Carcinoma of Prostate (Disorder) Clinical Trial
Official title:
An Observational Prospective Cohort Study About Quality of Life in Relation to the Physical Activity of Taiwanese Breast and Prostate Cancer Patients.
This study focuses on whether or not physical activity and sleep quality correlate with the
health of prostate and breast cancer patients. The activity data will be acquired using
wearable actigraphy devices, which the subjects will wear for the duration of seven days. The
sleep quality will be measured using a combination of actigraphy and the mandarin version of
the Pittsburgh Sleep Quality Index (PSQI) and the Quality of Life Questionnaire (QLQ). By
using this combination, the investigators will not only measure the objective physical
activity while the patient is asleep, but also the subjective sleep quality. The
questionnaire will also function as control data for the accuracy of the actigraphy device.
This study will recruit approximately 30 breast or prostate cancer patients. The participants
will wear a wearable actigraphy device for 7 consecutive days, which will provide accurate
and objective movement and sleep data. This data is linked to a unique Identification number
(ID), which will be noted in the participant's case report. This case report also contains
the participant's information and answers to the questionnaires.
Physical inactivity is a common issue amongst breast cancer patients. Previous studies have
shown that physical activity can be beneficiary to both the cancer outcomes and the quality
of life.
However, most comparable studies had western populations or included some participants of
Asian descent at best. Given the growing importance of effective and efficient follow-up care
[1] and the lack of research on physical activity and sleep quality in relation to the
Quality of Life (QoL) of cancer patients in Asian countries, the investigators aim to monitor
the physical activity, sleep quality and subjective QoL of Taiwanese breast- and prostate
cancer patients. Hence the investigators' main research question is: "Does physical and/or
sleep activity affect the quality of life of (Taiwanese) breast and prostate cancer
patients?". If this would be the case, the results might cover the bases for an intervention
study aimed at improving physical and/or sleep quality in these cancer patients.
This study focuses on whether or not physical activity and sleep quality correlate with the
health of prostate and breast cancer patients. The activity data will be acquired using
wearable actigraphy devices, which the subjects will wear for the duration of seven days. The
sleep quality will be measured using a combination of actigraphy and the mandarin version of
the Pittsburgh Sleep Quality Index (PSQI). By using this combination, the investigators will
not only measure the objective physical activity while the patient is asleep, but also the
subjective sleep quality. The questionnaire will also function as control data for the
accuracy of the actigraphy device.
Lastly, the quality of life will be measured using the European Organization for the Research
and Treatment of Cancer Quality of Life Questionnaire 30 (EORTC QLQ-C30). This will provide
an insight in the quality of life of the subjects, which will enable the investigators to
draw a conclusion whether or not physical activity and sleep quality are related to the
quality of life.
This study will recruit approximately 30 breast or prostate cancer patients. The participants
will wear a wearable actigraphy device for 7 consecutive days, which will provide accurate
and objective movement and sleep data. This data is linked to a unique ID, which will be
noted in the participant's case report. This case report also contains the participant's
information and answers to the questionnaires.
To retrieve results from the dataset, the data analysis will be divided in two parts:
correlation between sleep quality and the Quality of Life, and between physical activity and
the Quality of Life. Before commencing with the analysis itself, the data will be checked for
outliers and missing data.
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