications of concomitant depression appear to be most significant (Sullivan et al., 2016). At the same time, the suicide rate is particularly high for patients with lung cancer and especially shortly after diagnosis (Zaorsky et al., 2019). One of the greatest and most actionable risk factors for suicide prevention is early identification and implementation of depression management (Henson et al., 2019). However, it has become increasingly more apparent that a one-time screen for depression is not enough to change outcomes (Meijer et al., 2011; Carlson et al., 2012).

Many factors complicate the management of depression even after screening. These include convincing patients of the need to follow up, normalization of symptoms by family and even other healthcare workers, limited availability and expertise of psychosocial services in helping patients with cancer, and financial constraints, to name a few (Malowney et al., 2015; Funk et al., 2016). The presence of ECA may help indicate which patients with lung cancer are at high risk of developing significant physical and psychological symptoms such as depression during the course of their illness. Currently, both psychological and physical symptoms are under appreciated and under treated in cancer settings despite professional society mandates and guideline recommendations (Mei Hsien et al., 2012; Fallowfield et al., 2001). Oncologists tend to underestimate depression, may miss more covert signs of severe depression (e.g., cognitive aspects), and think that emotional functioning was discussed more often than what patients remember (Fagerlind et al., 2012; Passik et al., 1998). ECA may facilitate the prospective identification of high risk patients who are likely to develop significant psychological and physical symptoms as a result of ongoing cancer-related stressors. Consequently, the remediation of cancer related symptom burden (physical and psychological) has not only quality of life but potential survival implications (Sullivan et al., 2016; Basch et al., 2017). A serious limitation for medical services screening for depression is to identify a spectrum of depression severity so that special emphasis can be placed on the most at risk patients.

Anderson and colleagues describe a depression screening strategy where certain descriptive factors were more commonly associated with severe depression as measured by the Patient Health Questionnaire-9 (e.g., thoughts about cancer treatment futility, anxiety, hopelessness) (Andersen et al., 2019). Along similar lines, ECA could be used to enhance the identification of cancer patients at risk of heavy physical and psychological symptom burden before they become severe. Early identification of ECA may help risk stratify and provide more nuanced and compelling patient assessments than dichotomous depression screening scales, which have significant limitations (e.g., not cancer specific, overlap with physical symptoms, severity versus frequency of symptoms, and lack of functional assessments) (Zimmerman et al., 2018). This could help consultant psychiatrists and oncologists understand which patients are most likely to benefit from greater attention, follow up, and stronger recommendations. In support of this approach is that oncologist recommendation and attitude for psychological care predict greater utilization of mental health services (Frey Nascimento et al., 2019; Senf et al., 2019).

This study is limited by its cross-sectional design and control of potential covariates such as tobacco use and other significant medical co-morbidities. Smoking histories were not available for this analysis and may have introduced bias since smoking is a behavioral outcome of ECA and is also associated with depression (McFarland, 2020). Similarly, medical co-morbidity such as chronic pulmonary or heart disease are associated depression and may be the result of lifestyle factors related to ECA (Ostergaard et al., 2013). Another potential source of bias to consider is that patients with higher ECA may have died early and were therefore not accounted for in this study (mortality bias). Also, the study did not consider prior psychiatric history of depression, which also may have been associated with ECA. The study is observational in nature and therefore limits the conclusions can be drawn from it.

Lastly, ECA was higher in younger patients and lower in older patients. The effects of ECA in geriatric populations have been described and include poor psychosocial adjustment along with mood, anxiety, and personality disorders. In a large cohort of over 7,000 community dwelling individuals over 65 years old, age was not found to be moderator of ECA (Raposo et al., 2014; Wilson et al., 2006). In our study, it is possible that ECA was less low in older patients because those with elevated ECA had already succumbed to their disease and were missing from the cohort. Another explanation might be that greater resilience can be acquired with age and may moderate the effects of ECA over time (Gouin et al., 2017). ECA may have significantly different interactions in the cancer setting the nature of which would need to be assessed with a prospective cohort study starting at cancer diagnosis. Of note, our sample was younger than the average age of patients with lung cancer, which may reflect a referral center bias and the limitations of the study.

In summary, ECA may place patients with lung cancer at a higher risk of developing depression; thus, complicating lung cancer treatment, quality of life, and even survival outcomes (Sullivan et al., 2016). The identification of key risk factors for the development of depressive symptoms such as ECA may facilitate improved interdisciplinary management of cancer patients. These conclusions are preliminary but the current findings warrant future research in this area.

Acknowledgements

Funding: This research was supported by the NIH/NCI Cancer Center Support Grant [P30 CA008748] and the NIH Loan Repayment Program L30 CA220778.

Footnotes

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbi.2020.08.006.

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