Smith Lesley, Carmichael Jonathan, Cook Gordon, Shinkins Bethany, Neal Richard D
Leeds Diagnosis and Screening Unit, Leeds Institute of Health Sciences, University of Leeds, Leeds LS2 9JT, UK.
Cancer Research UK Clinical Trials Unit, Leeds Institute of Clinical Trial Research, University of Leeds, Leeds LS2 9JT, UK.
Cancers (Basel). 2023 Feb 3;15(3):975. doi: 10.3390/cancers15030975.
Myeloma is one of the hardest cancers to diagnose in primary care due to its rarity and non-specific symptoms. A rate-limiting step in diagnosing myeloma is the clinician considering myeloma and initiating appropriate investigations. We developed and internally validated a risk prediction model to identify those with a high risk of having undiagnosed myeloma based on results from routine blood tests taken for other reasons. A case-control study, based on 367 myeloma cases and 1488 age- and sex-matched controls, was used to develop a risk prediction model including results from 15 blood tests. The model had excellent discrimination (C-statistic 0.85 (95%CI 0.83, 0.89)) and good calibration (calibration slope 0.87 (95%CI 0.75, 0.90)). At a prevalence of 15 per 100,000 population and a probability threshold of 0.4, approximately 600 patients would need additional reflex testing to detect one case. We showed that it is possible to combine signals and abnormalities from several routine blood test parameters to identify individuals at high-risk of having undiagnosed myeloma who may benefit from additional reflex testing. Further work is needed to explore the full potential of such a strategy, including whether it is clinically useful and cost-effective and how to make it ethically acceptable.
由于骨髓瘤较为罕见且症状不具特异性，它是基层医疗中最难诊断的癌症之一。诊断骨髓瘤的一个限速步骤是临床医生考虑到骨髓瘤并启动适当的检查。我们开发并在内部验证了一种风险预测模型，以根据因其他原因进行的常规血液检查结果，识别那些未被诊断出骨髓瘤的高风险人群。一项基于367例骨髓瘤病例和1488例年龄及性别匹配对照的病例对照研究，被用于开发一个包括15项血液检查结果的风险预测模型。该模型具有出色的区分能力（C统计量为0.85（95%置信区间0.83，0.89））和良好的校准度（校准斜率为0.87（95%置信区间0.75，0.90））。在每10万人中有15例的患病率以及0.4的概率阈值下，大约需要对600名患者进行额外的反射试验才能检测出1例病例。我们表明，可以将来自多个常规血液检查参数的信号和异常情况结合起来，以识别那些未被诊断出骨髓瘤的高风险个体，他们可能会从额外的反射试验中受益。需要进一步开展工作来探索这种策略的全部潜力，包括它在临床上是否有用和具有成本效益，以及如何使其在伦理上可接受。
