Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, PO Box 100, Jinan, 250012, Shandong, China.
Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
BMC Med. 2023 Feb 21;21(1):63. doi: 10.1186/s12916-023-02773-2.
Current prognostic prediction models of colorectal cancer (CRC) include only the preoperative measurement of tumor markers, with their available repeated postoperative measurements underutilized. CRC prognostic prediction models were constructed in this study to clarify whether and to what extent the inclusion of perioperative longitudinal measurements of CEA, CA19-9, and CA125 can improve the model performance, and perform a dynamic prediction.
The training and validating cohort included 1453 and 444 CRC patients who underwent curative resection, with preoperative measurement and two or more measurements within 12 months after surgery, respectively. Prediction models to predict CRC overall survival were constructed with demographic and clinicopathological variables, by incorporating preoperative CEA, CA19-9, and CA125, as well as their perioperative longitudinal measurements.
In internal validation, the model with preoperative CEA, CA19-9, and CA125 outperformed the model including CEA only, with the better area under the receiver operating characteristic curves (AUCs: 0.774 vs 0.716), brier scores (BSs: 0.057 vs 0.058), and net reclassification improvement (NRI = 33.5%, 95% CI: 12.3 ~ 54.8%) at 36 months after surgery. Furthermore, the prediction models, by incorporating longitudinal measurements of CEA, CA19-9, and CA125 within 12 months after surgery, had improved prediction accuracy, with higher AUC (0.849) and lower BS (0.049). Compared with preoperative models, the model incorporating longitudinal measurements of the three markers had significant NRI (40.8%, 95% CI: 19.6 to 62.1%) at 36 months after surgery. External validation showed similar results to internal validation. The proposed longitudinal prediction model can provide a personalized dynamic prediction for a new patient, with estimated survival probability updated when a new measurement is collected during 12 months after surgery.
Prediction models including longitudinal measurements of CEA, CA19-9, and CA125 have improved accuracy in predicting the prognosis of CRC patients. We recommend repeated measurements of CEA, CA19-9, and CA125 in the surveillance of CRC prognosis.
目前结直肠癌(CRC)的预后预测模型仅包括术前肿瘤标志物的测量,而对其术后可重复测量的利用不足。本研究构建 CRC 预后预测模型,以明确纳入围手术期 CEA、CA19-9 和 CA125 的纵向测量是否以及在何种程度上可以提高模型性能并进行动态预测。
训练和验证队列分别纳入了 1453 例和 444 例接受根治性切除术的 CRC 患者,分别在术前和术后 12 个月内进行了两次或更多次测量。通过纳入术前 CEA、CA19-9 和 CA125 以及它们的围手术期纵向测量值,利用人口统计学和临床病理变量构建预测 CRC 总生存的模型。
在内部验证中,包含术前 CEA、CA19-9 和 CA125 的模型优于仅包含 CEA 的模型,其受试者工作特征曲线下面积(AUC:0.774 比 0.716)、Brier 评分(BS:0.057 比 0.058)和净重新分类改善(NRI=33.5%,95%CI:12.3~54.8%)在术后 36 个月时更高。此外,通过纳入术后 12 个月内 CEA、CA19-9 和 CA125 的纵向测量值,预测模型的预测准确性得到了提高,AUC 更高(0.849),BS 更低(0.049)。与术前模型相比,纳入三个标志物纵向测量值的模型在术后 36 个月时具有显著的 NRI(40.8%,95%CI:19.6 至 62.1%)。外部验证显示与内部验证结果相似。所提出的纵向预测模型可以为新患者提供个性化的动态预测,当在术后 12 个月内收集新的测量值时,可以更新估计的生存概率。
纳入 CEA、CA19-9 和 CA125 纵向测量值的预测模型提高了预测 CRC 患者预后的准确性。我们建议在 CRC 预后监测中重复测量 CEA、CA19-9 和 CA125。