JMIR Publications

ABSTRACT

Background:

Gastrointestinal Stromal Tumors (GISTs) present a complex clinical landscape, where precise preoperative risk assessment plays a pivotal role in guiding therapeutic decisions. Conventional methods for evaluating mitotic count, such as biopsy-based assessments, encounter challenges stemming from tumor heterogeneity and sampling biases, thereby underscoring the urgent need for innovative approaches to enhance prognostic accuracy.

Objective:

The primary objective of this study was to develop a robust and reliable computational tool, PROMETheus, aimed at refining patient stratification through precise estimation of mitotic count in GISTs.

Methods:

Leveraging advanced Bayesian Network methodologies, we constructed a Directed Acyclic Graph (DAG) integrating pertinent clinico-pathological variables essential for accurate mitotic count prediction on the surgical specimen. Key parameters identified and incorporated into the model encompassed tumor size, location, mitotic count from biopsy specimens, surface area evaluated during biopsy, and tumor response to therapy, when applicable. Rigorous testing procedures, including prior predictive simulations, validation utilizing synthetic datasets were employed. Finall, the model was trained on a comprehensive cohort of real-world GIST cases (n=80), drawn from the repository of IRCCS Humanitas Research Hospital, totaling 160 cases, were conducted.

Results:

Our computational model exhibited excellent diagnostic performance on syntetic data, different model architecture were selected based on lower deviance and robust out-of-sample predictive capabilities. Posterior predictive checks (retrodiction) further corroborated the model’s accuracy. Subsequently, the development of PROMETheus, an intuitive application dynamically computing predicted mitotic count and risk assessement on surgical specimens based on tumor-specific attributes, including size, location, surface area, and biopsy-derived mitotic count, using posterior probabilities derived from the model, was successfully achieved.

Conclusions:

The deployment of PROMETheus might herald a significant advancement in preoperative risk stratification for GISTs, offering clinicians a precise and reliable means to anticipate mitotic counts on surgical specimens and a solid base to stratify patients for clinical studies. By facilitating tailored therapeutic strategies, this innovative tool is poised to revolutionize clinical decision-making paradigms, ultimately translating into improved patient outcomes and enhanced prognostic precision in the management of GISTs.