Preoperative Findings of Ascites, Liver Involvement, and Pleural Effusion Can Predict Surgical Outcomes in Patients with Advanced Epithelial Ovarian Cancer
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Background: Advanced epithelial ovarian cancer has a poor prognosis, where the likelihood of suboptimal debulking surgery (PDS) is a primary cause of postoperative complications and delays in chemotherapy. Accurate diagnosis and efficient management are crucial for improving clinical outcomes in patients. This study aims to evaluate the predictive value of preoperative findings of ascites, liver involvement, and pleural effusion on surgical outcomes in patients with advanced ovarian cancer, as well as to provide additional insights into prognostic factors that may influence treatment strategies.
Methods: This diagnostic study was conducted at Prof. Dr. I.G.N.G. Ngoerah Hospital from January 2018 to December 2021. A total of 40 patients with advanced ovarian cancer were included in this study, with research variables including findings of ascites, liver involvement, and pleural effusion. Data were collected through medical records and comprehensive preoperative examinations.
Results: Among the total patients, 22 had ascites, 3 showed liver involve- ment, and 15 experienced pleural effusion. Diagnostic tests revealed a sensitivity and specificity of liver involvement for suboptimal PDS of 90.62% and 72.5%, respectively, with a positive predictive value of 100%. In contrast, findings of ascites and pleural effusion had low accuracy, at 45% and 62.5%, respectively, in predicting PDS outcomes. These results indicate that liver involvement is a more reliable indicator for predicting suboptimal PDS outcomes than ascites and pleural effusion.
Conclusion: Liver involvement is a good predictor of suboptimal PDS outcomes, showing potential to assist in preoperative management decisions. Meanwhile, ascites and pleural effusion findings are inconsistent in predict- ing surgical outcomes. This study highlights the importance of thoroughly evaluating these factors before surgical intervention. These findings can aid in the selection of more appropriate preoperative management for patients with advanced ovarian cancer and provide a basis for further research in this area.
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Introduction
Ovarian cancer remains one of the significant challenges in the medical field, with a high mortality rate and minimal improvement in patient survival rates over recent decades. Despite significant advancements in technology and medical treatment, the five-year survival rate for patients diagnosed with ovarian cancer has shown only slight improvement, particularly for those diagnosed at advanced stages. In advanced stages, management of ovarian cancer primarily involves primary debulking surgery (PDS). Still, this procedure often results in suboptimal debulking, increasing the risk of postoperative complications, delaying chemotherapy, and worsening clinical prognosis [1]. In Indonesia, ovarian cancer is the third most common cancer among women, with an incidence of 13,310 new cases and 7,842 deaths in 2018, indicating a significant burden on the healthcare system [2].
At advanced stages, ovarian cancer typically involves widespread metastasis to the peritoneum and other organs, such as the liver and diaphragm. More than 70% of patients with advanced-stage ovarian cancer will experience recurrence despite therapy [3], making it crucial to identify ways to predict PDS outcomes for optimal management strategies. Various studies have attempted to evaluate the effectiveness of inflammatory markers such as the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and CA-125 levels in predicting clinical outcomes for ovarian cancer patients; however, the results have been inconsistent [4]. Furthermore, research on clinical predictors based on radiological findings such as ascites, liver involvement, and pleural effusion is still limited, even though these findings frequently occur in cases of advanced malignancy and can provide critical insights into more appropriate therapeutic choices, such as neoadjuvant chemotherapy followed by interval debulking surgery (IDS) [5], [6].
Previous studies have also indicated that administering neoadjuvant chemotherapy followed by IDS can yield better outcomes compared to direct PDS, particularly in patients with a high tumor burden. However, clear clinical guidelines for choosing between PDS or neoadjuvant chemotherapy/IDS in ovarian cancer patients remain lacking [1]. Therefore, further research is needed to evaluate the predictive value of preoperative findings such as ascites, liver involvement, and pleural effusion on PDS outcomes, with the hope of assisting in the selection of more effective and cost-efficient preoperative management strategies [7].
Materials and Methods
This study utilized a diagnostic test design to evaluate the predictive value of clinical findings, including ascites, liver involvement, and pleural effusion, in predicting the outcomes of Primary Debulking Surgery (PDS) in patients with advanced ovarian cancer. The research was conducted at the Obstetrics and Gynecology Clinic and the Medical Records Installation of Prof. Dr. I.G.N.G. Ngoerah Hospital from January 2018 to December 2021.
The target population consisted of women aged 18 years and older with advanced epithelial ovarian cancer (FIGO stage III–IV). The accessible population included patients who underwent PDS at Prof. Dr. I.G.N.G. Ngoerah Hospital during this period. A consecutive sampling method was employed, with inclusion criteria encompassing women with advanced epithelial ovarian cancer who had undergone PDS and had confirmed anatomical pathology results.
Data for the study were collected from the medical records of patients who met the inclusion criteria. Information gathered included demographic data, PDS outcomes (optimal or suboptimal), and preoperative clinical findings such as ascites, liver involvement, and pleural effusion. Data were documented using a data collection sheet that contained results from abdominal ultrasound examinations, thoracic radiology, and anatomical pathology findings.
Data were analyzed using SPSS v22.0. The analysis included tests for normality and homogeneity of numerical variables. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated to assess the diagnostic value of clinical findings in predicting PDS outcomes.
Results
In this study, there were 148 cases of women diagnosed with ovarian cancer from January 2018 to December 2021. A total of 40 samples met the inclusion criteria. The characteristics of the study subjects, including age, parity, education, and occupation, indicated no significant differences between the groups with optimal and suboptimal debulking (Table I). The variable of disease stage showed a significant difference (p < 0.001), with higher stacges (IIIC and IVB) associated with suboptimal surgical outcomes.
Variable | Total (n = 40) | Suboptimal debulking (n = 32) | Optimal debulking (n = 8) | p-value |
---|---|---|---|---|
Age (years), mean ± SD | 49.8 ± 9.15 | 50 ± 1.8 | 49.5 ± 7.1 | 0.490 |
Parity median (IQR) | 2 (3) | 2 (3) | 2 (3) | 0.850 |
Education, n (%) | 0.130 | |||
Primary school | 19 (47.5) | 15 (37.5) | 4 (10) | |
Middle school | 14 (35) | 10 (25) | 4 (10) | |
Senior high school/college | 7 (17.5) | 7 (17.5) | 0 (0) | |
Occupation n (%) | 11 (27.5) | 0.335 | ||
Unemployed | 15 (37.5) | 12 (30) | 4 (10) | |
Entrepreneur | 16 (40) | 7 (17.5) | 4 (10) | |
Private employee | 7 (17.5) | 1 (2.5) | 0 | |
Healthcare worker | 1 (2.5) | 1 (2.5) | 0 | |
Civil servant | 1 (2.5) | 0 | ||
Menopausal status, n (%) | 1.000 | |||
Yes | 25 (62.5) | 20 (50) | 5 (12.5) | |
No | 15 (37.5) | 12 (30) | 3 (7.5) | |
Contraceptive, n (%) | 0.313 | |||
Ya | 1 (2.5) | 1 (2.5) | 0 (0) | |
Tidak | 39 (97.5) | 31 (77.5) | 8 (20) | |
Body mass index, n (%) | 0.400 | |||
Low | 2 (5) | 2 (5) | 0 (0) | |
Normal | 18 (45) | 16 (40) | 3 (7.5) | |
Overweight/obese | 20 (50) | 14 (37.5) | 5 (12.5) | |
Histological type, n (%) | 0.617 | |||
Serous | 18 (45) | 16 (40) | 2 (5) | |
Mucinous | 3 (7.5) | 2 (5) | 1 (2.5) | |
Endometrioid | 7 (17.5) | 5 (12.5) | 2 (5) | |
Clear cell | 9 (22.5) | 7 (17.5) | 2 (5) | |
Mixed epitel | 2 (5) | 1 (2.5) | 1 (2.5) | |
Undifferentiated | 1 (2.5) | 1 (2.5) | 0 (0) | |
Stage | <0.001 | |||
IIIA1 | 2 (5) | 0 (0) | 2 (5) | |
IIIA2 | 3 (7.5) | 0 (0) | 3 (7.5) | |
IIIC | 28 (70) | 25 (62.5) | 3 (7.5) | |
IVB | 7 (17.5) | 7 (17.5) | 0 (0) | |
Bilateral | 0.140 | |||
Yes | 16 (40) | 14 (35) | 2 (5) | |
No | 23 (57.5) | 18 (42.5) | 6 (15) | |
Tumor size, median (IQR) | 15 (5) | 15.5 (7) | 10 (10.2) | 0.235 |
Aascites finding | 22 (55) | 22 (55) | 18 (45) | |
Liver involvement | 3 (7.5) | 3 (7.5) | 3 (7.5) | |
Pleural effusion | 15 (37.5) | 15 (37.5) | 11 (27.5) |
Clinical Findings and Surgical Outcomes
An analysis of sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the findings of ascites, liver involvement, and pleural effusion was conducted to predict the outcomes of Primary Debulking Surgery (PDS).
Ascites
Of the 22 patients with ascites, 18 experienced suboptimal debulking (Table II). The analysis showed that ascites had a sensitivity of 50%, specificity of 43.75%, positive predictive value of 18.18%, and negative predictive value of 77.77%, with an overall accuracy of 45%.
Surgical outcomes | |||
---|---|---|---|
Optimal debulking | Suboptimal debulking | ||
Ascites | Yes | 4 | 18 |
No | 4 | 14 |
Liver Involvement
Of the 3 patients with liver involvement, all experienced suboptimal debulking (Table III). The results showed a sensitivity of 0%, specificity of 90.62%, positive predictive value of 0%, negative predictive value of 78.37%, and an accuracy of 72.5%.
Surgical outcomes | |||
---|---|---|---|
Optimal debulking | Suboptimal debulking | ||
Liver involvement | Yes | 0 | 3 |
No | 8 | 29 |
Pleural Effusion
Of the 15 patients with pleural effusion, 11 experienced suboptimal debulking (Table IV). The analysis resulted in a sensitivity of 50%, specificity of 65.62%, positive predictive value of 26.66%, negative predictive value of 84%, and an accuracy of 62.5%.
Surgical outcomes | |||
---|---|---|---|
Optimal debulking | Suboptimal debulking | ||
Pleural effusion | Yes | 4 | 11 |
No | 4 | 21 |
Discussion
Characteristics of Study Subjects
Ovarian cancer is one of the most commonly encountered and high-risk gynecological cancers, particularly in women aged 50 years and older. This study found that the average age at diagnosis was 49.8 ± 9.15 years, consistent with various studies indicating that more than two-thirds of patients are 55 years or older [3]. Age is a significant risk factor, with older women having worse prognoses, primarily due to late diagnosis. Epidemiological data suggest that individuals aged 64 years and above have a higher mortality risk associated with ovarian cancer [8]. Research conducted at Prof. Dr. I.G.N.G. Ngoerah Hospital indicated that most patients were diagnosed at stage IIIC (50.7%) with a histopathological type of surface epithelium [9]. These findings emphasize the importance of early screening and education regarding the signs of ovarian cancer, especially in high-risk age groups.
Parity was also a consideration in this study. The median parity found was 2, and no significant differences were observed in debulking outcomes between groups with varying parities. Previous research indicated that parity might act as a protective factor against ovarian cancer, particularly in women under 55 years [10]. However, this study’s results suggest that the influence of parity may diminish in the context of advanced ovarian cancer. This indicates that other risk factors, such as genetics, environment, and lifestyle, may have a more pronounced effect on women already diagnosed with ovarian cancer.
Education level also plays a role in ovarian cancer risk. This study found that most patients had low educational attainment, with 47.5% having completed only primary school or none. This finding aligns with previous research indicating that lower education levels correlate with a higher risk of ovarian cancer, likely due to limited access to health information and adequate medical services [5]. A lack of knowledge about risk factors, early symptoms, and the importance of regular check-ups may contribute to late diagnoses.
Ascites Findings in Predicting PDS Outcomes
Ascites is an essential clinical indicator in determining the prognosis of ovarian cancer patients. In this study, 22 patients were found to have ascites, with 18 experiencing suboptimal debulking. Nasioudis et al. [6] showed that patients without ascites had a higher rate of optimal debulking (65.9%) than those with ascites, regardless of volume. In this study, the sensitivity of ascites was 50%, the specificity was 43.75%, and the overall accuracy was only 45%. These results indicate that while ascites often signify advanced stages of cancer, their predictive value for surgical outcomes is not sufficiently robust [6].
Ascites, especially in large volumes, can reflect disease progression and increase the risk of poor outcomes. Previous research found that each liter of ascites is associated with decreased progression-free survival (PFS) and overall survival (OS) [11]. This highlights the need for further assessment of the volume and characteristics of ascites in the context of ovarian cancer, focusing on more aggressive management for patients with significant ascites. The underlying mechanisms linking ascites to survival are likely related to the extent of disease involvement and response to therapy. Patients with ascites often have more extensive and more aggressive tumors, presenting challenges in disease management [12]. Therefore, a more holistic treatment strategy, including close monitoring and palliative care, may be necessary to improve the quality of life for patients with ascites.
Liver Involvement in Predicting PDS Outcomes
Liver involvement is a crucial factor in determining the prognosis of ovarian cancer. In this study, 3 patients were found to have liver involvement, all of whom experienced suboptimal debulking. Despite the high specificity of liver involvement (90.62%), its sensitivity was very low (0%), indicating that not all patients with liver involvement will have suboptimal outcomes. This underscores the need for careful assessment when determining the prognosis of patients with liver metastasis.
Liver involvement is often associated with more advanced disease stages, limiting treatment options. According to Adamopoulou et al. [1], patients with liver metastasis are less likely to be eligible for cytoreductive surgery and are more often recommended for neoadjuvant chemotherapy. These findings suggest that liver involvement should be considered a strong indicator in clinical decision-making, and high-risk patients may benefit more from chemotherapy before surgery [1].
Pleural Effusion in Predicting PDS Outcomes
Pleural effusion was also a significant finding in this study, with 15 patients identified as having pleural effusion, of which 11 experienced suboptimal debulking. The sensitivity for pleural effusion was 50%, and specificity was 65.62%, indicating that while pleural effusion is often associated with advanced stages, its ability to predict suboptimal outcomes is also limited. Sørensen et al. [13] found that pleural effusion is linked to poor prognosis and increases the risk of suboptimal outcomes. Several mechanisms may explain the relationship between pleural effusion and ovarian cancer prognosis. Research indicates that pleural effusion often correlates with metastatic spread and more significant complications, affecting survival and quality of life [14]. Therefore, pleural effusion should prompt a deeper evaluation and consideration for more aggressive interventions.
Clinical Relevance and Recommendations
Overall, this study demonstrates that while ascites, liver involvement, and pleural effusion are related to PDS outcomes, these findings exhibit variability in their predictive accuracy. Liver involvement appears to be a more robust indicator than ascites and pleural effusion. Consequently, clinicians must consider the overall clinical context when utilizing these indicators in decision-making. To improve clinical outcomes, a more holistic and evidence-based approach is necessary. A management plan involving collaboration among various disciplines, including oncology, surgery, and palliative care, can help optimize outcomes for patients with advanced ovarian cancer. Further research is needed to explore the relationships between these factors and surgical outcomes and develop more robust clinical guidelines to aid in therapeutic decision-making.
The importance of early detection and better interventions for ovarian cancer patients cannot be overstated. Developing effective screening programs, along with raising awareness of risk factors and symptoms of ovarian cancer, should be a priority in efforts to reduce incidence rates and improve survival outcomes. Through ongoing research and the development of adaptive clinical guidelines, it is hoped that more effective management strategies can be created for patients with ovarian cancer.
Conclusion
This study demonstrates that the low sensitivity for ascites (50%), liver involvement (0%), and pleural effusion (50%) indicates limitations in identifying cases with suboptimal outcomes from Primary Debulking Surgery (PDS). Although the low specificity of ascites (43.75%) suggests that this finding does not always reflect poor surgical outcomes, the high specificity for liver involvement (90.62%) indicates consistency in predicting suboptimal results. Additionally, the low positive predictive values for ascites (18.18%), liver involvement (0%), and pleural effusion (26.66%) suggest that if these findings are positive, the likelihood of suboptimal surgical outcomes is also low. Conversely, the high negative predictive values for all three parameters (ascites: 77.7%; liver involvement: 78.37%; pleural effusion: 84%) indicate that if these findings are negative, the probability of optimal surgical outcomes is high.
The low accuracy for ascites (45%) and pleural effusion (62.5%) reflects uncertainty in predicting PDS outcomes, while the higher accuracy for liver involvement (72.5%) suggests a better predictive value. Although ascites, liver involvement, and pleural effusion can serve as prognostic indicators in advanced epithelial ovarian cancer, predictive values may vary based on population, clinical definitions, and sample sizes. Therefore, this study is a foundation for further research in identifying better predictive parameters. With accuracy values below 80%, this study has limitations, including a retrospective method and variability in surgical expertise. It is recommended that prospective studies be conducted with more comprehensive data collection and long-term monitoring to enhance the reliability and generalizability of the findings.
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