BCG therapy for bladder cancer: Exploring patient experiences and concerns through artificial intelligence-based social media analysis.

Background: There is a notable disparity between the guidelines for BCG therapy in non-muscle invasive bladder cancer (NMIBC). Reddit has emerged as a popular online platform for individuals seeking information and exchanging their experiences related to bladder cancer.

Objective: To investigate and classify public opinions about intravesical BCG therapy as shared on Reddit, a popular social media platform.

Methods: This study employed an artificial intelligence-based approach to examine discussions related to intravesical BCG therapy on a social media platform over the past ten years. An artificial intelligence framework was developed to categorize these conversations into distinct topics and thematic categories. This framework included a partially supervised model for processing natural language (using BERT [Bidirectional Encoder Representations from Transformers]), a method for reducing data complexity, and an algorithm for clustering. Additionally, each conversation was assessed for sentiment.

Results: A total of 1223 unique discussions related to BCG therapy were analyzed, comprising 110 unique posts and 1113 comments from 268 distinct authors. We identified four overarching thematic groups: 1) BCG administration procedures, (2) hesitancy in initiating or maintaining BCG treatment, (3) issues related to BCG shortage and alternative treatments, and (4) side effects of BCG treatment. Sentiment analysis of the 1223 discussions revealed that 25.2% (308) exhibited a negative sentiment, 58.3% (713) were neutral, and 16.5% (202) showed a positive sentiment.

Conclusion: Online social media often contains detailed personal experiences with BCG therapy, not commonly found in medical literature. Understanding these experiences can help medical professionals improve care and treatment adherence in NMIBC.