Department of Oncology, McMaster University, Hamilton, ON, Canada.
Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Oncologist. 2024 Jun 3;29(6):519-526. doi: 10.1093/oncolo/oyae041.
Developing prognostic tools specifically for patients themselves represents an important step in empowering patients to engage in shared decision-making. Incorporating patient-reported outcomes may improve the accuracy of these prognostic tools. We conducted a retrospective population-based study of transplant-ineligible (TIE) patients with multiple myeloma (MM) diagnosed between January 2007 and December 2018. A multivariable Cox regression model was developed to predict the risk of death within 1-year period from the index date. We identified 2356 patients with TIE MM. The following factors were associated with an increased risk of death within 1 year: age > 80 (HR 1.11), history of heart failure (HR 1.52), "CRAB" at diagnosis (HR 1.61), distance to cancer center (HR 1.25), prior radiation (HR 1.48), no proteosome inhibitor/immunomodulatory therapy usage (HR 1.36), recent emergency department (HR 1.55) or hospitalization (HR 2.13), poor performance status (ECOG 3-4 HR 1.76), and increasing number of severe symptoms (HR 1.56). Model discrimination was high with C-statistic of 0.74, and calibration was very good. To our knowledge, this represents one of the first prognostic models developed in MM incorporating patient-reported outcomes. This survival prognostic tool may improve communication regarding prognosis and shared decision-making among older adults with MM and their health care providers.
为患者自身开发预后工具代表着赋予患者参与共同决策能力的重要一步。纳入患者报告的结局可能会提高这些预后工具的准确性。我们对 2007 年 1 月至 2018 年 12 月期间诊断为不适合移植（TIE）的多发性骨髓瘤（MM）患者进行了一项回顾性基于人群的研究。建立了多变量 Cox 回归模型来预测从索引日期起 1 年内死亡的风险。我们确定了 2356 名 TIE MM 患者。以下因素与 1 年内死亡风险增加相关：年龄＞80 岁（HR 1.11）、心力衰竭史（HR 1.52）、诊断时存在“CRAB”（HR 1.61）、距癌症中心的距离（HR 1.25）、既往放疗（HR 1.48）、未使用蛋白酶体抑制剂/免疫调节治疗（HR 1.36）、近期急诊就诊（HR 1.55）或住院（HR 2.13）、较差的表现状态（ECOG 3-4 HR 1.76）和严重症状数量增加（HR 1.56）。模型的区分度很高，C 统计量为 0.74，校准效果非常好。据我们所知，这是第一个在 MM 中纳入患者报告的结局开发的预后模型之一。该生存预后工具可以改善老年人和他们的医疗保健提供者之间关于预后和共同决策的沟通。
