Smartphone-adapted cognition monitoring could be a useful complement to current clinical tools and enhance the care of patients with MS, according to a 1-year cohort study published in Multiple Sclerosis and Related Disorders.
“Digital monitoring with the smartphone has several advantages over traditional clinical assessment,” Ka-Hoo Lam, MD, and colleagues wrote. “Smartphone assessment can be self administered, reducing time spent by clinical personnel. Furthermore, measuring in a hospital environment is different from measuring in a real-life setting. Most importantly, smartphone measurements allow repeated assessments that could overall give a better indication of the patient’s state over time compared to singular evaluations.”
Study participants completed the smartphone-adapted Symbol Digit Modalities Test (sSDMT) themselves using an app. They entered nine randomized symbol-digit combinations at the top of the app screen using an on-screen numeric keypad. Each test lasted 90 seconds and the number of correct responses was scored as the measured sSDMT score, according to the study results. The study was conducted over the course of 1 year, with the test scheduled twice every 3 days during the first 4 weeks and then once a week from week 5 onward.
The responsiveness of the sSDMT in detecting relevant change in the clinically assessed SDMT (ie, a change of 4 points or more), which was administered every 3 months, was quantified by assessing the area under the receiver operating characteristic curve (AUC). Curve fitting of the weekly sSDMT scores was undertaken for each participant using a local linear trend model to estimate and visualize the de-noised cognitive state and 95% CI. Additionally, the optimal assessment frequency was established by evaluating the CI bandwidth as a function of sSDMT assessment frequency.
Comparing Outcomes: Clinical SDMT Vs Smartphone-Adapted SDMT
Dr. Lam and colleagues included 8,032 sSDMT scores from 100 patients with MS in their analysis. The mean age of participants was 46.5 and most (74%) were women. More than one-half of enrolled patients (60%) had relapsing-remitting MS.
Compared with 3-month clinical SDMT (cSDMT) assessments, weekly sSDMT demonstrated better reproducibility estimates (standard error of measurement, 2.94; smallest detectable change, 8.15).
“AUC values did not exceed 0.70 in classifying relevant change in cSDMT,” the investigators wrote. “However, utilizing weekly sSDMT measurements, estimated state curves and the 95% CI were plotted showing detailed changes within individuals over time. With a test frequency of once per 12 days, 4-point changes in sSDMT can be detected.”
The self-administered smartphone SDMT was found to have better reproducibility estimates compared with the clinical SDMT due to higher measurement frequency, according to the study results (Figure). “However, the sSDMT was unresponsive to clinical cognitive outcomes as a result of high variability in scores and, even more so, high variability in clinical cognitive outcomes,” Dr. Lam and colleagues noted. “To circumvent the high variability, a curve fitting approach making use of the high frequency smartphone tests was derived to estimate a de-noised sSDMT score. This curve fitting approach allows visualization of the sSDMT score trajectory and its confidence bands for individual patients.”
Regarding clinical monitoring, the researchers stated that—with weekly measurements— the estimated confidence bands of the trend can show significant differences in cognition. This approach “enables fine-grained, individual based monitoring that improves the detection of statistically reliable change in MS,” they wrote.
