Background:Despite the significant advancements of liver surgery in the last few decades, the survival rate of patients with liver and pancreatic cancers has improved by only 10% in 30 years. Precision medicine offers a patient-centered approach, which, when combined with machine learning, could enhance decision making and treatment outcomes in surgical management of ihCC. This study aims to develop a decision support model to optimize treatment strategies for patients with ihCC, a prevalent primary liver cancer.Methods:The decision support model, named MedMax, was developed using three data sources: studies retrieved through a systematic literature review, expert opinions from HPB surgeons, and data from ihCC patients treated at Heidelberg University Hospital. Expert opinions were collected via surveys, with factors rated on a Likert scale, while patient data were used to validate the model’s accuracy.Results:The model is structured into four decision-making phases, assessing diagnosis, treatment modality, surgical approach, and prognosis. Prospectively, 44 patients with ihCC were included for internal primary validation of the model. MedMax could predict the appropriate treatment considering the resectability of the lesions in 100% of patients. Also, MedMax could predict a decent surgical approach in 77% of the patients. The model proved effective in making decisions regarding surgery and patient management, demonstrating its potential as a clinical decision support tool.Conclusions:MedMax offers a transparent, personalized approach to decision making in HPB surgery, particularly for ihCC patients. Initial results show high accuracy in treatment selection, and the model’s flexibility allows for future expansion to other liver tumors and HPB surgeries. Further validation with larger patient cohorts is required to enhance its clinical utility.
背景：尽管过去几十年肝脏外科手术取得了显著进展，但肝胆癌患者的生存率在30年间仅提高了10%。精准医疗提供了一种以患者为中心的治疗方法，与机器学习相结合，有望改善肝内胆管癌（ihCC）外科治疗中的决策制定和治疗效果。本研究旨在开发一种决策支持模型，以优化ihCC（一种常见的原发性肝癌）患者的治疗策略。 方法：该决策支持模型命名为MedMax，其开发基于三个数据来源：通过系统文献检索获取的研究资料、肝胆胰外科专家的意见以及海德堡大学医院收治的ihCC患者数据。专家意见通过问卷调查收集，各因素采用李克特量表进行评分，患者数据则用于验证模型的准确性。 结果：该模型分为四个决策阶段，分别评估诊断、治疗方式、手术方法和预后。前瞻性纳入44例ihCC患者进行模型的内部初步验证。MedMax能够100%准确地预测考虑病灶可切除性的适宜治疗方案，并在77%的患者中预测出合适的手术方式。该模型在手术决策和患者管理方面证明有效，展现了其作为临床决策支持工具的潜力。 结论：MedMax为肝胆胰外科手术，特别是ihCC患者的决策制定提供了一种透明化、个性化的方法。初步结果显示其在治疗选择方面具有高准确性，且模型的灵活性允许未来扩展至其他肝脏肿瘤及肝胆胰外科手术。需要通过更大规模的患者队列进行进一步验证，以提升其临床实用性。
肿瘤(癌症)患者之家