AN INVESTIGATION ON ROUTINE FOLLOW-UP CARE FOR HEAD AND NECK CANCER

BACKGROUND: Follow-up care aims to provide surveillance with early detection of recurring cancers and to address treatment complications and other health issues in survivorship. It is assumed that follow-up care fulfills these aims, however little evidence supports routine surveillance detecting curable disease early enough to improve survival. Cancer survivors are a diverse patient population, suggesting that a single follow-up regimen may not meet all patients’ follow-up needs. Little is known about what effective follow-up care should include for head and neck cancer patients in a Canadian setting. Identification of subgroups of patients with specific needs and current practices would allow for hypotheses to be generated for enhancing follow-up care. OBJECTIVES: 1a) To describe the follow-up needs and preferences of head and neck cancer patients, 1b) to identify which patient characteristics predict needs and preferences, 1c) to evaluate how needs and preferences change over time, 2a) to describe follow-up care practices by physician visits and imaging tests, and 2b) to identify factors associated to the delivered follow-up care. METHODS: 1) 175 patients who completed treatment between 2012 and 2013 in Kingston and London, Ontario were recruited to participate in a prospective survey study on patients’ needs and preferences in follow-up care. Bivariate and multivariate analyses were employed to describe patient survey responses and to identify patient characteristics that predicted needs and preferences. 2) A retrospective cohort study of 3975 patients on routine follow-up from 2007 to 2015 was carried out using data linkages across registry and administrative databases to describe follow-up practices in Ontario by visits and tests. Multivariate regression analyses assessed factors related to follow-up care. RESULTS: 1) Patients’ needs and preferences were wide-ranging with several characteristics predicting needs and preferences (ORECOG=2.69 and ORAnxiety=1.13). Needs and preferences declined as patients transitioned into their second year of follow-up (p<0.05). 2) Wide variation in practices was found, with marked differences compared to existing consensus guidelines. Multiple factors were associated with follow-up practices (RRTumor site=0.73 and RRLHIN=1.47). CONCLUSIONS: Patient characteristics can be used to personalize care and guidelines are not informing practice. Future research should evaluate individualized approaches to follow-up care.

Multivariate Techniques in Biomechanical Analysis

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.