Impact of clinical factors on accuracy of ovarian cancer detection via platelet RNA profiling.

ABSTRACT:

Abstract

Ovarian cancer (OC) presents a diagnostic challenge, often resulting in poor patient outcomes. Platelet RNA sequencing, which reflects host response to disease, shows promise for earlier OC detection. This study examines the impact of sex, age, platelet count, and the training on cancer types other than OC on classification accuracy achieved in the previous platelet-alone training data set. A total of 339 samples from healthy donors and 1396 samples from patients with cancer, spanning 18 cancer types (including 135 OC cases) were analyzed. Logistic regression was applied to verify our classifiers' performance and interpretability. Models were tested at 100% specificity and 100% sensitivity levels. Incorporating patient age as an additional feature along with gene expressio

SUBMITTER: Jopek MA 

PROVIDER: S-EPMC11907454 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature