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

Analysis of influencing factors and prognosis of depression in patients with ovarian cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of influencing factors and prognosis of depression in patients with ovarian cancer Ruchun Yan, Heng Wang, Lin Wang, Xuefei Ke, Wenkang Cheng, Zhuyan Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8299744/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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 impa ct 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 Figures Figure 1 Introduction 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. Materials and Methods 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. Results 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 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). Discussion 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. Declarations 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. References Sung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49. Xia C, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl). 2022;135(5):584–90. Currier MB, Nemeroff CB. Depression as a risk factor for cancer: from pathophysiological advances to treatment implications. Annu Rev Med. 2014;65:203–21. Yang YL, et al. 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Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis. Int J Cancer. 2024;154(10):1745–59. Casavilca-Zambrano S, et al. Depression in women with a diagnosis of breast cancer. Prevalence of symptoms of depression in Peruvian women with early breast cancer and related sociodemographic factors. Semin Oncol. 2020;47(5):293–301. Zhang Q, et al. Factors influencing depressive symptoms in Chinese female breast cancer patients: a meta-analysis. Front Psychol. 2024;15:1332523. Fervaha G, et al. Depression and prostate cancer: A focused review for the clinician. Urol Oncol. 2019;37(4):282–8. Weissman S, et al. New-onset depression after colorectal cancer diagnosis: a population-based longitudinal study. Int J Colorectal Dis. 2021;36(12):2599–602. Liu CL, et al. Prevalence and its associated psychological variables of symptoms of depression and anxiety among ovarian cancer patients in China: a cross-sectional study. Health Qual Life Outcomes. 2017;15(1):161. Zainal NZ, et al. Prevalence of depression in breast cancer survivors: a systematic review of observational studies. Asian Pac J Cancer Prev. 2013;14(4):2649–56. Sun Y, et al. The validity and reliability of the PHQ-9 on screening of depression in neurology: a cross sectional study. BMC Psychiatry. 2022;22(1):98. Pinquart M, Duberstein PR. Depression and cancer mortality: a meta-analysis. Psychol Med. 2010;40(11):1797–810. Xia S, et al. Prognostic value of depression and anxiety on colorectal cancer-related mortality: a systematic review and meta-analysis based on univariate and multivariate data. Int J Colorectal Dis. 2024;39(1):45. Wang X, et al. Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients. Mol Psychiatry. 2020;25(12):3186–97. Wei Y-F et al. Worldwide patterns and trends in ovarian cancer incidence by histological subtype: a population-based analysis from 1988 to 2017. 2025. 79. Clarke CL, et al. Predictors of Long-Term Survival among High-Grade Serous Ovarian Cancer Patients. Cancer Epidemiol Biomarkers Prev. 2019;28(5):996–9. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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00:25:33","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79965,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8299744/v1/4a03ef6fcad3b70d5ad699a5.html"},{"id":99316738,"identity":"7ee32162-4f71-4b6c-b642-0105d0db07bd","added_by":"auto","created_at":"2025-12-31 16:29:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":835803,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival analysis revealed that the depressive status of ovarian cancer patients was associated with progression-free survival (PFS) and overall survival (OS) (P \u0026lt; 0.05). Compared to ovarian cancer patients without depression, those with depression had shorter PFS and OS.\u003c/p\u003e","description":"","filename":"Figure1EffectofdepressiononPFSandOSinovariancancerpatientsinKaplanMeiermethod..png","url":"https://assets-eu.researchsquare.com/files/rs-8299744/v1/f88aeea3da1a7f502e01675e.png"},{"id":103408971,"identity":"e26144ba-b6ed-4b14-9f52-777aa8612f24","added_by":"auto","created_at":"2026-02-25 10:40:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1630640,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8299744/v1/3f2388c3-e446-4fc5-9f3a-62aafce9949c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of influencing factors and prognosis of depression in patients with ovarian cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian 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\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. The incidence of ovarian cancer has been rising steadily, with approximately 57,000 new cases reported in China in 2022\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, and it is significantly more prevalent in cancer patients compared to non-cancer patients\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDepressive 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\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eThe 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.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe study retrospectively included 216 ovarian cancer\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e 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\u0026thinsp;\u0026gt;\u0026thinsp;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.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGeneral Information\u003c/h2\u003e \u003cp\u003eGeneral 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.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment of Depressive State\u003c/h3\u003e\n\u003cp\u003eDepressive state was assessed by certified psychological counselors using the 9-item Patient Health Questionnaire (PHQ-9)\u003csup\u003e[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. 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.\"\u003c/p\u003e\n\u003ch3\u003eMeasurement of Serum Biomarkers\u003c/h3\u003e\n\u003cp\u003eInflammatory 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.\u003c/p\u003e \u003cp\u003eTumor 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.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were tested for normality using the Shapiro-Wilk test. Data conforming to a normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and compared using Student\u0026rsquo;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\u0026rsquo;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 \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. SPSS 25.0 software was used for data analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eComparison of Baseline Characteristics\u003c/h2\u003e \u003cp\u003eA 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\u0026thinsp;\u0026plusmn;\u0026thinsp;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\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 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 \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eomparison of the clinical characteristics in ovarian cancer patients grouped by the status of depression.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Depression(N\u0026thinsp;=\u0026thinsp;124)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDepression(N\u0026thinsp;=\u0026thinsp;92)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eF/χ\u0026sup2;\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125(U/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.28\u0026thinsp;\u0026plusmn;\u0026thinsp;7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHE4(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340.58\u0026thinsp;\u0026plusmn;\u0026thinsp;90.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e420.46\u0026thinsp;\u0026plusmn;\u0026thinsp;80.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF-1(ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188.37\u0026thinsp;\u0026plusmn;\u0026thinsp;50.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165.28\u0026thinsp;\u0026plusmn;\u0026thinsp;68.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.03\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.26\u0026thinsp;\u0026plusmn;\u0026thinsp;7.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.18\u0026thinsp;\u0026plusmn;\u0026thinsp;7.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistological type(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-grade serous carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (38.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (61.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-high grade serous carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (82.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (17.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical stage(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (72.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (27.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (41.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (58.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node metastasis(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (61.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (38.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (46.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (53.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscites(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (43.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (56.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi-67(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (76.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (23.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: 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.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCorrelation Analysis\u003c/h3\u003e\n\u003cp\u003ePHQ-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\u0026thinsp;=\u0026thinsp;0.286 and r\u0026thinsp;=\u0026thinsp;0.375, respectively. The correlation coefficients for PHQ-9 scores with serum IL-6 and TNF-α levels were r\u0026thinsp;=\u0026thinsp;0.358 and r\u0026thinsp;=\u0026thinsp;0.485, respectively. And serum IGF-1 level was significantly negative with PHQ-9 scores. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation betweent serum marker levels and PHQ-9 scores.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarkers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePHQ-9 Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125(U/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHE4(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF-1(ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: 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.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMultivariate logistic regression to identify factors for depression\u003c/h3\u003e\n\u003cp\u003eVariables with P\u0026thinsp;\u0026lt;\u0026thinsp;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\u0026thinsp;=\u0026thinsp;0.012), CA125 (P\u0026thinsp;=\u0026thinsp;0.008), HE4 (P\u0026thinsp;=\u0026thinsp;0.018), IL-6 (P\u0026thinsp;=\u0026thinsp;0.026), TNF-α (P\u0026thinsp;=\u0026thinsp;0.009), histological type (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), clinical stage (P\u0026thinsp;=\u0026thinsp;0.002), and ascites (P\u0026thinsp;=\u0026thinsp;0.016) were independent risk factors for the depressive status of ovarian cancer patients. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression to identify factors for depression in ovarian cancer patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.204\u0026ndash;10.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125(U/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.325\u0026ndash;28.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHE4(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.123\u0026ndash;10.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGF-1(ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.986\u0026ndash;5.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.823\u0026ndash;9.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.463\u0026ndash;12.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistological type(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.053\u0026ndash;15.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical stage(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.312\u0026ndash;18.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscites(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.212\u0026ndash;8.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi-67(n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.864\u0026ndash;5.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: 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.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImpact of Depression on PFS and OS\u003c/h2\u003e \u003cp\u003eA cohort of 216 ovarian cancer patients were followed up through outpatient visits or phone consultations, with a median follow-up time of 45 (15\u0026ndash;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\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared to ovarian cancer patients without depression, those with depression had shorter PFS and OS. (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn 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\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eCurrent 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\u003csup\u003e[\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. 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.\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, but higher than the incidence rates reported in some foreign studies.\u003c/p\u003e \u003cp\u003eLiterature reports that the incidence of depression in cancer patients ranges from 1% to over 50%\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, 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\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur 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. \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003eand Wang et al. \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003eare 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.\u003c/p\u003e \u003cp\u003eCA125 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\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. This is consistent with our conclusion that depression affects PFS and OS in patients with ovarian cancer\u003c/p\u003e \u003cp\u003eThe 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.\u003c/p\u003e \u003cp\u003eIn 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.\u003c/p\u003e "},{"header":"Declarations","content":" \u003cp\u003e \u003cb\u003eAbbreviations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the Ethics Committee of Shiyan People\u0026rsquo;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.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003e 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.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe corresponding author received funding from the Sichuan International Medical Exchange Promotion Association.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe authors\u0026rsquo; 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.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors express their gratitude to the participants and their families for their cooperation in this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXia C, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl). 2022;135(5):584\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCurrier MB, Nemeroff CB. Depression as a risk factor for cancer: from pathophysiological advances to treatment implications. Annu Rev Med. 2014;65:203\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang YL, et al. The prevalence of depression and anxiety among Chinese adults with cancer: a systematic review and meta-analysis. BMC Cancer. 2013;13:393.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeng S, et al. Psychological factors increase the risk of ovarian cancer. J Obstet Gynaecol. 2023;43(1):2187573.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu M, et al. Pathogenesis and therapeutic strategies for cancer-related depression. Am J Cancer Res. 2024;14(9):4197\u0026ndash;217.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrudel-Fitzgerald C et al. Anxiety, Depression, and Colorectal Cancer Survival: Results from Two Prospective Cohorts. J Clin Med, 2020. 9(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang YH, et al. Depression and anxiety in relation to cancer incidence and mortality: a systematic review and meta-analysis of cohort studies. Mol Psychiatry. 2020;25(7):1487\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuh-Burgmann EJ, Alavi M. Detection of early stage ovarian cancer in a large community cohort. Cancer Med. 2019;8(16):7133\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonz\u0026aacute;lez-Mart\u0026iacute;n A, et al. Newly diagnosed and relapsed epithelial ovarian cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2023;34(10):833\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTimmerman D, et al. ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors. Int J Gynecol Cancer. 2021;31(7):961\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinn EH, et al. Comparison of four brief depression screening instruments in ovarian cancer patients: Diagnostic accuracy using traditional versus alternative cutpoints. Gynecol Oncol. 2017;145(3):562\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDegefa M, et al. Validation of the PHQ-9 depression scale in Ethiopian cancer patients attending the oncology clinic at Tikur Anbessa specialized hospital. BMC Psychiatry. 2020;20(1):446.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCostantini L, et al. Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): A systematic review. J Affect Disord. 2021;279:473\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Tuijl LA, et al. Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis. Cancer. 2023;129(20):3287\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasten M, et al. Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis. Int J Cancer. 2024;154(10):1745\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasavilca-Zambrano S, et al. Depression in women with a diagnosis of breast cancer. Prevalence of symptoms of depression in Peruvian women with early breast cancer and related sociodemographic factors. Semin Oncol. 2020;47(5):293\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Q, et al. Factors influencing depressive symptoms in Chinese female breast cancer patients: a meta-analysis. Front Psychol. 2024;15:1332523.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFervaha G, et al. Depression and prostate cancer: A focused review for the clinician. Urol Oncol. 2019;37(4):282\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeissman S, et al. New-onset depression after colorectal cancer diagnosis: a population-based longitudinal study. Int J Colorectal Dis. 2021;36(12):2599\u0026ndash;602.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu CL, et al. Prevalence and its associated psychological variables of symptoms of depression and anxiety among ovarian cancer patients in China: a cross-sectional study. Health Qual Life Outcomes. 2017;15(1):161.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZainal NZ, et al. Prevalence of depression in breast cancer survivors: a systematic review of observational studies. Asian Pac J Cancer Prev. 2013;14(4):2649\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun Y, et al. The validity and reliability of the PHQ-9 on screening of depression in neurology: a cross sectional study. BMC Psychiatry. 2022;22(1):98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinquart M, Duberstein PR. Depression and cancer mortality: a meta-analysis. Psychol Med. 2010;40(11):1797\u0026ndash;810.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXia S, et al. Prognostic value of depression and anxiety on colorectal cancer-related mortality: a systematic review and meta-analysis based on univariate and multivariate data. Int J Colorectal Dis. 2024;39(1):45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, et al. Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients. Mol Psychiatry. 2020;25(12):3186\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei Y-F et al. Worldwide patterns and trends in ovarian cancer incidence by histological subtype: a population-based analysis from 1988 to 2017. 2025. 79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClarke CL, et al. Predictors of Long-Term Survival among High-Grade Serous Ovarian Cancer Patients. Cancer Epidemiol Biomarkers Prev. 2019;28(5):996\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ovarian cancer, depression, CA125, progression-free survival, overall survival","lastPublishedDoi":"10.21203/rs.3.rs-8299744/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8299744/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOvarian cancer (OC) is one of the deadliest gynecological malignancies, with rising incidence rates globally. Depression\u003cstrong\u003e, a common mental health issue among cancer patients, has been shown to significantly impa\u003c/strong\u003ect 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.\u003c/p\u003e","manuscriptTitle":"Analysis of influencing factors and prognosis of depression in patients with ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 00:25:28","doi":"10.21203/rs.3.rs-8299744/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"48451bac-7302-416f-b14f-95bcb295520f","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-25T10:40:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 00:25:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8299744","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8299744","identity":"rs-8299744","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}