{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:16:09Z","timestamp":1760058969201,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,5,17]],"date-time":"2025-05-17T00:00:00Z","timestamp":1747440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background\/Objectives: Despite great efforts from both clinical and pathological sides to address the extent of metastatic inguinal lymph node involvement in patients with vulvar cancer, current research attempts are still mostly aimed at identifying new imaging parameters or superior tissue diagnostic workflows rather than alternative ways of statistical data analysis. In the present study, we therefore establish a supervised machine learning algorithm to predict groin metastasis in patients with squamous cell carcinoma of the vulva (VSCC) based on classical histomorphological features. Methods: In total, 157 patients with VSCC were included in this retrospective study. After initial exploration of valuable clinicopathological predictor variables by means of Spearman correlation, a decision tree was trained and internally validated (5-fold cross-validation) using a training data set (n = 126) and afterwards externally validated employing a holdout validation data set (n = 31) using standard metrices such sensitivity, positive predictive value, and AUROC curve. Results: Our established classifier can predict inguinal lymph node status with an internal accuracy of 79.4% (AUROC value = 0.64). Reaching similar performances and an overall accuracy of 83.9% on an unknown data input (external validation set), our classifier demonstrates robustness. Conclusions: The presented results suggest that machine learning can predict groin lymph node status in VSCC based on histological findings of the primary tumor. Such research attempts may be useful in the future for an additional assessment of inguinal lymph nodes, aiming to maximize oncological safety when targeting the most accurate diagnosis of lymph node involvement.<\/jats:p>","DOI":"10.3390\/jcm14103510","type":"journal-article","created":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T06:31:29Z","timestamp":1747636289000},"page":"3510","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5358-2751","authenticated-orcid":false,"given":"Gilbert Georg","family":"Klamminger","sequence":"first","affiliation":[{"name":"Department of General and Special Pathology, Saarland University (USAAR) and Saarland University Medical Center (UKS), 66424 Homburg, Germany"},{"name":"Department of Obstetrics and Gynecology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3865-6833","authenticated-orcid":false,"given":"Meletios P.","family":"Nigdelis","sequence":"additional","affiliation":[{"name":"Department of Gynecology, Obstetrics and Reproductive Medicine, Saarland University Medical Center (UKS), 66424 Homburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1055-7249","authenticated-orcid":false,"given":"Annick","family":"Bitterlich","sequence":"additional","affiliation":[{"name":"Department of General and Special Pathology, Saarland University (USAAR) and Saarland University Medical Center (UKS), 66424 Homburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bashar","family":"Haj Hamoud","sequence":"additional","affiliation":[{"name":"Department of Gynecology, Obstetrics and Reproductive Medicine, Saarland University Medical Center (UKS), 66424 Homburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erich-Franz","family":"Solomayer","sequence":"additional","affiliation":[{"name":"Department of Gynecology, Obstetrics and Reproductive Medicine, Saarland University Medical Center (UKS), 66424 Homburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1547-4968","authenticated-orcid":false,"given":"Annette","family":"Hasenburg","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mathias","family":"Wagner","sequence":"additional","affiliation":[{"name":"Department of General and Special Pathology, Saarland University (USAAR) and Saarland University Medical Center (UKS), 66424 Homburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1080\/00016340802506305","article-title":"Prognostic Factors for Recurrence and Survival in Primary Vulvar Squamous Cell Cancer","volume":"87","author":"Ayhan","year":"2008","journal-title":"Acta Obstet. Gynecol. Scand."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1097\/01.pgp.0000228140.94339.db","article-title":"Identification of Potential Prognostic Markers for Vulvar Cancer Using Immunohistochemical Staining of Tissue Microarrays","volume":"26","author":"Fons","year":"2007","journal-title":"Int. J. Gynecol. Pathol."},{"key":"ref_3","first-page":"1113","article-title":"Carcinoma of the Vulva: Clinicopathologic Factors Involved in Inguinal and Pelvic Lymph Node Metastasis","volume":"35","author":"Abrao","year":"1990","journal-title":"J. Reprod. Med. Obstet. Gynecol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.humpath.2022.05.009","article-title":"Tumor Budding Activity Is an Independent Prognostic Factor in Squamous Cell Carcinoma of the Vulva","volume":"126","author":"Zare","year":"2022","journal-title":"Hum. Pathol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1111\/aogs.14689","article-title":"TP53 Mutation and Human Papilloma Virus Status as Independent Prognostic Factors in a Norwegian Cohort of Vulva Squamous Cell Carcinoma","volume":"103","author":"Dongre","year":"2023","journal-title":"Acta Obstet. Gynecol. Scand."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1007\/s12672-025-02381-x","article-title":"Histopathological Biomarkers in Squamous Cell Carcinoma of the Vulva: The Prognostic Relevance of Tumor-Infiltrating Lymphocytes (TILs)\u2014A Retrospective Study of 157 Cases","volume":"16","author":"Klamminger","year":"2025","journal-title":"Discov. Oncol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1136\/ijgc-2019-000526","article-title":"Prognostic Factors in Patients with Vulvar Cancer: The VULCAN Study","volume":"30","author":"Zapardiel","year":"2020","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.ygyno.2005.12.027","article-title":"Clinical and Pathological Prognostic Factors in Squamous Cell Carcinoma of the Vulva","volume":"102","author":"Raspagliesi","year":"2006","journal-title":"Gynecol. Oncol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1111\/IGC.0b013e3181996a78","article-title":"Recurrence Patterns and Prognostic Factors in Chinese Patients With Squamous Cell Carcinoma of the Vulva Treated With Primary Surgery","volume":"19","author":"Cheng","year":"2009","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1016\/j.ygyno.2004.08.015","article-title":"Patterns of Recurrence and Disease-Free Survival in Advanced Squamous Cell Carcinoma of the Vulva","volume":"95","author":"Lataifeh","year":"2004","journal-title":"Gynecol. Oncol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1097\/IGC.0b013e31823eed4c","article-title":"Prognostic Role of Lymph Node Metastases in Vulvar Cancer and Implications for Adjuvant Treatment","volume":"22","author":"Woelber","year":"2012","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Schwab, R., Stewen, K., B\u00fchrer, T.-L., Schmidt, M.W., van der Ven, J., Anic, K., Linz, V.C., Hamoud, B.H., Brenner, W., and Peters, K. (2023). Current Approaches to the Management of Sentinel Node Procedures in Early Vulvar Cancer in Germany: A Web-Based Nationwide Analysis of Practices. J. Clin. Med., 12.","DOI":"10.3390\/jcm12052048"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1136\/ijgc-2023-004486","article-title":"European Society of Gynaecological Oncology Guidelines for the Management of Patients with Vulvar Cancer-Update 2023","volume":"33","author":"Oonk","year":"2023","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"117","DOI":"10.6004\/jnccn.2024.0013","article-title":"Vulvar Cancer, Version 3.2024, NCCN Clinical Practice Guidelines in Oncology","volume":"22","author":"Yashar","year":"2024","journal-title":"Natl. Compr. Cancer Netw."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Asami, Y., Hiranuma, K., Takayanagi, D., Matsuda, M., Shimada, Y., Kato, M.K., Kuno, I., Murakami, N., Komatsu, M., and Hamamoto, R. (2022). Predictive Model for the Preoperative Assessment and Prognostic Modeling of Lymph Node Metastasis in Endometrial Cancer. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-23252-3"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Ren, Z., Chen, B., Hong, C., Yuan, J., Deng, J., Chen, Y., Ye, J., and Li, Y. (2023). The Value of Machine Learning in Preoperative Identification of Lymph Node Metastasis Status in Endometrial Cancer: A Systematic Review and Meta-Analysis. Front. Oncol., 13.","DOI":"10.3389\/fonc.2023.1289050"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"9613","DOI":"10.3390\/curroncol29120755","article-title":"Prediction of Postoperative Pathologic Risk Factors in Cervical Cancer Patients Treated with Radical Hysterectomy by Machine Learning","volume":"29","author":"Ou","year":"2022","journal-title":"Curr. Oncol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e17","DOI":"10.3802\/jgo.2024.35.e17","article-title":"A Machine Learning-Based Prediction Model of Pelvic Lymph Node Metastasis in Women with Early-Stage Cervical Cancer","volume":"35","author":"Monthatip","year":"2024","journal-title":"J. Gynecol. Oncol."},{"key":"ref_19","first-page":"1852","article-title":"Construction of Prediction Model of Lymph Node Metastasis of Early Cervical Cancer Based on Machine Learning Algorithm and Its Application: Experience of 204 Cases in a Single Center","volume":"15","author":"Meng","year":"2023","journal-title":"Am. J. Transl. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/s43856-023-00282-0","article-title":"Predicting Lymph Node Metastasis from Primary Tumor Histology and Clinicopathologic Factors in Colorectal Cancer Using Deep Learning","volume":"3","author":"Krogue","year":"2023","journal-title":"Commun. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e20928","DOI":"10.1016\/j.heliyon.2023.e20928","article-title":"Application of Machine Learning Algorithms to Predict Lymph Node Metastasis in Gastric Neuroendocrine Neoplasms","volume":"9","author":"Liu","year":"2023","journal-title":"Heliyon"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Shahriarirad, R., Meshkati Yazd, S.M., Fathian, R., Fallahi, M., Ghadiani, Z., and Nafissi, N. (2024). Prediction of Sentinel Lymph Node Metastasis in Breast Cancer Patients Based on Preoperative Features: A Deep Machine Learning Approach. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-51244-y"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"zrae033","DOI":"10.1093\/bjsopen\/zrae033","article-title":"Use of Artificial Intelligence for the Prediction of Lymph Node Metastases in Early-Stage Colorectal Cancer: Systematic Review","volume":"8","author":"Thompson","year":"2024","journal-title":"BJS Open"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, Y., Xie, F., Xiong, Q., Lei, H., and Feng, P. (2022). Machine Learning for Lymph Node Metastasis Prediction of in Patients with Gastric Cancer: A Systematic Review and Meta-Analysis. Front. Oncol., 12.","DOI":"10.3389\/fonc.2022.946038"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"World Medical Association (2013). World Medical Association Declaration of Helsinki. JAMA, 310, 2191.","DOI":"10.1001\/jama.2013.281053"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Brierley, J.D., and Gospodarowicz, M.K. (2016). TNM Classification of Malignant Tumours, Wiley-Blackwell. [8th ed.].","DOI":"10.1002\/9780471420194.tnmc26.pub3"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"102164","DOI":"10.1016\/j.artmed.2021.102164","article-title":"Artificial Intelligence in Gynecologic Cancers: Current Status and Future Challenges\u2014A Systematic Review","volume":"120","author":"Akazawa","year":"2021","journal-title":"Artif. Intell. Med."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"103808","DOI":"10.1016\/j.critrevonc.2022.103808","article-title":"Machine Learning Applications in Gynecological Cancer: A Critical Review","volume":"179","author":"Fiste","year":"2022","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1007\/s10462-024-10872-6","article-title":"Comprehensive Analysis of Artificial Intelligence Techniques for Gynaecological Cancer: Symptoms Identification, Prognosis and Prediction","volume":"57","author":"Gandotra","year":"2024","journal-title":"Artif. Intell. Rev."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1136\/ijgc-2024-005580","article-title":"Preoperative Prediction Model of Lymph Node Metastasis in the Inguinal and Femoral Region Based on Radiomics and Artificial Intelligence","volume":"34","author":"Zhou","year":"2024","journal-title":"Int. J. Gynecol. Cancer"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1002\/uog.20378","article-title":"Ultrasound Morphometric and Cytologic Preoperative Assessment of Inguinal Lymph-node Status in Women with Vulvar Cancer: MorphoNode Study","volume":"55","author":"Garganese","year":"2020","journal-title":"Ultrasound Obstet. Gynecol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Fragomeni, S.M., Moro, F., Palluzzi, F., Mascilini, F., Rufini, V., Collarino, A., Inzani, F., Giac\u00f2, L., Scambia, G., and Testa, A.C. (2023). Evaluating the Risk of Inguinal Lymph Node Metastases before Surgery Using the Morphonode Predictive Model: A Prospective Diagnostic Study in Vulvar Cancer Patients. Cancers, 15.","DOI":"10.3390\/cancers15041121"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"201194","DOI":"10.1016\/j.humgen.2023.201194","article-title":"An Integrative Network Analysis to Reveal Network Biomarkers for Vulvar Cancer","volume":"37","author":"Suman","year":"2023","journal-title":"Hum. Gene"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.injury.2019.12.009","article-title":"Identifying Bladder Rupture Following Traumatic Pelvic Fracture: A Machine Learning Approach","volume":"51","author":"Hertz","year":"2020","journal-title":"Injury"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"vdab077","DOI":"10.1093\/noajnl\/vdab077","article-title":"Application of Raman Spectroscopy for Detection of Histologically Distinct Areas in Formalin-Fixed Paraffin-Embedded Glioblastoma","volume":"3","author":"Klamminger","year":"2021","journal-title":"Neuro-Oncol. Adv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1002\/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4","article-title":"Multivariable Prognostic Models: Issues In Developing Models, Evaluating Assumptions And Adequacy, And Measuring And Reducing Errors","volume":"15","author":"HARRELL","year":"1996","journal-title":"Stat. Med."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.ygyno.2013.04.023","article-title":"Lymphatic Mapping and Sentinel Node Biopsy in Squamous Cell Carcinoma of the Vulva: Systematic Review and Meta-Analysis of the Literature","volume":"130","author":"Hassanzade","year":"2013","journal-title":"Gynecol. Oncol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1200\/JCO.2007.14.0566","article-title":"Sentinel Node Dissection Is Safe in the Treatment of Early-Stage Vulvar Cancer","volume":"26","author":"Oonk","year":"2008","journal-title":"J. Clin. Oncol."},{"key":"ref_39","first-page":"408","article-title":"Management of Regional Lymph Nodes and Their Prognostic Influence in Vulvar Cancer","volume":"61","author":"Hacker","year":"1983","journal-title":"Obstet. Gynecol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1016\/0002-9378(91)90573-A","article-title":"Assessment of Current International Federation of Gynecology and Obstetrics Staging of Vulvar Carcinoma Relative to Prognostic Factors for Survival (a Gynecologic Oncology Group Study)","volume":"164","author":"Homesley","year":"1991","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"101525","DOI":"10.1016\/j.ijgc.2024.101525","article-title":"Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva","volume":"35","author":"Klamminger","year":"2025","journal-title":"Int. J. Gynecol. Cancer"}],"container-title":["Journal of Clinical Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/10\/3510\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:34:18Z","timestamp":1760031258000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0383\/14\/10\/3510"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,17]]},"references-count":41,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["jcm14103510"],"URL":"https:\/\/doi.org\/10.3390\/jcm14103510","relation":{},"ISSN":["2077-0383"],"issn-type":[{"type":"electronic","value":"2077-0383"}],"subject":[],"published":{"date-parts":[[2025,5,17]]}}}