Combining concurrent radiotherapy and immunotherapy for synergistic effects in recurrent endometrial cancer – A case report

Chepkemoi, Luiza; Ajayi, Oluwaseyi; Anabaraonye, Nancy; Balogun, Onyinye

doi:10.1016/j.gore.2022.101090

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…1). The patient case scenarios were publicly available published data [12][13][14][15][16][17] and then adapted into vignettes and prompts. This step is processed into a question by adding a command sentence and a structured writing system.…”

Section: Methodsmentioning

confidence: 99%

Disparities in medical recommendations from AI-based chatbots across different countries/regions

Gumilar,

Indraprasta,

Hsu

et al. 2024

Preprint

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This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-hour window. Responses were double-blinded and evaluated on relevance, clarity, depth, focus, and coherence by ten endometrial cancer experts. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight concerning disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This underscores the need for further research and development to ensure equitable access to reliable medical information through AI technologies.

show abstract

Section: Methodsmentioning

confidence: 99%

Disparities in medical recommendations from AI-based chatbots across different countries/regions

Gumilar,

Indraprasta,

Hsu

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In various cancer types, concurrent immune checkpoint inhibitors (ICIs) and radiotherapy, or ICIs after radiotherapy, are expected to enhance the antitumor effect, as represented by the abscopal effect ( Ashrafizadeh et al, 2020 , Chepkemoi et al, 2022 , Ngwa et al, 2018 ). However, there are fewer reports on radiotherapy after administration of ICIs.…”

Section: Introductionmentioning

confidence: 99%

“…However, there are fewer reports on radiotherapy after administration of ICIs. In a review of cases of endometrial cancer treated with radiotherapy and ICI, all eight patients received ICIs concurrent with or after radiotherapy, while there were no reports on radiotherapy after ICIs ( Chepkemoi et al, 2022 ). To the best of our knowledge, this is the first report of serious multiple immune-related adverse events (irAEs) coinciding with a complete response during radiotherapy for endometrial cancer performed several months after ICI discontinuation.…”

Section: Introductionmentioning

confidence: 99%

Locally advanced endometrial cancer with multiple immune-related adverse events coinciding with the complete response to radiotherapy after immune checkpoint inhibitor therapy: A case report

Tanaka,

Amano,

Takahashi

et al. 2023

Gynecologic Oncology Reports

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Disparities in medical recommendations from AI-based chatbots across different countries/regions

Gumilar,

Indraprasta,

Hsu

et al. 2024

Sci Rep

View full text Add to dashboard Cite

This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This emphasizes the necessity for more research and development to guarantee equal access to trustworthy medical information through AI technologies.

show abstract

Combining concurrent radiotherapy and immunotherapy for synergistic effects in recurrent endometrial cancer – A case report

Cited by 3 publications

References 6 publications

Disparities in medical recommendations from AI-based chatbots across different countries/regions

Disparities in medical recommendations from AI-based chatbots across different countries/regions

Locally advanced endometrial cancer with multiple immune-related adverse events coinciding with the complete response to radiotherapy after immune checkpoint inhibitor therapy: A case report

Disparities in medical recommendations from AI-based chatbots across different countries/regions

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