Value of HCC surveillance in a landscape of emerging surveillance options: Perspectives of a multi-stakeholder modified delphi panel.

Hepatocellular carcinoma (HCC) surveillance is recommended by liver professional societies but lacks broad acceptance by several primary care and cancer societies due to limitations in the existing data. We convened a diverse multidisciplinary group of cancer screening experts to evaluate current and future paradigms of HCC prevention and early detection using a rigorous Delphi panel approach. The experts had high agreement on twenty-one statements about primary prevention, HCC surveillance benefits, HCC surveillance harms, and the evaluation of emerging surveillance modalities.

ASSESSING SCREENING EFFICACY IN THE PRESENCE OF CANCER OVERDIAGNOSIS.

Cancer screening facilitates the early detection of cancer, at a stage when treatment is often most effective. However, it also brings the risk of over-diagnosis, where a diagnosis made through screening would not have led to symptoms or death during the patient's lifetime. In this paper, we tackle a significant unresolved issue in the evaluation of screening efficacy: selecting primary endpoints and inferential procedures that efficiently consider potential overdiagnosis in screening trials.

Phase 3 Validation of Prognostic Liver Secretome Signature With α-Fetoprotein Plus Age, Male Sex, Albumin-Bilirubin, and Platelets for Hepatocellular Carcinoma Risk Stratification in Cirrhosis.

Background & Aims: Hepatocellular carcinoma (HCC) risk stratification is an urgent unmet need for cost-effective HCC screening and early detection in patients with cirrhosis to improve poor HCC prognosis.

Methods: Molecular (prognostic liver secretome signature with α-fetoprotein) and clinical (aMAP [age, male sex, albumin-bilirubin, and platelets] score) variable-based scores were integrated into PAaM (prognostic liver secretome signature with α-fetoprotein plus age, male sex, albumin-bilirubin, and platelets), which was subsequently validated in 2 phase 3 biomarker validation studies: the statewide Texas HCC Consortium and nationwide HCC Early Detection Strategy prospective cohorts, following the prospective specimen collection, retrospective blinded evaluation design. The associations between baseline PAaM and incident HCC were assessed using Fine-Gray regression, with overall death and liver transplantation as competing events.

National Liver Cancer Screening Trial (TRACER) study protocol.

Background: Professional guidelines recommend HCC screening in at-risk patients using semi-annual ultrasound with or without alpha-fetoprotein (AFP); however, this strategy has limited effectiveness due to low adherence and sensitivity. Increasing data support the potential role of blood-based biomarker panels, which could improve both aspects. The biomarker panel GALAD, comprised of sex, age, and 3 blood biomarkers (AFP, AFP-L3, and des-carboxy prothrombin des-carboxy prothrombin), has shown high sensitivity and specificity in biomarker phase II (case-control) and phase III (retrospective cohort) validation studies.

Biomarker trajectory for earlier detection of lung cancer.

Background: To determine whether an algorithm based on repeated measurements of a panel of four circulating protein biomarkers (4 MP) for lung cancer risk assessment results in improved performance over a single time measurement.

Methods: We conducted data analysis of the 4 MP consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in pre-diagnostic sera from 2483 ever-smoker participants (389 cases and 2094 randomly selected non-cases) in the Prostate, Lung, Colorectal, Ovarian (PLCO) Study who had at least two sequential blood collections over 6 years. A parametric empirical Bayes (PEB) algorithm, which incorporates participant biomarker history at each time point, was compared to a single-threshold (ST) method.

Dynamic and concordance-assisted learning for risk stratification with application to Alzheimer's disease.

Dynamic prediction models capable of retaining accuracy by evolving over time could play a significant role for monitoring disease progression in clinical practice. In biomedical studies with long-term follow up, participants are often monitored through periodic clinical visits with repeat measurements until an occurrence of the event of interest (e.g.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer.

Importance: Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater).

Objective: To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers.

Design, Setting, And Participants: RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers.

High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker.

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study.

Revisiting the standard blueprint for biomarker development to address emerging cancer early detection technologies.

Novel liquid biopsy technologies are creating a watershed moment in cancer early detection. Evidence supporting population screening is nascent, but a rush to market the new tests is prompting cancer early detection researchers to revisit the standard blueprint that the Early Detection Research Network established to evaluate novel screening biomarkers. In this commentary, we review the Early Detection Research Network's Phases of Biomarker Development (PBD) for rigorous evaluation of novel early detection biomarkers and discuss both hazards and opportunities involved in expedited evaluation.

Immunoassay Detects Salivary Anti-SSA/Ro-52 Autoantibodies in Seronegative Patients with Primary Sjögren's Syndrome.

The diagnostic work-up for Sjögren's syndrome is challenging and complex, including testing for serum autoantibodies to SSA/Ro and a labial salivary gland biopsy. Furthermore, the diagnosis is often delayed. In this study, we tested the hypothesis that anti-SSA/Ro autoantibodies are detectable in the saliva of patients with primary Sjögren's syndrome (pSS) because the disease affects the salivary glands, and these autoantibodies display greater discriminatory performance in saliva than in serum.

Incidence and Risk Factors for Hepatocellular Carcinoma in Cirrhosis: The Multicenter Hepatocellular Carcinoma Early Detection Strategy (HEDS) Study.

Background & Aims: Worldwide, hepatocellular carcinoma (HCC) is a common malignancy. We aimed to prospectively determine the incidence and risk factors of HCC in a U.S.

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN).

Associations of Race and Ethnicity with Hepatocellular Carcinoma, Decompensation, and Mortality in US Veterans with Cirrhosis.

Background: Among patients with cirrhosis, it remains unclear whether there are racial/ethnic differences in cirrhosis complications and mortality. We examined the associations between race/ethnicity and risk for hepatocellular carcinoma (HCC), cirrhosis decompensation, and all-cause mortality overall and by cirrhosis etiology.

Methods: US Veterans diagnosed with cirrhosis from 2001 to 2014 (n = 120,992), due to hepatitis C virus (HCV; n = 55,814), alcohol-associated liver disease (ALD; n = 36,323), hepatitis B virus (HBV; n = 1,972), nonalcoholic fatty liver disease (NAFLD; n = 17,789), or other (n = 9,094), were followed through 2020 for incident HCC (n = 10,242), cirrhosis decompensation (n = 27,887), and mortality (n = 81,441).

A Flexible Method for Diagnostic Accuracy with Biomarker Measurement Error.

Diagnostic biomarkers are often measured with errors due to imperfect lab conditions or analytic variability of the assay. The ability of a diagnostic biomarker to discriminate between cases and controls is often measured by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, among others. Ignoring measurement error can cause biased estimation of a diagnostic accuracy measure, which results in misleading interpretation of the efficacy of a diagnostic biomarker.

Conditional concordance-assisted learning under matched case-control design for combining biomarkers for population screening.

Incorporating promising biomarkers into cancer screening practices for early-detection is increasingly appealing because of the unsatisfactory performance of current cancer screening strategies. The matched case-control design is commonly adopted in biomarker development studies to evaluate the discriminative power of biomarker candidates, with an intention to eliminate confounding effects. Data from matched case-control studies have been routinely analyzed by the conditional logistic regression, although the assumed logit link between biomarker combinations and disease risk may not always hold.

Multicenter Validation of Abbreviated MRI for Detecting Early-Stage Hepatocellular Carcinoma.

Background Abbreviated MRI is a proposed paradigm shift for hepatocellular carcinoma (HCC) surveillance, but data on its performance are lacking for histopathologically confirmed early-stage HCC. Purpose To evaluate the sensitivity and specificity of dynamic contrast-enhanced abbreviated MRI for early-stage HCC detection, using surgical pathologic findings as the reference standard. Materials and Methods This retrospective study was conducted at three U.

Contributions of Circulating microRNAs for Early Detection of Lung Cancer.

There is unmet need to develop circulating biomarkers that would enable earlier interception of lung cancer when more effective treatment options are available. Here, a set of 30 miRNAs, selected from a review of the published literature were assessed for their predictive performance in identifying lung cancer cases in the pre-diagnostic setting. The 30 miRNAs were assayed using sera collected from 102 individuals diagnosed with lung cancer within one year following blood draw and 212 controls matched for age, sex, and smoking status.

Combining FIB-4 and Liver Stiffness Into the FIB-5, a Single Model that Accurately Predicts Complications of Portal Hypertension.

Introduction: We aimed to combine the fibrosis (FIB)-4 score and fibroscan-derived liver stiffness (LS) into a single score (FIB-5) that predicts incident complications of portal hypertension (PH) in persons with compensated liver disease.

Methods: In this retrospective cohort study, we identified 5849 US veterans who underwent LS measurement from May 01, 2014 to June 30, 2019, and laboratory tests enabling FIB-4 calculation within 6 months of LS measurement. Patients were followed up from the LS measurement date until February 05, 2020, for incident complications of PH.

Imaging of the Pancreas in New-Onset Diabetes: A Prospective Pilot Study.

Introduction: The aim of this study was to assess the feasibility of cross-sectional imaging for detection of pancreatic cancer (PDAC) in patients with new-onset hyperglycemia and diabetes (NOD).

Methods: We conducted a prospective pilot study from November 2018 to March 2020 within an integrated health system. Patients aged 50-85 years with newly elevated glycemic parameters without a history of diabetes were invited to complete a 3-phase contrast-enhanced computed tomography pancreas protocol scan while participating in the Prospective Study to Establish a NOD Cohort.

Personalized statistical learning algorithms to improve the early detection of cancer using longitudinal biomarkers.

Background: Patients undergoing screening for early detection of cancer have serial biomarker measurements that are not traditionally being incorporated into decision making when evaluating biomarkers.

Objective: We discuss statistical learning algorithms that have the ability to learn from patient history to make personalized decision rules to improve the early detection of cancer. These artificial intelligence algorithms are able to learn in real time from data collected on the patient to identify changes in the patient that could signal asymptomatic cancer.

A multivariate parametric empirical Bayes screening approach for early detection of hepatocellular carcinoma using multiple longitudinal biomarkers.

The early detection of hepatocellular carcinoma (HCC) is critical to improving outcomes since advanced HCC has limited treatment options. Current guidelines recommend HCC ultrasound surveillance every 6 months in high-risk patients however the sensitivity for detecting early stage HCC in clinical practice is poor. Blood-based biomarkers are a promising direction since they are more easily standardized and less resource intensive.