Treatment options for ovarian cancer

Estimating the risk of malignancy of adnexal masses: validation of the ADNEX model in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China

Background

This study aims to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) the Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China.

Methods

This was a single oncology centre, retrospective diagnostic accuracy study of 620 patients. All patients underwent surgery, and the histopathological diagnosis was used as a reference standard. The masses were divided into five types according to the ADNEX model: benign ovarian tumours, borderline ovarian tumours (BOTs), stage I ovarian cancer (OC), stage II-IV OC and ovarian metastasis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the ADNEX model to classify tumours into different histological types with and without cancer antigen 125 (CA 125) results.

Results

Of the 620 women, 402 (64.8%) had a benign ovarian tumour and 218 (35.2%) had a malignant ovarian tumour, including 86 (13.9%) with BOT, 75 (12.1%) with stage I OC, 53 (8.5%) with stage II-IV OC and 4 (0.6%) with ovarian metastasis. The AUC of the model to differentiate benign and malignant adnexal masses was 0.97 (95% CI, 0.96–0.98). Performance was excellent for the discrimination between benign and stage II-IV OC and between benign and ovarian metastasis, with AUCs of 0.99 (95% CI, 0.99–1.00) and 0.99 (95% CI, 0.98–1.00), respectively. The model was less effective at distinguishing between BOT and stage I OC and between BOT and ovarian metastasis, with AUCs of 0.54 (95% CI, 0.45–0.64) and 0.66 (95% CI, 0.56–0.77), respectively. When including CA125 in the model, the performance in discriminating between stage II–IV OC and stage I OC and between stage II–IV OC ovarian metastasis was improved (AUC increased from 0.88 to 0.94, P = 0.01, and from 0.86 to 0.97, p = 0.01).

Conclusions

The IOTA ADNEX model has excellent performance in differentiating benign and malignant adnexal masses in the hands of nonexpert ultrasonographers with limited experience in China. In classifying different subtypes of ovarian cancers, the model has difficulty differentiating BOTs from stage I OC and BOTs from ovarian metastases.

Research Progress in Prognostic Factors and Biomarkers of Ovarian Cancer

Ovarian cancer is a serious threat to women's health; its early diagnosis rate is low and prone to metastasis and recurrence. The current conventional treatment for ovarian cancer is a combination of platinum and paclitaxel chemotherapy based on surgery. The recurrence and progression of ovarian cancer with poor prognosis is a major challenge in treatment. With rapid advances in technology, understanding of the molecular pathways involved in ovarian cancer recurrence and progression has increased, biomarker-guided treatment options can greatly improve the prognosis of patients. This review systematically discusses and summarizes existing and new information on prognostic factors and biomarkers of ovarian cancer, which is expected to improve the clinical management of patients and lead to effective personalized treatment.

CA-125 AUC as a new prognostic factor for patients with ovarian cancer

OBJECTIVE

The aim of the present study was to investigate the usefulness of the CA-125 area under the curve (AUC) as a new kinetic parameter for predicting overall survival in patients with ovarian cancer. In addition, the relationship of CA-125 AUC with other prognostic factors of ovarian cancer was evaluated.

METHODS

Ninety-two patients that underwent primary line chemotherapy within 4 months after submission to cytoreductive surgery were included. For each patient, CA-125 AUC was calculated and a statistical analysis was conducted to compare CA-125 AUC behavior among patients according to several covariates.

RESULTS

The mean age at diagnostic time was found to be 55.5 (16.1-82.4) years with a mean survival of 39.2 (3.5-100.1; SE = 2.6) months. Across FIGO stage I, II, III, and IV patients had a mean CA-125 AUC of 18.2, 24.6, 147.8, and 574.6 IU/ml*days, respectively (P < 0.05). At the evaluation date, living patients had a mean CA-125 AUC of 40.1 in contrast to 234.1 IU/ml*days (P < 0.05) for deceased ones. Patients with a complete response to primary chemotherapy had a mean CA-125 AUC of 48.8, while patients with a partial response had a mean of 251.7 IU/ml*days, and patients with no response or disease progression had a mean of 316.5 IU/ml*days (P < 0.05). The best CA-125 AUC performance is in predicting patient complete response to chemotherapy with a cut-off of 100 IU/ml*days and an accuracy of 82%.

CONCLUSIONS

Despite CA-125 AUC high correlation with the FIGO stage, residual disease, and patient final outcome, the main interest of CA-125 AUC calculation is to evaluate the treatment efficacy and to foresee a full chemotherapy response. Further studies should be carried out before extrapolating these results to other data sets.