Using personal trackers to assess cancer patient outcomes

Using personal trackers (Fitbit et al), cancer researchers are trying to objectively measure patient quality life.

According to the Guardian, researchers captured data for 60 days from 41 people undergoing chemotherapy.

The new trial observed 65 people with solid tumors undergoing difficult courses of chemotherapy with drugs likely to cause severe side effects, such as nausea and vomiting. Researchers measured patients’ physical activity from 10am to 7pm for 60 days using a Microsoft fitness band, then collected their data from smartphone apps.


Did the patients have less side effects because they were more active … or were they more active because they had fewer side effects?

There was more than one study focused on personal trackers research results in 2018; there was another one in 2017 that outlined a clinical trial.

From the ASCO 2018 library, the Microsoft study examined unplanned healthcare events of cancer patients undergoing chemotherapy.

This study was conducted as a multi-institutional single arm observational clinical trial of 65 patients with solid tumors undergoing highly emetogenic chemo based on Hesketh classification. We measured PA [physical activity] by analyzing daytime hourly metabolic equivalents (1 MET = resting metabolic rate) from 10 AM – 7 PM over 60 days via Microsoft band 2. Patient reported outcome data was collected using smartphone apps. UHE [unplanned healthcare events] were collected by review of medical records over the 60 days of band wear plus 90 days of clinical follow up.

Data was successfully captured from 41 of the 65 activity trackers. Patients were compliant with wearing the activity trackers for > 7 of 9 total hrs on 67.7% of study days. Only 9 out of 41 patients exhibited > 60 hours of non-sedentary activity, defined as > 1.5 METs, over the 60-day band wear period. Mean step counts/day were similar between higher and lower PA groups at 2564 steps/d and 2261 steps/d respectively. 9 patients with > 60 hrs of 1.5 METs had significantly fewer UHE compared to the 32 patients with < 60 hrs of 1.5 METs (p = 0.02). The physician reported ECOG scores had no correlation with PA or UHE.

In solid tumor patients undergoing highly emetogenic chemo regimens, activity trackers are feasible and identify those patients with a profile of lower activity that predicts UHE. Incorporation of activity trackers has the potential to identify patients who are at need for interventions to prevent hospitalization and may also predict the subset of patients enrolled in clinical trials who are more likely to record serious adverse events.

From the ASCO 2018 library, a different study using FitBits examines “the relationship between physical activity and sleep with domains of distress, wearable activity monitors may assist in the real-time detection of distress in advanced cancer patients.”

We conducted a prospective, observational study at Cedars-Sinai Medical Center and enrolled patients with measurable stage 3+ cancer, ≥18yr, English speaking, ambulatory, with a smartphone, and prognosis of > 3 months. Patients wore a Fitbit Charge HR continuously through 3 consecutive clinic visits, and completed NIH PROMIS tools (Physical Function, Pain, Sleep, Fatigue, and Emotional Distress) during visits. Fitbits recorded average daily step counts, stairs climbed, and sleep time. We conducted regression analyses that adjusted for baseline confounding variables and accounted for correlated responses.

35 patients (Mean age 62; 53% males; 82% GI cancers – emphasis added) were evaluated. Patients had ECOG PS of 0 (20%), 1 (40%), 2 (23%), and 3(17%). The table below displays regression coefficients for steps, floors, and sleep in each PROMIS distress domain.

There is a significant association between steps and floors climbed with multiple domains of distress and physical functioning. The lack of association between total sleep time and these PROs, may suggest that other metrics of sleep quality (i.e. awakenings), may be more relevant. These findings support further exploration of wearable data as a continuously monitored PRO surrogate in advanced cancer patients; wearable data should be further validated for use in both clinical and therapeutic trial settings. Clinical trial information: NCT02659358

fit bit research

And in 2017, researchers conducting a clinical trial noted that “exercise can alleviate side effects of chemotherapy, improve quality of life (QOL), and positively impact disease specific and overall survival.”

Those researchers seek to

  1. determine the feasibility/acceptability of using a Fitbit to measure PA and sleep throughout chemotherapy for breast cancer;
  2. describe patterns of PA [physical activity], sedentary time, and sleep during chemotherapy; and
  3. explore associations of activity and sleep with QOL [quality of life].

Non-metastatic breast cancer patients from UCSF and UCSD will be enrolled prior to starting chemotherapy. Eligibility criteria include ability to speak/read English, walk unassisted, and access to internet or Fitbit compatible smart phone.

Patients sign informed consent, receive a Fitbit Charge HR and guidance on how to use the device.

Patients are instructed to wear the Fitbit throughout their adjuvant or neoadjuvant chemotherapy and 6 months post therapy and to sync the Fitbit at least weekly. Patients complete surveys at start, midpoint, end, and 6 months post chemotherapy.

Questionnaires include PROMIS anxiety, depression, physical function, fatigue, cognitive function, social roles, comfort with technology and usefulness of the Fitbit.

Fitabase database collects minute level activity, sleep, and heart rate.

To assess feasibility, we will evaluate if a participant wears FitBit for at least 10 hour per day for ≥ 80% of the days during chemotherapy. We will use mixed effects regression models to assess patterns of PA and associations between activity and QOL. All models will include activity time and Fitbit wear time and will control for the potential confounding effects of age and other demographic or clinical variables.

As of February 6 2017, 48 out of a planned 80 patients are enrolled.

Acknowledgment: Athena Breast Health Network investigators and patients; support at UCSD by NCI (U54 CA155435-01) and by gift from Carol Vassiliadis and family; NCI grant K07CA181323 to SH; UCSF M Zion Health Fund Award, GBCTB unrestricted funding and TriValley SOCKS to MM.

Clinical trial information: NCT03041545

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