Optimizing stratified cancer survivorship care through multimorbidity risk prediction

迫切需要优化对医疗脆弱的儿童癌症幸存者的系统护理， 其复杂性植根于幸存者经历的重大总体多发病。然而，取决于 各种风险因素，幸存者的亚群经历了截然不同的疾病负担，使得 知情、高质量的生存护理对于及早识别和减少晚期发病率至关重要。多数 然而，社区提供者在他们的实践中只看到了少数幸存者，每个人的癌症类型、治疗方法都不同。 时代，和治疗暴露，从而支持由于不熟悉 指导方针的具体监督建议。此外，大多数医疗保健系统的能力 以多学科、为所有人提供生存医疗之家的形式提供预防和治疗服务 由于在非专科诊所实施指导方针的复杂性，个体数量仍然有限。至 为了适应这些限制，一些人采用了基本的、风险分层的护理模式，以分配最多的 为那些慢性健康状况(CHC)风险最高的人提供资源密集型、生存专门护理。这些 方法在很大程度上只使用基本的治疗暴露和发病率和流行率来对幸存者进行分层 对于单个社区卫生中心，忽视了由于多个社区卫生中心而导致的多发病和健康相关的生活质量。 根据多发病风险对幸存者群体进行分层的能力将简化和优化a) 基于幸存者个人风险和需求的个性化生存护理，以及b)向幸存者分配资源 最有可能从幸存者疗养院的常规护理中受益。为了开始满足这些需求，我们 建议使用SJLIFE累积负担个性化风险预测模型来建立低、中和 儿童癌症幸存者的高CHC负荷特征，以确定风险分层群体，将有助于 生存、医疗保健提供和干预。我们建议将HRQOL更多地纳入分级- 护理选择，以确定可能受益于更高级别的生存护理的幸存者，否则将是 仅考虑CHC的模型分类错误。拟议的研究将导致分层的生存护理 一种考虑累积负担和HRQL的多发病的方法，这两个特征是 它在实践中的有效传播和实施。

There is a critical need to optimize systematic care for medically vulnerable childhood cancer survivors, the complexity of which is rooted in the significant overall multimorbidity survivors experience. Yet, depending on a variety of risk factors, subsets of survivors experience vastly different disease burdens, making access to informed, high-quality survivorship care essential to early identification and mitigation of late morbidity. Most community providers, however, see only a few survivors in their practices, each varying by cancer type, treatment era, and treatment exposures, and thus endorse discomfort managing survivors due to unfamiliarity with the guidelines' specific surveillance recommendations. Furthermore, the ability of most healthcare systems to provide preventative and treatment services in the form of a multidisciplinary, survivorship medical home to all individuals remains limited due to the complexity of implementing guidelines in non-specialized clinics. To accommodate such constraints, some have adopted basic, risk-stratified models of care to allocate the most resource-intense, survivorship specialty care to those at highest risk of chronic health conditions (CHCs). These approaches have largely stratified survivors using only basic treatment exposures and incidence and prevalence of individual CHCs, overlooking multimorbidity due to multiple CHCs and health-related quality of life (HRQoL). The ability to stratify survivor groups based on risk of multimorbidity would both simplify and optimize a) personalized survivorship care based on individual survivors' risks and needs, and b) resource allocation to those most likely to benefit from routine care in a survivorship medical home. To begin to address these needs, we propose using the SJLIFE cumulative burden personalized risk-prediction model to establish low, moderate, and high CHC burden profiles among childhood cancer survivors to identify risk-stratified groups that will inform survivorship healthcare delivery and intervention. We propose additional incorporation of HRQoL into the tiered- care selection to identify survivors likely to benefit from higher-tiered survivorship care who would otherwise be misclassified by models only considering CHCs. The proposed study will result in a stratified survivorship care approach that considers the multimorbidity of cumulative burden and HRQoL, characteristics which are key to its effective dissemination and implementation in practice.