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THUR 121 Identifying participants with parkinson’s disease in uk biobank
  1. Bush Kathryn,
  2. Rannikmae Kristiina,
  3. Schnier Christian,
  4. Wilkinson Timothy,
  5. Nolan John,
  6. Bennett Michael,
  7. Cheng Jingjie,
  8. Sudlow Cathie,
  9. et al
  1. Edinburgh University


Background Linkage to routinely collected NHS data from primary, secondary care and death certificates enables identification of participants with Parkinson’s Disease (PD) within the UK Biobank cohort of 5 00 000 adults. Validation of the accuracy of this data is required prior to their use in research studies.

Method In this validation study participants (n=125) with a code indicating PD were identified from a sample of 17 000 participants in the cohort. Diagnoses were validated by expert adjudicators, based on free text electronic medical records. Positive predictive values (PPV,% of cases identified that are true cases) were calculated.

Results Primary care diagnostic codes identified 93% of PD cases, with a PPV of 95%. Combined secondary care and death data identified 42% of PD cases with a PPV of 84%.

Combining diagnostic and medication codes identified more participants, but did not increase the PPV.

Conclusions This study suggests that linkage to routinely collected healthcare data is a reliable method for identifying participants with PD in the UK Biobank cohort.

Primary care diagnostic codes identified the highest proportion of participants and had the highest PPV, demonstrating the value of using primary care data to identify cases of disease in large population based cohort studies.

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