The use of HE4 in the prediction of ovarian cancer in Asian women with a pelvic mass.

OBJECTIVE: The purpose of this study was to evaluate the performance of human epididymis protein 4 (HE4) and the Risk of Ovarian Malignancy Algorithm (ROMA) for distinguishing between benign and malignant pelvis masses in Asian women. METHODS: This was a prospective, multicenter (n=6) study with patients from six Asian countries. Patients had a pelvic mass on imaging and were scheduled to undergo surgery. Serum CA125 and HE4 were measured on preoperative samples. CA125, HE4, and ROMA were evaluated for sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: A total of 414 women with an adnexal mass were evaluated, of which 65 had epithelial ovarian (EOC) cancer, 16 had borderline tumors and 11 had other malignant diseases. Compared to CA125, HE4 had lower sensitivity (56.9% vs 90.8%) and NPV (91.8% vs 97.3%), but improved specificity (96.9% vs 67.1%) and PPV (78.7% vs 35.8%) for differentiating between benign pelvic mass and EOC. ROMA had similar sensitivity (89.2% vs 90.8%) and NPV (97.6% vs 97.3%) as CA125, but showed improved specificity (87.3% vs 67.1%) and PPV (58.6% vs 35.8%). ROMA accurately predicted 87.3% of benign cases as low risk, and 82.6% of stage I/II EOC and 89.2% of all EOC as high risk. CONCLUSION: ROMA showed similar sensitivity as CA125 but improved specificity and PPV, especially in premenopausal women. Using ROMA may help predict if a pelvic mass is benign or malignant and facilitate subsequent management planning.

Performance of the Abbott Architect Immuno-Chemiluminometric NT-proBNP Assay.

Background: We evaluated the performance of the Abbott N-terminal pro-brain natriuretic peptide (NT-proBNP) assay against the Roche NT-proBNP immunoassay across two sites. Methods: Precision, linearity, and sensitivity studies were performed. A combined method of comparison and regression analysis was performed between the Roche and Abbott assays using samples from both sites (n = 494). To verify biotin interference, lyophilised biotin powder was reconstituted and spiked into serum samples at two medical decision levels (final concentration 500/4250 ng/mL) and compared to controls. NT-proBNP was also measured in anonymised leftover sera (n = 388) in a cardio-renal healthy population and stratified into three age bands­<50 (n = 145), 50−75 (n = 183) and >75 (n = 60). Results: Between-run precision (CV%) for NT-proBNP was 4.17/4.50 (139.5/142.0 pg/mL), 3.83/2.17 (521.6/506.3), and 4.60/2.51 (5053/4973), respectively. The assay was linear from 0.7−41,501 pg/mL. The limit of blank/quantitation was 1.2/7.9 pg/mL. The assay showed no interference from biotin up to 4250 ng/mL. Passing−Bablok regression analysis showed excellent agreement between the two assays (r = 0.999, 95% CI 0.999 to 0.999, p < 0.0001). The Roche assay had a slightly persistent, negative bias across different levels of NT-proBNP. ESC age cut-offs for diagnosing acute heart failure are applicable for the Abbott assay, with the median NT-proBNP of subjects < 50 years old at 43.0 pg/mL (range 4.9−456 pg/mL), 50−75 years old at 95.1 pg/mL (range 10.5−1079 pg/mL), and >75 years old at 173.1 pg/mL (range 23.2−1948 pg/mL). Conclusions: The Abbott Architect NT-proBNP assay has good performance that agrees with the manufacturer's specifications. ESC/AHA recommended NT-proBNP age groups for acute heart failure diagnosis are applicable to this assay.

Distinguishing benign from malignant pelvic mass utilizing an algorithm with HE4, menopausal status, and ultrasound findings.

OBJECTIVE: The purpose of this study was to develop a risk prediction score for distinguishing benign ovarian mass from malignant tumors using CA-125, human epididymis protein 4 (HE4), ultrasound findings, and menopausal status. The risk prediction score was compared to the risk of malignancy index and risk of ovarian malignancy algorithm (ROMA). METHODS: This was a prospective, multicenter (n=6) study with patients from six Asian countries. Patients had a pelvic mass upon imaging and were scheduled to undergo surgery. Serum CA-125 and HE4 were measured on preoperative samples, and ultrasound findings were recorded. Regression analysis was performed and a risk prediction model was developed based on the significant factors. A bootstrap technique was applied to assess the validity of the HE4 model. RESULTS: A total of 414 women with a pelvic mass were enrolled in the study, of which 328 had documented ultrasound findings. The risk prediction model that contained HE4, menopausal status, and ultrasound findings exhibited the best performance compared to models with CA-125 alone, or a combination of CA-125 and HE4. This model classified 77.2% of women with ovarian cancer as medium or high risk, and 86% of women with benign disease as very-low, low, or medium-low risk. This model exhibited better sensitivity than ROMA, but ROMA exhibited better specificity. Both models performed better than CA-125 alone. CONCLUSION: Combining ultrasound with HE4 can improve the sensitivity for detecting ovarian cancer compared to other algorithms.