BACKGROUND: CA125 is the gold standard serum biomarker for monitoring patients with epithelial ovarian cancer (EOC). Human epididymal protein 4 (HE4) is a novel serum biomarker for EOC patients. OBJECTIVE: The objective of this trial was to examine the utility of measuring serum HE4 levels for monitoring EOC patients and to compare HE4 performance parameters to serum CA125. METHODS: A retrospective trial using residual longitudinal serum samples drawn during treatment and monitoring from EOC patients. Serum CA125 and HE4 levels were analyzed at each time point, and a velocity of change was calculated and correlated with clinical status. The null hypothesis was that HE4 is inferior to CA125, and this was tested using concordance and two-sided Fisher’s exact testing. McNemar’s test was used to assess the overall agreement of the two assays with the clinical status. RESULTS: A total of 129 patients with 272 separate clinical periods and 1739 events (serum samples) were evaluated. Using a 25% change in serum biomarker levels to indicate change in disease status, the accuracy and NPV determined for HE4 versus CA125 were 81.8% versus 82.6% (p = 0.846) and 87.4% versus 89.7% (p = 0.082), respectively. Concordance comparison of HE4 accuracy / CA125 accuracy was 0.990, indicating HE4 was not inferior to CA125 (McNemar’s test p-value = 0.522). Performing a velocity of change analysis, the accuracy and NPV determined for HE4 versus CA125 were 78.3% versus 78.6% (p = 0.995) and 74.9% versus 76.3% (p = 0.815), respectively. Concordance comparison of HE4 velocity accuracy / CA125 velocity accuracy was 0.996, again indicating HE4 was not inferior to CA125 (McNemar’s test p-value = 0.884). The combination of HE4 and CA125 velocity changes showed a similar accuracy of 81.3% (p = 0.797 compared to HE4 and CA125 alone) and NPV of 81.1% (p≥0.172 compared to HE4 and CA125 alone), and an increased sensitivity of 70.5% (p≤0.070 compared to HE4 and CA125 alone). CONCLUSION: HE4 is equivalent to CA125 for monitoring of EOC patients. The combination of CA125 and HE4 velocities is superior to either marker alone.
e18098 Background: The combination of HE4 and CA125 can be used as a predictive probability algorithm to determine the risk of malignancy in women with a uterine mass. Many studies have been done looking at ways to differentiate between benign fibroids and uterine sarcomas with limited success. This study examined the utility of using a logistics regression algorithm containing biomarkers HE4 and CA 125 to predict risk of malignancy of a uterine mass. Methods: This was an IRB retrospective study using de-identified data form 5 pelvic mass studies. Patients were included if they were diagnosed with either uterine fibroids or uterine sarcoma on final pathology. Pre-operative serum levels of HE4 and CA125 were obtained for each patient. A logistics regression analysis was performed in a prior pelvic mass prospective trial and utilized in this analysis. The predictive probability algorithm was used to classify patients into high and low risk groups for sarcoma. Wilson’s score interval was used to determine confidence intervals. Results: There were 71 patients identified with a uterine mass. The mean age of study participants was 54 (range 22-85). There were 10 (14.1%) sarcomas and 61 fibroids (85.9%) identified. Six of the sarcomas were leiomyosarcomas (60.0%). There was 1 adenosarcoma (10%), 1 mixed sarcoma (10%) and 2 sarcomas which were not further characterized. A threshold of 13.1% was used to classify masses as low or high risk. The predictive probability algorithm was found to have a sensitivity of 90.9% (CI 55.5-99.7%), specificity of 60.7% (CI 47.3-72.9%), PPV of 27.3% (13.3-45.5%), and NPV of 97.4% (86.2-99.9%). An elevated risk of malignancy was noted in 9 (90%) sarcomas and 24 (39%) of fibroids. Conclusions: A predictive probability algorithm using HE4 and CA 125 had a high sensitivity for determining high and low risk of malignancy in patients with presumed uterine fibroids with a sensitivity of 90.9% for detecting sarcoma. This algorithm will be validated in a prospective clinical trial.
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