Systemic Treatment Related Toxicity Identified With a Smartphone APPlication Measuring Step Count - Prospective Cohort Study

Rationale: Systemic treatment of patients with cancer has a multimodal approach with the goal of balancing quantity and quality of life. Treatment decisions are influenced by tumour and patient-related characteristics. Additionally, in clinical practice performance status is used to identify whether a patient is sufficiently fit for systemic treatment, as it has shown to be a valid prognostic factor for survival and adverse events during treatment. However, treatment-related toxicities and hospitalisations occur frequently during systemic treatment.

The disadvantages of performance status assessed with ECOG or Karnofsky, is that it is a subjective measurement which is prone to bias and has high interobserver variability. Also a patient's self-reported physical function is significantly associated with shorter (progression-free) survival, but it is also subjective and is prone to multiple forms of bias. Objective assessment of physical function might be a good alternative to counteract these shortcomings. A higher level of physical activity is associated with a reduction in cancer specific mortality and can be measured with accelerometers, pedometers or multisenor systems like smartphones.

Wearable measured step count assessed with a wrist worn device provided by the investigators has shown to be associated with adverse events. However, these devices cannot be provided to all patients in clinical practice.

Recently, the investigators showed that the smartphones' assessments of physical activity (step count), have excellent agreement with accelerometer assessments of physical activity and good test-retest reliability. Furthermore this smartphone measurements were associated with early trial discontinuation in phase 1/2 cancer trials.

The investigators hypothesize that a low baseline and/or a reduction in physical activity (step count) measured with smartphones will be predictive for clinically relevant adverse events during systemic treatment. Adding objective information of physical function in the process of selecting the best treatment for a patient may help prevent unnecessary adverse events. Additionally, a detection of a decline in physical activity during treatment may identify upcoming adverse events early, allowing timely management/support. This may help to optimize treatment and quality of life.