Analysis of influencing factors and prognosis of depression in patients with ovarian cancer

doi:10.21203/rs.3.rs-8299744/v1

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Analysis of influencing factors and prognosis of depression in patients with ovarian cancer

https://doi.org/10.21203/rs.3.rs-8299744/v1

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Ovarian cancer (OC) is one of the deadliest gynecological malignancies, with rising incidence rates globally. Depression, a common mental health issue among cancer patients, has been shown to significantly impact quality of life, treatment adherence, and overall prognosis. However, the relationship between depression and the prognosis of ovarian cancer remains poorly understood. This study aims to explore the factors influencing depression in ovarian cancer patients and assess its impact on progression-free survival (PFS) and overall survival (OS). A total of 216 ovarian cancer patients were assessed for depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9). Clinical data, including age, histological type, serum CA125 levels, and presence of ascites, were also collected. The results showed that 42.59% of the patients experienced clinically significant depression, significantly higher than the general population. Multivariate analysis revealed that age, histological type, serum CA125 levels, and ascites were independent risk factors for depression in ovarian cancer patients. Survival analysis indicated that depression was associated with worse PFS and OS. These findings suggest that depression is an important prognostic factor in ovarian cancer and highlight the need for early psychological assessment and intervention as part of the clinical management strategy to improve both psychological well-being and survival outcomes in ovarian cancer patients.

Ovarian cancer

depression

CA125

progression-free survival

overall survival

Ovarian cancer (OC) is one of the deadliest gynecological malignancies, ranking eighth in incidence among women. It accounts for approximately 3.7% of all cancer cases and 4.7% of cancer-related deaths in 2020^[1]. The incidence of ovarian cancer has been rising steadily, with approximately 57,000 new cases reported in China in 2022^[2]. The high recurrence rate and multifactorial pathophysiology of ovarian cancer further complicate its management, involving genetic, environmental, and psychosocial factors. Depression, an increasingly recognized psychosocial factor, is one of the most common mental disorders in cancer patients. The incidence of depression in cancer patients during the first five years after diagnosis is three times higher than in the general population^[3], and it is significantly more prevalent in cancer patients compared to non-cancer patients^[4]. Depression increases both physical and psychological suffering, reduces treatment adherence, exacerbates adverse treatment effects, and has been shown to negatively affect quality of life and prognosis^[5–8].

Depressive symptoms, such as weight loss and fatigue, may appear in ovarian cancer patients as early as 2 to 7 months before diagnosis, suggesting that depression could be associated with the development of malignant tumors^[9]. Depression in cancer patients is related to poorer treatment adherence, decreased immune function, and lower overall survival rates. These findings suggest that depression could be an important prognostic factor in ovarian cancer, although the exact mechanisms behind this association remain unclear.

The relationship between depression and ovarian cancer prognosis is an increasingly recognized area of research. This study aims to investigate the factors influencing the depressive state in ovarian cancer patients and explore the impact of depression on their prognosis, particularly its effect on progression-free survival (PFS) and overall survival (OS). By identifying key determinants of depression and understanding their prognostic significance, we hope to provide insights that will guide clinical strategies aimed at improving the psychological health and survival outcomes of ovarian cancer patients.

The study retrospectively included 216 ovarian cancer^[10–11] patients who were initially diagnosed and treated at the Department of Obstetrics and Gynecology, Shiyan People's Hospital, between August 2016 and August 2020. Inclusion criteria: (1) Age > 18 years; (2) Underwent comprehensive staging surgery for ovarian cancer or tumor debulking surgery, with postoperative pathological confirmation of primary epithelial ovarian cancer; (3) No neoadjuvant chemotherapy prior to surgery; (4) No history of psychiatric disorders. Exclusion criteria:(1) Pathological type of non-epithelial ovarian cancer or secondary ovarian tumors; (2) Coexisting primary malignant tumors in other parts of the body. Ethical approval was given by the Ethics Committee of Shiyan People's Hospital. Written informed consent was obtained from all participants and/or their families.

General Information

General information collected included age, occupation, education level, monthly income, histological type, clinical stage, lymph node status, Ki-67 expression level, and presence or absence of ascites. The follow-up methods primarily included telephone follow-up and outpatient reexamination, with the follow-up cutoff date set to June 30, 2024. For patients who were still alive at the follow-up cutoff, their survival time was defined as the period from diagnosis to the last follow-up. For patients who had passed away during the follow-up, their survival time was defined as the period from diagnosis to death.

Assessment of Depressive State

Depressive state was assessed by certified psychological counselors using the 9-item Patient Health Questionnaire (PHQ-9)^[12–14]. The scale contains 9 items, with each item scored from 0 to 3. A total score greater than 4 is defined as "depression," while a score of 4 or less is defined as "no depression."

Measurement of Serum Biomarkers

Inflammatory marker detection: On the day of testing, 5 mL of venous blood is drawn after overnight fasting in the morning. The blood is centrifuged at 3000 rpm for 10 minutes, and after standing for 1 hour, it is analyzed. Enzyme-linked immunosorbent assay (ELISA) is used to detect the serum levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the patient's serum.

Tumor marker detection: Electrochemiluminescence immunoassay (ECLIA) is used to detect serum CA125, HE4, and IGF-I levels. The HE4 reagent kit is provided by Abbott Laboratories, USA. The IGF-I reagent kit is provided by DRG, with the batch number: 18K091.

Statistical Analysis

Continuous variables were tested for normality using the Shapiro-Wilk test. Data conforming to a normal distribution were expressed as mean ± standard deviation and compared using Student’s t-test. Non-normally distributed data were analyzed using the Mann-Whitney U test. Categorical data were compared using the chi-square test. Correlations between PHQ-9 scores and CA125, HE-4, IGF-1, IL-6, and TNF-α levels were analyzed using Spearman’s correlation. Kaplan-Meier survival curves were used to compare progression-free survival and overall survival based on depression status, with differences analyzed using the Log-rank test. Multivariate logistic regression was employed to evaluate factors for depression in ovarian cancer patients. Statistical significance was set at a two-tailed P < 0.05. SPSS 25.0 software was used for data analysis.

Comparison of Baseline Characteristics

A total of 216 patients with ovarian cancer were included in this study, with 124 in the non-depression group and 92 in the depression group. The patients' ages ranged from 23 to 74 years, with an average age of (52.5 ± 10.8) years. Among them, 100 patients (46.30%) lived in rural areas, 160 patients (74.07%) had completed high school education or higher, 60 patients (27.78%) were retired, and 170 patients (78.70%) were married. As shown in Table 1, significant differences were observed in serum levels of CA125, HE4, IGF-1, IL-6, TNF-α, and histological type, clinical stage, ascites, and Ki-67 expression level. And the serum levels of CA125, HE4, IL-6, TNF-α in depression group were significantly higher than the non-depression (all P < 0.05).

Table 1

omparison of the clinical characteristics in ovarian cancer patients grouped by the status of depression.
Variable	Non-Depression(N = 124)	Depression(N = 92)	F/χ²	P-value
CA125(U/mL)	33.86 ± 3.56	50.28 ± 7.17	3.798	< 0.001
HE4(pmol/L)	340.58 ± 90.28	420.46 ± 80.72	3.156	0.003
IGF-1(ng/mL)	188.37 ± 50.89	165.28 ± 68.02	2.852	0.012
IL-6(ng/L)	25.03 ± 8.34	39.26 ± 7.95	3.126	0.003
TNF-α(ng/L)	28.18 ± 7.18	45.17 ± 6.85	3.582	0.005
Histological type(n, %)
High-grade serous carcinoma	48 (38.71)	76 (61.29)	4.589	< 0.001
Non-high grade serous carcinoma	76 (82.61)	16 (17.39)
Clinical stage(n, %)
I-II	80 (72.73)	30 (27.27)	5.256	0.003
III-IV	44 (41.51)	62 (58.49)
Lymph node metastasis(n, %)
No	96 (61.54)	60 (38.46)	2.459	0.167
Yes	28 (46.67)	32 (53.33)
Ascites(n, %)
No	72 (75.00)	24 (25.00)	6.528	0.003
Yes	52 (43.33)	68 (56.67)
Ki-67(n, %)
<40%	46 (76.67)	14 (23.33)	4.257	0.026
≥40%	78 (50.00)	78 (50.00)
Note: CA125, Cancer Antigen 125; HE4, Human Epididymis Protein-4; IGF-1, Insulin-like Growth Factor-1; IL-6, Interleukin-6; TNF-α,Tumor Necrosis Factor-α.

Correlation Analysis

PHQ-9 scores in ovarian cancer patients were positively correlated with the expression levels of CA125, HE4, IL-6, and TNF-α. The Spearman correlation coefficients for PHQ-9 scores with serum CA125 and HE4 levels were r = 0.286 and r = 0.375, respectively. The correlation coefficients for PHQ-9 scores with serum IL-6 and TNF-α levels were r = 0.358 and r = 0.485, respectively. And serum IGF-1 level was significantly negative with PHQ-9 scores. (Table 2)

Table 2

Correlation betweent serum marker levels and PHQ-9 scores.
Markers	PHQ-9 Score
Markers	r	P
CA125(U/mL)	0.286	0.005
HE4(pmol/L)	0.375	0.026
IGF-1(ng/mL)	-0.212	0.018
IL-6(ng/L)	0.358	0.002
TNF-α(ng/L)	0.485	< 0.001
Note: CA125, Cancer Antigen 125; HE4, Human Epididymis Protein-4; IGF-1, Insulin-like Growth Factor-1; IL-6, Interleukin-6; TNF-α,Tumor Necrosis Factor-α; PHQ-9,Patient Health Questionnaire-9.

Multivariate logistic regression to identify factors for depression

Variables with P < 0.05 in the univariate analysis were included as independent variables in the multivariate logistic regression analysis. The factors included were age, CA125, HE4, IGF-1, IL-6, TNF-α, histological type, clinical stage, ascites, and Ki-67 expression level. Multivariate logistic regression analysis confirmed that age(P = 0.012), CA125 (P = 0.008), HE4 (P = 0.018), IL-6 (P = 0.026), TNF-α (P = 0.009), histological type (P < 0.001), clinical stage (P = 0.002), and ascites (P = 0.016) were independent risk factors for the depressive status of ovarian cancer patients. (Table 3).

Table 3

Multivariate logistic regression to identify factors for depression in ovarian cancer patients.
Variable	OR	95% CI	P-value
Age	3.121	1.204–10.282	0.012
CA125(U/mL)	5.132	1.325–28.724	0.008
HE4(pmol/L)	2.358	1.123–10.856	0.018
IGF-1(ng/mL)	1.825	0.986–5.246	0.056
IL-6(ng/L)	3.569	1.823–9.248	0.026
TNF-α(ng/L)	4.178	2.463–12.564	0.009
Histological type(n, %)	5.286	2.053–15.724	< 0.001
Clinical stage(n, %)	4.568	2.312–18.568	0.002
Ascites(n, %)	2.475	0.212–8.263	0.016
Ki-67(n, %)	1.568	0.864–5.269	0.182
Note: CA125, Cancer Antigen 125; HE4, Human Epididymis Protein-4; IGF-1, Insulin-like Growth Factor-1; IL-6, Interleukin-6; TNF-α,Tumor Necrosis Factor-α.

Impact of Depression on PFS and OS

A cohort of 216 ovarian cancer patients were followed up through outpatient visits or phone consultations, with a median follow-up time of 45 (15–62) months. Six patients were lost to follow-up, and 68 patients experienced recurrence during the follow-up period. 38 patients died during the follow-up. Survival analysis revealed that the depressive status of ovarian cancer patients was associated with progression-free survival (PFS) and overall survival (OS) (P < 0.05). Compared to ovarian cancer patients without depression, those with depression had shorter PFS and OS. (Fig. 1).

In clinical practice, it has been observed that patients with strong psychological resilience, who are able to face reality positively, often have a better clinical quality of life and longer effective survival periods compared to ovarian cancer patients with poor psychological resilience who are unable to accept the diagnosis of cancer. This phenomenon, commonly seen in cancer patients, is considered to be cancer related depression^[15–16]. Ovarian cancer patients are often elderly women with poor psychological endurance, and after diagnosis, they have a weakened ability to self-regulate. The impact of their depressive symptoms on the progression of ovarian cancer remains an area with insufficient research. In this study, we analyze whether there are changes in serum tumor markers, inflammatory markers, and other indicators in patients with different depressive states. We further aim to clarify whether there are differences in clinical progression-free survival (PFS) and overall survival (OS) between patients with different depressive states.

Current research on the relationship between malignancy and depression mainly focuses on epidemiological studies. The incidence of depression in cancer patients is significantly higher than that in non-cancer patients^[17–20]. In this study, we used the PHQ-9 to conduct face-to-face interviews with ovarian cancer patients before treatment and found that the incidence of depressive states in ovarian cancer patients was 42.59%, significantly higher than in the general population of China. This result is consistent with the findings of Liu et al.^[21], but higher than the incidence rates reported in some foreign studies.

Literature reports that the incidence of depression in cancer patients ranges from 1% to over 50%^[22], with such a wide range possibly due to the type of study and design choices, particularly the selection of depression scales used in each study. Therefore, selecting an effective and convenient screening tool is crucial, and the screening tool should have high sensitivity to avoid missed diagnoses. The PHQ-9 is a simple and practical method for depression assessment, and research has confirmed its scientific validity and effectiveness^{[14, 23]}.

Our results indicate that age is an independent risk factor for depressive states in ovarian cancer patients. This finding is consistent with the results of Pinquart et al.[24], who found that older cancer patients have a higher risk of depression. However, the results of studies by Xia et al. ^[25]and Wang et al. ^[26]are contrary to this, as their research on the relationship between depression and colorectal cancer and breast cancer, respectively, concluded that the correlation between depression and mortality was stronger in younger patients than in older ones. The inconsistency in these results may be related to differences in the mechanisms of death associated with different cancer types.

CA125 is the most commonly used biomarker for ovarian cancer and is of significant importance for assessing prognosis and diagnosing recurrence. High-grade serous ovarian cancer is the most common histological type of epithelial ovarian cancer, accounting for more than 80% of epithelial tumors. It is the most malignant, with the highest recurrence and mortality rates^[27]. This study explored the relationship between clinical-pathological features of ovarian cancer and depressive states. The results suggest that histological type and serum CA125 levels are independent risk factors for depression in ovarian cancer patients. Currently, similar studies are limited, with only one study investigating the relationship between depressive symptoms and survival in patients with high-grade serous ovarian cancer. This study found that depressive symptoms were negatively correlated with survival in ovarian cancer patients^[28]. This is consistent with our conclusion that depression affects PFS and OS in patients with ovarian cancer

The interpretation of our findings warrants caution because of several limitations. The sample size included in this study is limited, and there may be biases in the correlation between the observed indicators and depressive states, which require further validation. Additionally, aside from the disease itself, other factors may influence the patients' mental status, such as their living environment and cognitive ability regarding the tumor. Therefore, potential confounding biases may exist. Future studies should pay more attention to the impact of these factors.

In conclusion, despite continuous improvements in anti-tumor treatments and advancements in medical technology, they may not be sufficient to alleviate the ongoing suffering that patients experience due to psychological issues. Therefore, we advocate for focusing on the psychological problems of ovarian cancer patients and providing timely, targeted psychological interventions. This should be considered a supplementary aspect of ovarian cancer treatment strategies, aiming to enhance the effectiveness of anti-tumor therapies. It holds significant practical importance in the clinical management of cancer treatment.

Abbreviations

Not applicable.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Shiyan People’s Hospital (Ethical Approval Number: SYRMYY-2025-014). Written informed consent to participate in the study was obtained from all clinical participants prior to enrollment. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the principles of the Declaration of Helsinki.

Consent for publication

Written informed consent for publication was obtained from all clinical participants prior to enrollment. All participants explicitly agreed that their anonymized clinical data could be used for scientific publication. Identifying personal information was removed to ensure participant confidentiality.

Competing interests

The authors declare that they have no competing interests.

Funding

The corresponding author received funding from the Sichuan International Medical Exchange Promotion Association.

Author Contribution

The authors’ contributions are consistent with their order of authorship. All authors contributed to the study conception and design, data acquisition, analysis, and manuscript preparation. All authors read and approved the final manuscript.

Acknowledgements

The authors express their gratitude to the participants and their families for their cooperation in this study.

Data Availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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You are reading this latest preprint version

Analysis of influencing factors and prognosis of depression in patients with ovarian cancer

Status:

Version 1

Abstract

Figures

Introduction

Materials and Methods

General Information

Assessment of Depressive State

Measurement of Serum Biomarkers

Statistical Analysis

Results

Comparison of Baseline Characteristics

Correlation Analysis

Multivariate logistic regression to identify factors for depression

Impact of Depression on PFS and OS

Discussion

Declarations

Competing interests

Funding

Author Contribution

Acknowledgements

Data Availability

References

Additional Declarations

Status:

Version 1