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Romanian Journal of Preventive Medicine
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  • Review
  • Open Access

28 November 2025

Biomarkers and Early Detection Strategies for Ovarian Tumors

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and
1
Department of Obstetrics and Gynecology, “Carol Davila” University of Medicine and Pharmacy Bucharest, 37 Dionisie Lupu, 020021 Bucharest, Romania
2
Doctoral School, “Dunărea de Jos” University of Medicine and Pharmacy, 35 Al. I. Cuza, 800010 Galați, Romania
3
Department of General Surgery, Fundeni Clinical Institute, 022328 Bucharest, Romania
4
Physical Medicine and Rehabilitation Department, Altstadtpraxis Aarau GmbH, 5000 Aarau, Switzerland
Rom. J. Prev. Med.2025, 3(1), 4;https://doi.org/10.3390/rjpm3010004
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Abstract

Ovarian cancer is a highly aggressive disease with a poor prognosis, largely due to challenges in early detection. Traditional screening methods, including transvaginal ultrasound (TVS) and CA125 testing, have notable limitations in detecting early-stage disease and are not advised for widespread use. This article examines emerging early detection technologies, such as novel biomarkers, circulating DNA, PCR assays from Pap swabs, autoantibodies, microRNAs, and advanced imaging techniques. Future advancements in therapeutic methods may enhance survival outcomes linked to early detection. While general population screening remains unendorsed, targeted screening might be valuable for high-risk groups, such as those with Lynch syndrome, but should not replace risk-reducing surgeries. Developing comprehensive screening guidelines for high-risk individuals is essential for improving early detection and survival rates in ovarian cancer.

1. Introduction

Ovarian cancer was identified as the eighth most prevalent cancer among women worldwide in the GLOBOCAN 2020 report, with an estimated 313,959 new diagnoses and 207,252 deaths occurring that year [1]. Despite advancements in therapeutic methods, ovarian cancer remains a condition with high mortality and poor prognosis, thus limiting the efficacy of the current efforts of the oncology community to improve patient outcomes and overall quality of life [2,3,4,5,6]. The majority of cases are diagnosed at stage III or IV, where the survival rates are only 27% and 13%, respectively. Furthermore, the most aggressive histological type of this cancer, high-grade serous ovarian carcinoma, accounts for 80% of ovarian cancer cases [7,8]. The negative outcomes associated with this disease have driven intensive research into identifying effective screening methods for ovarian cancer. A significant aspect of this research focuses on hereditary ovarian cancers, which are often linked to mutations in BRCA1 and BRCA2. These mutations are associated with substantial cumulative risks of developing ovarian cancer—40% for BRCA1 and 18% for BRCA2 by age 70 [9]. While Lynch syndrome primarily increases the risk of colorectal and endometrial cancers, it also raises the risk of ovarian cancer. The cumulative risks of ovarian cancer by age 70 for Lynch syndrome mutations in MLH1 and MSH2 are 11% and 15%, respectively, while no specific ovarian cancer risk has been identified for mutations in MSH6 or PMS2 [10]. In the past decade, several moderate penetrance mutations have also been linked to an increased risk of ovarian cancer. Mutations in RAD51C and RAD51D are estimated to elevate the risk by approximately 5-fold [11] and 12-fold [12], respectively. For BRIP1 mutation carriers, the cumulative lifetime risk of developing ovarian cancer by age 80 is estimated at 5.8% [13]. Techniques such as transvaginal ultrasound and the measurement of tumor markers like CA 125 have been evaluated both in the general population and in high-risk groups. Despite these efforts, these methods have not proven effective, and currently, there are no established screening protocols or guidelines for ovarian cancer screening. This comprehensive review aims to present the current state of knowledge regarding early detection methods for ovarian tumors, including emerging biomarkers that are currently under investigation [14].

2. The Impact of Genetics on the Early Diagnosis of Ovarian Cancer

It is important to note that women at risk for ovarian cancer due to having a first-degree relative diagnosed with this malignancy have an estimated 2.96-fold increased familial relative risk of developing ovarian cancer. This risk increases proportionally with the number of affected first-degree relatives [14].
In current clinical practice, cancer susceptibility genes (CSGs) such as BRCA1 and BRCA2 are routinely tested. However, the incorporation of moderate-penetrance genes (PALB2, RAD51D, BRIP1, and RAD51C) into routine genetic screening, along with DNA mismatch repair genes that are associated with Lynch syndrome, has significantly enhanced the detection of women with a high risk of developing ovarian cancer. This advancement has facilitated the implementation of preventive surgical interventions, which have been shown to effectively reduce ovarian cancer risk in mutation carriers. Depending on the reproductive status of these women, risk-reducing surgery has contributed to a decrease in ovarian cancer-related mortality [15].
It is crucial to recognize that approximately 15–22% of ovarian cancer cases are attributed to an underlying genetic mutation, indicating that ovarian cancer could be preventable in this subset of patients. This underscores the need for comprehensive genetic screening programs to mitigate the future burden of ovarian cancer through personalized risk assessment and intervention strategies [16].
While several countries have implemented genetic screening programs, current guidelines primarily target high-risk individuals based on family history or clinical criteria. However, significant limitations exist within this framework: 50–80% of CSG mutation carriers do not qualify for genetic testing due to restrictive eligibility criteria. An astonishing 97% of individuals carrying high-penetrance monogenic BRCA mutations remain undiagnosed, despite 25 years of criteria-based genetic testing [16].
Future advancements are expected to reshape the paradigm of population-based genetic testing, potentially enhancing the effectiveness of ovarian cancer prevention on a global scale [17].
It is important to emphasize that universal genetic testing for all cancer patients has demonstrated high efficacy in identifying individuals carrying CSG mutations. This approach enables: secondary cancer prevention in affected individuals and cascade testing of family members, allowing for primary prevention of ovarian cancer in mutation carriers [18].
Although current genetic testing strategies primarily focus on individuals already diagnosed with cancer, until more feasible options for early diagnosis and prevention emerge, this remains a viable and impactful strategy that should be considered [19].

3. Role of Transvaginal Ultrasound and CA-125 in Ovarian Cancer Screening

When it comes to ovarian cancer screening in the general population, two major randomized controlled trials have assessed the role of transvaginal ultrasound (TVUS) and CA-125 in early detection. The UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) included 202,638 women with a median follow-up of 16.3 years. This study compared transvaginal ultrasound (as both first and second-line tests) and multimodal screening (longitudinal CA 125 measurements followed by TVUS as a second-line test) with a control group that underwent non-screening. The results showed that neither multimodal screening nor screening with ultrasound alone led to a reduction in ovarian cancer mortality. Compared with patients who were not screened at all, there was a 39.2% higher incidence of stage I or II cancer in the MMS group, and a 10.2% lower incidence of stage III or IV cancer in the multimodal screening group compared to the non-screening group [7].
The other major randomized controlled trial is the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, which included 34,253 women in the intervention group and 34,304 in the usual care group, with a median follow-up of 12.4 years. This study compared annual screening using transvaginal ultrasound (TVUS) and CA 125 with usual care. The PLCO trial concluded that there was no difference in ovarian cancer mortality between the two groups. Additionally, unlike the UKCTOCS trial, the PLCO study did not observe a reduction in the incidence of advanced-stage disease [20]. This difference could be attributed to the use of longitudinal CA 125 measurements in UKCTOCS versus a single CA 125 cut-off in PLCO [21].
Rosenthal et al. investigated the effectiveness of BRIP1-based screening in women at high risk for ovarian cancer who chose not to undergo bilateral prophylactic salpingo-oophorectomy. The ROCA test evaluates the risk of epithelial ovarian cancer (OC) or fallopian tube cancer (FTC) in women by analyzing fluctuations in the CA 125 tumor marker and classifying individuals into different risk categories using a specialized algorithm. This approach was linked to a reduced incidence of high-volume disease at the initial surgery and demonstrated a high rate of zero residual disease with less complex surgical procedures [22]. In a different study, Skates et al. found that more frequent CA 125 testing analyzed with ROCA was linked to greater specificity and a notable increase in the detection of early-stage ovarian cancer compared to historical control data. Notably, ROCA identified 50% of new cases before the standard cutoff of 35 U/mL. In addition, the use of ROCA in screening contributed to a greater likelihood of achieving optimal debulking during surgery in newly diagnosed patients [23]. Nevertheless, bilateral prophylactic salpingo-oophorectomy remains the gold standard for patients at high risk of developing ovarian cancer, and these screening methods should not replace it [24].

4. Emerging Methods for Early Detection of Ovarian Cancer

Currently, new methods for the early detection of ovarian cancer are being studied. One such method is the PapSEEK test, which involves PCR analysis of DNA obtained from routine Pap smears. This method aims to identify 18 genetic mutations or aneuploidies and has a sensitivity of 33% for detecting ovarian cancer, which can increase to 45% with intrauterine sampling using a Tao brush. When analyzing circulating plasma DNA using the same method, the sensitivity for detecting ovarian cancer was 43%, and when both methods were used together, the sensitivity increased to 63% [25].
Over time, the role of numerous biomarkers has been studied with the aim of detecting ovarian cancer in its early stages. Among these, Human Epididymis Protein 4 (HE4) has proven its effectiveness, showing elevated levels in 70% of ovarian cancers. Unlike CA 125, HE4 has a higher specificity for ovarian cancer, as it is less frequently elevated in benign ovarian tumors [26]. CA 125 levels are elevated in over 90% of patients with advanced-stage (III-IV) ovarian cancer and in approximately 50–60% of those with stage I ovarian cancer [27]. Moreover, the combined use of CA 125 and HE4 has facilitated the differential diagnosis between benign ovarian tumors and ovarian cancer, achieving a sensitivity of 76.4% and a specificity of 95% [28]. Other biomarkers that have been studied and shown to be associated with ovarian cancer include CA 72.4 and CA 15.3 [29,30]. These biomarkers were used in combination with CA 125, but their use did not improve early detection of ovarian cancer compared to CA 125 alone [31,32].
However, a longitudinal, multi-biomarker-based approach for early diagnosis could identify cancers that CA 125 alone might miss, potentially allowing earlier detection than routine clinical methods. This strategy may also detect ovarian cancer before CA125 does, thereby contributing to a greater reduction in late-stage disease incidence. Several emerging biomarkers under investigation for ovarian cancer detection are the Copenhagen Index, specific CA 125 glycovariant forms, the Olink proteomic panel, and the ORF1p protein derived from LINE-1 elements [33,34,35,36].
The limited effectiveness of protein biomarkers in detecting early ovarian cancer may stem from the small size of early-stage tumors and/or the low levels of biomarker expression or release. However, even small quantities of cancer might be sufficient to stimulate the production of autoantibodies [37]. Most high-grade serous ovarian cancers are characterized by mutations in the tumor suppressor gene TP53. These autoantibodies are elevated in over 20% of ovarian cancers, and these increases can be detected months before a diagnosis or before changes in CA 125 levels are observed [38]. Other autoantibodies being studied for the early detection of ovarian cancer include anti-interleukin 8 (IL-8) antibodies and anti-homeobox gene A7 (HOXA7) antibodies [39,40].
MicroRNAs (miRNAs) are stable molecules circulating in body fluids, either bound to proteins or within vesicles like exosomes [41]. These short, non-coding RNAs regulate gene expression and have shown potential as cancer biomarkers, particularly for epithelial ovarian cancer (EOC) [42]. Specific miRNA profiles, such as elevated levels of miR-182, miR-200a, miR-200b, and miR-200c, have been linked to serous EOC, with some combinations, like miR-200b and miR-200c, effectively distinguishing EOC from controls [43]. The diagnostic performance of miR-205 combined with let-7f was particularly strong in identifying epithelial ovarian cancer, with notable effectiveness in early-stage cases [44]. An eight-miRNA signature effectively discriminated between early-stage EOC and benign tumors [45]. Additionally, a neural network-based miRNA algorithm achieved the most accurate performance for EOC diagnosis so far [27]. However, there is a need for further studies comparing miRNAs with established biomarkers like CA125, HE4, and transvaginal sonography (TVS) in prospective trials [26].
A study conducted between 2018 and 2022 on cohorts of 96 and 26 patients, respectively, analyzed intrauterine fluid following the instillation of 5–10 mL of saline solution into the uterus. The cohort included women diagnosed with early-stage ovarian cancer, advanced-stage ovarian cancer, benign uterine pathologies, and endometrial cancer. Lavage samples were analyzed after centrifugation, leading to the identification of a panel of seven metabolites. These metabolites included norepinephrine, beta-alanine, vanillylmandelic acid, phenylalanine, 12-S-hydroxy-5,8,10-heptadecatrienoic acid, tyrosine, and crithmumdiol. The analyses revealed decreased levels of vanillylmandelic acid and elevated levels of norepinephrine in the majority of patients diagnosed with ovarian cancer [46]. It has been demonstrated that the increase in metabolite levels varies depending on the stage of tumor growth. During the initial phase of tumor development, metabolites such as epinephrine and crithmumdiol show a marked increase, whereas, in the accelerated growth phase, oxidized glutathione and L-3,4-dihydroxyphenylalanine (L-DOPA) exhibit significant elevation during tumor progression. These metabolites provide valuable potential for the early diagnosis of ovarian cancer, with some of them offering insights into the different stages of tumor growth, thereby providing important contextual information [46].
Genomics and its role in the early diagnosis of ovarian cancer have been extensively studied. With the advancement of technology, the economic burden has decreased, allowing targeted next-generation sequencing (NGS) to become increasingly accessible in clinical practice. This approach assists specialists in the early identification of predictive tumor markers. There is a wide range of genomic testing available, from targeted sequencing to whole-exome sequencing (WES) and whole-genome sequencing (WGS). These technologies enable the identification of nucleotide variations, chromosomal rearrangements, and copy number alterations. Copy number alterations (CNAs) involve the deletion or amplification of genomic fragments, which are particularly prevalent in cancer and play a crucial role in its development and progression [47].
Another important aspect involves epigenetic modifications. Abnormal DNA methylation is a commonly encountered modification in cancers, with ovarian cancer being no exception. Several studies have explored this issue, suggesting that DNA methylation could serve as an early diagnostic marker for ovarian cancer [47].
The WID-OC Index (Women’s Risk Identification for Ovarian Cancer) is an example of a diagnostic test utilizing DNA methylation analysis for the detection of ovarian and endometrial cancer. The methylated DNA is extracted from cervical cell samples [48].
Circulating tumor DNA (ctDNA) also plays a significant role in the early detection of ovarian cancer. It can be quantified from blood samples, as cancer cells release it into the bloodstream. Techniques such as targeted next-generation sequencing (NGS) and digital polymerase chain reaction (PCR) can be employed for this purpose. Some studies have suggested that combining chromosomal anomaly analysis with genetic mutation detection may enhance ctDNA detection sensitivity [47].

5. Emerging Imaging Techniques for Early Detection of Ovarian Cancer

Early-stage ovarian tumors are currently estimated to measure less than 3 mm and may persist at this size for several years. This underscores the need for advanced imaging techniques capable of detecting tumors at such minimal dimensions [49]. Magnetic resonance imaging (MRI) and magnetic relaxometry (MRX) can detect magnetic nanoparticles without using ionizing radiation [50]. SQUID-based technology detects differences in magnetic relaxation behavior, enabling the distinction between ovarian cancer cells and healthy cells by tracking how specific nanoparticles interact at the cellular level [34,50].
This technique has been applied in various cancer models, including breast cancer and leukemia, and shows promise for early ovarian cancer detection [51]. Additionally, an optical sensor, engineered with an HE4 antibody-carbon nanotube complex, was tested in mouse models of ovarian cancer and successfully detected cancer biomarkers noninvasively [52].
A systematic review analyzing 14 articles by Sian Mitchell et al. highlighted the significant potential of artificial intelligence (AI) in the early diagnosis of ovarian cancer, with the prospect of improving patient management and minimizing unnecessary interventions. Furthermore, AI could contribute to the centralization, triage, and referral of patients to specialized centers based on imaging examination results. In this context, the introduction of 3D imaging could enhance diagnostic accuracy. A study conducted by Acharya et al. demonstrated a diagnostic accuracy of 100% with a sensitivity of 99.2%. However, a current limitation is the restricted access to 3D imaging technology [53].
Doppler ultrasound is commonly used to assess central ovarian blood flow to distinguish between benign and malignant ovarian masses, but it cannot detect small ovarian cancers [54,55]. The introduction of microbubble contrast agents in ultrasound has improved the visualization of neovascularization in some ovarian masses. A study by Xiang et al. demonstrated that 3-D microbubble contrast-enhanced transvaginal sonography (TVS) could differentiate small benign and malignant ovarian masses with high sensitivity (100%) and specificity (98%). However, this technique still faces limitations in imaging the fallopian tubes and detecting small ovarian lesions [55,56].
Light-induced autofluorescence has been used to detect precancerous lesions in various organs, such as the cervix. Autofluorescence imaging, utilized on fallopian tubes obtained through surgical removal, demonstrated a sensitivity of 73%, a specificity of 83%, and a positive predictive value (PPV) of 57% in identifying ovarian or serous tubal intraepithelial carcinomas. Advancing this technology further, the subsequent phase will incorporate in vivo screening using falloposcopy [57].
As summarized in Table 1, the key biomarkers identified in this study demonstrate diverse patterns of expression across samples, highlighting their potential utility in improving early detection strategies and guiding the development of more effective screening methods for ovarian cancer.
Table 1. Overview of Prognostic Markers for Early Detection of Ovarian Cancer (Table 1 provides a concise summary of all prognostic markers discussed throughout the article, integrating the main findings for ease of reference).

6. Surgical Approach

In women at high risk for ovarian cancer, such as those carrying BRCA1 and BRCA2 mutations, individuals with Lynch syndrome, or those harboring mutations in genes associated with ovarian cancer—BRIP1, RAD51C, RAD51D, TP53, and PALB2—as well as those with a family history of Lynch syndrome, colorectal, breast, or ovarian cancer, bilateral salpingo-oophorectomy is the recommended prophylactic intervention.
For these patients, it is crucial that histopathological examination includes a meticulous analysis of the fallopian tubes, particularly the fimbriae. This approach follows the SEE-FIM (Sectioning and Extensively Examining the Fimbria) protocol, which is designed to enhance the detection of precursor lesions [50].
The necessity of applying this protocol arises from the fact that fallopian tube cancer, particularly high-grade serous carcinoma (HGSC), can exhibit an extremely aggressive biological behavior. A precise and early diagnosis is crucial, as it directly impacts the oncologic management and therapeutic approach for the patient [52].
Furthermore, even a seemingly localized tubal carcinoma has a high propensity for peritoneal dissemination, leading to secondary implants with rapid disease progression. Therefore, a thorough histopathological assessment using the SEE-FIM protocol is essential for accurate staging, prognosis determination, and treatment planning [49].

7. Future Directions

On one hand, genomics and proteomics, and on the other, the inclusion of artificial intelligence in the early diagnosis of ovarian cancer, are making a significant impact on the diagnosis of this highly debated cancer due to its unique characteristic of being diagnosed at advanced stages, when survival rates dramatically decrease [46].
DNA methylation represents an epigenetic regulatory mechanism that occurs through the covalent addition of a CH3 (methyl) group to a DNA base. These modifications lead to an increased presence of methyl groups along the DNA, constituting a form of epigenetic regulation. The accumulation of methyl groups, known as hypermethylation, can result in the silencing of tumor suppressor genes. By understanding this process, it becomes possible to investigate its dynamics in ovarian tissue and thereby identify oncogenic alterations at an early stage [46,58]. Barrett et al. analyzed DNA methylation in the context of ovarian cancer. Part of their analysis involved a cohort of 786 patients, for which the AUC (area under the curve) for ovarian neoplasm detection was 0.76, indicating a fair to good discriminative ability, which can be considered an encouraging result. On the other hand, they also analyzed a group of BRCA1 gene carriers, focusing in this case exclusively on patients at high risk. In this subgroup, an AUC of 0.62 was obtained, reflecting only modest accuracy for risk prediction in these patients. This demonstrates that, at least at present, this test cannot be considered sufficiently reliable to be implemented in clinical guidelines [46,59,60].
Widschwendter et al. conducted a study on a cohort of 648 serum samples and 699 ovarian tissue samples. The researchers analyzed the amount of circulating cell-free DNA, also addressing cases in which leukocyte-derived DNA leakage into the serum led to abnormally elevated DNA levels. Despite this limitation, the study successfully demonstrated that, through methylation-based techniques and a well-defined panel of markers, it is possible to distinguish patients with neoplastic lesions from those with benign ovarian formations. The findings of this study highlight the potential for earlier diagnosis—up to two years before current diagnostic methods—representing a significant step forward in reducing ovarian cancer–related mortality [46,61].
Building on the study conducted by Isaac Kinde et al., who observed the evolution of the Papanicolaou (Pap) test from conventional smears to liquid-based testing and correlated this with the possibility of analyzing HPV DNA from these samples, they drew a parallel based on the premise that tumor DNA from endometrial and ovarian cancers should be present in such samples through the gravitational migration of these DNA fragments toward the cervix. Their study analyzed 22 types of ovarian neoplasms and successfully detected tumor DNA in approximately 41% of ovarian-origin neoplasms. Although further research and methodological improvements are needed, they demonstrated that ovarian tumor DNA can indeed be detected in Pap samples [46,62]. Building on these premises, Tzu-I Wu et al. conducted a study involving both healthy and pathological ovarian tissue, as well as healthy and pathological cervical smears, and also included retrospective data comprising both pathological ovarian tissue and healthy fallopian tissue. Following the classification of 151 genes, only four genes met the stringent criteria of their study: AMPD3, TBX15, NRN1, and AOX1. Using these data, they established a predictive equation incorporating only three of the four genes, excluding AOX1. This three-gene model demonstrated a sensitivity of 81% and a specificity of 84%. Through this study, they not only validated the findings of Isaac Kinde et al. but also emphasized that the careful selection of biomarkers is crucial. They concluded that, although promising, this method requires additional studies to confirm its clinical utility [46,63].
These new diagnostic approaches have the potential to become powerful tools for early detection, but further studies are needed to assess their implementation in future best practice guidelines [53].

8. Conclusions

Ovarian cancer is notorious for its aggressive behavior and dismal outcomes, largely due to the persistent difficulties in early detection. Traditional screening methods, such as transvaginal ultrasound (TVS) and CA125 testing, have significant limitations in detecting early-stage ovarian cancer. However, new early detection strategies are being actively researched, focusing on innovative biomarkers, circulating DNA, PCR tests from Pap swabs, autoantibodies, microRNAs, and advanced imaging techniques. The UKCTOCS study showed that multimodal screening can increase the detection of early-stage ovarian cancer, potentially reducing the incidence of advanced-stage cases. However, this approach did not lead to a reduction in mortality. In the future, as therapeutic methods improve, early detection could translate into better survival rates. While routine ovarian cancer screening is not currently recommended for the general population by international guidelines, it may be appropriate for high-risk groups, such as those with Lynch syndrome. In these populations, screening should not replace risk-reducing surgery, but guidelines for ovarian cancer screening are urgently needed for women who decline surgical intervention. In this context, a rigorous analysis of the utility of genomics in this pathology is essential, considering the significant role of epigenetic factors. Both standalone genomics and the reevaluation of existing scores, such as ROMA, with the aim of developing new integrated scores with higher accuracy and sensitivity, are crucial for understanding this pathology and, consequently, for creating opportunities to modify the prognosis of this oncologic condition. A molecular-level understanding of this disease will facilitate the development of effective methods for early diagnosis, leading to timely treatment and significantly improved clinical outcomes. In conclusion, there is a critical need for the development of more effective screening methods, particularly for high-risk populations, to improve early detection and ultimately enhance survival outcomes in ovarian cancer.

Author Contributions

Conceptualization, R.-E.B. and C.-E.D.; writing—original draft preparation, M.-N.M., R.D.C. and C.-E.D.; writing—review and editing, R.-E.B. and C.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created. All data supporting this article are available online.

Conflicts of Interest

Author Robert Daniel Ciortan was employed by the company Altstadtpraxis Aarau GmbH. The remaining 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.

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Advancing Preventive Medicine: Highlights from the First International Congress of Preventive Medicine
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