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

通过时变模型有效诊断和治疗与年龄相关的疾病

• 批准号: EP/T014105/1
• 负责人: Rebecca Killick
• 金额: $ 18.18万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT014105%2F1
• 关键词: Effective; Diagnosis; Treatment; Age; related

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.

在医疗保健领域，有一种传统，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。在今天的医疗保健中，我们进行了许多测量，这些测量在时间上的观察结果密集，但传统的将这些信息汇总为单个数字（例如，max、mean、most current）的方法很普遍。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一值来改善医疗保健决策。Killick博士是非平稳时间序列分析方面的专家，正在寻求扩大医疗保健技术方面的知识，以推动医疗保健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与老龄化相关的医疗保健的两个初始领域，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。这一学科跳跃将推动Killick博士进入医疗保健的两个领域；整形外科和结直肠外科，以便1)了解所采取的测量所需的基础科学；2)确定临床需求，为建模提供信息。我们将进一步详细说明下面两个已确定领域背后的动机。骨质疏松症（OP）是一种由骨密度（BMD）随年龄减少而引起的衰弱性疾病。它主要影响绝经后的妇女，三分之一的妇女在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进行DXA扫描（L1-4）。从DXA扫描中，密度测量在6个点进行，尽管临床上通常只使用1或2个点。实际上，骨密度在DXA图像上是不同的，骨折风险取决于骨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，但在其他未监测的部位发生骨折的风险很高，这些治疗和管理更具挑战性。因此，利用统计技术更准确地评估不同骨骼和时间的骨密度变化，不仅有助于对患者的诊断，还有助于开发治疗整个骨骼而不是特定区域的新药。结直肠癌每年影响超过41,000人，是英国第三大最常见的恶性肿瘤，唯一的治疗方法是手术。然而，这与重大风险有关。发病率与年龄密切相关，85-89岁年龄组发病率最高（44%的新病例是75岁及以上的人）。英国国家医疗服务体系的一项审计表明，健康水平较高的结直肠癌患者术后预后更好，总体生存期更长。心肺运动测试（CPET）是一种评估手术适应度的方法。CPET输出的标准用法是取最大/峰值摄氧量（VO2 max/peak），并以此作为心肺健康的衡量标准。一般来说，CPET比其他临床危险因素更能有效地在手术前识别高危患者，因此是患者是否接受手术决策树中的关键组成部分。在老年患者中使用CPET的一个共同特点是，他们单独的VO2峰值非常相似，对手术结果的预测能力很小。相比之下，呼吸测量的整个时间序列在患者之间产生了显着差异。这促使我们利用CPET进展的全时间序列结构对患者进行分类。这将识别高风险患者，并根据生物科学的进一步研究，可能提示新的术前方案，以减少术后结果。

项目成果

Identifying irregular activity sequences: an application to passive household monitoring

• DOI: 10.1093/jrsssc/qlad005
• 发表时间: 2023-05
• 期刊: Journal of the Royal Statistical Society Series C: Applied Statistics
• 作者: Jess Gillam;R. Killick;Simon Taylor;Jack Heal;Ben Norwood

Assessing daily patterns using home activity sensors and within period changepoint detection

• DOI: 10.1111/rssc.12472
• 发表时间: 2021-02-24
• 期刊: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
• 影响因子: 1.6
• 作者: Taylor, Simon A. C.;Killick, Rebecca;Rogerson, Louise
• 通讯作者: Rogerson, Louise

Delay in loop ileostomy reversal surgery does not impact upon post-operative clinical outcomes. Complications are associated with an increased loss of microflora in the defunctioned intestine.

• DOI: 10.1080/19490976.2023.2199659
• 发表时间: 2023-01
• 期刊: Gut microbes
• 影响因子: 12.2

Advancing Reproducible Research by Publishing R Markdown Notebooks as Interactive Sandboxes Using the learnr Package

通过使用 learnr 包将 R Markdown 笔记本发布为交互式沙箱来推进可重复研究

• DOI: 10.32614/rj-2022-021
• 发表时间: 2022
• 期刊: The R Journal
• 作者: Hau Michael Tso C

Modeling and forecasting of at home activity in older adults using passive sensor technology.

• DOI: 10.1002/sim.9529
• 发表时间: 2022-10-15
• 期刊: STATISTICS IN MEDICINE
• 影响因子: 2
• 作者: Gillam, Jess;Killick, Rebecca;Heal, Jack;Norwood, Ben
• 通讯作者: Norwood, Ben