A Novel Online Calculator Based on Serum Biomarkers to Detect Hepatocellular Carcinoma among Patients with Hepatitis B

Abstract

BACKGROUND Early detection of hepatocellular carcinoma (HCC) among hepatitis B virus (HBV)-infected patients remains a challenge, especially in China. We sought to create an online calculator of serum biomarkers to detect HCC among patients with chronic hepatitis B (CHB). METHODS Participants with HBV-HCC, CHB, HBV-related liver cirrhosis (HBV-LC), benign hepatic tumors, and healthy controls (HCs) were recruited at 11 Chinese hospitals. Potential serum HCC biomarkers, protein induced by vitamin K absence or antagonist-II (PIVKA-II), α-fetoprotein (AFP), lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3) and α-L-fucosidase (AFU) were evaluated in the pilot cohort. The calculator was built in the training cohort via logistic regression model and validated in the validation cohort. RESULTS In the pilot study, PIVKA-II and AFP showed better diagnostic sensitivity and specificity compared with AFP-L3 and AFU and were chosen for further study. A combination of PIVKA-II and AFP demonstrated better diagnostic accuracy in differentiating patients with HBV-HCC from patients with CHB or HBV-LC than AFP or PIVKA-II alone [area under the curve (AUC), 0.922 (95% CI, 0.908–0.935), sensitivity 88.3% and specificity 85.1% for the training cohort; 0.902 (95% CI, 0.875–0.929), 87.8%, and 81.0%, respectively, for the validation cohort]. The nomogram including AFP, PIVKA-II, age, and sex performed well in predicting HBV-HCC with good calibration and discrimination [AUC, 0.941 (95% CI, 0.929–0.952)] and was validated in the validation cohort [AUC, 0.931 (95% CI, 0.909–0.953)]. CONCLUSIONS Our results demonstrated that a web-based calculator including age, sex, AFP, and PIVKA-II accurately predicted the presence of HCC in patients with CHB. ClinicalTrials.gov Identifier NCT03047603

Biomarkers for hepatocellular carcinoma based on body fluids and feces

“…Three diagnostic prediction models ( i.e. , the GALAD model[ 7 ], the ASAP model[ 8 ], and the HES algorithm[ 9 ]) have been developed to provide excellent diagnostic performance for HCC patients. To detect Barcelona Clinic Liver Cancer (BCLC) stage 0-A HCC, the GALAD model, which integrates age and gender into an algorithm based on serum AFP, AFP-L3, and DCP levels, had an area under curve of 0.92 with 92% sensitivity and 79% specificity at a cut-off of -1.18[ 7 ].…”

Suggestions for designing studies investigating diagnostic accuracy of biomarkers

“…Some researchers also use it to graphically calculate the probability of a disease for a given patient based on an index test or diagnostic model. In a recently published, prospective, multicenter study regarding the diagnostic accuracy of alpha-fetoprotein (AFP) and PIVKA-II for HCC, the authors constructed a diagnostic nomogram using age, gender, ln(AFP) and ln(PIVKA-II) (23). A nomogram is very straightforward method, and it can be easily interpreted.…”

“…For example, if a patient is male (approximately 5 points), aged more than 65 years (approximately 20 points), ln(AFP) is 6 (approximately 30 points), and ln(PIVKA-II) is 3 (approximately 20 points), his total point sum is 75, and the corresponding probability of HCC in the nomogram is approximately 80%. An online risk calculator can also be built to facilitate the use of a nomogram, like in the previous study (23).…”

Identification of Potentially Therapeutic Target Genes of Hepatocellular Carcinoma

“…The pathogenesis of liver cancer is complicated [11]. Multiple risk factors, such as age and race [12], hepatitis C virus [13], and hepatitis B virus [14], are considered to contribute to the abnormal expression of genes associated with initiation or progression of HCC. One of the strategies under…”