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. METHODS: The multicenter Hepatocellular Carcinoma Early Detection Strategy study of the National Institutes of Health prospectively enrolled patients with cirrhosis who underwent standard surveillance for HCC. Demographics, medical and family history, etiology of liver disease, and clinical features were evaluated for associations with HCC. RESULTS: Between April 10, 2013 and December 31, 2021, 1723 patients were enrolled and confirmed eligible. During median follow-up of 2.2 years (range, 0-8.7 years), there were 109 incident cases of HCC for an incidence rate of 2.4 per 100 person-years: 88 (81%) patients with very early/early Barcelona Clinic Liver Cancer stage (0, A), 20 (18%) intermediate stage (B), and 1 (1%) unknown stage. Risk factor analyses were restricted to 1325 patients, including 95 incident HCC, with at least 6 months of follow-up. The majority were men (53.2%), obese or severely obese (median body mass index, 30.2 kg/m2), and white (86.3%); 42.0% had history of hepatitis C virus infection, 20.7% had alcoholic liver disease, and 24.9% had nonalcoholic fatty liver disease. Fourteen risk factors for HCC were significant (P < .05) in univariate analyses, and a multivariate subset was selected using stepwise logistic regression. The multivariate subset contained gender (P < .001; male; odds ratio [OR], 2.47; 95% confidence interval [CI], 1.54-4.07), years with cirrhosis (P = .004; OR, 1.06; 95% CI, 1.02-1.1), family history of liver cancer (P = .02; yes; OR, 2.69; 95% CI, 1.11-5.86), age (per 5 years; P = .02; OR, 1.17; 95% CI, 1.03-1.33), obesity (P = .02; yes; OR, 1.7; 95% CI, 1.08-2.73), aspartate aminotransferase (log(1+AST); P = .06; OR, 1.54; 95% CI, 0.97-2.42), alpha-fetoprotein (log(1+AFP); P = .07; OR, 1.32; 95% CI, 0.97-1.77), and albumin (P = .10; OR, 0.7; 95% CI, 0.46-1.07). CONCLUSIONS: Thus far, this is the largest prospective and geographically diverse study of a U.S. cohort of patients with cirrhosis that validates known risk factors for HCC (gender, age, obesity, years with cirrhosis, family history of liver cancer, baseline AFP, albumin, and AST). The incidence of HCC was 2.4% per 100 person-years.

Mortality Benefit of a Blood-Based Biomarker Panel for Lung Cancer on the Basis of the Prostate, Lung, Colorectal, and Ovarian Cohort.

PURPOSE: To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model on the basis of subject characteristics to identify individuals at high risk of harboring a lethal lung cancer. METHODS: Data from an established logistic regression model that combines four-marker protein panel (4MP) together with the Prostate, Lung, Colorectal, and Ovarian (PLCO) risk model (PLCOm2012) assayed in prediagnostic sera from 552 lung cancer cases and 2,193 noncases from the PLCO cohort were used in this study. Of the 552 lung cancer cases, 387 (70%) died of lung cancer. Cumulative incidence of lung cancer death and subdistributional and cause-specific hazard ratios (HRs) were calculated on the basis of 4MP + PLCOm2012 risk scores at a predefined 1.0% and 1.7% 6-year risk thresholds, which correspond to the current and former US Preventive Services Task Force screening criteria, respectively. RESULTS: When considering cases diagnosed within 1 year of blood draw and all noncases, the area under receiver operation characteristics curve estimate of the 4MP + PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI, 0.86 to 0.90). The cumulative incidence of lung cancer death was statistically significantly higher in individuals with 4MP + PLCOm2012 scores above the 1.0% 6-year risk threshold (modified χ2, 166.27; P < .0001). Corresponding subdistributional and lung cancer death-specific HRs for test-positive cases were 9.88 (95% CI, 6.44 to 15.18) and 10.65 (95% CI, 6.93 to 16.37), respectively. CONCLUSION: The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.

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.S. liver transplant centers in patients with cirrhosis who underwent liver resection or transplant between January 2009 and December 2019 and standard "full" liver MRI with and without contrast enhancement within 3 months before surgery. Patients who had HCC-directed treatment before surgery were excluded. Dynamic abbreviated MRI examinations were simulated from the presurgical full MRI by selecting the coronal T2-weighted and axial three-dimensional fat-suppressed T1-weighted dynamic contrast-enhanced sequences at precontrast, late arterial, portal venous, and delayed phases. Two abdominal radiologists at each center independently interpreted the simulated abbreviated examinations with use of the Liver Imaging Reporting and Data System version 2018. Patients with any high-risk liver observations (>LR-3) were classified as positive; otherwise, they were classified as negative. With liver pathologic findings as the reference standard for the presence versus absence of early-stage HCC, the sensitivity, specificity, and their 95% CIs were calculated. Logistic regression was used to identify factors associated with correct classification. Results A total of 161 patients with early-stage HCC (median age, 62 years [IQR, 58-67 years]; 123 men) and 138 patients without HCC (median age, 55 years [IQR, 47-63 years]; 85 men) were confirmed with surgical pathologic findings. The sensitivity and specificity of abbreviated MRI were 88.2% (142 of 161 patients) (95% CI: 83.5, 92.5) and 89.1% (123 of 138 patients) (95% CI: 84.4, 93.8), respectively. Sensitivity was lower for Child-Pugh class B or C versus Child-Pugh class A cirrhosis (64.1% vs 94.2%; P < .001). Conclusion With surgical pathologic findings as the reference standard, dynamic abbreviated MRI had high sensitivity and specificity for early-stage hepatocellular carcinoma detection in patients with compensated cirrhosis but lower sensitivity in those with decompensated cirrhosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim in this issue.

The COMPASS study: A prospective, randomized, multi-center trial testing the impact of a clinic-based intervention informing patients of colorectal cancer screening options on screening completion.

BACKGROUND: Colorectal cancer (CRC) screening is underutilized despite evidence that screening improves survival. Since healthcare provider recommendation is a strong predictor of CRC screening completion, providers are encouraged to engage eligible patients in collaborative decision-making that attends to patients' values, needs, and preferences for guideline-concordant screening modalities. METHODS: This three-arm randomized controlled trial is testing the effectiveness of an evidence-based video intervention informing patients of screening choices delivered in a clinic prior to a healthcare appointment. We hypothesize that participants randomized to watch a basic video describing CRC and screening in addition to an informed choice video showing the advantages and disadvantages of fecal immunochemical test (FIT), stool DNA FIT (s-DNA FIT), and colonoscopy (Arm 3) will exhibit a greater proportion of time adherent to CRC screening guidelines after 1, 3 and 6 years than those who only watch the basic video (Arm 2) or no video at all (Arm 1). Primary care and Obstetrician/Gynecology clinics across the United States are recruiting 5280 patients, half who have never been screened and half who previously screened but are currently not guideline adherent. Participants complete surveys prior to and following an index appointment to self-report personal, cognitive, and environmental factors potentially associated with screening. Proportion of time adherent to screening guidelines will be assessed using medical record data and supplemented with annual surveys self-reporting screening. CONCLUSION: Results will provide evidence on the effectiveness of informational and motivational videos to encourage CRC screening that can be easily integrated into clinical practice. CLINICALTRIALS: gov #NCT05246839.

Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment.

PURPOSE: To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics. METHODS: A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCOm2012) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera. RESULTS: The 4MP alone yielded an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77 to 0.82) for case sera collected within 1-year preceding diagnosis and 0.74 (95% CI, 0.72 to 0.76) among the entire specimen set. The combined 4MP + PLCOm2012 model yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.82 to 0.88) for case sera collected within 1 year preceding diagnosis. The benefit of the 4MP in the combined model resulted from improvement in sensitivity at high specificity. Compared with the USPSTF2021 criteria, the combined 4MP + PLCOm2012 model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCOm2012 model would have identified for annual screening 9.2% more lung cancer cases and would have reduced referral by 13.7% among noncases compared with USPSTF2021 criteria. CONCLUSION: A blood-based biomarker panel in combination with PLCOm2012 significantly improves lung cancer risk assessment for lung cancer screening.

Statistical inference for net benefit measures in biomarker validation studies.

Referral strategies based on risk scores and medical tests are commonly proposed. Direct assessment of their clinical utility requires implementing the strategy and is not possible in the early phases of biomarker research. Prior to late-phase studies, net benefit measures can be used to assess the potential clinical impact of a proposed strategy. Validation studies, in which the biomarker defines a prespecified referral strategy, are a gold standard approach to evaluating biomarker potential. Uncertainty, quantified by a confidence interval, is important to consider when deciding whether a biomarker warrants an impact study, does not demonstrate clinical potential, or that more data are needed. We establish distribution theory for empirical estimators of net benefit and propose empirical estimators of variance. The primary results are for the most commonly employed estimators of net benefit: from cohort and unmatched case-control samples, and for point estimates and net benefit curves. Novel estimators of net benefit under stratified two-phase and categorically matched case-control sampling are proposed and distribution theory developed. Results for common variants of net benefit and for estimation from right-censored outcomes are also presented. We motivate and demonstrate the methodology with examples from lung cancer research and highlight its application to study design.

Applying sequential surveillance methods that use regression adjustment or weighting to control confounding in a multisite, rare-event, distributed setting: Part 2 in-depth example of a reanalysis of the measles-mumps-rubella-varicella combination vaccine and seizure risk.

OBJECTIVE: In-depth example of two new group sequential methods for postmarket safety monitoring of new medical products. STUDY DESIGN AND SETTING: Existing trial-based group sequential approaches have been extended to adjust for confounders, accommodate rare events, and address privacy-related constraints on data sharing. Most adaptations have involved design-based confounder strategies, for example, self-controlled or exposure matching, while analysis-based approaches like regression and weighting have received less attention. We describe the methodology of two new group sequential approaches that use analysis-based confounder adjustment (GS GEE) and weighting (GS IPTW). Using data from the Food and Drug Administration's Sentinel network, we apply both methods in the context of a known positive association: the measles-mumps-rubella-varicella vaccine and seizure risk in infants. RESULTS: Estimates from both new approaches were similar and comparable to prior studies using design-based methods to address confounding. The time to detection of a safety signal was considerably shorter for GS IPTW, which estimates a risk difference, compared to GS GEE, which provides relative estimates of excess risk. CONCLUSION: Future group sequential safety surveillance efforts should consider analysis-based confounder adjustment techniques that evaluate safety signals on the risk difference scale to achieve greater statistical power and more timely results.

Assessing the Clinical Impact of Risk Models for Opting Out of Treatment.

Decision curves are a tool for evaluating the population impact of using a risk model for deciding whether to undergo some intervention, which might be a treatment to help prevent an unwanted clinical event or invasive diagnostic testing such as biopsy. The common formulation of decision curves is based on an opt-in framework. That is, a risk model is evaluated based on the population impact of using the model to opt high-risk patients into treatment in a setting where the standard of care is not to treat. Opt-in decision curves display the population net benefit of the risk model in comparison to the reference policy of treating no patients. In some contexts, however, the standard of care in the absence of a risk model is to treat everyone, and the potential use of the risk model would be to opt low-risk patients out of treatment. Although opt-out settings were discussed in the original decision curve paper, opt-out decision curves are underused. We review the formulation of opt-out decision curves and discuss their advantages for interpretation and inference when treat-all is the standard.

A Plasma Biomarker Panel to Identify Surgically Resectable Early-Stage Pancreatic Cancer.

Background: Blood-based biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are urgently needed. Current biomarkers lack high sensitivity and specificity for population screening. The gold-standard biomarker, CA 19-9, also fails to demonstrate the predictive value necessary for early detection. Methods: To validate a functional genomics-based plasma migration signature biomarker panel, plasma tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FN III-C), and CA 19-9 levels were measured by enzyme-linked immunosorbent assays in three early-stage PDAC plasma cohorts, including two independent blinded validation cohorts containing a total of 43 stage I, 163 stage II, 86 chronic pancreatitis, 31 acute biliary obstruction, and 108 controls. Logistic regression models developed classification rules combining TFPI and/or TNC-FN III-C with CA 19-9 for patient cases and control subjects, with or without adjustment for age and diabetes status. Model classification performance was evaluated and analyses repeated among subpopulations without diabetes and pancreatitis history. Two-sided P values were calculated using bootstrap method. Results: The TFPI/TNC-FN III-C/CA 19-9 panel improved CA 19-9 performance in all early-stage cohorts, including discriminating stage IA/IB/IIA, stage IIB, and all early-stage cancer from healthy controls. Statistical significance was reached for a number of subcohorts, including for all early-stage cancer vs healthy controls (cohort 1 AUC = 0.92, 95% CI = 0.86 to 0.96, P = .04; cohort 3 AUC = 0.83, 95% CI = 0.76 to 0.89, P = .045). Among subcohorts without diabetes and pancreatitis history, the panel approaches potential clinical utility for early detection to discriminate early-stage PDAC from healthy controls including an area under the curve (AUC) of 0.87 (95% CI = 0.77 to 0.95) for stage I/IIA, an AUC of 0.93 (95% CI = 0.87 to 0.98) for stage IIB, and a statistically significant AUC of 0.89 (95% CI = 0.82 to 0.95) for all early-stage cancer ( P = .03). Conclusions: TFPI/TNC-FN III-C migration signature adds statistically significantly to CA 19-9's predictive power to detect early-stage PDAC and may have clinical utility for early detection of surgically resectable PDAC, as well as for enhanced survival from this routinely lethal cancer.

Validation of Models Used to Inform Colorectal Cancer Screening Guidelines: Accuracy and Implications.

BACKGROUND: Microsimulation models synthesize evidence about disease processes and interventions, providing a method for predicting long-term benefits and harms of prevention, screening, and treatment strategies. Because models often require assumptions about unobservable processes, assessing a model's predictive accuracy is important. METHODS: We validated 3 colorectal cancer (CRC) microsimulation models against outcomes from the United Kingdom Flexible Sigmoidoscopy Screening (UKFSS) Trial, a randomized controlled trial that examined the effectiveness of one-time flexible sigmoidoscopy screening to reduce CRC mortality. The models incorporate different assumptions about the time from adenoma initiation to development of preclinical and symptomatic CRC. Analyses compare model predictions to study estimates across a range of outcomes to provide insight into the accuracy of model assumptions. RESULTS: All 3 models accurately predicted the relative reduction in CRC mortality 10 years after screening (predicted hazard ratios, with 95% percentile intervals: 0.56 [0.44, 0.71], 0.63 [0.51, 0.75], 0.68 [0.53, 0.83]; estimated with 95% confidence interval: 0.56 [0.45, 0.69]). Two models with longer average preclinical duration accurately predicted the relative reduction in 10-year CRC incidence. Two models with longer mean sojourn time accurately predicted the number of screen-detected cancers. All 3 models predicted too many proximal adenomas among patients referred to colonoscopy. CONCLUSION: Model accuracy can only be established through external validation. Analyses such as these are therefore essential for any decision model. Results supported the assumptions that the average time from adenoma initiation to development of preclinical cancer is long (up to 25 years), and mean sojourn time is close to 4 years, suggesting the window for early detection and intervention by screening is relatively long. Variation in dwell time remains uncertain and could have important clinical and policy implications.

Plasma biomarker for detection of early stage pancreatic cancer and risk factors for pancreatic malignancy using antibodies for apolipoprotein-AII isoforms.

We recently reported that circulating apolipoprotein AII (apoAII) isoforms apoAII-ATQ/AT (C-terminal truncations of the apoAII homo-dimer) decline significantly in pancreatic cancer and thus might serve as plasma biomarkers for the early detection of this disease. We report here the development of novel enzyme-linked immunosorbent assays (ELISAs) for measurement of apoAII-ATQ/AT and their clinical applicability for early detection of pancreatic cancer. Plasma and serum concentrations of apoAII-ATQ/AT were measured in three independent cohorts, which comprised healthy control subjects and patients with pancreatic cancer and gastroenterologic diseases (n = 1156). These cohorts included 151 cases of stage I/II pancreatic cancer. ApoAII-ATQ/AT not only distinguished the early stages of pancreatic cancer from healthy controls but also identified patients at high risk for pancreatic malignancy. AUC values of apoAII-ATQ/AT to detect early stage pancreatic cancer were higher than those of CA19-9 in all independent cohorts. ApoAII-ATQ/AT is a potential biomarker for screening patients for the early stage of pancreatic cancer and identifying patients at risk for pancreatic malignancy (161 words).

Validation sampling can reduce bias in health care database studies: an illustration using influenza vaccination effectiveness.

OBJECTIVES: Estimates of treatment effectiveness in epidemiologic studies using large observational health care databases may be biased owing to inaccurate or incomplete information on important confounders. Study methods that collect and incorporate more comprehensive confounder data on a validation cohort may reduce confounding bias. STUDY DESIGN AND SETTING: We applied two such methods, namely imputation and reweighting, to Group Health administrative data (full sample) supplemented by more detailed confounder data from the Adult Changes in Thought study (validation sample). We used influenza vaccination effectiveness (with an unexposed comparator group) as an example and evaluated each method's ability to reduce bias using the control time period before influenza circulation. RESULTS: Both methods reduced, but did not completely eliminate, the bias compared with traditional effectiveness estimates that do not use the validation sample confounders. CONCLUSION: Although these results support the use of validation sampling methods to improve the accuracy of comparative effectiveness findings from health care database studies, they also illustrate that the success of such methods depends on many factors, including the ability to measure important confounders in a representative and large enough validation sample, the comparability of the full sample and validation sample, and the accuracy with which the data can be imputed or reweighted using the additional validation sample information.

Vaccination site and risk of local reactions in children 1 through 6 years of age.

OBJECTIVE: Our objective was to assess whether the occurrence of medically attended local reactions to intramuscularly administered vaccines varies by injection site (arm versus thigh) in children 1 to 6 years of age. METHODS: This is a retrospective cohort study of children in the Vaccine Safety Datalink population from 2002 to 2009. Site of injection and the outcome of medically attended local reactions were identified from administrative data. RESULTS: The study cohort of 1.4 million children received 6.0 million intramuscular (IM) vaccines during the study period. The primary analyses evaluated the IM vaccines most commonly administered alone, which included inactivated influenza, hepatitis A, and diphtheria-tetanus-acellular pertussis (DTaP) vaccines. For inactivated influenza and hepatitis A vaccines, local reactions were relatively uncommon, and there was no difference in risk of these events with arm versus thigh injections. The rate of local reactions after DTaP vaccines was higher, and vaccination in the arm was associated with a significantly greater risk of this outcome compared with vaccination in the thigh, both for children 12 to 35 months (relative risk: 1.88 [95% confidence interval: 1.34-2.65]) and 3 to 6 years of age (relative risk: 1.41 [95% confidence interval: 0.84-2.34]), although this difference was not statistically significant in the older age group. CONCLUSIONS: Injection in the thigh is associated with a significantly lower risk of a medically attended local reaction to a DTaP vaccination among children 12 to 35 months of age, supporting current recommendations to administer IM vaccinations in the thigh for children younger than 3 years of age.

Statistical approaches to group sequential monitoring of postmarket safety surveillance data: current state of the art for use in the Mini-Sentinel pilot.

PURPOSE: This manuscript describes the current statistical methodology available for active postmarket surveillance of pre-specified safety outcomes using a prospective incident user concurrent control cohort design with existing electronic healthcare data. METHODS: Motivation of the active postmarket surveillance setting is provided using the Food and Drug Administration's Mini-Sentinel Pilot as an example. Four sequential monitoring statistical methods are presented including the Lan-Demets error spending approach, a matched likelihood ratio test statistic approach with the binomial MaxSPRT as a special case, the conditional sequential sampling procedure with stratification, and a generalized estimating equation regression approach using permutation. Information on the assumptions, limitations, and advantages of each approach is provided, including how each method defines sequential monitoring boundaries, what test statistic is used, and how robust it is to settings of rare events or frequent testing. RESULTS: A hypothetical example of how the approaches could be applied to data comparing a medical product of interest, drug A, to a concurrent control drug, drug B, is presented including providing the type of information one would have available for monitoring such drugs.