Biomarkers are key components of the clinical management of patients with cancer, as they have contributed to major survival improvements in these patients.1Robertson D.J. Lee J.K. Boland C.R. et al.Recommendations on fecal immunochemical testing to screen for colorectal neoplasia: a consensus statement by the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2017; 152: 1217-1237.e3Abstract Full Text Full Text PDF PubMed Scopus (148) Google Scholar According to the National Cancer Institute, a biomarker is a biological molecule found in blood, other body fluids (eg, urine), or tissues that is a sign of a normal or abnormal process, or of a condition or disease. They allow classification of patients based on common features and facilitate risk stratification, early detection, diagnosis, and prediction of prognosis or treatment response. In hepatocellular carcinoma (HCC), there are few biomarkers incorporated in clinical practice despite a need to better stratify patients at different steps of clinical management. However, this has been an extensive area of research in recent years, with increasing efforts to identify biomarkers across the cancer care continuum from risk stratification to early detection to prognostication and treatment response (Table 1, Figure 1).Table 1Types of BiomarkersType of biomarkerDefinitionRisk stratificationBiomarker that predicts the future development of HCC in an at-risk patientEarly detectionBiomarker that detects HCC at an early tumor stage, when therapy can be delivered which would reduce HCC-related mortalityDiagnosisBiomarker that can confirm or exclude presence of HCC in patients with a suspicious nodule or clinical concern for HCCPrognosisBiomarker that predicts overall cancer outcome, regardless of treatmentTreatment responseBiomarker that predicts favorable or unfavorable response to a specific treatmentHCC, hepatocellular carcinoma. Open table in a new tab HCC, hepatocellular carcinoma. One of the first systematic sets of recommendations dealing with biomarkers in cancer was introduced in 1996 by Hayes et al,2Hayes D.F. Bast R.C. Desch C.E. et al.Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers.J Natl Cancer Inst. 1996; 88: 1456-1466Crossref PubMed Scopus (618) Google Scholar known as the Tumor Marker Utility Grading System (TMGUS). These recommendations covered not only technical aspects of assay development, but also issues related to clinical utility and levels of evidence. TMGUS was later expanded by the Reporting recommendations for tumor marker prognostic studies (REMARK) guidelines,3McShane L.M. Altman D.G. Sauerbrei W. et al.Reporting recommendations for tumor marker prognostic studies (REMARK).J Natl Cancer Inst. 2005; 97: 1180-1184Crossref PubMed Scopus (1084) Google Scholar a more focused approach on recommendations for reporting prognostic biomarkers in oncology. There have also been specific initiatives to describe study design thoroughly for cancer biomarkers in specific clinical scenarios, such as the Early Detection Research Network (EDRN) publishing a framework for 5 phases of biomarker development and validation for cancer screening.4Pepe M.S. Etzioni R. Feng Z. et al.Phases of biomarker development for early detection of cancer.J Natl Cancer Inst. 2001; 93: 1054-1061Crossref PubMed Google Scholar In brief, these phases extend from biomarker discovery (phase I) to evaluation of biomarker performance (phases II-III) and clinical benefits and harms (phase IV-V) (Table 2).Table 2Outcomes, Study Design, and Analysis for Early Detection of HCCPhasesOutcomesStudy designAnalysis1Exploratory TPR and FPRPreclinical case-control study-TPR, FPR, ROC curves to identify potential biomarkers2Clinical assay TPR and FPRCase-control study-TPR, FPR, ROC curves-Comparison with AFP ± ultrasound-Combinations of markers-Impact of covariates on biomarker performance3Detection of preclinical HCCPRoBE (prospective specimen collection, retrospective blinded evaluation) design-TPR, FPR, ROC curves-Comparison with AFP ± ultrasound-Time between outcome and biomarker measurement-Combination of markers4HCC detection ratesProspective cohort-PPV-HCC Stage distribution-TPR, FPR, ROC curves-Benefits (early HCC detection) and harms (false positive rate)-Comparison with AFP ± ultrasound5Decrease in HCC mortalityRandomized study-Survival analysis and Cox regression-Cost and quality of life-Overdiagnosis and overtreatmentAFP, alpha-fetoprotein; FPR, false positive rate; HCC, hepatocellular carcinoma; PPV, positive predictive value; ROC, receiver operating characteristics curve; TPR, true positive rate. Open table in a new tab AFP, alpha-fetoprotein; FPR, false positive rate; HCC, hepatocellular carcinoma; PPV, positive predictive value; ROC, receiver operating characteristics curve; TPR, true positive rate. Although these guidelines provide a useful general framework of data elements required at each step, deviations from this framework may be possible or necessary in specific circumstances. Further, modifications may be required when applied to other clinical scenarios, including risk stratification and treatment response assessment. Finally, singularities unique to HCC, particularly the coexistence of chronic liver disease in most patients, lead to necessary considerations when designing biomarker studies. To address these issues, the International Liver Cancer Association has assembled a group of experts on biomarker development to provide a framework on best practices to design, execute, and interpret biomarker studies for risk stratification, early detection, diagnosis, prognostication, and treatment response assessment in HCC. Risk of HCC is elevated in patients with chronic liver disease, particularly those with cirrhosis from any etiology, and HCC is one of the leading causes of death in these patients.5Fujiwara N. Friedman S.L. Goossens N. et al.Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine.J Hepatol. 2018; 68: 526-549Abstract Full Text Full Text PDF PubMed Scopus (244) Google Scholar Contemporary cohorts, which have higher numbers of patients with hepatitis C post-sustained viral response and those with nonalcoholic steatohepatitis (NASH), have demonstrated an annual HCC risk of 1% to 3%, substantially lower than the traditional annual HCC risk of 3% to 5% from older cohorts.6Moon A.M. Singal A.G. Tapper E.B. Contemporary epidemiology of chronic liver disease and cirrhosis.Clin Gastroenterol Hepatol. 2020; 18: 2650-2666Abstract Full Text Full Text PDF PubMed Scopus (114) Google Scholar,7Goossens N. Bian C.B. Hoshida Y. Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?.Curr Hepatol Rep. 2017; 16: 64-71Crossref PubMed Google Scholar However, patient characteristics, such as age, sex, race/ethnicity, and degree of fibrosis, introduce heterogeneity in HCC risk between patients.8Rich N.E. Hester C. Odewole M. et al.Racial and ethnic differences in presentation and outcomes of hepatocellular carcinoma.Clin Gastroenterol Hepatol. 2019; 17: 551-559.e1Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar Subgroups of patients with chronic hepatitis B virus (HBV) infection without cirrhosis, such as Asian men older than 40 years and Asian women older than 50 years, have an annual HCC incidence of 0.4% to 0.6%, whereas younger individuals have a lower HCC incidence of 0.2%. Refined risk stratification could have several implications for clinical practice, such as tailoring of HCC surveillance intensity in the future and targeting chemoprevention efforts (eg, coffee, lipophilic statins, aspirin9Athuluri-Divakar S.K. Hoshida Y. Generic chemoprevention of hepatocellular carcinoma.Ann N Y Acad Sci. 2019; 1440: 23-35Crossref PubMed Scopus (9) Google Scholar) to high-risk persons. For example, the “one-size-fits-all” surveillance strategy of semi-annual ultrasound with or without alpha-fetoprotein (AFP) could be tailored based on the individual HCC risk in each patient.10Goossens N. Singal A.G. King L.Y. et al.Cost-effectiveness of risk score-stratified hepatocellular carcinoma screening in patients with cirrhosis.Clin Transl Gastroenterol. 2017; 8e101Crossref PubMed Google Scholar Further, risk stratification biomarkers could help select patients for chemoprevention clinical trials, thereby reducing necessary sample sizes and making these trials more feasible. In addition to patients with cirrhosis, risk stratification is also needed for patients with chronic HBV infection or with advanced fibrosis, particularly in the setting of NASH or post-sustained viral response. Although HCC can occur in the absence of cirrhosis,11Mittal S. El-Serag H.B. Sada Y.H. et al.Hepatocellular carcinoma in the absence of cirrhosis in United States veterans is associated with nonalcoholic fatty liver disease.Clin Gastroenterol Hepatol. 2016; 14: 124-131.e1Abstract Full Text Full Text PDF PubMed Scopus (273) Google Scholar patients without cirrhosis have a low annual HCC rate and surveillance is not cost-effective.12Loomba R. Lim J.K. Patton H. et al.AGA clinical practice update on screening and surveillance for hepatocellular carcinoma in patients with nonalcoholic fatty liver disease: expert review.Gastroenterology. 2020; 158: 1822-1830Abstract Full Text Full Text PDF PubMed Google Scholar,13Farhang Zangneh H. Wong W.W.L. Sander B. et al.Cost effectiveness of hepatocellular carcinoma surveillance after a sustained virologic response to therapy in patients with hepatitis C virus infection and advanced fibrosis.Clin Gastroenterol Hepatol. 2019; 17: 1840-1849.e16Abstract Full Text Full Text PDF PubMed Scopus (39) Google Scholar Effective risk stratification biomarkers may identify subgroups of those with advanced fibrosis but not cirrhosis who would benefit from surveillance. The EDRN framework for phases of biomarker evaluation for early detection do not directly apply to risk stratification, although several of the concepts are similar. Derivation of risk stratification biomarkers can be done in a retrospective cohort and/or nested case-control study, in which the biomarker assay would be assessed at baseline, cases develop HCC during follow-up, and controls remain HCC-free over equivalent or longer follow-up. The time frame between biomarker assessment and HCC diagnosis should be long enough (eg, > 2 years) to minimize the likelihood of detecting preexisting undetected tumoral disease. A 2-year time frame is recommended given the low sensitivity of imaging to detect very early-stage HCC and some patients with HCC exhibiting indolent growth patterns, thereby potentially remaining subclinical for many months.14Nathani P. Gopal P. Rich N. et al.Hepatocellular carcinoma tumour volume doubling time: a systematic review and meta-analysis.Gut. 2021; 70: 401-407PubMed Google Scholar,15Rich N.E. John B.V. Parikh N.D. et al.Hepatocellular carcinoma demonstrates heterogeneous growth patterns in a multi-center cohort of patients with cirrhosis.Hepatology. 2020; 72: 1664-1665Crossref Scopus (43) Google Scholar Therefore, case-control studies with shorter periods between biomarker assessment and HCC diagnosis may confound a biomarker’s performance for risk stratification versus early detection (Figure 2). When selecting patients for a nested case-control design, cases and controls should be matched for known clinical risk factors, such as age, gender, and etiology and severity of liver disease. When available, archived biospecimens from a prospective cohort study (ie, prospective-retrospective design) would allow more reliable estimation of biomarker performance based on time-to-event data analysis.16Simon R.M. Paik S. Hayes D.F. Use of archived specimens in evaluation of prognostic and predictive biomarkers.J Natl Cancer Inst. 2009; 101: 1446-1452Crossref PubMed Scopus (742) Google Scholar As needed, early-phase validation can be conducted in independent nested case-control studies or cohorts, where model parameters and/or thresholds to define risk groups could be further optimized. Late-phase validation is then conducted in an adequately powered independent prospective-retrospective or prospective cohort to compare the HCC incidence rate between high-risk and low-risk groups or assess association of the biomarker and HCC incidence. Biomarker performance should be evaluated using a combination of several metrics. Overall model performance (degree of variation explained by the biomarker panel) is typically assessed by R2 or Brier scores. Discrimination (ability to distinguish between patients who develop versus do not develop HCC) is assessed by the magnitude of risk separation between high-risk and low-risk groups measured by fitness of the model determined by time-dependent area under the receiver operator characteristic curve, concordance index (c-index), and/or Akaike’s Information Criterion. Calibration (difference between observed and predicted event rates) is often assessed by the Hosmer-Lemeshow statistic and improvement of prediction (or reclassification) is assessed via net reclassification index misclassification tables or standardized net benefit. Following validation of risk-predictive capability, the implementation phase would evaluate the benefit of incorporating risk stratification biomarkers in an experimental system, for example, individual-risk-stratified HCC screening, for outcomes including early detection, overall survival (OS), and cost-effectiveness. This is a complex problem, for which simulation analyses such as cost-effectiveness models can be helfpul.7Goossens N. Bian C.B. Hoshida Y. Tailored algorithms for hepatocellular carcinoma surveillance: Is one-size-fits-all strategy outdated?.Curr Hepatol Rep. 2017; 16: 64-71Crossref PubMed Google Scholar Relevant variables to consider include performance of the biomarker to stratify HCC risk groups, HCC incidence in each risk group, costs for medical care including the biomarker, and benefits and harms of HCC screening in each risk group. These models can also provide information about desired biomarker performance and costs to meet the cost-effectiveness threshold. There are several analytical issues that should be considered including the following: (1) use of a continuous risk measure versus assigning risk categories, with the former providing more granular information but the latter being easier to interpret by providers; (2) evaluating a biomarker in isolation vs combining with clinical variables as an integrative risk score, with the latter likely being needed in light of the heterogeneity of cancer pathogenesis; (3) accounting for changes in risk over time due to natural disease progression or clinical interventions (eg, antiviral therapy); and (4) optimizing risk stratification models in specific clinical contexts defined by clinical characteristics such as liver disease etiology. Decisions regarding these model optimization issues must balance clinically meaningful benefit vs practical feasibility. HCC fulfills all of the World Health Organization criteria for a cancer screening program, including high morbidity and mortality, an identifiable target population, a recognizable preclinical stage, accepted recall procedures, and efficacious treatment. Therefore, professional society guidelines recommend semi-annual surveillance using abdominal ultrasound with or without AFP among at-risk patients, including subgroups of patients with chronic HBV infection and those with cirrhosis from any etiology.17Marrero J.A. Kulik L.M. Sirlin C.B. et al.Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases.Hepatology. 2018; 68: 723-750Crossref PubMed Scopus (1290) Google Scholar,18Galle P.R. Forner A. Llovet J.M. et al.EASL clinical practice guidelines: management of hepatocellular carcinoma.J Hepatol. 2018; 69: 182-236Abstract Full Text Full Text PDF PubMed Scopus (2663) Google Scholar Ultrasound and AFP are the only 2 surveillance tests recommended in guidelines and have been the long-standing cornerstone of HCC surveillance. However, ultrasound can have highly variable performance given its operator-dependent nature and the sensitivity of ultrasound with AFP, at a cutoff of 20 ng/mL, for early HCC detection is suboptimal, at only 63%.19Tzartzeva K. Obi J. Rich N.E. et al.Surveillance imaging and alpha fetoprotein for early detection of hepatocellular carcinoma in patients with cirrhosis: a meta-analysis.Gastroenterology. 2018; 154: 1706-1718.e1Abstract Full Text Full Text PDF PubMed Scopus (240) Google Scholar Evolving data also highlight the potential for poor ultrasound visualization, particularly among obese patients and those with NASH, as well as false positive or indeterminate results causing screening-related harms.20Simmons O. Fetzer D.T. Yokoo T. et al.Predictors of adequate ultrasound quality for hepatocellular carcinoma surveillance in patients with cirrhosis.Aliment Pharmacol Ther. 2017; 45: 169-177Crossref PubMed Google Scholar,21Atiq O. Tiro J. Yopp A.C. et al.An assessment of benefits and harms of hepatocellular carcinoma surveillance in patients with cirrhosis.Hepatology. 2017; 65: 1196-1205Crossref PubMed Scopus (100) Google Scholar Finally, ultrasound-based surveillance programs often require a separate appointment, creating potential barriers to adherence, contributing to underuse of HCC surveillance in clinical practice, occurring in less than 50% across geographic regions.22Singal A.G. Tiro J.A. Murphy C.C. et al.Patient-reported barriers are associated with receipt of hepatocellular carcinoma surveillance in a multi-center cohort of patients with cirrhosis.Clin Gastroenterol Hepatol. 2021; 19: 987-995.e1Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar,23Wolf E. Rich N.E. Marrero J.A. et al.Use of hepatocellular carcinoma surveillance in patients with cirrhosis: a systematic review and meta-analysis.Hepatology. 2021; 73: 713-725Crossref PubMed Scopus (30) Google Scholar Overall, the limitations of our current strategy highlight a strong need for alternative surveillance tests, particularly highly accurate blood-based biomarkers. Patients with cirrhosis from any etiology comprise the group with the highest risk for developing HCC and account for >90% of all cases in the United States and Europe, whereas chronic HBV infection remains the most common target population globally. Although contemporary cohorts suggest a lower annual HCC incidence of ∼2%,24Ioannou G.N. Beste L.A. Green P.K. et al.Increased risk for hepatocellular carcinoma persists up to 10 years after HCV eradication in patients with baseline cirrhosis or high FIB-4 Scores.Gastroenterology. 2019; 157: 1264-1278.e4Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar, 25Bertot L.C. Adams L.A. Trends in hepatocellular carcinoma due to non-alcoholic fatty liver disease.Expert Rev Gastroenterol Hepatol. 2019; 13: 179-187Crossref PubMed Scopus (20) Google Scholar, 26Ganne-Carrie N. Chaffaut C. Bourcier V. et al.Estimate of hepatocellular carcinoma incidence in patients with alcoholic cirrhosis.J Hepatol. 2018; 69: 1274-1283Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar HCC incidence among patients with cirrhosis still exceeds the cost-effectiveness threshold of 1.5% per year.17Marrero J.A. Kulik L.M. Sirlin C.B. et al.Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases.Hepatology. 2018; 68: 723-750Crossref PubMed Scopus (1290) Google Scholar,18Galle P.R. Forner A. Llovet J.M. et al.EASL clinical practice guidelines: management of hepatocellular carcinoma.J Hepatol. 2018; 69: 182-236Abstract Full Text Full Text PDF PubMed Scopus (2663) Google Scholar,27Singal A.G. Parikh N.D. Hutton D.W. et al.Cost effectiveness of hepatocellular carcinoma surveillance: An assessment of benefits and harms.Am J Gastro. 2020; 115: 1642-1649Crossref PubMed Scopus (13) Google Scholar Similarly, annual HCC incidence in subgroups with chronic HBV infection exceeds the cost-effectiveness threshold of 0.2%. Therefore, patients with cirrhosis or chronic HBV infection should be the target population for studies examining HCC surveillance biomarkers.17Marrero J.A. Kulik L.M. Sirlin C.B. et al.Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases.Hepatology. 2018; 68: 723-750Crossref PubMed Scopus (1290) Google Scholar Further, surveillance studies should be restricted to those who would potentially benefit from a therapeutic intervention. For example, surveillance is only of benefit in patients with preserved liver function, as those with significant hepatic decompensation (eg, Child Pugh C cirrhosis if not eligible for liver transplantation) or comorbidity have higher competing risk of non-HCC mortality. Patients with advanced fibrosis but not cirrhosis are known to develop HCC, but with incidence rates well below the threshold recommended for surveillance. Biomarker studies in HCC should not combine patients with cirrhosis and those with advanced fibrosis, as this will lead to underestimating sample size calculations, longer accrual to identify a sufficient number of HCC cases, and ultimately lead to biased conclusions and uncertainty if there is a benefit of the new biomarker. If an accurate risk stratification biomarker can identify a subset of patients with advanced fibrosis and similar HCC risk as those with cirrhosis, these patients may be included in early detection trials in the future. A frequent misconception in the field is the confusion between early detection and diagnostic biomarkers. As tools for cancer surveillance, early detection biomarkers will trigger a confirmatory diagnostic procedure, but per se, they are not sufficient to assign an HCC diagnosis. The appropriate study design and outcomes will be dependent on the phase of biomarker development (Table 2 and Figure 3).4Pepe M.S. Etzioni R. Feng Z. et al.Phases of biomarker development for early detection of cancer.J Natl Cancer Inst. 2001; 93: 1054-1061Crossref PubMed Google Scholar Phase 1 studies aim to identify biomarkers and determine how well they distinguish HCC and non-HCC controls, that is, the true positive rate (TPR) and false positive rate (FPR). These studies can include genes (single or array), proteins, and radiologic tests and may start with measurement of the biomarker at the tissue level, with or without correlation with serum or plasma. Phase 2 is the clinical assay development based on a specimen that can be obtained noninvasively. Outcomes at this phase are estimation of TPR and FPR or the receiver operating characteristics curve for the biomarker to distinguish subjects with HCC from those with cirrhosis but without HCC. The same analytic principles comparing cases and controls apply to phase 1 and phase 2 studies. However, phase 2 studies should be appropriately powered to not only estimate TPR, FPR, and area under the receiver operator characteristic curve but also determine the impact of covariates such as age, sex, etiology of liver disease, and degree of liver dysfunction on biomarker performance. These covariates of interest cannot be used as matching variables, as doing so would render their effects toward null. In a phase II study, HCC cases should be ideally restricted to those at an early stage, either defined by Barcelona Clinic Liver Cancer (BCLC) staging system or Milan Criteria, because the goal of HCC is detection of early-stage disease and biomarker performance would otherwise be overestimated.17Marrero J.A. Kulik L.M. Sirlin C.B. et al.Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases.Hepatology. 2018; 68: 723-750Crossref PubMed Scopus (1290) Google Scholar,18Galle P.R. Forner A. Llovet J.M. et al.EASL clinical practice guidelines: management of hepatocellular carcinoma.J Hepatol. 2018; 69: 182-236Abstract Full Text Full Text PDF PubMed Scopus (2663) Google Scholar It is at this stage that comparison with the current standard is performed and the study should be powered to compare the new biomarker to ultrasound with or without AFP, although it should be noted this comparison may have bias given ultrasound and AFP were likely to trigger diagnostic testing in a subset of the cohort. Depending on the biomarker, one may consider subgroup analyses of particular interest, such as among those with NASH cirrhosis. Similarly, one could consider subgroup analyses by baseline HCC risk if accurate risk stratification biomarkers are available in the future. Phase 3 studies leverage prospective cohort studies, in which samples are collected at regular semi-annual intervals, with the main outcome to evaluate the ability of the biomarker to detect preclinical HCC. The samples are stored initially and then analyzed using the PRoBE design (prospective specimen collection, retrospective blinded evaluation), allowing a nested case-control analysis.28Pepe M.S. Feng Z. Janes H. et al.Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design.J Natl Cancer Inst. 2008; 100: 1432-1438Crossref PubMed Scopus (452) Google Scholar Adequate sample size to facilitate a sufficient number of incident HCC and provide strong conclusions is critical, including facilitating subgroup analyses in subpopulations of interest to help determine the impact of covariates on the biomarker’s accuracy. Protocols should detail specimen handling (including collection, processing, storage, and retrieval), and there should be strict definitions for incident HCC, per guidelines,17Marrero J.A. Kulik L.M. Sirlin C.B. et al.Diagnosis, staging, and management of hepatocellular carcinoma: 2018 practice guidance by the American Association for the Study of Liver Diseases.Hepatology. 2018; 68: 723-750Crossref PubMed Scopus (1290) Google Scholar,18Galle P.R. Forner A. Llovet J.M. et al.EASL clinical practice guidelines: management of hepatocellular carcinoma.J Hepatol. 2018; 69: 182-236Abstract Full Text Full Text PDF PubMed Scopus (2663) Google Scholar including the use of a multidisciplinary tumor board or adjudication committee. Phase 3 studies should also incorporate end-of-study imaging or a follow-up period among non-HCC patients to minimize risk of ascertainment bias. It is important to identify if the biomarker will be used alone or combined with other markers or demographic information (such as age and sex, as has been done with GALAD).29Berhane S. Toyoda H. Tada T. et al.Role of the GALAD and BALAD-2 serologic models in diagnosis of hepatocellular carcinoma and prediction of survival in patients.Clin Gastroenterol Hepatol. 2016; 14: 875-886.e6Abstract Full Text Full Text PDF PubMed Scopus (113) Google Scholar Based on ultrasound and AFP performance, minimally acceptable TPR and FPR rates for new biomarkers for early HCC detection are approximately 65% and 10%, respectively, and these should be measured at preclinical lag times of interest (eg, at diagnosis, or 6 to 12 months before HCC diagnosis). Thresholds for TPR and FPR vary by population-level HCC risk in the local area, so strategies with higher TPR may be desired in areas with higher HCC risk populations. Phase 4 studies are prospective cohort studies in which the biomarker of interest is applied to individuals in real-time and diagnostic procedures are performed for those with a positive test. For such studies, the assay must be reliable and reproducible, and readily available to clinicians to make decisions for diagnosis and treatment. There are 4 potential outcomes at each surveillance interval: (1) the biomarker is positive and HCC is confirmed (true positive), (2) the biomarker is positive and HCC is not confirmed (false positive), (3) the biomarker is negative and HCC is discovered (false negative), and (4) the biomarker is negative and HCC is absent (true negative). Without adequate follow-up to confirm false negatives or true negatives, positive predictive value can be calculated after workup for test positives but sensitivity or specificity could not be calculated. Therefore, measures such as an additional follow-up period of 6 to 12 months with ultrasound-based surveillance, or diagnostic computed tomography (CT) or magnetic resonance imaging (MRI) in patients with negative surveillance tests, are needed to exclude HCC and minimize risk of ascertainment bias. Outcomes of interest from a phase IV biomarker study include the detection rate, that is, the proportion of cirrhotic subjects who tested positive and have HCC, and false-referral rate, that is, the proportion who have a positive surveillance test but do not have HCC on diagnostic imaging. Tumor characteristics including stage and any features of tumor biology should be collected to inform power calculations for a subsequent phase 5 study. An issue with phase 4 studies is that they can be costly and time-consuming, thereby delaying availability of new biomarkers for early detection of HCC. A well-performed phase 3 study may obviate the need for a phase 4 study if the following are present: (1) the biomarker is readily available and reproducible, (2) phase III study accounted for potential ascertainment bias in controls without HCC, (3) phase III study performed longitudinal evaluation of the biomarker in non-HCC patients to characterize FPR over time, (4) phase III study assessed biomarker performance at early detectable time points among HCC patients to characterize TPR, and (5) phase III