Diagnostic performance comparisons of two commonly used multi-biomarker-based scores for detection of hepatocellular carcinoma in non-alcoholic fatty liver disease

Prognostic Value of the ASAP Score for Patients Undergoing Hepatic Resection for Hepatocellular Carcinoma: A Multicenter Analysis of 1,239 Patients

BACKGROUND AND AIMS

The ASAP score, which incorporates age, sex, alpha-fetoprotein (AFP), and protein induced by vitamin K absence-II, has demonstrated promise for early detection of hepatocellular carcinoma (HCC). However, its prognostic value after HCC treatment remains unknown. The current study sought to evaluate the prognostic value of the ASAP score to predict recurrence and survival following curative hepatic resection for HCC.

METHODS

This study using prospectively collected data included HCC patients who underwent curative-intent hepatic resection. The ASAP score was calculated preoperatively, and X-tile analysis was used to determine the optimal cutoff value. Univariate and multivariate analyses were performed to identify independent risk factors associated with recurrence and overall survival (OS).

RESULTS

Among 1239 patients in the analytic cohort, the optimal ASAP score cutoff was 4.8; patients were divided into low (n = 749) and high (n = 490) ASAP score subgroups. Patients with high ASAP scores had a higher incidence of 5-year recurrence (73.9% vs 51.0%, P < 0.001) and worse OS (31.7% vs 60.1%, P < 0.001) versus individuals with low scores. Multivariate analysis identified ASAP score ≥4.8 as an independent risk factor of both recurrence (hazard ratio [HR] 1.976, 95% confidence interval [CI]: 1.633-2.390, P < 0.001) and OS (HR 1.407, 95% CI 1.170-1.691, P < 0.001) after controlling for established clinicopathological factors.

CONCLUSION

Preoperative ASAP score was independently associated with recurrence and survival after HCC resection. The clinical utility of the ASAP score may be applicable to both diagnosis and prognosis, potentially improving postoperative surveillance and management strategies for HCC patients.

Tumor biology characteristics score based on alpha-fetoprotein and protein induced by vitamin K absence or antagonist II as a predictor for recurrence and survival after curative resection for hepatocellular carcinoma: a multicenter cohort study

BACKGROUND

Current hepatocellular carcinoma (HCC) staging systems lack comprehensive assessment of tumor biologic characteristics. This study aimed to develop and validate a tumor biology characteristics score (TBCS) based on alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist II (PIVKA-II) to predict long-term oncologic outcomes after HCC resection.

METHODS

In this multicenter retrospective cohort study, patients who underwent curative resection for HCC between June 2018 and December 2022 were included. TBCS (range, 2-6 points) was calculated by combining preoperative AFP (<20, 20-199, and ≥200 ng/mL) and PIVKA-II levels (<40, 40-399, and ≥400 mAU/mL). Patients were stratified into low (2 points), medium (3-4 points), and high TBCS groups (5-6 points). The primary outcomes were recurrence-free survival (RFS) and overall survival (OS).

RESULTS

A total of 695 patients were analyzed; the low, medium, and high TBCS groups comprised 132 (19.0%), 233 (33.5%), and 330 patients (47.5%), respectively. Notably, 5-year RFS was 30.4%, 14.7%, and 9.7%, whereas 5-year OS was 42.1%, 35.5%, and 23.5% for low, medium, and high TBCS groups, respectively (both P <.001). Multivariate analysis identified TBCS as an independent predictor of both RFS (medium TBCS: hazard ratio [HR], 1.583; 95% CI, 1.219-2.057; P =.001; high TBCS: HR, 1.895; 95% CI, 1.473-2.438; P <.001) and OS (high TBCS: HR, 1.781; 95% CI, 1.353-2.343; P <.001).

CONCLUSION

The novel TBCS combining AFP and PIVKA-II effectively stratified patients with HCC into distinct prognostic groups after curative-intent resection, independently predicting both RFS and OS. This score may help identify high-risk patients for more intense postoperative recurrence surveillance and receipt of adjuvant therapies.

The Value of Clinical Decision Support in Healthcare: A Focus on Screening and Early Detection

In a rapidly changing technology landscape, "Clinical Decision Support" (CDS) has become an important tool to improve patient management. CDS systems offer medical professionals new insights to improve diagnostic accuracy, therapy planning, and personalized treatment. In addition, CDS systems provide cost-effective options to augment conventional screening for secondary prevention. This review aims to (i) describe the purpose and mechanisms of CDS systems, (ii) discuss different entities of algorithms, (iii) highlight quality features, and (iv) discuss challenges and limitations of CDS in clinical practice. Furthermore, we (v) describe contemporary algorithms in oncology, acute care, cardiology, and nephrology. In particular, we consolidate research on algorithms across diseases that imply a significant disease and economic burden, such as lung cancer, colorectal cancer, hepatocellular cancer, coronary artery disease, traumatic brain injury, sepsis, and chronic kidney disease.