This is a really interesting study. It looks at the relationship between inflammatory bowel disease and Parkinson's disease, which is something I have been wanting to do for sometime. There is lots of seemingly circumstantial evidence linking IBD and PD, including gastrointestinal inflammation, unusual relationships with smoking (for ulcerative colitis) and an association with the LRRK2 gene (for Crohn's disease). Here the authors show an association between PD and all IBD, and between PD and Crohn's disease and ulcerative colitis separately. People with IBD appeared to be at increased risk of PD during follow-up...
Perhaps more intriguing is that fact that they show a reduction in that increased risk if people were treated with drugs targeted against the mechanisms of IBD. Whether this represents a reduction in risk because the IBD is better treated or because the same drugs target a pathway that is important to PD remains to be seen....
Inga Peter, PhD; Marla Dubinsky, MD; Susan Bressman, MD; Andrew Park, PhD, MPH; Changyue Lu, MS; Naijun Chen, MS; Anthony Wang, PhD, MPH
JAMA Neurology 23rd April 2018
https://jamanetwork.com/journals/jamaneurology/fullarticle/2679038
Importance
Despite established genetic and pathophysiologic links between inflammatory bowel disease (IBD) and Parkinson disease (PD), clinical data supporting this association remain scarce. Although systemic inflammation is considered a potential biological mechanism shared between the 2 diseases, the role of reduced systemic inflammation through IBD-directed anti–tumor necrosis factor (anti-TNF) therapy in PD risk is largely unknown.
Objective
To compare the incidence of PD among individuals with or without IBD and to assess whether PD risk among patients with IBD is altered by anti-TNF therapy.
Design, Setting, and Participants
This is a retrospective cohort study analyzing information in the Truven Health MarketScan administrative claims database and the Medicare Supplemental Database between January 1, 2000, and March 31, 2016. Individuals were selected who had at least 2 claims for IBD diagnoses, at least 6 months of follow-up, and no prior diagnosis of PD on or before the IBD index date. Exposure to Anti-TNF therapy was measured from the anti-TNF index date to the last date of anti-TNF coverage or the end of enrollment or PD index date, whichever was earliest. Incidence rates per 1000 person-years were calculated, and crude and adjusted incidence rate ratios were estimated by Poisson regression models and presented with 95% CIs.
Main Outcomes and Measures
Incidence of PD among patients with IBD with or without exposure to anti-TNF therapy.
Results
In total, 144 018 individuals with IBD were matched on age, sex, and year of index date with 720 090 unaffected controls. Of them, 1796 individuals had at least 2 PD diagnoses and at least 1 filled PD-related prescription. The mean (SD) age of individuals with IBD was 51 (17) years, and 44% were men. The incidence of PD among patients with IBD was 28% higher than that among unaffected matched controls (adjusted incidence rate ratio, 1.28; 95% CI, 1.14-1.44; P < .001). A 78% reduction in the incidence rate of PD was detected among patients with IBD who were exposed to anti-TNF therapy compared with those who were not exposed (adjusted incidence rate ratio, 0.22; 95% CI, 0.05-0.88; P = .03).
Conclusions and Relevance
A higher incidence of PD was observed among patients with IBD than among individuals without IBD. Early exposure to antiinflammatory anti-TNF therapy was associated with substantially reduced PD incidence. These findings support a role of systemic inflammation in the pathogenesis of both diseases. Further studies are required to determine whether anti-TNF treatment administered to high-risk individuals may mitigate PD risk.
Thursday, 26 April 2018
Tuesday, 17 April 2018
Changing Tack
In a very wide ranging and well written review, two leaders of the
Parkinson’s field lay down set the terms of engagement and (to mix my combative
metaphors), lay down the gauntlet in the quest to find disease modifying
treatments.
After defining three kinds of ‘disease modification’ (neuroprotection:
preventing the progression of PD; neurorescue: repairing damaged brain cells;
neurorestoration: replacing what has been lost), they provide a brief but
comprehensive overview of why every attempt so far has failed, from both a
mechanistic perspective as well as a methodological perspective.
The key messages to take from this article are thus:
1.
We really need to stop thinking of Parkinson’s
as a single condition. As well as many different ways that people experience
their Parkinson’s (the different phenotypes), there are also many different
molecular and cellular processes. Each person will likely have a different
milieu of process that results in their particular phenotype.
2.
Once we can do this, we can start
approaching disease modification in a more personalised way. This means
recruiting the people with the right kind of Parkinson’s, at the right time, to
the right study. We need to become much more sophisticated in the way we study
new treatments, probably recruiting very specific groups of participants, for
example people with particular genetic changes related to their Parkinson’s, and
testing cocktails of treatments, rather than our current blunderbuss approach.
3.
Given that Parkinson’s is a complex, and
slowly progressive condition, we must have better progression markers on which
to design our studies.
This is going to require a lot of work, with the Parkinson’s
population, scientists, clinicians, and industry. In order to get the highly
effective treatments that our oncologists have avaiable to them, we need to
change the terms of warfare.
What can we all do in the mean time? Pay attention to these three
battles. Not necessarily throw the baby out with the bathwater if a particular
study doesn’t prove miraculous (which it almost certainly won’t). And if you
have Parkinson’s: exercise more!
At PREDICT-PD towers, we strongly believe that identifying the disease
earlier, in the prodromal phase, will bring us closer to many of these objectives.
Earlier disease is more likely to be simpler disease; it may be possible to identify
early phenotypes that map onto particular pathological pathways; we have an
opportunity to identify biomarkers that predict the development of established
Parkinson’s, thus giving an ideal method of proving efficacy of new treatments.
RNR
Disease modification in Parkinson's Disease: Current
approaches, challenges, and future considerations.
Anthony E Lang and Alberto J Espay.
Mov Disord, 2018 vol. 386 p. 896.
http://doi.wiley.com/10.1002/mds.27360
The greatest unmet therapeutic need in Parkinson's disease
is the development of treatment that slows the relentless progression of the
neurodegenerative process. The concept of "disease modification"
encompasses intervention types ranging from those designed to slow the
underlying degeneration to treatments directed at regenerating or replacing
lost neurons. To date all attempts to develop effective disease-modifying
therapy have failed. Many reasons have been proposed for these failures
including our rudimentary understanding of disease pathogenesis and the
assumption that each targeted mechanisms of disease apply to most patients with
the same clinical diagnosis. Here we review all aspects of this broad field
including general concepts and past challenges followed by a discussion of
treatment approaches under the following 4 categories: (1) α-synuclein, (2)
pathogenic mechanisms distinct from α-synuclein (most also potentially
triggered by α-synuclein toxicity), (3) non-SNCA genetic subtypes of "PD,"
and (4) possible disease-modifying interventions not directly influencing the
underlying PD pathobiology. We emphasize treatments that are currently under
active clinical development and highlight a wide range of important outstanding
questions and concerns that will need to be considered to advance the field of
disease modification in PD. Critically, it is unknown whether the dysfunctional
molecular pathways/organelles amenable to modification occur in a sequential
fashion across most clinically affected individuals or manifest differentially
in independent molecular subtypes of PD. It is possible that there is no
"order of disruption" applicable to most patients but, rather,
"type of disruption" applicable to subtypes dependent on unknown factors,
including genetic variability and other causes for heterogeneity in PD. Knowing
when (early vs late), which (eg, synaptic transmission, endosomal sorting and
maturation, lysosomal degradation, mitochondrial biogenesis), and in whom (PD
subtype) specific disrupted cell pathways are truly pathogenic versus
compensatory or even protective, will be important in considering the use of
single or combined ("cocktails") putative disease-modifying therapies
to selectively target these processes. Beyond the current phase 2 or 3 studies
underway evaluating treatments directed at oxidative stress (inosine),
cytosolic Ca2+ (isradipine), iron (deferiprone), and extracellular α-synuclein
(passive immunization), and upcoming trials of interventions affecting c-Abl,
glucagon-like peptide-1, and glucocerebrosidase, it might be argued that
further trials in populations not enriched for the targeted pathogenic process
are doomed to repeat the failures of the past. © 2018 International Parkinson
and Movement Disorder Society.
Friday, 6 April 2018
Costing the earth
We know that Parkinson’s exacts
a heavy price. The individual has a raft of motor and non-motor symptoms that
significantly reduce their quality of life. Their loved ones share that burden,
and research has shown that their quality of life of suffers greatly, too.
To use they hackneyed
phrase, “in these times of austerity”, it is vital to legitamise and acount for
every penny spent. In order to pursuade people (more explicitly, funders) of
the need to provide a service, talking about loss of quality of life is not
enough. It all comes down to the ‘bottom line’.
We heartily welcome the
comprehensive and up to date analysis of the cost of Parkinson’s in the UK. The
authors (including Professor Anette Schrag, one of the leading investigators of
the PREDICT-PD study) report the results of a review of UK national GP and
health records from 1993 – 2013. They compared the health service use of
everyone 30 years or older who were given a new diagnosis of Parkinson’s during
this 20-year period, with people of the same age, gender and location (attend
the same GP surgery).
Their results are both
astounding and unsuprising. GP and hospital care costs £5000 per year on
average for people with Parkinson’s, compared to only £2000 per year for the
controls. Furthermore, as the condition became more advanced, so did the costs
associated with it. These costs were due to GP visits, outpatient hospital
visits, inpatient care, A&E attendances and medications.
What this study brings is
an up to date assessment of the cost of Parkinson’s. When considering the
number of people with the condition is likely to increase, this represents an
invaluable method of identifying how crucial it is to provide better, more
efficient services to the Parkinson’s community. It also underscores just how
important it is to be able to provide a disease modifying treatment, that will
reduce the rate of progression to the more advance, more expensive stages of
the disease.
What this study was unable
to account for is the non-NHS based costs. These have recently been estimated
at around £16,500 per person per year: through lost earnings, time off work,
and other out-of-pocket expenses (see figure – from Parkinson’s
UK). Including all of these brings the average cost of PD for British
society to about £25,000 per person per year!
| Financial cost of living with Parkinson's including out of pocket expenses |
RNR
https://onlinelibrary.wiley.com/doi/pdf/10.1002/mds.
Short- and long-term cost and utilization of health
care resources in Parkinson's disease in the UK.
Mov Disord. 2018 Mar 30;12(12):956.
BACKGROUND:There
is currently no robust long-term data on costs of treating patients with
Parkinson's disease. The objective of this study was to report levels of health
care utilization and associated costs in the 10 years after diagnosis among PD
patients in the United Kingdom.
METHODS:We
undertook a retrospective population-based cohort study using linked data from
the UK Clinical Practice Research Datalink and Hospital Episode Statistics
databases. Total health care costs of PD patients were compared with those of a
control group of patients without PD selected using 1:1 propensity score
matching based on age, sex, and comorbidity.
RESULTS:Between
1994 and 2013, 7271 PD patients who met study inclusion criteria were
identified in linked Clinical Practice Research Datalink-Hospital Episode
Statistics; 7060 were matched with controls. The mean annual health care cost
difference (at 2013 costs) between PD patients and controls was £2471 (US$3716)
per patient in the first year postdiagnosis (P < 0.001), increasing to £4004
(US$6021) per patient (P < 0.001) 10 years following diagnosis because of
higher levels of use across all categories of health care utilization. Costs in
patients with markers of advanced PD (ie, presence of levodopa-equivalent daily
dose > 1100 mg, dyskinesias, falls, dementia, psychosis, hospital admission
primarily due to PD, or nursing home placement) were on average higher by £1069
(US$1608) per patient than those with PD without these markers.
CONCLUSIONS:This
study provides comprehensive estimates of health care costs in PD patients
based on routinely collected data. Health care costs attributable to PD
increase in the year following diagnosis and are higher for patients with
indicators of advanced disease. © 2018 International Parkinson and Movement
Disorder Society.
Wednesday, 4 April 2018
Application of the Movement Disorder Society prodromal criteria in healthy G2019S-LRRK2 carriers
This is an interesting application of the MDS Task Force criteria for prodromal PD. Here the Ashkenazi Jewish consortium applied the MDS criteria to non-manifesting carriers and non-carriers of the G2019S-LRRK2 mutation.
Despite relatively small numbers of participants being diagnosed with PD during the follow-up period, they report impressive specificity of the criteria for idenitfying those in the pre-diagnostic (prodromal) phase of PD. 8 of the 10 patients (80%) that were diagnosed during follow-up were in the highest probability group at baseline. Unfortunately I could not find the raw data in the manuscript to determine how they arrived at 91.8 % specificity but working backwards from the reported specificity and positive predictive value I think there must have 9 out of 110 (8.2%) who were in the high probability group at baseline, but did not subsequently get diagnosed with PD during follow-up. It will be interesting to see what happens to those participants with more time.
The positive predictive value (PPV) tells us about the probability of getting a diagnosis of PD over time if you are in the highest risk group at baseline. Based on the follow-up so far, 47% of people that screened positive at baseline have been diagnosed with PD. Whilst that's approximately 50:50 - if you imagine a scenario where a preventive treatment were available and the toxicity or side effects of that treatment were low then perhaps 50% PPV for a screening test is not widely inappropriate. Of course these data only apply to carriers of the G2019S LRRK2 mutation which in itself puts people at significantly higher risk of PD. The MDS Task Force criteria have been applied to other at risk cohorts, but we are in the final stages of applying them to the PREDICT-PD population-based cohort... watch this space.
- Alastair Noyce
Mov Disord. 2018 Mar 30. doi: 10.1002/mds.27342. [Epub ahead of print]
Mirelman A, Saunders-Pullman R, Alcalay RN, Shustak S, Thaler A, Gurevich T, Raymond D, Mejia-Santana H, Orbe Reilly M, Ozelius L, Clark L, Gana-Weisz M, Bar-Shira A, Orr-Utreger A, Bressman SB, Marder K, Giladi N; AJ LRRK2 Consortium.
https://onlinelibrary.wiley.com/doi/full/10.1002/mds.27342
BACKGROUND: In 2015, the International Parkinson and Movement Disorder Society Task Force recommended research criteria for the estimation of prodromal PD.
OBJECTIVES: We aimed to evaluate, for the first time, the criteria in first-degree relatives of Ashkenazi Jewish G2019S-LRRK2 PD patients, who are considered a population at risk for developing PD, and assess the sensitivity and specificity of the criteria in identifying phenoconverters.
METHODS: Participants were evaluated longitudinally over a period of 5 years (average follow-up: 49.2 ± 12.3 months). Likelihood ratios and probability estimations were calculated based on the International Parkinson and Movement Disorder Society Research Criteria for Prodromal Parkinson's Disease markers and examined for each assessment point.
RESULTS: One hundred twenty healthy carriers (49.53 ± 13.4 years; 54% female) and 111 healthy noncarriers (48.43 ± 15.79 years; 49% female) participated in this study. Probability scores were significantly higher in healthy carriers than healthy noncarriers (P < 0.0001). Of the 20 participants (8.6%) who met criteria for probable prodromal PD at baseline, 17 were healthy carriers. Participants who reached the threshold were older (P < 0.0001), had higher UPDRS-III (P < 0.001), lower cognitive function (P = 0.001), and more nonmotor symptoms (P < 0.0001), compared to those who did not. Ten participants were diagnosed with incident PD within 5 years from baseline resulting in a specificity of 91.82% (95% confidence interval: 86.69-96.94), sensitivity of 80% (95% confidence interval: 55.21-100), positive predictive value of 47.06% (95% confidence interval: 23.33-70.79), and negative predictive value of 98.06% (95% confidence interval: 95.39-100). All 10 phenoconvertors were G2019S-LRRK2 carriers.
CONCLUSIONS: The results showed the utility of using the criteria and high sensitivity and specificity in identifying prodromal PD in this high-risk unique cohort. These results may be valuable for future disease modification clinical trials. © 2018 International Parkinson and Movement Disorder Society.
© 2018 International Parkinson and Movement Disorder Society.
Despite relatively small numbers of participants being diagnosed with PD during the follow-up period, they report impressive specificity of the criteria for idenitfying those in the pre-diagnostic (prodromal) phase of PD. 8 of the 10 patients (80%) that were diagnosed during follow-up were in the highest probability group at baseline. Unfortunately I could not find the raw data in the manuscript to determine how they arrived at 91.8 % specificity but working backwards from the reported specificity and positive predictive value I think there must have 9 out of 110 (8.2%) who were in the high probability group at baseline, but did not subsequently get diagnosed with PD during follow-up. It will be interesting to see what happens to those participants with more time.
The positive predictive value (PPV) tells us about the probability of getting a diagnosis of PD over time if you are in the highest risk group at baseline. Based on the follow-up so far, 47% of people that screened positive at baseline have been diagnosed with PD. Whilst that's approximately 50:50 - if you imagine a scenario where a preventive treatment were available and the toxicity or side effects of that treatment were low then perhaps 50% PPV for a screening test is not widely inappropriate. Of course these data only apply to carriers of the G2019S LRRK2 mutation which in itself puts people at significantly higher risk of PD. The MDS Task Force criteria have been applied to other at risk cohorts, but we are in the final stages of applying them to the PREDICT-PD population-based cohort... watch this space.
- Alastair Noyce
Mov Disord. 2018 Mar 30. doi: 10.1002/mds.27342. [Epub ahead of print]
Mirelman A, Saunders-Pullman R, Alcalay RN, Shustak S, Thaler A, Gurevich T, Raymond D, Mejia-Santana H, Orbe Reilly M, Ozelius L, Clark L, Gana-Weisz M, Bar-Shira A, Orr-Utreger A, Bressman SB, Marder K, Giladi N; AJ LRRK2 Consortium.
https://onlinelibrary.wiley.com/doi/full/10.1002/mds.27342
BACKGROUND: In 2015, the International Parkinson and Movement Disorder Society Task Force recommended research criteria for the estimation of prodromal PD.
OBJECTIVES: We aimed to evaluate, for the first time, the criteria in first-degree relatives of Ashkenazi Jewish G2019S-LRRK2 PD patients, who are considered a population at risk for developing PD, and assess the sensitivity and specificity of the criteria in identifying phenoconverters.
METHODS: Participants were evaluated longitudinally over a period of 5 years (average follow-up: 49.2 ± 12.3 months). Likelihood ratios and probability estimations were calculated based on the International Parkinson and Movement Disorder Society Research Criteria for Prodromal Parkinson's Disease markers and examined for each assessment point.
RESULTS: One hundred twenty healthy carriers (49.53 ± 13.4 years; 54% female) and 111 healthy noncarriers (48.43 ± 15.79 years; 49% female) participated in this study. Probability scores were significantly higher in healthy carriers than healthy noncarriers (P < 0.0001). Of the 20 participants (8.6%) who met criteria for probable prodromal PD at baseline, 17 were healthy carriers. Participants who reached the threshold were older (P < 0.0001), had higher UPDRS-III (P < 0.001), lower cognitive function (P = 0.001), and more nonmotor symptoms (P < 0.0001), compared to those who did not. Ten participants were diagnosed with incident PD within 5 years from baseline resulting in a specificity of 91.82% (95% confidence interval: 86.69-96.94), sensitivity of 80% (95% confidence interval: 55.21-100), positive predictive value of 47.06% (95% confidence interval: 23.33-70.79), and negative predictive value of 98.06% (95% confidence interval: 95.39-100). All 10 phenoconvertors were G2019S-LRRK2 carriers.
CONCLUSIONS: The results showed the utility of using the criteria and high sensitivity and specificity in identifying prodromal PD in this high-risk unique cohort. These results may be valuable for future disease modification clinical trials. © 2018 International Parkinson and Movement Disorder Society.
© 2018 International Parkinson and Movement Disorder Society.
Sunday, 1 April 2018
Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score
Smart phone technology and app-based approaches for measuring PD symptoms and signs have been around for some time and there are seemingly innumerable companies and groups that all suggest that their approach is the best...
The results of this recent study published in JAMA Neurology do however look really impressive. I have always felt that given the heterogeneity of PD (motor and non-motor), a good measuring device will take account of multiple domains. This app measures voice, gait, balance, reaction time and finger tapping (which you might argue are exclusively motor)... but the results suggest that it does measure these really well.
The hardest thing is to develop a tool that captures fluctuation well and objectively. Some purpose-built devices do (the PKG for example), but it is impressive to see these kind of results through utilisation of the standard hardware that comes with a smart phone. Furthermore the objective response to dopaminergic therapy is substantial and apparently clinically meaningful.
Will we see this app used in clinical trials in the coming years... I expect we might!
- Alastair Noyce
JAMA Neurol. 2018 Mar 26. doi: 10.1001/jamaneurol.2018.0809. [Epub ahead of print]
Zhan A, Mohan S, Tarolli C, Schneider RB, Adams JL, Sharma S, Elson MJ, Spear KL, Glidden AM, Little MA, Terzis A, Dorsey ER, Saria S.
https://jamanetwork.com/journals/jamaneurology/fullarticle/2676504
IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.
OBJECTIVES: To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy.
DESIGN, SETTING, AND PARTICIPANTS: This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months.
MAIN OUTCOMES AND MEASURES: Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication.
RESULTS: The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy.
CONCLUSIONS AND RELEVANCE: Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics.
The results of this recent study published in JAMA Neurology do however look really impressive. I have always felt that given the heterogeneity of PD (motor and non-motor), a good measuring device will take account of multiple domains. This app measures voice, gait, balance, reaction time and finger tapping (which you might argue are exclusively motor)... but the results suggest that it does measure these really well.
The hardest thing is to develop a tool that captures fluctuation well and objectively. Some purpose-built devices do (the PKG for example), but it is impressive to see these kind of results through utilisation of the standard hardware that comes with a smart phone. Furthermore the objective response to dopaminergic therapy is substantial and apparently clinically meaningful.
Will we see this app used in clinical trials in the coming years... I expect we might!
- Alastair Noyce
JAMA Neurol. 2018 Mar 26. doi: 10.1001/jamaneurol.2018.0809. [Epub ahead of print]
Zhan A, Mohan S, Tarolli C, Schneider RB, Adams JL, Sharma S, Elson MJ, Spear KL, Glidden AM, Little MA, Terzis A, Dorsey ER, Saria S.
https://jamanetwork.com/journals/jamaneurology/fullarticle/2676504
IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings.
OBJECTIVES: To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy.
DESIGN, SETTING, AND PARTICIPANTS: This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months.
MAIN OUTCOMES AND MEASURES: Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication.
RESULTS: The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy.
CONCLUSIONS AND RELEVANCE: Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics.
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