Prognostic factors for the development of upper limb dysfunctions after breast cancer: the UPLIFT-BC prospective longitudinal cohort study protocol.

INTRODUCTION: Upper limb (UL) dysfunctions are highly prevalent in people after breast cancer and have a great impact on performing activities in daily living. To improve care, a more comprehensive understanding of the development and persistence of UL dysfunctions is needed. Therefore, the UPLIFT-BC study will primarily examine the prognostic value of different factors at the body functions and structures, environmental and personal level of the International Classification of Functioning, Disability and Health (ICF) framework at 1-month post-surgery for persisting UL dysfunctions at 6 months after finishing cancer treatment. METHODS AND ANALYSIS: A prospective longitudinal cohort study, running from 1-week pre-surgery to 6 months post-local cancer treatment, is performed in a cohort of 250 women diagnosed with primary breast cancer. Different potentially prognostic factors to UL dysfunctions, covering body functions and structures, environmental and personal factors of the ICF, are assessed pre-surgically and at different time points post-surgery. The primary aim is to investigate the prognostic value of these factors at 1-month post-surgery for subjective UL function (ie, QuickDASH) at 6 months post-cancer treatment, that is, 6 months post-radiotherapy or post-surgery (T3), depending on the individuals' cancer treatment trajectory. In this, factors with relevant prognostic value pre-surgery are considered as well. Similar analyses are performed with an objective measure for UL function (ie, accelerometry) and a composite score of the combination of subjective and objective UL function. Second, in the subgroup of participants who receive radiotherapy, the prognostic value of the same factors is explored at 1-month post-radiotherapy and 6 months post-surgery. A forward stepwise selection strategy is used to obtain these multivariable prognostic models. ETHICS AND DISSEMINATION: The study protocol was approved by the Ethics Committee of UZ/KU Leuven (reference number s66248). The results of this study will be published in peer-reviewed journals and will be presented at several research conferences. TRIAL REGISTRATION NUMBER: NCT05297591.

Assessing Upper Limb Function in Breast Cancer Survivors Using Wearable Sensors and Machine Learning in a Free-Living Environment.

(1) Background: Being able to objectively assess upper limb (UL) dysfunction in breast cancer survivors (BCS) is an emerging issue. This study aims to determine the accuracy of a pre-trained lab-based machine learning model (MLM) to distinguish functional from non-functional arm movements in a home situation in BCS. (2) Methods: Participants performed four daily life activities while wearing two wrist accelerometers and being video recorded. To define UL functioning, video data were annotated and accelerometer data were analyzed using a counts threshold method and an MLM. Prediction accuracy, recall, sensitivity, f1-score, 'total minutes functional activity' and 'percentage functionally active' were considered. (3) Results: Despite a good MLM accuracy (0.77-0.90), recall, and specificity, the f1-score was poor. An overestimation of the 'total minutes functional activity' and 'percentage functionally active' was found by the MLM. Between the video-annotated data and the functional activity determined by the MLM, the mean differences were 0.14% and 0.10% for the left and right side, respectively. For the video-annotated data versus the counts threshold method, the mean differences were 0.27% and 0.24%, respectively. (4) Conclusions: An MLM is a better alternative than the counts threshold method for distinguishing functional from non-functional arm movements. However, the abovementioned wrist accelerometer-based assessment methods overestimate UL functional activity.