The frequency and validity of self-reported diagnosis of Parkinson's Disease in the UK elderly: MRC CFAS cohort

BACKGROUND: Estimates of the incidence and prevalence of chronic diseases can be made using established cohort studies but these estimates may have lower reliability if based purely on self-reported diagnosis. METHODS: The MRC Cognitive Function & Ageing Study (MRC CFAS) has collected longitudinal data from a population-based random sample of 13004 individuals over the age of 65 years from 5 centres within the UK. Participants were asked at baseline and after a two-year follow-up whether they had received a diagnosis of Parkinson's disease. Our aim was to make estimates of the incidence and prevalence of PD using self-reporting, and then investigate the validity of self-reported diagnosis using other data sources where available, namely death certification and neuropathological examination. RESULTS: The self-reported prevalence of Parkinson's disease (PD) amongst these individuals increases with age from 0.7% (95%CI 0.5–0.9) for 65–75, 1.4% (95%CI 1.0–1.7) for 75–85, and 1.6% (95%CI 1.0–2.3) for 85+ age groups respectively. The overall incidence of self reported PD in this cohort was 200/100,000 per year (95%CI 144–278). Only 40% of the deceased individuals reporting prevalent PD and 35% of those reporting incident PD had diagnoses of PD recorded on their death certificates. Neuropathological examination of individuals reporting PD also showed typical PD changes in only 40%, with the remainder showing basal ganglia pathologies causing parkinsonism rather than true PD pathology. CONCLUSION: Self-reporting of PD status may be used as a screening tool to identify patients for epidemiological study, but inevitably identifies a heterogeneous group of movement disorders patients. Within this group, age, male sex, a family history of PD and reduced cigarette smoking appear to act as independent risk factors for self-reported PD

Inventory of real world data sources in Parkinson’s disease

Abstract Background Real world data have an important role to play in the evaluation of epidemiology and burden of disease; and in assisting health-care decision-makers, especially related to coverage and payment decisions. However, there is currently no overview of the existing longitudinal real world data sources in Parkinson’s disease (PD) in the USA. Such an assessment can be very helpful, to support a future effort to harmonize real world data collection and use the available resources in an optimal way. Methods The objective of this comprehensive literature review is to systematically identify and describe the longitudinal, real world data sources in PD in the USA, and to provide a summary of their measurements (categorized into 8 main dimensions: motor and neurological functions, cognition, psychiatry, activities of daily living, sleep, quality of life, autonomic symptoms and other). The literature search was performed using MEDLINE, EMBASE and internet key word search. Results Of the 53 data sources identified between May and August 2016, 16 were still ongoing. Current medications (81%) and comorbidities (79%) were frequently collected, in comparison to medical imaging (36%), genetic information (30%), caregiver burden (11%) and healthcare costs (2%). Many different measurements (n = 108) were performed and an interesting variability among used measurements was revealed. Conclusions Many longitudinal real world data sources on PD exist. Different types of measurements have been performed over time. To allow comparison and pooling of these multiple data sources, it will be essential to harmonize practices in terms of types of measurements

Self-reported parkinsonian symptoms in the EPIC-Norfolk cohort

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Parkinsonian symptoms have been associated with increased morbidity and mortality. Several studies have reported on the prevalence of signs and symptoms. Symptoms questionnaires can identify potential PD cases for further neurological examination to save resources. They can also provide information about how much of the population reports specific signs and symptoms. The objective of the study was to determine the self-reported prevalence of parkinsonian symptoms from a questionnaire, and to examine their association with age and self-reported Parkinson's disease in a large cohort. Methods A cross-sectional study was conducted within a sub-cohort of the EPIC-Norfolk (European Prospective Investigation of Cancer) cohort study. Results The prevalence of six self-reported parkinsonian symptoms are reported for 11539 individuals who answered all symptoms questions (62% of sub-cohort): rest tremor (4%), difficulty starting to walk (4%), difficulty getting out of a chair (6%), slower walking (34%), smaller handwriting (micrographia- 9%), and less acute sense of smell (olfactory dysfunction- 9%). The presence of individual symptoms increased with age except for difficulty getting out of a chair. Conclusion The results support previous findings that the presence of self-reported parkinsonian symptoms is strongly associated with age and self-reported PD diagnosis. The data also provide information regarding the prevalence of symptoms in a large, younger population of adults than previously reported in the literature

Parkinson's Disease Case Ascertainment in the EPIC Cohort : The NeuroEPIC4PD Study

BACKGROUND/AIMS: Large epidemiological prospective studies represent an important opportunity for investigating risk factors for rare diseases such as Parkinson's disease (PD). Here we describe the procedures we used for ascertaining PD cases in the EPIC (European Prospective Investigation into Cancer and Nutrition) study. METHODS: The following three-phase procedure was used: (1) elaboration of a NeuroEPIC4PD template for clinical data collection, (2) identification of all potential PD cases via record linkage and (3) validation of the diagnosis through clinical record revision, in a population of 220,494 subjects recruited in 7 European countries. All cases were labelled with the NeuroEPIC4PD diagnoses of 'definite', 'very likely', 'probable', or 'possible' PD. RESULTS: A total of 881 PD cases were identified, with over 2,741,780 person-years of follow-up (199 definite, 275 very likely, 146 probable, and 261 possible). Of these, 734 were incident cases. The mean age at diagnosis was 67.9 years (SD 9.2) and 458 patients (52.0%) were men. Bradykinesia was the most frequent presenting motor sign (76.5%). Tremor-dominant and akinetic rigid forms of PD were the most common types of PD. A total of 289 patients (32.8%) were dead at the time of the last follow-up. CONCLUSIONS: This exercise proved that it is feasible to ascertain PD in large population-based cohort studies and offers a potential framework to be replicated in similar studies