Improving Liver Fibrosis Diagnosis in Primary Care Using FibroX AI
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorYale University
About this trial
The goal of this clinical trial is to learn whether an artificial intelligence (AI) tool called FibroX can help primary care providers better diagnose significant liver fibrosis (≥F2) and clinically significant portal hypertension in adults with metabolic dysfunction-associated steatotic liver disease (MASLD).
The main questions it aims to answer are:
* Can FibroX improve the accuracy of diagnosing significant liver fibrosis (≥F2) and clinically significant portal hypertension compared to usual care? * Is FibroX easy to use and acceptable to primary care providers in simulated clinical settings? * Do providers trust FibroX as a decision-support tool?
Researchers will compare FibroX-assisted care to usual care to see if FibroX improves diagnostic accuracy, provider trust, and supports better decision-making.
Participants will:
* Be primary care providers (MDs, DOs, NPs, PAs) from diverse clinics * Review simulated patient cases with MASLD risk factors * Use either usual care tools (standard labs and optional FIB-4 calculator) or FibroX (AI-generated risk score, triage band, and explainability panel) * Make diagnostic and referral decisions for each case * Complete surveys on usability, trust in AI, confidence, and cognitive workload
This study will help determine whether FibroX can be integrated into real-world primary care workflows to support earlier and more accurate detection of liver fibrosis and portal hypertension, potentially reducing missed diagnoses, unnecessary referrals, and improving patient outcomes.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Licensed primary care providers (MD, DO, NP, or PA)
Currently practicing in adult primary care (≥0.5 Full-Time Equivalent)
Affiliated with one of the participating clinics (academic, community, or Federally Qualified Health Center)
Willing and able to participate in simulated electronic health record (EHR)-based case reviews
Disqualifiers
Providers not actively practicing in adult primary care
Providers with less than 0.5 FTE in clinical practice
Prior involvement in the development or validation of the FibroX tool
Inability to complete both simulation periods due to scheduling or other constraints
Trial design
Design model
Crossover
Treatments tested in this trial
FibroX
DeviceFibroX is an explainable artificial intelligence (AI) tool designed to assist primary care providers in diagnosing significant liver fibrosis (≥F2) and clinically significant portal hypertension in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). It uses routinely available clinical data (e.g., age, AST, ALT, platelets, BMI, HbA1c, creatinine) to generate a risk probability score, a triage band (rule-out, indeterminate, rule-in), and a one-line explainability panel using Shapley Additive Explanations (SHAP). Providers use FibroX during simulated patient encounters to guide diagnostic and referral decisions (e.g., order VCTE, refer to hepatology, initiate guideline-based therapy). The tool aims to improve diagnostic accuracy, increase provider trust, reduce missed diagnoses, and support guideline-concordant triage in primary care.
Usual Care
Other interventionIn the usual care condition, primary care providers assess simulated patient cases using standard clinical tools available in routine practice. These include laboratory results, vital signs, problem lists, medications, and prior imaging. Providers may optionally use the FIB-4 calculator to estimate liver fibrosis risk. No AI decision support is provided. This intervention serves as the comparator to evaluate whether FibroX improves diagnostic accuracy for significant liver fibrosis (≥F2) and clinically significant portal hypertension, as well as provider trust, decision-making quality, and workflow efficiency compared to usual care.
Treatment groups
40 Participants
are divided into 2 treatment groupsGroup A: FibroX-Enabled CareExperimental treatment 1 intervention
Group B: Usual CareActive comparator 1 intervention
Trial outcomes
Primary outcomes
1
Diagnostic Accuracy for Significant Liver Fibrosis (≥F2) and Clinically Significant Portal Hypertension Using FibroX Compared to Usual Care
Within-provider diagnostic accuracy for detecting significant liver fibrosis (≥F2) and clinically significant portal hypertension in simulated primary care encounters. Accuracy will be assessed using sensitivity, specificity, and AUROC at clinically relevant thresholds. Ground truth for fibrosis stage and portal hypertension will be derived from biopsy, Vibration-Controlled Transient Elastography (VCTE)-based expert consensus, and guideline-defined criteria. Unit of Measure: Proportion (sensitivity and specificity in %, AUROC as a unitless value)
Time frame
Immediately after each simulation period, up to 24 weeks2
System Usability Scale (SUS) Score for FibroX Integration
Usability of FibroX assessed using the System Usability Scale (SUS), a validated 10-item questionnaire scored from 0 to 100, where higher scores indicate better usability. Unit of Measure: Score (range: 0-100; higher scores = better usability)
Time frame
Immediately after each simulation period, up to 24 weeks3
Provider Trust in AI Tool (FibroX)
Provider trust in FibroX assessed using the validated AI-Trust Scale, which includes 12 items scored on a Likert scale. Higher scores indicate greater trust in the AI tool. Unit of Measure: Score (range: 12-60; higher scores = greater trust)
Time frame
Immediately after the FibroX-enabled simulation period, up to 24 weeks4
Median Decision Time per Case
Median time (in minutes) taken by providers to complete management decisions for simulated MASLD cases using FibroX versus usual care. Unit of Measure: Minutes
Time frame
Immediately after each simulation period, up to 24 weeksSecondary outcomes
1
Appropriate Referral Rate
Proportion of simulated cases where provider referral decisions (e.g., hepatology referral, VCTE order) align with guideline-concordant triage rules for MASLD risk stratification. Unit of Measure: Proportion (%)
Time frame
Immediately after each simulation period, up to 24 weeks2
Net Reclassification Improvement (NRI)
Change in classification accuracy for MASLD risk categories (rule-out, indeterminate, rule-in) when using FibroX compared to usual care. Unit of Measure: NRI score (unitless)
Time frame
Immediately after each simulation period, up to 24 weeks3
Calibration of Risk Predictions
Calibration of FibroX predictions compared to observed outcomes, assessed using calibration intercept, slope, and calibration plot. Unit of Measure: Intercept and slope (unitless)
Time frame
Immediately after each simulation period, up to 24 weeks4
Provider Confidence in Decision-Making
Provider-reported confidence in MASLD management decisions during simulated cases, measured on a 5-point Likert scale (1 = very low confidence; 5 = very high confidence). Unit of Measure: Score (range: 1-5; higher scores = greater confidence)
Time frame
Immediately after each simulation period, up to 24 weeksLocations
Sponsors and contacts
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Source ClinicalTrials.gov
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