CHHiP试验评估了在局部前列腺癌中中度低剂量放疗的效果。我们利用长期收集的前列腺特异性抗原（PSA）测量值评估和描述患者预后。我们开发了一种临床动态预测联合模型，用于预测生化或临床复发的风险。建模包括重复的PSA值，并根据年龄、肿瘤特征和接受的治疗的基线预后风险因素进行调整。我们使用混合效应子模型处理纵向PSA，使用时间发生危险子模型预测前列腺癌的复发。我们评估了基线预后因子亚组对非线性PSA水平随时间变化的影响，并量化了PSA对时间-复发的关联。我们评估了经过抽样优化的预测性能的校准和区分能力。此外，我们对具有不同预后因素的患者进行了比较动态预测，并研究了与预后相关的里程碑时间的PSA阈值。发生复发的患者在随访期间的基线和整体PSA值通常较高，并在复发前两年呈指数增长。此外，大多数基线风险因素在混合效应和相对危险子模型中都很重要。PSA值和变化率预示着复发。模型的预测性能在8年期间的不同预测时间段中良好，平均AUC为0.70，平均布里耶得分为0.10，平均集成校准指数为0.048；对于在治疗后累积时间超过5年的纵向PSA评估后的预测结果进一步得到改善。3年后PSA阈值小于0.23ng/ml表明8年内复发的风险很小。我们成功地开发了一种联合统计模型来预测前列腺癌复发，评估预后因素和纵向PSA。我们展示了动态更新的PSA信息可以改善预后预测，从而用于指导随访和治疗管理。版权所有 © 2023 Elsevier Inc.

The CHHiP trial assessed moderately hypofractionated radiotherapy in localised prostate cancer. We utilised longitudinal prostate-specific antigen (PSA) measurements collected over time to evaluate and characterise patient prognosis.We developed a clinical dynamic prediction joint model to predict the risk of biochemical or clinical recurrence. Modelling included repeated PSA values and adjusted for baseline prognostic risk factors of age, tumour characteristics and treatment received. We included 3,071 trial participants for model development using a mixed-effect submodel for the longitudinal PSAs, and a time-to-event hazard submodel for predicting recurrence of prostate cancer. We evaluated how baseline prognostic factor subgroups impacted on the nonlinear PSA levels over time and quantify the association of PSA on time-to-recurrence. We assessed bootstrapped optimism-adjusted predictive performance on calibration and discrimination. Additionally, we performed comparative dynamic predictions on patients with contrasting prognostic factors and investigated PSA thresholds over landmark times to correlate with prognosis.Patients that developed recurrence had generally higher baseline and overall PSA values during follow-up and had an exponentially rising PSA in the two-years before recurrence. Additionally, most baseline risk factors were significant in the mixed-effect- and relative risk submodels. PSA value- and rate-of-change was predictive of recurrence. Predictive performance of the model was good across different prediction times over an 8-year period, with an overall mean AUC of 0.70, mean Brier score of 0.10, and mean integrated calibration index of 0.048; these were further improved for predictions after 5 years of accrued longitudinal post-treatment PSA assessments. PSA thresholds less than 0.23ng/mL after 3 years were indicative of a minimal risk of recurrence by 8 years.We successfully developed a joint statistical model to predict prostate cancer recurrence, evaluating prognostic factors and longitudinal PSA. We showed dynamically updated PSA information can improve prognostication, which can be used to guide follow-up and treatment management options.Copyright © 2023. Published by Elsevier Inc.