# Evaluating the utility of multi-gene, multi-disease population-based panel testing accounting for uncertainty in penetrance estimates

## TL;DR

This paper evaluates how useful multi-gene testing is for detecting disease risks, considering uncertainties in how likely gene variants are to cause disease.

## Contribution

The study introduces a new formula to assess the clinical utility of multi-gene panels by incorporating variant frequency, penetrance estimates, and subjective disutilities.

## Key findings

- Rare, highly penetrant variants often provide positive net utility despite uncertainty.
- Moderate-penetrance variants' utility depends heavily on assumed disutilities.
- Including genes in panels should consider variant frequency, penetrance, and uncertainties.

## Abstract

Panel germline testing allows for the efficient detection of deleterious variants for multiple conditions, but the benefits and harms of identifying these variants are not always well understood. We present a multi-gene, multi-disease aggregate utility formula that allows the user to consider adding or removing each gene in a panel based on variant frequency, estimated penetrances, and subjective disutilities for testing positive but not developing the disease and testing negative but developing the disease. We provide credible intervals for utility that reflect uncertainty in penetrance estimates. Rare, highly penetrant deleterious variants tend to contribute positive net utilities for a wide variety of user-specified disutilities, even when accounting for parameter estimation uncertainty. However, the clinical utility of deleterious variants with moderate, uncertain penetrance depends more on assumed disutilities. The decision to include a gene on a panel depends on variant frequency, penetrance, and subjective utilities and should account for uncertainties around these factors.