Diagnostic Accuracy of the Circulating Cell-free DNA-based Epigenetic Biomarker mSEPT9 for Hepatocellular Carcinoma Detection Among Cirrhotic Patients: the SEPT9_CROSS Study
Diagnostic Accuracy of the Circulating Cell-free DNA-based Epigenetic Biomarker mSEPT9 for Hepatocellular Carcinoma Detection Among Cirrhotic Patients: the SEPT9_CROSS Study
Brief Summary (Plain-Language Version - Compliant with ClinicalTrials.gov Guidelines)
The goal of this observational study is to learn whether a blood test called methylated SEPT9 (mSEPT9) can help diagnose hepatocellular carcinoma (HCC), the most common type of liver cancer, in people who already have cirrhosis. The study also compares how well this new test works compared with the current standard blood test called alpha-fetoprotein (AFP).
The main questions the study aims to answer are:
The study, called SEPT9-CROSS, is a phase III, multicenter, cross-sectional diagnostic accuracy study. It includes 639 adults with cirrhosis who were enrolled across participating hospitals in France. After reviewing eligibility and exclusion criteria, 574 participants were included in the final analysis: 118 people with liver cancer and 456 people with cirrhosis but no liver cancer.
The main outcome (primary outcome) is the presence of liver cancer at the time of study enrollment, confirmed by imaging or biopsy based on international medical guidelines. An exploratory outcome looks at participants who developed liver cancer within 12 months after joining the study. This second measure helps researchers understand whether the test can identify early or hidden disease.
All participants gave written informed consent before joining the study. As part of their regular medical care, participants received clinical exams, blood tests, and imaging studies (such as ultrasound). During routine blood draws, an extra 20 milliliters of blood (about 4 teaspoons) was collected for the mSEPT9 test. These blood samples were processed and safely stored at the CRB Lorrain biobank at the University Hospital of Nancy, France, for later analysis.
The study compares the performance of AFP and mSEPT9 individually and in combination. Two diagnostic strategies were tested:
Researchers used statistical models to measure how well the tests identified cancer. This included estimating the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and predictive values (how likely a result is to be correct). These calculations were repeated 10,000 times using computer simulations to ensure reliability.
Advanced Bayesian statistical models were also used to confirm the stability and strength of the results and to compare the performance of mSEPT9 and AFP. A risk model (called a nomogram) was created to estimate each participant's probability of having liver cancer based on their test results.
All analyses were planned before the study started and carried out using the software R (version 4.3.0) and Python (PyCharm environment) with validated scripts to ensure accuracy and reproducibility.
Clinical Trial Rationale and Design
Epigenetic alterations represent a fundamental hallmark of human malignancy. Although individual epigenetic biomarkers have begun to enter clinical practice, their translational validation remains limited. This limitation is particularly evident in hepatocellular carcinoma (HCC), the most common primary malignant tumor of the liver. Alpha-fetoprotein (AFP) has long been used as a diagnostic biomarker for HCC; however, as stated in international guidelines from the American Association for the Study of Liver Diseases and the European Association for the Study of the Liver, AFP lacks sufficient sensitivity and specificity for effective screening or early detection. Aberrant DNA methylation events are a frequent molecular feature of malignant transformation and can be detected in the circulation of patients with cancer using polymerase chain reaction-based assays.
Among epigenetic targets, the SEPT9 gene has emerged as a key regulator of cell division and a tumor suppressor whose promoter hypermethylation is closely associated with carcinogenesis. Experimental evidence implicates SEPT9 in the early stages of hepatocarcinogenesis, and promoter hypermethylation of SEPT9 has been consistently observed in human HCC. Loss or downregulation of SEPT9 expression due to aberrant promoter methylation has also been reported in several other malignancies.
Building on a proof-of-concept study conducted in France and an independent replication study in Germany, we previously demonstrated that plasma methylated SEPT9 (mSEPT9), a circulating cell-free DNA-based epigenetic biomarker, shows strong potential for the noninvasive diagnosis of HCC in patients with cirrhosis (EBioMedicine 2018:30:138-147). The SEPT9_CROSS study is a phase III, multicenter, cross-sectional diagnostic accuracy investigation designed to validate the clinical performance of plasma methylated SEPT9 (mSEPT9) for the diagnosis of HCC in a large-scale cohort of 639 patients with cirrhosis initially enrolled across participating centers. After application of the predefined eligibility and exclusion criteria, 65 patients were excluded, resulting in 574 analyzable patients retained in the final study population.
Patient Recruitment and Sample Handling
Patients with cirrhosis who met the study eligibility criteria were enrolled after providing informed consent. Each participant signed a participation agreement form, and documentation of study participation was recorded in the medical record. As part of their routine follow-up, all patients underwent clinical, biochemical, and imaging assessments, including measurement of alpha-fetoprotein, in accordance with international guidelines. During routine phlebotomy performed for biochemical evaluation, an additional 20 mL of blood was collected into two 10 mL EDTA tubes dedicated to the mSEPT9 assay. Plasma was separated from these samples, aliquoted, and handled and stored under standardized conditions in the CRB Lorrain biobank at -80 °C until analysis of mSEPT9.
Data Collection and Management
Patient data were entered into an electronic case report form (eCRF) using the CleanWeb system, with role-based access control. Data were analyzed by the methodologist-statistician of the Methodology, Data Management, and Statistics Unit (UMDS) within the Department of Clinical Research and Innovation (DRCI) at the University Hospital of Nancy (France). All data were recorded and securely stored on the protected network of the University Hospital of Nancy (CHRU de Nancy).
Sample Size and Power Calculation
According to Substantial Amendment No. 2 (MS No. 2, October 5, 2021), the sample size distribution between study groups was modified based on updated recruitment data. Based on the revised power calculation, the theoretical sample size required to achieve adequate statistical power was 530 patients, including 106 HCC-positive cirrhotic patients (cases) and 424 HCC-free cirrhotic patients (controls), instead of the initially planned 220 patients per group.
This adjustment was derived from a recalculated statistical power analysis designed to detect an increase of at least 0.05 in the area under the receiver operating characteristic curve (AUC) for mSEPT9 compared with alpha-fetoprotein (AFP), with a two-sided α level of 0.05, a β risk of 0.20 (power of 80%), and a case-to-control ratio of 1:4. Under these assumptions, 101 cases and 404 controls were required for analysis. Allowing for approximately 5% of unevaluable data, the final theoretical target enrollment was set at 106 cases and 424 controls, yielding a total of 530 patients.
In total, 639 patients with cirrhosis were initially enrolled across participating centers in the SEPT9-CROSS study. After application of the predefined eligibility and exclusion criteria, 65 patients were excluded because they did not meet inclusion criteria or were identified as duplicates. The final analyzable population included 574 patients, comprising 118 HCC-positive cirrhotic patients (cases) and 456 HCC-free cirrhotic patients (controls) retained for statistical analysis.
Study Duration
According to Substantial Amendment No. 4 (MS No. 4, March 1, 2023), the inclusion period was extended by an additional 12 months, from 60 to 72 months, resulting in a total study duration of 76 months instead of the initially planned 64 months. The amendment also included a change of principal investigator for the Metz-Thionville University Hospital center.
Statistical and Analytical Framework
The statistical analysis plan (version 3), finalized prior to database lock, prespecified all analytical procedures. The primary objective was to evaluate the diagnostic accuracy of plasma methylated SEPT9 (mSEPT9) for detecting hepatocellular carcinoma (HCC) in patients with cirrhosis and to compare its performance with that of alpha-fetoprotein (AFP).
Outcome Definitions
The primary outcome was the presence of hepatocellular carcinoma at enrollment. A sensitivity analysis restricted controls to patients who remained free of hepatocellular carcinoma throughout 12 months of follow-up. A prespecified composite outcome encompassed prevalent hepatocellular carcinoma at baseline and incident hepatocellular carcinoma diagnosed within 12 months after enrollment.
Endpoint definitions
The primary endpoint was diagnostic accuracy for detecting hepatocellular carcinoma, assessed by area under the receiver operating characteristic curve, comparing methylated SEPT9 with alpha-fetoprotein greater than 20 nanograms per milliliter. Secondary endpoints included diagnostic performance stratified by Barcelona Clinic Liver Cancer stage, with prespecified subgroup analyses for very early and early-stage disease (stages 0 and A) versus more advanced stages (stages B, C, and D). Exploratory endpoints included evaluation of combination diagnostic strategies (Tier 1 approaches maximizing sensitivity and Tier 2 approach maximizing specificity), net reclassification improvement, conditional recovery analysis, development of a risk stratification nomogram, and validation of the biological replicate design through correlation analysis between the number of positive replicates and cycle threshold values.
Analytical framework Nine diagnostic algorithms were prespecified in the statistical analysis plan and evaluated across all outcome definitions: methylated SEPT9 as a continuous variable (0 to 3 positive replicates); methylated SEPT9 with three binary thresholds (single-positive, double-positive, and triple-positive); alpha-fetoprotein greater than 20 nanograms per milliliter; three Tier 1 strategies using OR logic (methylated SEPT9 at each threshold or alpha-fetoprotein greater than 20 nanograms per milliliter) to maximize sensitivity; and Tier 2 strategy using AND logic (triple-positive methylated SEPT9 and alpha-fetoprotein greater than 20 nanograms per milliliter) to maximize specificity.
Performance metrics included area under the receiver operating characteristic curve, sensitivity, specificity, positive and negative predictive values, and diagnostic odds ratio, with 95 percent confidence intervals obtained through bootstrap resampling with 10,000 iterations using bias-corrected and accelerated estimation. Bayesian modeling was applied to estimate posterior distributions of area under the receiver operating characteristic curve values, with Bayes factors computed to quantify the strength of evidence supporting comparative performance across diagnostic algorithms.
Prespecified subgroup analyses evaluated performance in patients with very early or early-stage hepatocellular carcinoma (Barcelona Clinic Liver Cancer stage 0 or A), representing the clinically relevant population eligible for curative interventions.
Prespecified exploratory analyses included net reclassification improvement to measure the proportion of patients correctly reclassified when adding methylated SEPT9 to alpha-fetoprotein-based testing, conditional recovery analysis to assess the complementarity of diagnostic strategies, development of a multivariable risk-stratification nomogram to provide individualized probability estimates of hepatocellular carcinoma, and validation of the biological replicate design through correlation analysis between the number of positive replicates and cycle threshold values.
All analyses were performed using R version 4.3.0 and Python. Custom Python scripts were implemented to automate receiver operating characteristic curve simulations, bootstrap iterations, Bayesian inference, and predictive modeling, ensuring analytical reproducibility.
INCLUSION CRITERIA
NON-INCLUSION CRITERIA FOR CASES :
NON-INCLUSION CRITERIA FOR CASES AND CONTROLS: