Clinical Practice Guideline Generation from Quality of Life Studies in Rare Diseases

Authors

• S Moon
• P Gahan
• Q Zhu

Abstract

Quality of Life (QoL) is an individual's subjective assessment of their overall well-being and satisfaction with life within the context of their cultural, social, and personal values and goals. For patients with rare diseases (RDs), QoL is crucial as it directly affects their daily lives and impacts a substantial burden on caregivers, especially given the long journey of diagnosis and limited treatment options available. However, conducting QoL research in health and medicine poses challenges, mainly due to the scarcity of RD patient samples and the complexities involved in developing and validating Health-Related Quality of Life (HRQoL) assessment. To address these challenges, this preliminary study identifies essential QoL-related components from RD-pertained biomedical literature (the Disease Research State Model Corpus ), assessing positive and negative impacts on RD patients, thereby generating the groundwork of clinical practice guidelines to manage effectively those RDs. We analyzed 2,477 abstracts using large language models (LLMs) like ChatGPT and Meta AI, and we manually evaluated and compared the results of ten randomly selected abstracts associated with nine different RDs, including Primary sclerosing cholangitis. Sixty-five unique HRQoL elements were generated from these ten abstracts. Specific QoL factors such as 'Pain and discomfort' are predominantly associated with negative impacts, whereas 'Freedom, physical safety, and security' are linked to positive impacts. ChatGPT provided in-depth descriptions of each QoL concept, while Meta AI contributed numerous additional QoL elements. This study presented a promising solution with LLMs to systematically identify clinical guidelines in assisting RD management from QoL-related biomedical literature.

Scientific Focus Area: Clinical Research

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