Worse Depression Profiles Are Associated With Higher Symptom Burden and Poorer Quality of Life in Patients With Gynecologic Cancer

Patients and Settings

This study is part of a larger, longitudinal study of the symptom experience of oncology outpatients receiving chemotherapy that used the Theory of Symptom Management as its theoretical framework.¹⁷ Briefly, patients were ≥18 years of age; had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and provided written informed consent. Patients were recruited from two Comprehensive Cancer Centers, one Veteran’s Affairs hospital, and four community-based oncology programs during their first or second cycle of chemotherapy.

Study Procedures

Study was approved by the Institutional Review Board at each of the study sites. Of the 2234 patients approached, 1343 consented to participate. Patients were approached in the infusion unit during their first or second cycle of chemotherapy by a research nurse who explained the study procedures and obtained informed consent. The major reason for refusal was being overwhelmed by their cancer treatments. Patients completed the CES-D a total of six times over two chemotherapy cycles (i.e., prior to chemotherapy administration, approximately 1 week after chemotherapy administration, and approximately 2 weeks after chemotherapy administration). All of the other measures were completed at enrollment (i.e., prior to the second or third cycle of chemotherapy). For this analysis, data from patients with gynecological cancer (n = 231) who had complete data on the depression measure were evaluated.

Instruments

Other symptom measures

The 20 items on the Spielberger Trait-State Anxiety Inventories (STAI-T and STAI-S) were rated from 1 to 4.²⁴ The STAI-S measures a person’s temporary anxiety response to a specific situation or how anxious or tense a person is “right now” in a specific situation. The STAI-T measures a person’s predisposition to anxiety as part of one’s personality. Cutoff scores of ≥ 31.8 and ≥ 32.2 indicate high levels of trait and state anxiety, respectively. Cronbach’s alphas for the STAI-T and STAI-S were .92 and .96, respectively.

The 18-item Lee Fatigue Scale (LFS) was designed to assess physical fatigue and energy.²⁵ Each item was rated on a 0 to 10 numeric rating scale (NRS). Total fatigue and energy scores were calculated as the mean of the 13 fatigue items and the 5 energy items, respectively. Higher scores indicate greater fatigue severity and higher levels of energy. Using separate LFS questionnaires, patients were asked to rate each item based on how they felt within 30 minutes of awakening (i.e., morning fatigue, morning energy) and prior to going to bed (i.e., evening fatigue, evening energy). The LFS has established cut-off scores for clinically meaningful levels of fatigue (i.e., ≥3.2 for morning fatigue, ≥5.6 for evening fatigue) and energy (i.e., ≤6.2 for morning energy, ≤3.5 for evening energy).²⁶ Cronbach’s alphas were 0.96 for morning and 0.93 for evening fatigue and 0.95 for morning and 0.93 for evening energy.

The 21-item General Sleep Disturbance Scale (GSDS) was designed to assess various aspects of sleep disturbance. Each item was rated on a 0 (never) to 7 (everyday) NRS. The GSDS total score ranges from 0 (no disturbance) to 147 (extreme sleep disturbance).^27–29 A GSDS total score of 343 indicate a significant level of sleep disturbance that warrants clinical evaluation and management.²⁶ In this study, Cronbach’s alpha for the GSDS total score was 0.83.

The 16-item Attentional Function Index (i.e., AFI) was designed to assesses an individual’s perceived effectiveness in performing daily activities that are supported by attention, working memory, and executive functions (e.g., setting goals, planning and carrying out tasks). A higher total mean score on a 0 to 10 NRS indicates greater capacity to direct attention.³⁰ Clinically meaningful cutpoints for attentional function are as follows: <5.0 low function, 5.0 to 7.5 moderate function, >7.5 high function.³¹ Cronbach’s alpha for the AFI was 0.93.

Worst pain severity was assessed using the Brief Pain Inventory (BPI).³² Patients were asked to indicate whether they were generally bothered by pain (yes/no). Those who were bothered by pain noted if their pain was or was not associated with cancer. In addition, they rated worst pain severity in the past 24 hours using a 0 (no pain) to 10 (worst pain imaginable) numeric rating scale (NRS) and completed the pain interference score of the BPI.

Data Analysis

LPA was used to identify unobserved subgroups of patients (i.e., latent classes) with distinct depression profiles over the six assessments using the patients’ CES-D scores. LPA was performed using Mplus version 8.4.³⁵ Estimation was carried out with full information maximum likelihood with standard errors and a Chi square test that is robust to non-normality and non-independence of observations (“estimator=MLR”). Model fit was evaluated to identify the solution that best characterized the observed latent class structure with the Bayesian Information Criterion, Vuong-Lo-Mendell-Rubin likelihood ratio test, entropy, and latent class percentages that were large enough to be reliable.^35,36 Missing data were accommodated for with the use of the Expectation-Maximization algorithm.³⁷

All of the other data were analyzed using SPSS version 28 (IBM Corporation, Armonk, NY). Differences among the depression latent classes in demographic and clinical characteristics, symptom severity scores, and QOL outcomes at enrollment were evaluated using parametric (e.g., analysis of variance) and nonparametric (e.g., Kruskal Wallis) tests. Bonferroni corrected p-value of <.017 was considered statistically significant for the pairwise contrasts (i.e., .05/3 possible pairwise contrasts).

Latent profile analysis

As noted in Table 1, a three-class solution was selected based on the fit indices. Using the CES-D clinically meaningful cutoff score of ≥16,²³ as shown in Figure 1, the depression classes were labeled: “Low depression” (60.1%, Low); “High depression” (35.1%, High); and “Very High depression” (4.8%, Very High). Except for the Very High class, patients in the other two classes had depression scores that increased slightly at the second and fifth assessments (i.e., following the administration of chemotherapy). For the Very High class, depression scores remained relatively stable across the six assessments.

Differences in demographic and clinical characteristics

Compared to the Low class, the High class was more likely to be younger; had fewer years of education; was less likely to be employed; and was more likely to have a lower annual household income (Table 2). Compared to the Low class, the Very High class was more likely to have child care responsibilities and was more likely to self-report a diagnosis of ulcer or stomach disease. Compared to the Low class, the other two classes had lower functional status and were more likely to self-report a diagnosis of depression. Compared to the Low and High classes, the Very High class was less likely to have had prior cancer treatments and was more likely to self-report a diagnosis of lung disease, kidney disease, and back pain. In addition, significant differences were found among the three latent classes in total number of comorbid conditions and SCQ scores (i.e., Low < High < Very High).

Differences in common symptoms

As shown in Table 3, significant differences were found among the three latent classes for trait and state anxiety, evening fatigue, and sleep disturbance (i.e., Low < High < Very High). Compared to the Low class, the other two classes reported higher levels of morning fatigue, lower levels of cognitive function, the occurrence of both non-cancer and cancer pain, and higher pain interference scores. Compared to the Low class, the High class reported lower levels of evening energy. Compared to the Low class, the Very High class reported lower levels of morning energy.

Differences in QOL outcomes

For the SF-12’s physical functioning, role physical, bodily pain, general health, vitality, and social functioning domains, compared to the Low class, the other two classes reported lower scores (Figure 2). Significant differences were found among the three latent classes for role emotional, mental health, and MCS scores (i.e., Low > High > Very High). For the PCS domain, compared to the Low class, patients in the High class reported lower scores.

Significant differences were found among the three latent classes for the QOL-PV’s psychological and total QOL scores (i.e., Low > High > Very High; Figure 3). For the physical and social well-being domains, compared to the Low class, the other two classes reported lower scores. For the spiritual well-being domain, compared to the Low class, the Very High class reported lower scores.

Demographic and clinical characteristics

While younger age, lower levels of education, being unemployed, and having a lower annual income were primarily non-modifiable risk factors associated with membership in the High class (Table 2), similar trends were seen in the Very High class compared to the Low class. The lack of significance may be related to the small number of patients (n = 11) in the Very High class. Consistent with previous reports,^3,13,14,38 younger women with gynecological cancer had higher rates of depression. One plausible explanation for this association is that the site of the cancer and associated treatments have adverse effects on sexual and hormonal functions.³⁹ Therefore, younger women who experience premature menopause;³⁹ alterations in sexual activity;^3,38 and/or sexual dysfunction may become depressed.³⁸ Equally plausible, significant changes in body image may contribute to higher levels of depression in younger patients.⁴⁰

Having child care responsibilities was the only distinct demographic characteristic associated with membership in the Very High class. This finding, that is consistent with younger age, may be related to the psychological burden of having to care for younger children while facing a potentially life-threatening condition (e.g., sadness at potentially not seeing one’s children reach adulthood). Equally important, being unemployed and having a lower annual income were risk factors associated with membership in the High class. As noted in prior reports,^41,42 receipt of chemotherapy interferes with patients’ ability to work and contributes to financial toxicity. In addition, the enormous financial cost of cancer treatments⁴³ and a higher symptom burden^42,44 may exacerbate financial hardship due to patients’ inability to remain employed. Given that oncology patients with a lower socioeconomic status are less likely to be referred to specialized mental health services,⁴⁵ clinicians should screen patients for both depression and financial toxicity and initiate appropriate referrals to social services.

Compared to the Low class, women in the other two classes had a higher number of comorbidities, higher comorbidity burden, a poorer functional status, and higher rates of a self-reported diagnosis of depression (Table 2). Consistent with a previous study of multimorbidity in patients with gynecological cancer,⁴⁶ a dose-response effect was seen in the SCQ scores (i.e., measure of comorbidity burden) among our depression classes. Equally important, women in the Very High class self-reported higher rates of lung disease, kidney disease, and back pain that may complicate the receipt of chemotherapy.

Consistent with this high comorbidity burden, women in our two highest classes reported KPS scores that suggest that they “can care for themselves but are not able to carry on normal activity or do normal work.” A similar association was found between depression and performance status in a study of patients with breast and gynecological cancers.⁴⁷ These findings warrant careful consideration because oncology patients who experience multimorbidity have a two to four times increase in the odds of reporting depression,⁴⁷ lower functional status,⁴⁷ poorer QOL,⁴⁸ and increased mortality.⁴⁸ While multimorbidity may not be a modifiable risk factor, optimal management of women’s chronic conditions and referrals to physical therapy to improve functional status are warranted.

It should be noted that a large number of patients in the High and Very High classes self-reported a diagnosis of depression. This association validates the LPA findings and suggests that the CES-D score can be used to screen these vulnerable patients who warrant referral to psychological services. While detailed information on our patients’ use of antidepressants is not available, the high rates of the depression in our sample may be related to the fact that less than 12% of women with gynecological cancer receive pharmacological treatment for depression and that only 5% are referred for counseling or participate in a cancer support group.⁴⁷

Symptom severity

Our findings highlight important associations between depression and the severity of other common symptoms in patients with gynecological cancer. For all of the symptoms except decrements in morning and evening energy, our two higher classes had worse scores (Table 3). Furthermore, the severity scores for state and trait anxiety, morning and evening fatigue, and sleep disturbance were above the clinically meaningful cutoff scores. In addition, the differences between the Low and High classes, as well as between the Low and Very High classes, represent not only statistically significant but clinically meaningful differences in symptom severity scores (i.e., effect sizes ranged from 0.51 [morning fatigue] to 1.0 [trait and state anxiety]).⁴⁹ These findings suggest additive or synergistic interactions among these symptoms.

Equally important, the state and trait anxiety, evening fatigue, and sleep disturbance scores demonstrated a “dose response effect” in that as the depression profile worsened, the severity of these symptoms increased significantly. Our findings are consistent with studies of the general population that found dose response relationships between depression and both anxiety⁵⁰ and sleep disturbance.⁵¹ Of note, while no studies have evaluated for a dose response effect between depression and fatigue, in our previous study of patients with gastrointestinal cancer,⁵² depression scores increased as the evening fatigue profiles worsened. Given that our study is the first to describe dose response relationships between depression and anxiety, fatigue, and sleep disturbance in patients with gynecological cancer undergoing chemotherapy, additional studies need to confirm these findings and evaluate common and distinct underlying mechanisms.

In terms of pain, compared to the 26.3% of women in the Low class, 50% and 63.6% of the patients in the High and Very High depression classes, respectively, reported the occurrence of both non-cancer and cancer pain. In addition, patients with the worst two profiles had moderate to severe levels of pain interference associated with routine activities (e.g., normal work, walking activity; Table 3). Our findings are consistent with previous studies that found an association between depression and pain.^53,54 For example, in a study that examined factors associated with depression in patients with cervical cancer,⁵³ women who reported high pain scores were more likely to report depression. In another study that evaluated for associations between pain and depression,⁵⁴ patients with advanced cancer who reported pain were 4.2 times more likely to report depression.

One plausible explanation for the association between depression and other common symptoms is that the receipt of chemotherapy results in dysregulation of common inflammatory and neurotransmission pathways.⁵⁵ For example, in patients with heterogenous types of cancer, elevations in proinflammatory cytokines (e.g., interleukin 6 (IL6)) were associated with higher levels of depression,⁵⁶ anxiety,^57,58 sleep disturbance,^56,59 fatigue,^56,59 and pain,⁵⁶ as well as poorer cognitive function.⁶⁰ Equally important, altered levels of monoamine neurotransmitters (e.g., serotonin, dopamine) were associated with higher levels of anxiety,⁶¹ fatigue,⁶² depression,⁶¹ and sleep disturbance.⁶¹

An equally plausible explanation for these relationships is stress. While albeit limited, evidence suggests that increases in levels of stress in oncology patients were associated with higher levels of depression, anxiety, fatigue, sleep disturbance, and pain. For example, in a study of patients with head and neck cancer,⁶³ higher levels of all five symptoms were associated with a flattened cortisol slope. Additional research is warranted to determine the mechanisms that may contribute to the development and/or exacerbation of a higher symptom burden in patients with gynecological cancer who report multiple common symptoms associated with cancer and its treatments. This knowledge will assist with the development of tailored interventions that can target multiple symptoms simultaneously and improve patients’ QOL.

QOL outcomes

Consistent with prior research,^64,65 our High and Very High classes reported worse scores for all of the QOL domains on both the general and disease-specific measures (Figures 2 and 3). Furthermore, patients in the High and Very High classes reported PCS and MCS scores of less than 50, that were lower than the normative score for the general population.³⁴ These findings highlight how depression can have a negative impact on both physical and psychological well-being.⁶⁴

A cancer diagnosis and associated treatments can result in significant role changes and disruptions in daily activities that are risk factors for depression.⁶⁴ In addition, patients with gynecological cancer often receive chemotherapy regimens that are associated with the occurrence of multiple common symptoms that effect all aspects of their daily life. Taken together, our findings suggest that clinicians need to screen patients on a routine basis and provide tailored interventions to decrease symptom burden and prevent decrements in QOL.