Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.
Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Pharmacoeconomics. 2024 Jun;42(6):679-691. doi: 10.1007/s40273-024-01371-1. Epub 2024 Apr 7.
Accurate risk stratification of patients with stage II and III colorectal cancer (CRC) prior to treatment selection enables limited health resources to be efficiently allocated to patients who are likely to benefit from adjuvant chemotherapy. We aimed to investigate the cost-effectiveness of a recently developed deep learning-based prognostic method, Histotyping, from the perspective of the Norwegian healthcare system.
Two partitioned survival models were developed to assess the cost-effectiveness of Histotyping for two treatment cohorts: patients with CRC stage II and III. For each of the two cohorts, Histotyping was used for risk stratification to assign adjuvant chemotherapy and was compared with the standard of care (SOC) (adjuvant chemotherapy to all patients). Health outcomes measured in the model were quality-adjusted life years (QALYs) and life years (LYs) gained. Deterministic and probabilistic sensitivity analyses were performed to determine the impact of uncertainty. Scenario analyses were performed to assess the impact of the parameters with the greatest uncertainty.
Risk-stratifying patients with CRC stage II and III using Histotyping was dominant (less costly and more effective) compared to SOC. In patients with CRC stage II, the net monetary benefit of Histotyping was 270,934 Norwegian kroners (NOK) (year of valuation is 2021), and the net health benefit of Histotyping was 0.99. In stage III, the net monetary benefit of Histotyping was 195,419 NOK, and the net health benefit of Histotyping was 0.71.
Risk-stratifying patients with CRC using Histotyping prior to the administration of adjuvant chemotherapy is likely to be a cost-effective strategy in Norway.
在选择治疗方案之前，对 II 期和 III 期结直肠癌（CRC）患者进行准确的风险分层，使有限的卫生资源能够有效地分配给可能从辅助化疗中获益的患者。我们旨在从挪威医疗保健系统的角度调查最近开发的基于深度学习的预后方法 Histotyping 的成本效益。
开发了两个分区生存模型来评估 Histotyping 在两个治疗队列中的成本效益：CRC 分期为 II 期和 III 期的患者。对于两个队列中的每一个，Histotyping 用于风险分层以分配辅助化疗，并与标准护理（SOC）（所有患者均接受辅助化疗）进行比较。模型中测量的健康结果是质量调整生命年（QALY）和生命年（LY）。进行了确定性和概率敏感性分析以确定不确定性的影响。进行了情景分析以评估具有最大不确定性的参数的影响。
与 SOC 相比，使用 Histotyping 对 CRC 分期 II 期和 III 期患者进行风险分层具有优势（成本更低，效果更好）。在 CRC 分期 II 期患者中，Histotyping 的净货币收益为 270,934 挪威克朗（NOK）（估值年份为 2021 年），Histotyping 的净健康收益为 0.99。在 III 期，Histotyping 的净货币收益为 195,419 NOK，Histotyping 的净健康收益为 0.71。
在挪威，在给予辅助化疗之前使用 Histotyping 对 CRC 患者进行风险分层可能是一种具有成本效益的策略。
