alexa Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis.


Journal of General Practice

Author(s): Kaijser J, Sayasneh A, Van Hoorde K, GhaemMaghami S, Bourne T, , Kaijser J, Sayasneh A, Van Hoorde K, GhaemMaghami S, Bourne T, , Kaijser J, Sayasneh A, Van Hoorde K, Kaijser J, GhaemMaghami S, Sayasneh A, Bourne T, Van Hoorde K, , GhaemMaghami S, Bourne T,

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Abstract BACKGROUND Characterizing ovarian pathology is fundamental to optimizing management in both pre- and post-menopausal women. Inappropriate referral to oncology services can lead to unnecessary surgery or overly radical interventions compromising fertility in young women, whilst the consequences of failing to recognize cancer significantly impact on prognosis. By reflecting on recent developments of new diagnostic tests for preoperative identification of malignant disease in women with adnexal masses, we aimed to update a previous systematic review and meta-analysis. METHODS An extended search was performed in MEDLINE (PubMed) and EMBASE (OvidSp) from March 2008 to October 2013. Eligible studies provided information on diagnostic test performance of models, designed to predict ovarian cancer in a preoperative setting, that contained at least two variables. Study selection and extraction of study characteristics, types of bias, and test performance was performed independently by two reviewers. Quality was assessed using a modified version of the QUADAS assessment tool. A bivariate hierarchical random effects model was used to produce summary estimates of sensitivity and specificity with 95\% confidence intervals or plot summary ROC curves for all models considered. RESULTS Our extended search identified a total of 1542 new primary articles. In total, 195 studies were eligible for qualitative data synthesis, and 96 validation studies reporting on 19 different prediction models met the predefined criteria for quantitative data synthesis. These models were tested on 26 438 adnexal masses, including 7199 (27\%) malignant and 19 239 (73\%) benign masses. The Risk of Malignancy Index (RMI) was the most frequently validated model. The logistic regression model LR2 with a risk cut-off of 10\% and Simple Rules (SR), both developed by the International Ovarian Tumor Analysis (IOTA) study, performed better than all other included models with a pooled sensitivity and specificity, respectively, of 0.92 [95\% CI 0.88-0.95] and 0.83 [95\% CI 0.77-0.88] for LR2 and 0.93 [95\% CI 0.89-0.95] and 0.81 [95\% CI 0.76-0.85] for SR. A meta-analysis of centre-specific results stratified for menopausal status of two multicentre cohorts comparing LR2, SR and RMI-1 (using a cut-off of 200) showed a pooled sensitivity and specificity in premenopausal women for LR2 of 0.85 [95\% CI 0.75-0.91] and 0.91 [95\% CI 0.83-0.96] compared with 0.93 [95\% CI 0.84-0.97] and 0.83 [95\% CI 0.73-0.90] for SR and 0.44 [95\% CI 0.28-0.62] and 0.95 [95\% CI 0.90-0.97] for RMI-1. In post-menopausal women, sensitivity and specificity of LR2, SR and RMI-1 were 0.94 [95\% CI 0.89-0.97] and 0.70 [95\% CI 0.62-0.77], 0.93 [95\% CI 0.88-0.96] and 0.76 [95\% CI 0.69-0.82], and 0.79 [95\% CI 0.72-0.85] and 0.90 [95\% CI 0.84-0.94], respectively. CONCLUSIONS An evidence-based approach to the preoperative characterization of any adnexal mass should incorporate the use of IOTA Simple Rules or the LR2 model, particularly for women of reproductive age. This article was published in Hum Reprod Update and referenced in Journal of General Practice

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