Centre for Health Economics, Monash Business School, Monash University, Melbourne, Victoria, Australia.
Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
PLoS One. 2024 Aug 27;19(8):e0308812. doi: 10.1371/journal.pone.0308812. eCollection 2024.
Multiple myeloma is a haematological malignancy typically characterised by neoplastic plasma cell infiltration of the bone marrow. Treatment for multiple myeloma consists of multi-line chemotherapy with or without autologous stem cell transplantation and has been rapidly evolving in recent years. However, clinical trials are unable to provide patients and clinicians with long-term prognostic information nor policymakers with the full body of evidence needed to perform economic evaluation of new therapies or make reimbursement decisions. To address these limitations of the available evidence, this study aimed to develop and validate the EpiMAP Myeloma model, a discrete-event simulation model of multiple myeloma disease outcomes and treatment pathways. Risk equations were estimated using the Australian and New Zealand Myeloma & Related Diseases Registry after multiple imputation of missing data. Risk equation coefficients were combined with multiple myeloma patients at diagnosis from the Registry to perform the simulation. The model was validated with 100 bootstraps of an out-of-sample prediction analysis using a 70/30 split of the 4,121 registry patients diagnosed between 2009 and 2023, resulting in 2,884 and 1,237 patients in the training and validation cohorts, respectively. For 90% of the 120 months in the 10-year post-diagnosis period, there was no significant difference in overall survival between the validation and simulated cohorts. These results highlight that the EpiMAP Myeloma model is robust at predicting multiple myeloma disease outcomes and treatment pathways in Australia & New Zealand. In the future, clinicians will be able to use the EpiMAP Myeloma model to provide personalised estimates of life expectancy to patients based on their specific characteristics, disease stage, and response to treatment. Policymakers will also be able to use the model to perform economic evaluation, to forecast the number of patients receiving treatment at different stages, and to determine the downstream impact of listing new, effective therapies.
多发性骨髓瘤是一种血液系统恶性肿瘤，通常以骨髓中肿瘤浆细胞浸润为特征。多发性骨髓瘤的治疗包括多线化疗联合或不联合自体造血干细胞移植，近年来发展迅速。然而，临床试验无法为患者和临床医生提供长期预后信息，也无法为政策制定者提供进行新疗法的经济评估或做出报销决策所需的全部证据。为了解决现有证据的这些局限性，本研究旨在开发和验证 EpiMAP 骨髓瘤模型，这是一种多发性骨髓瘤疾病结局和治疗途径的离散事件模拟模型。使用澳大利亚和新西兰骨髓瘤和相关疾病登记处对缺失数据进行多次插补后，估计风险方程。将风险方程系数与登记处的多发性骨髓瘤患者合并，以进行模拟。使用登记处诊断为 2009 年至 2023 年的 4121 例患者的 70/30 数据集进行了 100 次样本外预测分析的 100 次 bootstrap 验证，分别得到训练和验证队列中的 2884 例和 1237 例患者。在诊断后 10 年的 120 个月中，验证队列和模拟队列的总生存无显著差异。这些结果突出表明，EpiMAP 骨髓瘤模型在预测澳大利亚和新西兰的多发性骨髓瘤疾病结局和治疗途径方面具有稳健性。在未来，临床医生将能够根据患者的具体特征、疾病阶段和对治疗的反应，使用 EpiMAP 骨髓瘤模型为患者提供个性化的预期寿命估计。政策制定者还将能够使用该模型进行经济评估，预测不同阶段接受治疗的患者人数，并确定新的有效疗法上市的下游影响。
