Frailty is very common among older people with gastric cancer and seriously affects their prognosis. The development of frailty is continuous and dynamic, increasing the difficulty and burden of care. The aims of this study were to delineate the developmental trajectory of frailty in older people with gastric cancer 1 year after surgery, identify heterogeneous frailty trajectories, and further explore their predictors to construct a nomogram for prediction. We conducted a prospective longitudinal observation study. Clinical evaluation and data collection were performed at discharge, and at 1, 3, 6, and 12 months. This study was conducted in a tertiary hospital and 381 gastric cancer patients over 60 years who underwent radical gastrectomy completed the 1-year follow-up. A growth mixture model (GMM) was used to delineate the frailty trajectories, and identify heterogeneous trajectories. A regression model was performed to determine their predictors and further construct a nomogram based on the predictors. Bootstrap with 1000 resamples was used for internal validation of nomogram, a receiver operating characteristic (ROC) curve to evaluate discrimination, calibration curves to evaluate calibration and decision curve analysis (DCA) to evaluate the clinical value. GMM identified three classes of frailty trajectories: “frailty improving”, “frailty persisting” and “frailty deteriorating”. The latter two were referred to as heterogeneous frailty trajectories. Regression analysis showed 8 independent predictors of heterogeneous frailty trajectories and a nomogram was constructed based on these predictors. The area under ROC curve (AUC) of the nomogram was 0.731 (95 % CI = 0.679–0.781), the calibration curves demonstrated that probabilities predicted by the nomogram agreed well with the actual observation with a mean absolute error of 0.025, and the DCA of nomogram indicated that the net benefits were higher than that of the other eight single factors. Older gastric cancer patients have heterogeneous frailty trajectories of poor prognosis during one-year postoperative survival. Therefore, early assessment to predict the occurrence of heterogeneous frailty trajectories is essential to improve the outcomes of elderly gastric cancer patients. Scientific and effective frailty interventions should be further explored in the future to improve the prognosis of older gastric cancer patients. This study constructed a static and dynamic online nomogram with good discrimination and calibration, which can help to screen high-risk patients, implement preoperative risk stratification easily and promote the rational allocation of medical resources greatly. (Number: ). Our findings identified three frailty trajectories and constructed a nomogram to implement preoperative risk stratification and improve patient outcomes.

中文翻译：

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用于预测老年胃癌幸存者虚弱异质性轨迹的动态在线列线图


衰弱在老年胃癌患者中非常常见，严重影响其预后。衰弱的发展是持续的、动态的，增加了护理的难度和负担。本研究的目的是描绘老年胃癌患者术后 1 年衰弱的发展轨迹，识别异质衰弱轨迹，并进一步探索其预测因素，构建用于预测的列线图。我们进行了一项前瞻性纵向观察研究。在出院时以及第 1、3、6 和 12 个月时进行临床评估和数据收集。本研究在三级医院进行，对381名60岁以上接受根治性胃切除术的胃癌患者完成了1年的随访。使用生长混合模型（GMM）来描绘脆弱轨迹，并识别异质轨迹。执行回归模型以确定其预测变量并根据预测变量进一步构建列线图。使用 1000 次重采样的 Bootstrap 进行列线图的内部验证、用于评估辨别力的受试者工作特征 (ROC) 曲线、用于评估校准的校准曲线和用于评估临床价值的决策曲线分析 (DCA)。 GMM 确定了三类衰弱轨迹：“衰弱改善”、“衰弱持续”和“衰弱恶化”。后两者被称为异质脆弱轨迹。回归分析显示了异质衰弱轨迹的 8 个独立预测因子，并根据这些预测因子构建了列线图。列线图的 ROC 曲线下面积 (AUC) 为 0.731 (95% CI=0.679–0.781），校准曲线表明列线图预测的概率与实际观测结果吻合较好，平均绝对误差为0.025，列线图的DCA表明净效益高于其他8个单因子。老年胃癌患者术后一年的生存期具有不同的衰弱轨迹，预后不良。因此，早期评估以预测异质衰弱轨迹的发生对于改善老年胃癌患者的预后至关重要。未来应进一步探索科学有效的衰弱干预措施，以改善老年胃癌患者的预后。本研究构建了具有良好区分性和校准性的静态和动态在线列线图，有助于筛选高危患者，轻松实施术前风险分层，极大促进医疗资源的合理配置。 （数字： ）。我们的研究结果确定了三种衰弱轨迹，并构建了列线图来实施术前风险分层并改善患者预后。