The aim of this paper is to discuss the ADNEX model in more detail and provide some guidance for clinical management. Such a ‘multiclass’ or polytomous model is uncommon and poses new practical challenges. This is the first risk model to differentiate between benign, borderline tumors, stage I invasive, stage II-IV invasive ovarian cancer and secondary metastatic cancer (Van Calster et al., 2014). Recently, the International Ovarian Tumor Analysis (IOTA) group proposed the Assessment of Different NEoplasias in the adneXa (ADNEX) model. Finally, for cancers of other primary origin metastasized to the ovary, treatment depends on the type of tumor. Furthermore, stage I ovarian cancer may be managed more conservatively than stage II-IV disease (Trimbos et al., 2003). Borderline tumors can be treated with less aggressive techniques than invasive tumors, which is of interest when fertility preservation is desired (Tinelli et al., 2006 Daraï et al., 2013). Secondly, optimal treatment of adnexal malignancies depends on the type of tumor. Benign ovarian masses can be managed expectantly or by conservative surgical management with reduced morbidity and fertility preservation (Carley et al., 2002). This is an important factor that positively influences prognosis (Earle et al., 2006 Engelen et al., 2006 Woo et al., 2012 Bristow et al., 2013). Firstly, accurate differentiation between benign and malignant tumors can lead to referral of patients with malignant tumors to gynecological oncology centers for further diagnosis or staging, followed by debulking surgery and/or administration of systemic therapy. Nevertheless, this paper provides a guidance on how the ADNEX model may be adopted into clinical practice.Īlthough often overlooked, the preoperative characterization of an adnexal mass is of crucial importance for selecting the optimal management strategy. We cannot propose a generally applicable algorithm with fixed cut-offs, because (as with any risk model) this depends on the specific clinical setting in which the model will be used. This is illustrated with a few example patients. Furthermore, we formulate suggestions about the selection and interpretation of risk cut-offs for patient stratification and choice of appropriate clinical management. In the present paper, we first provide an in-depth discussion about the predictors used in ADNEX and the ability for risk prediction with different tumor histologies. This approach is novel compared to existing tools that only differentiate between benign and malignant tumors, and therefore questions may arise on how ADNEX can be used in clinical practice. Recently, the International Ovarian Tumor Analysis (IOTA) consortium published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, the first risk model that differentiates between benign and four types of malignant ovarian tumors: borderline, stage I cancer, stage II-IV cancer, and secondary metastatic cancer.
All gynecologists are faced with ovarian tumors on a regular basis, and the accurate preoperative diagnosis of these masses is important because appropriate management depends on the type of tumor.
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