Statistical approaches using longitudinal biomarkers for disease early detection: A comparison of methodologies

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. Combining of multiple biomarkers is more likely to achieve the sensitivity required for a clinically useful screening algorithm and the longitudinal trajectory of biomarkers contains valuable information that should be utilized. We propose a multivariate parametric empirical Bayes (mPEB) screening approach that defines personalized thresholds for each patient at each screening visit to identify significant deviations that trigger additional testing with more sensitive imaging. The Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) trial provides a valuable source of data to study HCC screening algorithms. We study the performance of the mPEB algorithm applied to serum α -fetoprotein, a widely used HCC surveillance biomarker, and des- γ carboxy prothrombin, an HCC risk biomarker that is FDA approved but not used in practice in the United States. Using cross-validation, we found that the mPEB algorithm demonstrated moderate but improved sensitivity compared to alternative screening approaches. Future research will validate the clinical utility of the approach in larger cohort studies with additional biomarkers.

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease

BACKGROUND

The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias.

OBJECTIVE

To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD.

METHODS

3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions.

RESULTS

Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis.

CONCLUSION

Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Time-varying discrimination accuracy of longitudinal biomarkers for the prediction of mortality compared to assessment at fixed time point in severe burns patients

BACKGROUND

The progression of biomarkers over time is considered an indicator of disease progression and helps in the early detection of disease, thereby reducing disease-related mortality. Their ability to predict outcomes has been evaluated using conventional cross-sectional methods. This study investigated the prognostic performance of biomarkers over time.

METHODS

Patients aged > 18 years admitted to the burn intensive care unit within 24 h of a burn incident were enrolled. Information regarding longitudinal biomarkers, including white blood cells; platelet count; lactate, creatinine, and total bilirubin levels; and prothrombin time (PT), were retrieved from a clinical database. Time-dependent receiver operating characteristic curves using cumulative/dynamic and incident/dynamic (ID) approaches were used to evaluate prognostic performance.

RESULTS

Overall, 2259 patients were included and divided into survival and non-survival groups. By determining the area under the curve using the ID approach, platelets showed the highest c-index [0.930 (0.919-0.941)] across all time points. Conversely, the c-index of PT and creatinine levels were 0.862 (0.843-0.881) and 0.828 (0.809-0.848), respectively.

CONCLUSIONS

Platelet count was the best prognostic marker, followed by PT. Total bilirubin and creatinine levels also showed good prognostic ability. Although lactate was a strong predictor, it showed relatively poor prognostic performance in burns patients.

Trajectories of longitudinal biomarkers for mortality in severely burned patients

This study aimed to investigate the differences in the trajectory of blood biomarkers routinely assessed through forward- and backward-looking approaches among burn patients. This cohort study included patients above 18 years of age from February 2007 to December 2018. All the biomarkers were estimated from admission to discharge from the intensive care unit. Significant differences were observed in the platelet count at 40 days, prothrombin time (PT) at 32 days, white blood cell count at 26 days, creatinine levels at 22 days, and lactate and total bilirubin levels at 19 days before death. In reverse order, significant differences were observed in the fitted model in platelet count at 44 days and in the platelet count and PT at 33 days. We obtained more valuable information from the longitudinal biomarker trajectory using the backward-looking method than using the forward-looking method. The platelet count served as the earliest predictor of mortality among burn patients.