Background: The number of people living with and beyond a cancer diagnosis has increased, however survivors may experience long-term side-effects from treatment that can impact on physical fitness and cardiovascular health. Lifestyle interventions enhance outcomes after cancer treatment but innovations and technology are needed to provide consistency and scalability. Interventions to support exercise and dietary modification in secondary care settings have been limited by the lack of personalisation, clinician time and resources. Community pharmacies are well positioned to provide lifestyle advice for people with cancer and long-term conditions. This study is the first to develop a tailored lifestyle intervention using a computer algorithm to enable community pharmacists to provide personalised advice for cancer patients. Objective: To create a computer-based algorithm to support community pharmacists to deliver a tailored lifestyle intervention for men during and after treatment for prostate cancer. Method: An observational study was conducted at two UK centres involving 83 men with prostate cancer who were 3-36 months’ post-diagnosis. Physical fitness, strength and cardiovascular health were assessed. Qualitative interviews were undertaken with 20 participants to understand their interpretation of the assessment and analysed using a framework analysis. These data were used to inform our computer-based algorithm and lifestyle prescriptions. Results: Physical fitness varied across participants. Limb strength was categorised with upper body strength low for 40% of men compared to their age (40 out of 83) and lower limb strength (44 of 83) 53% of men were low in comparison to age normative values. The Siconolfi step test provided classification of cardiopulmonary fitness with 26.5% (22 of 83) men unable to complete level 1 with very low physical fitness and 41% (34 of 83) of men moderate completing stage 2 of the test. Cardiovascular risk was categorised as high (>20% QRISK2) in 41% of men contributed to by the number of men who had a high hip to waist ratio 72 of 83 men (86.7%) indicating abdominal fat. Three emergent themes from the qualitative analysis highlighted different perceptions of the physical assessment experience. The algorithm provided a clear pathway for decision making, that it was safe and effective to enable community pharmacists to prescribe tailored lifestyle advice for men with prostate cancer. Conclusion: We have developed a computer algorithm that uses simple, safe and validated assessments to provide tailored lifestyle advice which addresses specific areas of cardiovascular risk, strength and physical fitness in men with prostate cancer. It generates a real-time lifestyle prescription at the point of care and has been integrated into the software platform used by pharmacies in the UK. The algorithm was integrated into the software platform used by pharmacies within the UK.
|Journal||Journal of Medical Internet Research|
|Publication status||Accepted/In press - 3 Jun 2019|