Heisinger Stephan, Salzmann Stephan N, Senker Wolfgang, Aspalter Stefan, Oberndorfer Johannes, Matzner Michael P, Stienen Martin N, Motov Stefan, Huber Dominikus, Grohs Josef Georg
Department of Orthopedics and Trauma Surgery, Medical University of Vienna, 1090 Vienna, Austria.
Department of Neurosurgery, Kepler University Hospital, 4020 Linz, Austria.
J Clin Med. 2024 Dec 23;13(24):7864. doi: 10.3390/jcm13247864.
The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT-4, is transforming healthcare. ChatGPT's potential to assist in decision-making for complex cases, such as spinal metastasis treatment, is promising but widely untested. Especially in cancer patients who develop spinal metastases, precise and personalized treatment is essential. This study examines ChatGPT-4's performance in treatment planning for spinal metastasis cases compared to experienced spine surgeons. Five spine metastasis cases were randomly selected from recent literature. Consequently, five spine surgeons and ChatGPT-4 were tasked with providing treatment recommendations for each case in a standardized manner. Responses were analyzed for frequency distribution, agreement, and subjective rater opinions. ChatGPT's treatment recommendations aligned with the majority of human raters in 73% of treatment choices, with moderate to substantial agreement on systemic therapy, pain management, and supportive care. However, ChatGPT's recommendations tended towards generalized statements, with raters noting its generalized answers. Agreement among raters improved in sensitivity analyses excluding ChatGPT, particularly for controversial areas like surgical intervention and palliative care. ChatGPT shows potential in aligning with experienced surgeons on certain treatment aspects of spinal metastasis. However, its generalized approach highlights limitations, suggesting that training with specific clinical guidelines could potentially enhance its utility in complex case management. Further studies are necessary to refine AI applications in personalized healthcare decision-making.
人工智能（AI）的整合，尤其是像ChatGPT-4这样的大型语言模型（LLMs），正在改变医疗保健行业。ChatGPT在协助处理复杂病例（如脊柱转移瘤治疗）决策方面的潜力很有前景，但尚未得到广泛测试。特别是在发生脊柱转移的癌症患者中，精确和个性化的治疗至关重要。本研究将ChatGPT-4在脊柱转移瘤病例治疗规划中的表现与经验丰富的脊柱外科医生进行了比较。从最近的文献中随机选取了5例脊柱转移瘤病例。随后，让5名脊柱外科医生和ChatGPT-4以标准化方式为每个病例提供治疗建议。对回答进行了频率分布、一致性和主观评分者意见分析。ChatGPT的治疗建议在73%的治疗选择上与大多数人类评分者一致，在全身治疗、疼痛管理和支持性护理方面有中度到高度的一致性。然而，ChatGPT的建议倾向于泛泛而谈，评分者指出其回答较为笼统。在排除ChatGPT的敏感性分析中，评分者之间的一致性有所提高，特别是在手术干预和姑息治疗等有争议的领域。ChatGPT在脊柱转移瘤的某些治疗方面与经验丰富的外科医生意见一致方面显示出潜力。然而，其泛泛的方法突出了局限性，表明用特定临床指南进行训练可能会提高其在复杂病例管理中的效用。有必要进行进一步研究，以完善人工智能在个性化医疗决策中的应用。
