Yeng, Lou Wei
(2017)
Validation of CliEndomet as a diagnostic tool for endometriosis.
Masters thesis, Universiti Sains Malaysia.
Abstract
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.
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