Effective Diagnosis and Treatment of Age-related Disease Through Time-varying Modelling

在医疗保健领域，有一种传统，即使用在单个时间点或少数接触点进行的测量来推断诊断和治疗计划。在当今的医疗保健中，我们进行了许多测量，这些测量在时间上的观察是密集的，但传统上对这些信息的总结是单个数字（例如，max、mean、most current）是普遍的。通过应用非平稳时间序列分析，我们希望通过考虑所有数据而不是单个值来改善医疗保健决策。Killick博士是一位非平稳时间序列分析专家，他正在寻求扩展医疗技术方面的知识，以推动医疗技术挑战所激发的进一步统计研究。这一学科跳跃建议确定了医疗保健的两个最初领域，与老龄化有关，在这些领域中，利用这些信息将为患者及其护理提供一个新的视角。这一学科的跳跃将推动Killick博士进入两个医疗保健领域;骨科和结直肠手术，以1）学习所需的测量基础科学; 2）确定临床需求，为建模提供信息。骨质疏松症（Osteoporosis，OP）是一种由年龄相关的骨矿物质密度（bone mineral density，BMD）降低引起的衰弱性疾病。它主要影响绝经后妇女，其中三分之一在80岁时受到影响。目前NHS评估骨密度的方法是对髋关节和腰椎（L1-4）进行DXA扫描。从DXA扫描中，在6个点进行密度测量，尽管通常临床上仅使用1或2个点。在实践中，DXA图像上的骨密度各不相同，并且根据丢失是发生在一个特定区域还是均匀区域，存在不同的骨折风险。目前的治疗提高了测量位置的骨密度，但在未监测的其他位置发生骨折的风险很高，这些位置的治疗和管理更具挑战性。因此，使用统计技术来更准确地评估骨密度在不同骨骼和不同时间的变化，不仅有助于患者的诊断，而且还能激发治疗整个骨骼而不是特定区域的新药开发。结直肠癌每年影响超过41，000人，是英国第三大常见的恶性肿瘤，唯一的治愈性治疗方法是手术。然而，这与重大风险有关。发病率与年龄密切相关，85-89岁年龄组的发病率最高（44%的新病例是75岁及以上的人）。NHS内部的一项审计表明，健康水平较高的结直肠癌患者在手术后有更好的结果和更长的总生存期。心肺功能运动测试（CPET）是一种用于评估手术适应性的方法。CPET输出的标准使用是获取最大/峰值摄氧量（VO 2 max/peak），并将其用作心肺适应性的测量。通常，CPET可以在手术前比其他临床风险因素更有效地识别高风险患者，因此是患者是否接受手术的决策树中的关键组成部分。对老年患者使用CPET时的一个共同特征是，他们的VO 2峰值非常相似，对手术结局的预测能力很小。相比之下，整个时间序列的呼吸的呼吸测量产生了显着的差异患者之间。这促使我们利用其CPET进展的完整时间序列结构来提供患者分类。这将识别高风险患者，并在进一步调查生物科学后，可能表明新的术前方案，以减少术后结局。

Within healthcare, there is a tradition of using measurements taken at a single point in time, or at a small number of contact points to infer diagnoses and treatment plans. In the healthcare of today we have many measurements taken that are dense in observations across time yet the traditional summary of this information in a single number (e.g., max, mean, most current) is prevalent. By applying non-statioonary time series analysis we hope to improve the decisions made in healthcare by taking all data into account instead of single values. Dr. Killick is an expert in non-stationary time series analysis and is seeking to expand knowledge in healthcare technologies in order to drive further statistical research motivated by challenges in healthcare technologies.This discipline hopping proposal identifies two initial areas of healthcare, related to ageing, where utilising this information across time will provide a novel perspective on patients and their care. This discipline hop will propel Dr Killick into two areas of healthcare; orthopaedics and colorectal surgery, in order to 1) learn the required underlying science of the measurements taken; and 2) identify clinical needs to inform modelling. We provide further detail on the motivation behind the two identified areas below.Osteoporosis (OP) is a debilitating condition caused by a reduction in bone mineral density (BMD) associated with age. It primarily affects post-menopausal women with 1 in 3 affected at 80 years of age. The current NHS approach to assessing bone density is to take a DXA scan of the hips and lumbar spine (L1-4). From the DXA scan, measurements of density are taken at 6 points, although typically only 1 or 2 points are used clinically. In practice, bone density varies across the DXA image and there is a different fracture risk depending on whether loss occurs in one specific region or uniformly. Current treatment improves the bone density at the measured locations but at a high risk of fractures in other locations which are not monitored, these are more challenging to treat and manage. Thus using statistical techniques to create a more accurate assessment of how bone density varies both across bones and across time will not only aid diagnosis of patients, but also spark new drug development that treats the whole bone rather than specific areas.Colorectal cancer affects over 41,000 people every year, is the third most common malignancy in the UK, and the only curative treatment is surgery. This is however associated with significant risks. The incidence is strongly related to age with the highest rates in the 85-89 age group (44% of new cases are people aged 75 and over). An audit within the NHS suggested that colorectal cancer patients with higher level of fitness have better outcomes after surgery and longer overall survival. Cardiopulmonary Exercise Testing (CPET) is a method used to assess fitness for surgery. Standard use of CPET output is to take the maximal/peak oxygen uptake (VO2 max/peak) and use this as a measure of cardiorespiratory fitness. Generally, CPET can more effectively identify high risk patients before surgery than other clinical risk factors and is therefore a critical component within the decision tree for whether a patient undergoes surgery. A common feature when using CPET on elderly patients is that their VO2 peak values alone are very similar providing little predictive power of surgical outcomes. In contrast, the entire time series of breath by breath measurements produces a marked difference between patients. This motivates us to provide a classification of patients utilising the full time series structure of their CPET progression. This will identify high risk patients and, following further investigation of the biological science, may indicate new pre-operative regimes to reduce post-surgery outcomes.