Although cardiovascular disease (CVD) is a major health challenge in Malaysia, many Malaysians are unaware of their CVD risk. The measurement of biomarkers in the general population may help to identify at-risk individuals before the onset of symptomatic CVD. The aim of this community health screening project was to determine the distribution of high-sensitivity troponin I (hsTnI) and other biomarkers of CVD risk in the general population of Johor, Malaysia. A sampling of self-declared healthy volunteers was conducted during the 2016 Kembara Mahkota community event in Johor. Levels of hsTnI, B-type natriuretic peptide (BNP) and homocysteine (HCY) were analyzed using the ARCHITECT immunoassay and clinical chemistry platforms utilizing fresh venous blood samples. Based on previous data, biomarker levels indicative of high risk were >10 and >12 ng/mL for hsTnI in women and men, respectively, BNP >50 pg/mL in the overall population, and HCY >13.6 µmol/L in women and >16.2 µmol/L in men. A total of 2744 volunteers participated in biomarker testing. Biomarker measurements showed that up to 10% of participants had moderate or high CVD risk based on hsTnI, approximately 2% were above the BNP threshold and >50% of subjects were above the HCY threshold. General population biomarker testing shows distribution of biomarker levels that may be indicative of CVD risk or the presence of disease and suggests that biomarker-guided risk strategies should be more widely implemented to determine the impact they would have on early detection and prevention of disease.

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.
Adult ; *Algorithms ; Biomarkers, Tumor/*blood ; CA-125 Antigen/blood ; Decision Support Techniques ; Diagnosis, Differential ; Female ; Humans ; Menopause ; Middle Aged ; Ovarian Neoplasms/*diagnosis/ultrasonography ; Predictive Value of Tests ; Prospective Studies ; Proteins/*analysis ; ROC Curve ; Risk Assessment/methods ; Sensitivity and Specificity