Assessment of Different Neoplasias in the Adnexa (ADNEX) is the best-performing model to estimate the risk of malignancy in ovarian tumors. We assessed the incremental value of serum proteins over ADNEX predictors in an exploratory multicenter study. In a cohort of 932 patients with an adnexal mass scheduled for surgery, 33 serum proteins were preoperatively quantified using multiplex high-throughput and electrochemiluminescence immunoassays. Using multivariable logistic regression, ADNEX predictors alone had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% confidence interval, 0.89-0.93) to discriminate benign from malignant tumors. This AUC increased most after adding HE4 (+0.03) or CA125 (+0.02). CA72.4 increased AUCs to discriminate secondary metastatic tumors from benign (+0.03), borderline (+0.03), and stage I tumors (+0.03). CA15.3 increased AUCs to discriminate borderline tumors from stage I (+0.01) and stage II-IV tumors (+0.03). While CA125 and HE4 had the highest added value over ADNEX predictors, CA72.4 and CA15.3 may improve discrimination between malignant subtypes.

Department of Biomedical Data Sciences Leiden University Medical Centre Leiden the Netherlands

Department of Development and Regeneration KU Leuven Leuven Belgium

Department of Gynecologic Oncology National Cancer Institute of Milan Milan Italy

Department of Laboratory Medicine University Hospitals Leuven Leuven Belgium

Department of Metabolism Digestion and Reproduction Faculty of Medicine Imperial College London London UK

Department of Microbiology Immunology and Transplantation Laboratory of Virology and Chemotherapy KU Leuven Leuven Belgium

Department of Obstetrics and Gynaecology University Hospitals Leuven Leuven Belgium

Department of Obstetrics and Gynecology Ziekenhuis Oost Limburg Genk Belgium

Department of Oncology Gynaecological Oncology Leuven Cancer Institute KU Leuven Leuven Belgium

Department of Oncology Laboratory of Tumor Immunology and Immunotherapy Leuven Cancer Institute KU Leuven Leuven Belgium

Department of Pathology University Hospitals Leuven Leuven Belgium

Dipartimento Scienze della Salute della Donna del Bambino e di Sanità Pubblica Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy

Gynecologic Oncology Centre Department of Gynecology Obstetrics and Neonatology 1st Faculty of Medicine Charles University and General University Hospital Prague Prague Czech Republic

Leuven Unit for Health Technology Assessment Research KU Leuven Leuven Belgium

Oncoinvent AS Oslo Norway

Queen Charlotte's and Chelsea Hospital Imperial College London UK

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Database SEER. National Cancer Institute Cancer Stat Facts: Ovarian Cancer. https://seer.cancer.gov/statfacts/html/ovary.html

Froyman W., Landolfo C., De Cock B., Wynants L., Sladkevicius P., Testa A.C., Van Holsbeke C., Domali E., Fruscio R., Epstein E., et al. Risk of complications in patients with conservatively managed ovarian tumours (IOTA5): a 2-year interim analysis of a multicentre, prospective, cohort study. Lancet Oncol. 2019;20:448–458. doi: 10.1016/S1470-2045(18)30837-4. PubMed DOI

Colombo N., Ledermann J.A., ESMO Guidelines Committee Electronic address clinicalguidelines@esmo org Updated treatment recommendations for newly diagnosed epithelial ovarian carcinoma from the ESMO Clinical Practice Guidelines. Ann. Oncol. 2021;32:1300–1303. doi: 10.1016/j.annonc.2021.07.004. PubMed DOI

Harter P., Gershenson D., Lhomme C., Lecuru F., Ledermann J., Provencher D.M., Mezzanzanica D., Quinn M., Maenpaa J., Kim J.-W., et al. Gynecologic Cancer InterGroup (GCIG) Consensus Review for Ovarian Tumors of Low Malignant Potential (Borderline Ovarian Tumors) Int. J. Gynecol. Cancer. 2014;24:S5–S8. doi: 10.1097/IGC.0000000000000282. PubMed DOI

Van Calster B., Van Hoorde K., Valentin L., Testa A.C., Fischerova D., Van Holsbeke C., Savelli L., Franchi D., Epstein E., Kaijser J., et al. Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study. BMJ. 2014;349:g5920. doi: 10.1136/bmj.g5920. PubMed DOI PMC

Van Calster B., Valentin L., Froyman W., Landolfo C., Ceusters J., Testa A.C., Wynants L., Sladkevicius P., Van Holsbeke C., Domali E., et al. Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study. BMJ. 2020;370 doi: 10.1136/bmj.m2614. PubMed DOI PMC

Barreñada L., Ledger A., Dhiman P., Collins G., Wynants L., Verbakel J.Y., Timmerman D., Valentin L., Van Calster B. ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies. BMJ Med. 2024;3 doi: 10.1136/bmjmed-2023-000817. PubMed DOI PMC

Olsen M., Lof P., Stiekema A., van den Broek D., Wilthagen E.A., Bossuyt P.M., Lok C.A.R. The diagnostic accuracy of human epididymis protein 4 (HE4) for discriminating between benign and malignant pelvic masses: a systematic review and meta-analysis. Acta Obstet. Gynecol. Scand. 2021;100:1788–1799. doi: 10.1111/aogs.14224. PubMed DOI

Holder A.M., Dedeilia A., Sierra-Davidson K., Cohen S., Liu D., Parikh A., Boland G.M. Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours. Nat. Rev. Cancer. 2024;24:498–512. doi: 10.1038/s41568-024-00705-7. PubMed DOI

Hanahan D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 2022;12:31–46. doi: 10.1158/2159-8290.CD-21-1059. PubMed DOI

Hiam-Galvez K.J., Allen B.M., Spitzer M.H. Systemic immunity in cancer. Nat. Rev. Cancer. 2021;21:345–359. doi: 10.1038/s41568-021-00347-z. PubMed DOI PMC

Sato E., Olson S.H., Ahn J., Bundy B., Nishikawa H., Qian F., Jungbluth A.A., Frosina D., Gnjatic S., Ambrosone C., et al. Intraepithelial CD8 + tumor-infiltrating lymphocytes and a high CD8 +/regulatory T cell ratio are associated with favorable prognosis in ovarian cancer. Proc. Natl. Acad. Sci. USA. 2005;102:18538–18543. doi: 10.1073/pnas.0509182102. PubMed DOI PMC

Curiel T.J., Coukos G., Zou L., Alvarez X., Cheng P., Mottram P., Evdemon-Hogan M., Conejo-Garcia J.R., Zhang L., Burow M., et al. Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival. Nat. Med. 2004;10:942–949. doi: 10.1038/nm1093. PubMed DOI

Sprooten J., Vankerckhoven A., Vanmeerbeek I., Borras D.M., Berckmans Y., Wouters R., Laureano R.S., Baert T., Boon L., Landolfo C., et al. Peripherally-driven myeloid NFkB and IFN/ISG responses predict malignancy risk, survival, and immunotherapy regime in ovarian cancer. J. Immunother. Cancer. 2021;9 doi: 10.1136/jitc-2021-003609. PubMed DOI PMC

Fucikova J., Coosemans A., Orsulic S., Cibula D., Vergote I., Galluzzi L., Spisek R. Immunological configuration of ovarian carcinoma: features and impact on disease outcome. J. Immunother. Cancer. 2021;9 doi: 10.1136/jitc-2021-002873. PubMed DOI PMC

Coosemans A., Baert T., Ceusters J., Busschaert P., Landolfo C., Verschuere T., Van Rompuy A.-S., Vanderstichele A., Froyman W., Neven P., et al. Myeloid-derived suppressor cells at diagnosis may discriminate between benign and malignant ovarian tumors. Int. J. Gynecol. Cancer. 2019;29:1381–1388. doi: 10.1136/ijgc-2019-000521. PubMed DOI

Landolfo C., Achten E.T.L., Ceusters J., Baert T., Froyman W., Heremans R., Vanderstichele A., Thirion G., Van Hoylandt A., Claes S., et al. Assessment of protein biomarkers for preoperative differential diagnosis between benign and malignant ovarian tumors. Gynecol. Oncol. 2020;159:811–819. doi: 10.1016/j.ygyno.2020.09.025. PubMed DOI

Mantovani A., Gray P.A., Van Damme J., Sozzani S. Macrophage-derived chemokine (MDC) J. Leukoc. Biol. 2000;68:400–404. PubMed

Lopez-Yrigoyen M., Cassetta L., Pollard J.W. Macrophage targeting in cancer. Ann. N. Y. Acad. Sci. 2021;1499:18–41. doi: 10.1111/nyas.14377. PubMed DOI

Palmer C., Duan X., Hawley S., Scholler N., Thorpe J.D., Sahota R.A., Wong M.Q., Wray A., Bergan L.A., Drescher C.W., et al. Systematic Evaluation of Candidate Blood Markers for Detecting Ovarian Cancer. PLoS One. 2008;3 doi: 10.1371/journal.pone.0002633. PubMed DOI PMC

Mor G., Visintin I., Lai Y., Zhao H., Schwartz P., Rutherford T., Yue L., Bray-Ward P., Ward D.C. Serum protein markers for early detection of ovarian cancer. Proc. Natl. Acad. Sci. USA. 2005;102:7677–7682. doi: 10.1073/pnas.0502178102. PubMed DOI PMC

Mari R., Mamessier E., Lambaudie E., Provansal M., Birnbaum D., Bertucci F., Sabatier R. Liquid Biopsies for Ovarian Carcinoma: How Blood Tests May Improve the Clinical Management of a Deadly Disease. Cancers (Basel) 2019;11:774. doi: 10.3390/cancers11060774. PubMed DOI PMC

Husseinzadeh N. Status of tumor markers in epithelial ovarian cancer has there been any progress? A review. Gynecol. Oncol. 2011;120:152–157. doi: 10.1016/j.ygyno.2010.09.002. PubMed DOI

Pils D., Tong D., Hager G., Obermayr E., Aust S., Heinze G., Kohl M., Schuster E., Wolf A., Sehouli J., et al. A combined blood based gene expression and plasma protein abundance signature for diagnosis of epithelial ovarian cancer - a study of the OVCAD consortium. BMC Cancer. 2013;13:178. doi: 10.1186/1471-2407-13-178. PubMed DOI PMC

Mukama T., Fortner R.T., Katzke V., Hynes L.C., Petrera A., Hauck S.M., Johnson T., Schulze M., Schiborn C., Rostgaard-Hansen A.L., et al. Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer. Br. J. Cancer. 2022;126:1301–1309. doi: 10.1038/s41416-021-01697-z. PubMed DOI PMC

Ghose A., McCann L., Makker S., Mukherjee U., Gullapalli S.V.N., Erekkath J., Shih S., Mahajan I., Sanchez E., Uccello M., et al. Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4. Ther. Adv. Med. Oncol. 2024;16 doi: 10.1177/17588359241233225. PubMed DOI PMC

Timmerman D., Valentin L., Bourne T.H., Collins W.P., Verrelst H., Vergote I., International Ovarian Tumor Analysis IOTA Group Terms, definitions and measurements to describe the sonographic features of adnexal tumors: a consensus opinion from the International Ovarian Tumor Analysis (IOTA) group. Ultrasound Obstet. Gynecol. 2000;16:500–505. doi: 10.1046/j.1469-0705.2000.00287.x. PubMed DOI

Sauerbrei W., Taube S.E., McShane L.M., Cavenagh M.M., Altman D.G. Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): An Abridged Explanation and Elaboration. J. Natl. Cancer Inst. 2018;110:803–811. doi: 10.1093/jnci/djy088. PubMed DOI PMC

Prat J., FIGO Committee on Gynecologic Oncology Staging classification for cancer of the ovary, fallopian tube, and peritoneum. Int. J. Gynaecol. Obstet. 2014;124:1–5. doi: 10.1016/j.ijgo.2013.10.001. PubMed DOI

Hauptmann S., Friedrich K., Redline R., Avril S. Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria. Virchows Arch. 2017;470:125–142. doi: 10.1007/s00428-016-2040-8. PubMed DOI PMC

Yokoyama Y., Moriya T., Takano T., Shoji T., Takahashi O., Nakahara K., Yamada H., Yaegashi N., Okamura K., Izutsu T., et al. Clinical outcome and risk factors for recurrence in borderline ovarian tumours. Br. J. Cancer. 2006;94:1586–1591. doi: 10.1038/sj.bjc.6603139. PubMed DOI PMC

Buuren S.v., Groothuis-Oudshoorn K. mice : Multivariate Imputation by Chained Equations in R. J. Stat. Softw. 2011;45:1–67. doi: 10.18637/jss.v045.i03. DOI

Gengsheng Q., Hotilovac L. Comparison of non-parametric confidence intervals for the area under the ROC curve of a continuous-scale diagnostic test. Stat. Methods Med. Res. 2008;17:207–221. doi: 10.1177/0962280207087173. PubMed DOI

Devriendt S., Antonio K., Reynkens T., Verbelen R. Sparse regression with Multi-type Regularized Feature modeling. Insur. Math. Econ. 2021;96:248–261. doi: 10.1016/j.insmatheco.2020.11.010. DOI

Friedman J., Hastie T., Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent. J. Stat. Softw. 2010;33:1–22. doi: 10.18637/jss.v033.i01. PubMed DOI PMC

Van Calster B., Vergouwe Y., Looman C.W.N., Van Belle V., Timmerman D., Steyerberg E.W. Assessing the discriminative ability of risk models for more than two outcome categories. Eur. J. Epidemiol. 2012;27:761–770. doi: 10.1007/s10654-012-9733-3. PubMed DOI

Van Calster B., Van Belle V., Vergouwe Y., Timmerman D., Van Huffel S., Steyerberg E.W. Extending the c -statistic to nominal polytomous outcomes: the Polytomous Discrimination Index. Stat. Med. 2012;31:2610–2626. doi: 10.1002/sim.5321. PubMed DOI

Steyerberg E.W., Harrell F.E., Borsboom G.J., Eijkemans M.J., Vergouwe Y., Habbema J.D. Internal validation of predictive models. J. Clin. Epidemiol. 2001;54:774–781. doi: 10.1016/S0895-4356(01)00341-9. PubMed DOI

Newcombe R.G. Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat. Med. 1998;17:857–872. doi: 10.1002/(SICI)1097-0258(19980430)17:8<857::AID-SIM777>3.0.CO;2-E. PubMed DOI