Assessing the accuracy and consistency of generative pretrained transformers in assigning Eastern Cooperative Oncology Group performance status

Abstract

The Eastern Cooperative Oncology Group (ECOG) is a commonly used performance status (PS) scale in oncology. It influences cancer treatment decisions and clinical trial recruitment. However, there can be significant inter-rater variability in ECOG-PS scoring, due to subjectivity in human scoring and innate cognitive biases.1,2 We propose that generative pretrained transformers (GPT), a foundational large language model (LLM), can accurately and reliably score ECOG-PS.