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

在医疗保健领域，有一个传统，即使用在单个时间点或在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，这些测量是在不同时间的观察中进行的，但这种信息在单个数字(例如，最大值、平均值、最新值)中的传统汇总很普遍。通过应用非统计时间序列分析，我们希望通过考虑所有数据而不是单个值来改进医疗保健决策。Killick博士是非平稳时间序列分析方面的专家，他正在寻求扩展医疗技术方面的知识，以推动进一步的统计研究，以推动医疗技术方面的挑战。这项学科跳跃建议确定了医疗保健的两个与老龄化相关的初始领域，在这些领域中，随着时间的推移利用这些信息将提供关于患者及其护理的新视角。这一学科跳跃将推动基里克博士进入医疗保健的两个领域：骨科和结直肠外科，以1)学习所做测量所需的基本科学；2)识别临床需求，为建模提供信息。我们提供了下面两个已识别区域背后的动机的进一步细节。骨质疏松症(OP)是一种由与年龄相关的骨密度(BMD)降低而引起的衰弱状况。它主要影响绝经后妇女，三分之一的人在80岁时受到影响。目前NHS评估骨密度的方法是对髋部和腰椎(L1-4)进行DXA扫描。在DXA扫描中，密度测量是在6个点上进行的，尽管临床上通常只使用1到2个点。实际上，DXA图像上的骨密度各不相同，骨折风险也不同，这取决于丢失是发生在一个特定区域还是均匀发生。目前的治疗方法改善了测量部位的骨密度，但在其他没有监测的部位有很高的骨折风险，治疗和管理起来更具挑战性。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，还会引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4.1万人，是英国第三大最常见的恶性肿瘤，唯一有效的治疗方法是手术。然而，这与重大风险相关。发病率与年龄密切相关，85-89岁年龄组发病率最高(44%的新病例为75岁及以上人群)。NHS内部的一项审计表明，健康水平较高的结直肠癌患者手术后结果更好，总体生存时间更长。心肺运动试验(CPET)是一种用于评估手术适合性的方法。CPET输出量的标准用法是取最大/最大摄氧量(最大摄氧量/最大摄氧量)，并将其作为心肺功能的衡量标准。一般来说，CPET可以比其他临床风险因素更有效地在手术前识别高危患者，因此是决策树中决定患者是否接受手术的关键组成部分。老年患者使用CPET时的一个共同特征是，他们的VO2峰值非常相似，几乎不能预测手术结果。相比之下，一口气测量的整个时间序列在患者之间产生了显著的差异。这促使我们利用CPET进展的完整时间序列结构来提供患者的分类。这将确定高危患者，并在对生物科学进行进一步研究后，可能指示新的术前方案以减少手术后的结果。

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.