TPE: finding the turning point in disease progression

Thu, 18 Jun 2026 00:00:00 +0000

A disease does not progress in a straight line. It drifts, then turns, and the turn is the part that matters.

A biomarker can changes gradually until it passes a critical point and then accelerates. The trajectory bends, and from one patient to the next that bend lands in a different place, pushed around by age, genetics, and everything else that makes a person who they are. Average the curves together and the turn smears into nothing.

I built the transition point estimator (TPE) to find that turn directly. It uses machine learning to model the nonlinear link between a biomarker and an outcome, keeps the confounders in check, and reads off the point where each marker’s behavior shifts. That point becomes its cutpoint.

A cutpoint set this way is important in how the disease actually moves. Find the turn, and you find the moment worth acting on.

Cognition Prediction

Sun, 01 Sep 2024 00:00:00 +0000

Predicting cognitive status and future decline from imaging and fluid biomarkers.

Predicting cognition is hard. Forecasts of cognitive decline from neuroimaging have never exceeded an R² of 0.50. Plasma biomarkers for diagnosing Alzheimer’s disease have gained traction in recent years, so we tested how well they predict cognition, alone and in combination, both at baseline and over roughly five years. Published in Brain Communications, 2024.

Biomarkers | Robel Gebre

TPE: finding the turning point in disease progression

Cognition Prediction