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31st October 2022
Using a daily steps AI model, US researchers were able to predict an unplanned hospitalisation for cancer patients undergoing chemo-radiation according to the findings of a study presented at the recent American Society for Radiation Oncology (ASTRO) annual meeting.
Globally, cancer is a leading cause of death and the World Health Organisation has estimated that in 2020, there were nearly 10 million deaths in 2020. While oncologists manage patients with cancer, such individuals may also develop health issues due to treatment-related side-effects that prompts an emergency department (ED) visit. In fact, such unplanned visits are not uncommon and in one study of 402 study participants, 20% experienced an ED visit, and 18% experienced a hospital admission while receiving cancer treatment. The potential consequences of these visits might include interruption of chemotherapy, and this may impact on cancer therapy outcomes. As a result, there is a need for interventions to identify patients at a higher risk of complications and therefore prevent unplanned hospital visits.
The current researchers previously developed a machine learning model which could predict emergency visits and hospitalisation during cancer therapy. Moreover, in a further study, they also showed that a machine learning model, accurately triaged patients undergoing radiotherapy and chemoradiation and was able to direct clinical management, reducing acute care rates in comparison to standard care. With increased use of wearable devices which collect large amounts of health data, the researchers wondered if it would be possible to utilise this data, such as daily step count, to predict unplanned ED visits. The team developed a daily steps AI model and set out to validate the model before and during chemoradiation (CRT). They turned to data collected in three prospective trials in which patients were asked to wear commercial fitness trackers continuously before and during curative-intent CRT for multiple cancer types. The team collated a wealth of data including age, ECOG performance status, sex, diagnosis, radiotherapy plan metrics and daily step count. The model was trained both with and without step count-derived features and used to predict a first hospitalisation event within one week based on data from the preceding two weeks. The models were then evaluated in terms of the area under the receiver operating characteristic curve (AUC).
Daily steps AI model and prediction of hospitalisation
In total, 214 patients with a median age 61 were included and the most common diagnoses were head and neck cancer (30%) and lung cancer (29%). The model was trained using 70% of patients and validated in the remaining 30%.
When step count was included in the model, it had strong a predictive performance for hospitalisation the following week (AUC = 0.81, 95% CI 0.62 – 0.91). In fact, inclusion of step count significantly improved the predictability of the model compared to when this data was excluded (AUC = 0.57, 95% CI 0.40 – 0.74, p = 0.004). The top five contributing variables were step counts from each of the past two days, the absolute difference in minimum step counts over the past two weeks, relative decrease in the maximum step count over the past two weeks, and relative decrease in the step count range over the past two weeks.
In an associated press release, lead author Dr Hong said that ‘The step counts immediately preceding the prediction window ended up being generally more predictive than clinical variables. The dynamic nature of the step counts, the fact that they’re changing every day, seems to make them a particularly good indicator of a patient’s health status.’
The authors concluded that based on these findings, they plan to clinically validate the model in a further study which will randomise patients undergoing CRT for lung cancer to treatment with or without daily step count monitoring.
Friesner I et al. Machine Learning-Based Prediction of Hospitalization Using Daily Step Counts for Patients Undergoing Chemoradiation. No 132. ASTRO annual meeting, 2022
12th September 2022
Adults who take just short of 10,000 steps/day, particularly if those steps are more intense, have a reduced dementia risk according to a study by a team from Denmark and Australia.
Dementia describes a syndrome in which there is a deterioration in cognitive function beyond what might be expected from the usual consequences of biological ageing and which according to the world health organisation, globally, affects around 55 million people. In a 2020 report published in the Lancet, it was noted how there is a growing body of evidence that supports the nine potentially modifiable risk factors for dementia, one of which is physical inactivity. The authors recommended keeping cognitively, physically and socially active in midlife and later life although little evidence exists for any single specific activity protecting against dementia. In an analysis of 15 cohort studies with over 47,000 adults, researchers concluded that taking more steps per day was associated with a progressively lower risk of all-cause mortality. Despite this benefit, evidence also suggests that step cadence, i.e., the number of steps per minute, or step intensity does not appear to be significantly associated with mortality.
With a lack of supportive evidence for the value of greater physical activity in reducing the risk of developing dementia, in the present study, researchers examined the association between daily step count as well as intensity and dementia risk. They used data held within the UK Biobank where a cohort of over 100,000 individuals had agreed to wear an accelerometer on their dominant wrist 24 hours a day and 7 days a week, to measure physical activity. All were free of dementia at the start and as well as recording total daily steps, the researchers also examined step cadence. This was divided into incidental steps, defined as fewer than 40 steps/minute, such as walking between rooms at home, purposeful steps, which > 40 steps/minute, for instance, while exercising and finally, peak 30-minute cadence, which was the average steps/minute recorded for the 30 highest, but not necessarily consecutive, minutes in a day. The researchers estimated the optimal dose of steps, where the maximum significant dementia risk reduction was observed and the minimal dose, which was defined as the number of steps at which the risk reduction was 50% of the maximum. In regression models, adjustments were made for age, sex, lifestyle and co-morbidities.
Dementia risk and daily steps
The overall cohort included 78,430 individuals with a mean age of 61.1 years (55.3% female) and who were followed for a median of 6.9 years. During the follow-up period, 866 participants developed dementia at a mean age of 68.3 years.
The optimal dose of daily steps was 9826 and this led to a 51% lower risk of developing dementia (hazard ratio, HR = 0.49, 95% CI 0.39 – 0.62) and the minimal dose of 3826 steps/day (HR = 0.75, 95% CI 0.67 – 0.83).
For peak 30-minute cadence, the optimal dose was 112 steps/minute (HR = 0.38, 95% CI 0.24 – 0.60) and 6315 for purposeful steps.
The authors concluded that taking more daily steps was associated with a reduced dementia risk with the optimal dose just short of 10,000 steps/day and also that step intensity led to stronger associations. They suggested that future guidelines for dementia prevention should promote step-based recommendations.
del Pozo Cruz B et al. Association of Daily Step Count and Intensity With Incident Dementia in 78 430 Adults Living in the UK JAMA Neurol 2022
15th March 2022
A mortality benefit accrues from taking more daily steps but this benefit plateaus and depends upon an individual’s age. This was the main finding of a meta-analysis by a team from the Department of Kinesiology and Institute for Applied Life Sciences, University of Massachusetts Amherst, Massachusetts, US.
Measuring the number of steps taken each day has become much easier over the last few years largely because of an increase in the availability of fitness trackers. Moreover, though the idea that the target for beneficial health is at least 10,000 steps/day, there is a lack of evidence to justify this figure. Indeed, it is possible that the actual number of steps/day required could be actually much lower, with one study in older women finding that the mortality rates progressively decreased before levelling at approximately 7500 steps/day. In addition, the optimal number of steps needed to achieve a mortality benefit is likely to be influenced by other factors such as age and gender, as well as the pace of walking, although observational studies have found that there is no significant association between step intensity and mortality after adjusting for total steps per day.
For the present study, the US team set out to assess the mortality benefit derived from the number of steps taken per day and considered how this might be affected by both age and gender. They also sought to clarify if there was an association between the stepping rate (i.e., how fast someone walked) and all-cause mortality. They searched for studies which examined the relationship between daily steps and mortality in adults (> 18 years of age). After identifying relevant articles, the US team asked the study investigators to provide additional data and to calculate the peak 30 and 60 minute stepping rates, as well as the time spent walking at 40 steps/min or faster and 100 steps/min. The primary outcome was set as all-cause mortality. The total number of median daily steps was categorised into quartiles; up to 3553 (quartile 1); 5801 (quartile 2); 7842 (quartile 3) and 10,901 (quartile 4). Hazard ratios were calculated for the mortality benefits and adjusted for several factors including age, sex, education level, body mass index and other health-related variables.
Mortality benefit and daily step count
The authors identified a total of 15 eligible studies which included 47,471 individuals with a mean age of 65 years (68% female) and who were followed-up for a median of 7.1 years. The overall median number of steps was 6495 and individuals under 60 years of age had a higher median number of daily steps compared to those over 60. (7803 vs 5649, under 60 years vs over 60 years of age). In the cohort as a whole, there were 3013 deaths recorded.
Compared to the lowest quartile, the overall adjusted hazard ratio for all-cause mortality in the highest quartile was 0.47 (95% CI 0.39 – 0.57). When comparing those under versus over 60 years of age, there was a greater mortality benefit for older individuals (HR = 0.60 vs HR = 0.43, under 60 vs over 60). In addition, there was a higher benefit for women compared to men (HR = 0.43 vs HR = 0.52, female vs male).
The hazard ratios for mortality plateaued for adults 60 years and older at 6000 – 8000 steps/day and between 8,000 – 10,000 for those under 60 years of age.
The mortality benefit was also significant for a higher step rate for both 30 and 60 minutes but not significant for the time spent walking at 40 or faster, at 100 steps/minute. In other words, didn’t seem to matter if someone walked faster.
The authors concluded that while mortality benefits can be achieved at below the popular reference value of 10,000 steps/day, these benefits plateau and are not increased by taking further steps.
Paluch AE et al. Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts Lancet Public Health 2022