Validation of CliEndomet as a diagnostic tool for endometriosis - Yeng, Lou Wei (2017)
Background: Endometriosis is one of the most common gynaecological disorders affecting the reproductive age group of women. The current gold standard in diagnosing this disease is via direct visualisation of endometriosis lesion intraoperatively and followed histological confirmation. Detection of non-invasive test is one of the priorities in endometriosis research. CliEndomet which was formulated by a group of researchers in Hospital Universiti Sains Malaysia using clinical manifestations, ultrasound findings and serum CA-125 had shown to be in substantial agreement with the intraoperative findings of endometriosis, but there is a need to validate the accuracy and reliability of CliEndomet using a more objective method i.e. histology confirmation. Objectives: The main objective of this study is to assess the accuracy of CliEndomet in the diagnosis of endometriosis with histopathology as the confirmation. It also serves to determine the accuracy of CliEndomet in staging the severity of endometriosis. Methodology: This was a cross sectional study that involving 94 patients who presented with symptoms of dysmenorrhea and chronic pelvic pain suggestive of endometriosis. Data regarding the symptoms, physical examination, scan findings and serum CA-125 were obtained preoperatively and scoring done according to CliEndomet into high possibility and low possibility group. Patients were then subjected to operation accordingly and the intraoperative findings were obtained regarding presence of endometriotic lesion. If endometriosis was clinically diagnosed, the disease was staged according to the revised American Society for Reproductive Medicine (ASRM) staging system. Regardless of the presence oftypical endometriotic lesion, tissue biopsy was taken during the operation for histopathology confirmation. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), positive likelihood ratio (PPV) , negative likelihood ratio (NPV), likelihood ratio positive (LR +) and likelihood ratio negative (LR-). The reliability for the diagnosis of endometriosis using CliEndomet was tested using Kappa coefficient. Results: A total of 94 patients were recruited into this study. Of the 94 patients, 56 were confirmed to have endometriosis by histology examination, and 50 were noted to have high risk for endometriosis using the CliEndomet scoring system. CliEndomet was shown to be 69.6% sensitive to diagnose endometriosis with positive predictive value of 78%. It has 71.1% of specificity and 61.4% negative predictive value. Its positive likelihood ratio was 2.41 and negative likelihood ratio of 0.43. CliEndomet was shown to have a fair agreement in diagnosing endometriosis (κ = 0,397 (95% CI, 0,21-0,58), p <0.005). During the surgery, 62 patients were found to have endometriosis. These patients were classified into having early stage endometriosis (AFS scoring system: minimal and mild endometriosis), and advanced stage disease (AFS scoring system: moderate and severe endometriosis). Of those who have early stage endometriosis, 5 patients had low risk and 2 had high risk of endometriosis according to the CliEndomet scoring system. Among those in the advanced stage disease, 12 patients were scored as low risk and 43 were scored as high risk. The sensitivity of CliEndomet to detect early stage endometriosis was 42% with positive predictive value of 29%. It is more capable to detect advanced stage disease (specificity 78%, negative predictive value of 96%).Conclusions: CliEndomet has a role to diagnose endometriosis in patients who refuse invasive diagnostic method. It is more accurate to predict the existence of advanced disease then early stage disease.