Scoring systems for the evaluation of adnexal masses nature: current knowledge and clinical applications.

Milan Terzic, Gulzhanat Aimagambetova, Melanie Norton, Luigi Della Corte, Alejandro Marín-Buck, Juan Francisco Lisón, Juan José Amer-Cuenca, Gabriella Zito, Simone Garzon, Salvatore Caruso, Agnese Maria Chiara Rapisarda, Antonio Cianci

Journal: Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology 2021;41(3):340-347

PMID: 32347750

Full Text on Atypon View on PubMed

Abstract

Adnexal masses are a common finding in women, with 20% of them developing at least one pelvic mass during their lifetime. There are more than 30 different subtypes of adnexal tumours, with multiple different subcategories, and the correct characterisation of the pelvic masses is of paramount importance to guide the correct management. On that basis, different algorithms and scoring systems have been developed to guide the clinical assessment. The first scoring system implemented into the clinical practice was the Risk of Malignancy Index, which combines ultrasound evaluation, menopausal status, and serum CA-125 levels. Today, current guidelines regarding female patients with adnexal masses include the application of International Ovarian Tumours Analysis simple rules, logistic regression model 1 (LR1) and LR2, OVERA, cancer ovarii non-invasive assessment of treating strategy, and assessment of Different Neoplasias in the adnexa. In this scenario, the choice of the scoring system for the discrimination between benign and malignant ovarian tumours can be complex when approaching patients with adnexal masses. This review aims to summarise the available evidence regarding the different scoring systems to provide a complete overview of the topic.

Address: Department of Medicine, Nazarbayev University School of Medicine, Astana, Kazakhstan.; Department of Obstetrics and Gynecology, National Research Center of Mother and Child Health, University Medical Center, Astana, Kazakhstan.; Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.; Department of Biomedical Sciences, Nazarbayev University School of Medicine, Astana, Kazakhstan.; Department of Urogynaecology, Whittington Hospital, London, UK.; Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy.; Department of Surgery, Universidad Cardenal Herrera-CEU, CEU Universities, Valencia, Spain.; Department of Gynecology, Hospital Provincial de Castellón, Castellón, Spain.; Department of Medicine, Universidad Cardenal Herrera-CEU, CEU Universities, Valencia, Spain.; CIBER of Physiopathology of Obesity and Nutrition CIBERobn, CB06/03 Carlos III Health Institute, Madrid, Spain.; Department of Physiotherapy, Universidad Cardenal Herrera-CEU, CEU Universities, Valencia, Spain.; Department of Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste, Italy.; Department of Obstetrics and Gynecology, "Filippo Del Ponte" Hospital, University of Insubria, Varese, Italy.; Obstetrics and Gynecology Unit, Department of General Surgery and Medical Surgical Specialties, University of Catania, Catania, Italy.

DOI: 10.1080/01443615.2020.1732892

Link outs

Free resources

Medical:

https://medlineplus.gov/ovariancancer.html

Miscellaneous:

https://assays.cancer.gov/CPTAC-2227

Research Materials:

https://antibodies.cancer.gov/detail/CPTC-CPE-1

Subscription / membership required

Full Text Sources:

https://www.tandfonline.com/doi/10.1080/01443615.2...

MeSH Terms: Adnexal Diseases, Algorithms, Clinical Decision Rules, Diagnosis, Differential, Female, Genital Neoplasms, Female, Humans, Logistic Models, Ovarian Neoplasms, Risk Assessment, Sensitivity and Specificity