REVIEW article

Front. Oncol., 27 September 2024

Sec. Cancer Epidemiology and Prevention

Volume 14 - 2024 | https://doi.org/10.3389/fonc.2024.1442814

Evaluating pretreatment serum CA-125 levels as prognostic biomarkers in endometrial cancer: a comprehensive meta-analysis

  • Department of Obstetrics and Gynecology, Shengjing Hospital of China MedicalUniversity, Shenyang, Liaoning, China

Abstract

Background:

In recent years, the incidence of endometrial cancer (EC) has been rising. This meta-analysis aims to clarify the prognostic significance of serum CA-125 levels in EC.

Methods:

Articles up to March 1, 2024, were systematically searched in EMBASE, Cochrane Library, PubMed, and Web of Science. This analysis pooled hazard ratios (HR) and 95% confidence intervals (CI) from qualifying studies to evaluate the association of CA-125 levels with overall survival (OS), progression-free survival (PFS), disease-free/relapse-free survival (DFS/RFS), and disease-specific survival (DSS).

Results:

25 studies involving 7,716 patients were included. The analysis revealed that elevated CA-125 levels correlate with poorer OS (HR = 1.848, 95% CI: 1.571-2.175, p < 0.001). This association persisted across various study regions and sample sizes, and was notably strong in subgroups with a CA-125 cut-off value of less than 35 (HR = 2.07, 95% CI: 1.13-3.80, p = 0.019) and equal to 35 (HR = 2.04, 95% CI: 1.49-2.79, p < 0.001), and among type II pathology patients (HR = 1.72, 95% CI: 1.07-2.77, p = 0.025). Similarly, high CA-125 levels were linked to reduced PFS, particularly in subgroups with a CA-125 cut-off value less than 35 (HR = 1.87, 95% CI: 1.15-3.04, p = 0.012) and equal to 35 (HR = 4.94, 95% CI: 2.56-9.54, p < 0.001), and in endometrioid endometrial cancer patients (HR = 2.28, 95% CI: 1.18-4.40, p = 0.014). Elevated CA-125 levels were also indicative of worse DFS/RFS (HR = 2.17, 95% CI: 1.444-3.262, p < 0.001) and DSS (HR = 2.854; 95% CI: 1.970-4.133, p < 0.001).

Conclusion:

Serum CA-125 levels before treatment was highly associated with prognosis of EC patients.

1 Introduction

Endometrial cancer (EC) ranks among the top three malignant tumors in the female reproductive system, predominantly affecting perimenopausal and postmenopausal women, with rising global incidence over the past two decades (). In 2020, there were over 417,000 new cases of EC worldwide, resulting in approximately 97,737 deaths (). Major risk factors for EC include anthropometric indices, diet, physical activity, medical conditions, hormonal therapy, biochemical markers, gynecological history, and smoking (–). The primary treatment for EC, as per guidelines, involves comprehensive staging surgery, complemented by radiotherapy, chemotherapy, hormonal therapy, and targeted therapies (, ). Early-stage EC usually offers a favorable outlook with a recurrence rate between 10%-15%, whereas advanced-stage EC, particularly stage IV, has a poor prognosis with a five-year survival rate of only 15% ().

CA-125, a macromolecular sugar chain antigen, is linked to tumorigenesis, cell proliferation, and metastasis (–) in various malignancies (–). Despite its sensitivity as a tumor marker, CA-125 levels can be elevated due to various factors such as menstrual periods, pregnancy, inflammation, radiation damage, benign ovarian tumors, and heart disease (–). CA-125 level correlates with EC clinicopathological features and predicts lymph node metastasis or extra-uterine spread in advanced cases (–). This study aims to elucidate the contentious role of pretreatment serum CA-125 levels in prognosticating EC, thereby contributing to the resolution of existing academic debates (–).

2 Materials and methods

2.1 Search strategy

This Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant meta-analysis (CRD42023443479) () searched PubMed, Web of Science, Embase, and Cochrane Library up to March 1, 2024, using keywords related to EC and CA-125. (Endometrial Neoplasm OR Endometrial Carcinoma OR Endometrial Cancer OR Endometrium Cancer OR cancer of the endometrium OR Carcinoma of Endometrium OR Carcinoma of Endometrium OR Cancer of Endometrium OR Endometrium Cancers) AND (CA-125 OR CA 125 OR Carbohydrate antigen 125 OR Cancer antigen 125) AND (prognosis OR prediction)) (search details were showed in the Supplementary Tables 1–4). Additionally, references from selected articles and grey literature were reviewed to ensure inclusion of all relevant studies. Since the data used in this article were extracted from previous literature, no patient consent or ethical approval was required.

2.2 Eligibility criteria

Studies were included if they: (1) diagnosed EC pathologically or clinically; (2) measured pre-treatment serum CA-125 with a specified cut-off; (3) provided hazard ratios (HRs) and 95% confidence intervals (CIs) or sufficient data to calculate them; (4) reported survival outcomes [overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), relapse-free survival (RFS), disease-specific survival (DSS), or cancer-specific survival (CSS)]; (5) were full-text; and (6) were in English. Exclusion criteria were: (1) non-original articles; (2) in vitro or animal studies; (3) duplicates; and (4) insufficient data.

2.3 Data collection and quality assessment

Data collection was performed by two independent investigators, with disputes resolved by a third investigator. Extracted information included study characteristics, patient demographics, and survival outcomes. HRs were sourced from either multivariate or univariate analyses. In cases where HRs and CIs were not directly provided, they were calculated using Kaplan-Meier survival curves (). Due to a limited number of studies addressing RFS (only two included), survival data were grouped into OS, PFS, disease-free/relapse-free survival (DFS/RFS), and DSS categories for analysis to enhance statistical robustness. The Newcastle-Ottawa Scale (NOS) () evaluated the methodological quality of the studies, assigning scores from 0 to 9 based on criteria such as patient selection, comparability, follow-up, and outcome accuracy. Studies scoring 6 or higher were deemed high-quality.

2.4 Statistical analysis

Pooled HRs and 95% CIs evaluated the impact of pretreatment CA-125 on prognosis. Heterogeneity among studies was measured using the Chi-squared test and I2 value, with I2 > 50% indicating significant heterogeneity and prompting a random-effects model (). A fixed-effects model was used for lower heterogeneity. Subgroup analyses were conducted to identify the sources of heterogeneity, considering variables such as study region, sample size, pathology classifications, CA-125 threshold values, and data origins. The integrity of the results was verified through sensitivity analysis, while Egger’s test investigated publication bias, with adjustments made using the trim-and-fill method where necessary (). Statistical computations were conducted using STATA 15.0 with HR > 1 indicating poorer survival and significance at 95% CI not intersecting 1 and a p-value less than 0.05 in a two-sided test.

3 Results

3.1 Study retrieval, selection, and characteristics

The initial search yielded 4,918 articles from the system database; after removing 1,562 duplicates and excluding 3,286 based on title/abstract analysis, 70 articles were fully reviewed. Of these, 45 were excluded for lacking relevant outcome indicators (35 articles), inability to extract survival data (7 articles), or unavailability of the full text (3 articles). Ultimately, 25 studies were selected for meta-analysis, as illustrated in the search flow chart (Figure 1). The 25 studies, spanning from 1997 to 2023, encompassed 7,716 patients with sample sizes ranging from 40 to 1,483. Study breakdown included 20 assessing the correlation between CA-125 levels and OS, 10 on DFS/RFS, six on PFS, and three on DSS. CA-125 cut-off values varied from 18 to 70.8 U/mL. Most studies (24) were retrospective, with one prospective study. Geographic distribution included 9 studies from Europe, 13 from Asia, and 3 from the Americas. Statistical analyses employed multivariate methods in 19 studies, univariate in two, and survival curves in 4. Specific cancer types analyzed were endometrioid endometrial cancer (EEC) in 2 studies and Type II EC, including uterine carcinosarcomas (UCSs), uterine papillary serous carcinoma (UPSC), and mixed Type II EC (G3 endometrioid and non-endometrioid cancers) in 5 studies. Seventeen studies covered mixed pathological types of both Type I and Type II EC. All studies achieved NOS scores between 6 and 9, indicating high quality (Table 1).

Figure 1

Table 1

AuthorYearCountryStudy designSample sizeAgeTreatmentTypes of pathologyLymph node metastasisCA-125 cut-off value (U/mL)Data sourceSurvival outcomeNOS score
Lo, S. S. T. et al1997Hongkongretrospective9757.3not mentionedType I and Type II–35Multivariate analysisOS6
Sood, A. K. et al1997USAretrospective21062.7(27-93)SType I and Type II15.23%35Survival curveOS8
Huang, G. S. et al2007USAretrospective9565S alone, S + adjuvant (RT+/- CT)Uterine carcinosarcomas (UCSs)–30Univariate analysisOS7
Olawaiye, A. B. et al2008USAretrospective4168(46-87)S alone, S + adjuvant (RT+/- CT)Uterine papillary serous carcinoma (UPSC)39%35Multivariate analysisOS8
Kim, H. S. et al2010Korearetrospective41352(25-83)S alone, S + adjuvant (RT+/- CT), RT+/- CTEndometrioid endometrial cancer(EEC)11.10%18Multivariate analysisOS, PFS8
Pinar Cilesiz Goksedef, B. et al2011Turkeyretrospective9860(32-80)SEndometrioid endometrial cancer(EEC)12%35Survival curveOS, PFS8
Gupta, D. et al2011USAretrospective5269.9(55-83 )S alone, S + adjuvant (RT+/- CT)Uterine papillary serous carcinoma (UPSC)20%30Multivariate analysisRFS8
Chen, Y. L. et al2011Taiwanretrospective12054.0(27-79)S alone, S + adjuvant (RT+/- CT)Type I and Type II12.50%40Multivariate analysisRFS9
Mutz-Dehbalaie, I. et al2012Austriaretrospective18368(38-89)SType I and Type II23%35Multivariate analysisOS, DFS9
Roelofsen, T. et al2012Netherlandsretrospective6670(51-87)S alone, S + adjuvant (RT+/- CT), no treatmentUterine papillary serous carcinoma (UPSC)50%45Multivariate analysisOS, PFS8
Chao, A. et al2013Taiwanretrospective75752(25-93)S alone, S + adjuvant (RT+/- CT), RT+/- CTType I and Type II12.28%35Multivariate analysisDSS8
Li, J. et al2015Chinaretrospective28253(21-76)SType I and Type II4.96%35Multivariate analysisOS, DSS9
Haruma, T. et al2015Japanretrospective32057.5(23-86)S, preoperative CT+SType I and Type II13.75%27.95Multivariate analysisOS, DFS9
Harano, K. et al2016Japanretrospective48365(35-92)S alone, S + adjuvant (RT+/- CT)Uterine carcinosarcomas (UCSs)–35Multivariate analysisOS, DFS8
Biler, A. et al2017Turkeyretrospective4038(21-40)S alone, S + adjuvant (RT+/- CT)Type I and Type II–35Multivariate analysisOS, PFS7
Kotowicz, B. et al2017Polandretrospective7461(42-84)S alone, S + adjuvant (RT+/- CT)Type I and Type II14%70.8Survival curveDFS8
Abbink, K. et al2018Netherlandsretrospective15763(56-71)S alone, S + adjuvant (RT+/- CT)Type I and Type II25%35Multivariate analysisOS9
Reijnen, C. et al2019Netherlandsretrospective33366(41-89)S alone, S + adjuvant (RT+/- CT)Type I and Type II5.11%35Multivariate analysisDFS, DSS9
Cymbaluk-Płoska, A. et al2021Polandprospective34960.8(36-79)SType I and Type II17.70%35Multivariate analysisOS, DFS9
Lin, H. et al2021Chinaretrospective25557(50-61)S alone, S + adjuvant (RT+/- CT)Type I and Type II–35Multivariate analysisOS9
Li, Q. et al2021Chinaretrospective103856(51-61)S, preoperative CT or RT+SType I and Type II3.66%34.13Multivariate analysisOS, PFS8
Huang, Y. et al2021Chinaretrospective24654.17±8.38S alone, S + adjuvant (RT+/- CT)Type I and Type II7.30%24.58Univariate analysisOS7
Quan, Q. et al2021Chinaretrospective19160(35-89)S alone, S + adjuvant (RT+/- CT)Type II (G3 endometrioid and non-endometrioid)14.66%46.5Multivariate analysisOS, DFS8
Li, Q. et al2022Chinaretrospective148356(51-61)S alone, S + adjuvant (RT+/- CT)Type I and Type II–35Multivariate analysisOS, PFS8
Lombaers, M.S. et al2023Netherlandsretrospective33335-93S alone, S + adjuvant (RT+/- CT), RT+/- CTType I and Type II29.50%35Survival curveOS, DFS7

Characteristics of included studies at baseline.

S = surgery; RT = radiotherapy; CT = chemotherapy.

3.2 Correlation of pretreatment serum CA-125 level with OS in EC

The analysis of data from 6,380 EC patients across 20 studies revealed that higher pretreatment serum CA-125 levels detrimentally influenced OS (HR = 1.848, 95% CI: 1.571-2.175, p < 0.001) (Figure 2) (, –48). A fixed-effects model (I2 = 47.7%, p = 0.010), confirmed that higher CA-125 levels adversely affected OS across all study regions and sample sizes. Subgroup analyses revealed a significant negative association between CA-125 and OS for cut-off values ≤35 (HR = 2.07, 95% CI: 1.13-3.80, p = 0.019; HR = 2.04, 95% CI: 1.49-2.79, p < 0.001, respectively) but not >35 (HR = 2.03, 95% CI: 0.70-5.89, p = 0.192). High CA-125 levels were linked with worse OS in type II (HR = 1.72, 95% CI: 1.07-2.77, p = 0.025) and mixed pathology types (HR = 2.10, 95% CI: 1.52-2.91, p < 0.001) but not in EEC (HR = 2.91, 95% CI: 0.95-8.89, p = 0.061). Data source subgroups from multiple analyses (HR = 1.76, 95% CI: 1.34-2.31, p < 0.001) and survival curves (HR = 3.02, 95% CI: 2.07-4.40, p < 0.001) also showed an association between high CA-125 and poorer OS. These detailed findings are summarized in Table 2.

Figure 2

Table 2

VariableIncluded studiesTest of associationEffects modelTest of heterogeneity
HR95%CIPI²P
OS
Study regionAsia101.871.31-2.670.001random32.10%0.152
Europe71.981.22-3.220.006random65.80%0.008
America32.951.81-4.80<0.001random0.00%0.469
Sample size<10063.071.83-5.16<0.001random0.00%0.476
>100141.841.39-2.43<0.001random53.10%0.01
Cut-off value<3542.071.13-3.800.019random31.60%0.223
35142.041.49-2.79<0.001random56.90%0.004
>3522.030.70-5.890.192random33.20%0.221
Types of pathologymixed132.11.52-2.91<0.001random57.50%0.005
EEC22.910.95-8.890.061random0.00%0.324
Type II51.721.07-2.770.025random27.70%0.237
Data sourceMultivariate analysis151.761.34-2.31<0.001random39.40%0.059
Univariate analysis23.750.67-21.010.133random60.90%0.11
Survival curve33.022.07-4.40<0.001random0.00%0.494
PFS
Study regionAsia32.471.39-4.400.002random50.70%0.131
Europe33.680.85-15.920.081random52.20%0.123
Sample size<10033.680.85-15.920.081random52.20%0.123
>10032.471.39-4.400.002random50.70%0.131
Cut-off value<3521.871.15-3.040.012fixed0.00%0.611
3534.942.56-9.54<0.001fixed0.00%0.475
>3511.560.64-3.810.329fixed––
Types of pathologymixed33.541.25-10.020.017random69.10%0.039
EEC22.281.18-4.400.014random0.00%0.53
Type II11.560.64-3.810.329–––
Data sourceMultivariate analysis52.381.65-3.42<0.001fixed49.80%0.093
Survival curve14.270.54-33.630.168––
DFS/RFS
Study regionAsia41.60.91-2.820.105random46.50%0.132
Europe52.41.34-4.270.003random92.90%<0.001
America12.330.80-6.810.122–––
Sample size<10024.012.42-6.65<0.001random27.90%0.239
>10081.791.33-2.41<0.001random61.60%0.011
Cut-off value<3521.510.88-2.590.137random0.00%0.357
3551.761.26-2.450.001random70.40%0.009
>3534.513.46-5.90<0.001random0.00%0.479
Types of pathologymixed72.361.42-3.930.001random90.10%<0.001
Type II31.430.93-2.220.107random10.40%0.328
Data sourceMultivariate analysis81.811.30-2.51<0.001random60.60%0.013
Survival curve23.041.34-6.910.008random89.50%0.002
DSS
Study regionAsia22.291.44-3.64<0.001fixed0.00%0.709
Europe14.182.27-7.71<0.001–––
Data sourceMultivariate analysis23.031.51-6.100.002random51.60%0.151
Survival curve12.451.36-4.410.003–––

Subgroup analysis of the association between CA-125 and survival outcomes in EC.

3.3 Correlation of pretreatment serum CA-125 level with PFS in EC

Data from 6 studies with 3,138 participants showed that elevated pretreatment serum CA-125 levels were significantly linked to poorer PFS in EC patients (HR = 2.42, 95% CI: 1.692–3.463, p < 0.001) (Figure 3) (32, 35, 37, 41, 45, 46). A fixed-effects model was used (I2 = 39.5%, p = 0.142). Subgroup analysis revealed that higher CA-125 levels correlated with poorer PFS in Asian EC patients, studies with sample sizes >100 (HR = 2.47, 95% CI: 1.39-4.40, p = 0.002), and cut-off values ≤35 (HR = 1.87, 95% CI: 1.15-3.04, p = 0.012; HR = 4.94, 95% CI: 2.56-9.54, p < 0.001, respectively) but not >35 (HR = 1.56, 95% CI: 0.64-3.81, p = 0.329). Elevated CA-125 was associated with worse PFS in EEC (HR = 2.28, 95% CI: 1.18-4.40, p = 0.014) and mixed pathology types (HR = 3.54, 95% CI: 1.25-10.02, p = 0.017) but not in type II EC (HR = 1.56, 95% CI: 0.64-3.81, p = 0.329). High CA-125 also associated worse PFS in studies with data from multiple analyses (HR = 2.38, 95% CI: 1.65-3.42, p < 0.001). Details of these findings are available in Table 2.

Figure 3

3.4 Correlation of pretreatment serum CA-125 level with DFS/RFS in EC

Data from 10 studies with 2,438 patients showed that higher pretreatment serum CA-125 levels were associated with poorer DFS/RFS outcomes in EC (HR = 2.170, 95% CI: 1.444–3.262, p < 0.001) (, , 34, 38, 39, 42, 47–50) (Figure 4). A random-effects model was used (I2 = 86.4%, p < 0.001). Subgroup analysis demonstrated that elevated CA-125 adversely affected DFS/RFS in European patients (HR = 2.40, 95% CI: 1.34–4.27, p = 0.003), subgroups with CA-125 cutoff values ≥35 (HR = 4.51, 95% CI: 3.46–5.90, p < 0.001; HR = 1.76, 95% CI: 1.26–2.45, p = 0.001, respectively), and patients with mixed pathology types (HR = 2.36, 95% CI: 1.42–3.93, p = 0.001). The negative correlation between high CA-125 levels and poor DFS/RFS was consistent across varying sample sizes and data sources. These results are detailed in Table 2.

Figure 4

3.5 Correlation of pretreatment serum CA-125 level with DSS in EC

In a smaller cohort, three studies with 1,372 patients showed that elevated pretreatment serum CA-125 levels were linked to poorer DSS outcomes in EC (HR = 2.854, 95% CI: 1.970-4.133, p < 0.001) (, , 36) (Figure 5). A fixed-effects model was used (I2 = 19.9%, p = 0.287). Subgroup analysis indicated that the adverse effects of high CA-125 levels on DSS were consistent across different study regions and data sources, as summarized in Table 2.

Figure 5

3.6 Sensitivity analysis

Sensitivity analyses using the leave-one-out method demonstrated that excluding any single study from the pool did not significantly alter HRs for survival outcomes, suggesting the meta-analysis results were stable and reliable (Figures 6A–D).

Figure 6

3.7 Publication bias

Egger’s test detected bias in the OS analysis (p = 0.031) (Supplementary Figure 1A). The trim-and-fill method, introducing six hypothetical studies, produced an adjusted HR for OS (HR = 1.762, 95% CI: 1.502-2.067, p < 0.001) (Supplementary Figure 1B). The adjusted outcome indicated no significant alteration in the overall effect size, suggesting that the observed bias did not compromise the conclusions. For PFS, DFS/RFS, and DSS, Egger’s tests indicated no significant publication bias (PFS: p = 0.271; DFS/RFS: p = 0.424; DSS: p = 0.670) (Supplementary Figures 1C–E).

4 Discussion

EC represents a significant gynecologic malignancy within the female reproductive system. Given the rising morbidity and mortality among high-risk and advanced EC patients, identifying prognostic factors is crucial (51). Prior research has highlighted the significance of various surgical and pathological features in prognosticating EC, including FIGO stage, tumor grade, histopathological type, lymph vascular space infiltration, myometrial infiltration, and cervical involvement (52, 53). A preoperative HE4 was associated with tumor’s features and has a good performance in prognosis and monitoring of EC (34, 40, 54). Moreover, molecular characteristics such as DNA mismatch repair deficiency (dMMR), CTNNB1 exon-3 mutation, TP53 mutation, and aberrant p53 expression patterns on IHC have been identified as poor prognostic indicators based on recent TCGA molecular typing (55–60). Additionally, factors like estrogen receptors (ERs), progesterone receptors (PRs), bcl-2, c-erb-B2 (HER2/neu), and proliferation markers (PCNA, Ki-67, MIB-1) are also associated with poor survival in EC (61–63).

CA-125, a well-established biomarker in gynecological malignancies, is crucial for diagnosing, predicting clinical outcomes, and monitoring treatment response in ovarian cancer (OC) (64–66). However, its prognostic value in EC remains contentious. Some studies report that elevated pretreatment serum CA-125 levels correlate with poor EC prognosis (31, 33, 37, 40, 41, 43, 45), while others have produced inconclusive or non-significant findings (–, 34, 35, 38, 39, 42, 48). These discrepancies may stem from variations in sample size, patient characteristics, pathological types, and CA-125 cut-off values. To address these inconsistencies, this meta-analysis synthesized data from 25 studies involving 7,716 patients to evaluate the impact of pretreatment serum CA-125 levels on EC survival outcomes, including OS, PFS, DFS/RFS, and DSS.

Elevated pretreatment serum CA-125 levels have been substantially associated with adverse prognostic indicators in EC patients, affirming the marker’s effectiveness in prognostication, similar to findings in OC (67) and other malignancies such as bladder urothelial carcinoma (68), pancreatic ductal adenocarcinoma (69), and renal cell carcinoma (70). This meta-analysis corroborates the pivotal prognostic value of CA-125 in EC, suggesting its potential to enhance prediction of clinical outcomes and guide effective treatment strategies to reduce mortality. Subgroup analyses examining variables such as study region, sample size, cut-off values, pathological types, and data sources revealed no significant differences, reinforcing the consistency of CA-125’s prognostic capacity across diverse clinical settings.

CA-125 is also known to relate closely with clinical pathological characteristics in EC. Higher CA-125 levels are typically linked with extrauterine tumor spread, advanced disease stages (, 71), and are indicative of lymph node metastasis and greater myometrial invasion depth (72, 73). Furthermore, CA-125 levels vary with different pathological types of EC, being more prevalent in type II EC (48). Subgroup analysis focused on pathological types showed that heightened CA-125 levels significantly correlate with poorer prognosis in both EEC and type II EC, although the studies focusing on a single pathological type were limited.

Previous research often used a CA-125 range of 0–35 IU/mL to determine normal levels. In our meta-analysis, among the 25 studies, 15 studies selected 35 as the cut-off value. The number of studies involving other specific cut-off values is too small to form a subgroup. Therefore, we could only conduct subgroup analysis according to cut-off value equal to 35, greater than 35, and less than 35. Our analysis suggested that when the cut-off value was equal to 35 U/mL, elevated CA125 was associated with all the poor survival outcomes, including OS, PFS, DFS/RFS, DSS. When the cut-off value was greater than 35, elevated CA125 was associated with poor DFS/RFS. When the cut-off value was less than 35, elevated CA125 was associated with poor OS and PFS. According to previous studies, elevated CA-125 was found associated with advanced stages in EC patients, a universal cut-off value of 35 might not accurately reflect disease severity or evaluate prognosis across different EC stages. Because the study objects in all the included articles were patients with EC from stage I to stage IV, future studies should include more detailed stage-specific analyses to refine the prognostic utility of CA-125 in EC.

Serum CA-125, a well-studied tumor biomarker in EC, reflects the expression levels of MUC16, the largest known transmembrane mucin, which is highly expressed in various epithelial cancers (74). The molecular dynamics of CA-125 as a prognostic biomarker are closely linked to the abnormal, high expression of MUC16 in tumor cells, facilitating oncogenesis, proliferation, and metastasis (75–77). Additionally, elevated MUC16 expression is associated with increased chemotherapeutic resistance, metabolic alterations, immune surveillance evasion, and pro-inflammatory signaling (78–80). Mutations in MUC16 also correlate with EC prognosis by enhancing the infiltration of cytotoxic T lymphocytes, which play a critical role in antitumor immunity (81). With numerous clinical trials currently exploring MUC16 as a therapeutic target in OC (82–84), there is growing optimism that targeting MUC16 may similarly improve prognostic outcomes in EC patients.

This meta-analysis identified some intriguing outcomes but also faced several limitations. First, the number of studies analyzing the relationship between CA-125 and various survival outcomes was limited. Second, the predominance of retrospective studies could introduce selection bias. Third, extracting HRs from univariate analyses and survival curves might have resulted in overestimated effects. Additionally, a lack of detailed staging prevented subgroup analyses across different FIGO stages as the studies encompassed all stages collectively. Moreover, the lack of data on menopausal status prevented stratification of analyses. Despite these limitations, the study underscores the potential of CA-125. Cancer’s multifactorial nature often diminishes the accuracy of individual markers (85). A combined approach, integrating various biomarkers with clinicopathological features, is likely to yield more precise and sensitive prognostic assessments (86).

5 Conclusions

Generally, this study substantiates the association between elevated CA-125 levels and adverse prognosis in EC, supporting its prospective role as a pivotal molecular biomarker.

Statements

Author contributions

ZY: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Writing – original draft. YS: Data curation, Formal analysis, Software, Writing – original draft. CG: Supervision, Validation, Visualization, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2024.1442814/full#supplementary-material

Supplementary Figure 1

Publication bias assessment of included studies. (A) Egger’s test for OS; (B) Filled funnel plot using trim and fill method for OS; (C) Egger’s test for PFS; (D) Egger’s test for DFS/RFS; (E) Egger’s test for DSS.

Supplementary Table 1

Search strategy details and results in PubMed.

Supplementary Table 2

Search strategy details and results in Web of Science.

Supplementary Table 3

Search strategy details and results in Embase.

Supplementary Table 4

Search strategy details and results in Cochrane Library.

Abbreviations

EC, endometrial cancer; HR, Hazard ratio; PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses; CI, Confidence interval; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; RFS, relapse free survival; DSS, disease-specific survival; DFS/RFS, disease-free/relapse-free survival.

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Summary

Keywords

endometrial cancer, CA-125, prognosis, survival, meta – analysis

Citation

Yu Z, Sun Y and Guo C (2024) Evaluating pretreatment serum CA-125 levels as prognostic biomarkers in endometrial cancer: a comprehensive meta-analysis. Front. Oncol. 14:1442814. doi: 10.3389/fonc.2024.1442814

Received

03 June 2024

Accepted

28 August 2024

Published

27 September 2024

Volume

14 - 2024

Edited by

Philip Rosenberg, National Cancer Institute (NIH), United States

Reviewed by

Stefano Restaino, Ospedale Santa Maria della Misericordia di Udine, Italy

Boya Guo, Fred Hutchinson Cancer Center, United States

Updates

Copyright

*Correspondence: Cuishan Guo,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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