1 / 24

Drug Efficacy in the Wild Tim Vaughan 8-Sep-2011

Drug Efficacy in the Wild Tim Vaughan 8-Sep-2011. PatientsLikeMe – Three brothers’ story . ALS − Rare neurologic disease. ALS − Time is of the essence. PatientsLikeMe web site. Stephen Heywood (alsking101). Data collection. Why is Mike taking lithium?. Lithium.

tansy
Download Presentation

Drug Efficacy in the Wild Tim Vaughan 8-Sep-2011

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Drug Efficacy in the WildTim Vaughan8-Sep-2011

  2. PatientsLikeMe– Three brothers’ story

  3. ALS − Rare neurologic disease

  4. ALS − Time is of the essence

  5. PatientsLikeMe web site

  6. Stephen Heywood (alsking101)

  7. Data collection

  8. Why is Mike taking lithium? Lithium

  9. Lithium delays progression of ALS?! Fornai et al., PNAS 105:2052-2057 (2008)

  10. The observational study germinates

  11. Timeline

  12. Patients track their progress

  13. The “kitchen sink” plot

  14. Random control may not be a “patient like me”

  15. Demographics – age

  16. Demographics – onset site

  17. Demographics – sex

  18. Matching algorithm

  19. Pre-treatment progression bias reduced

  20. Results of lithium treatment

  21. Kaplan-Meier for patients & data

  22. Biases and other stuff that worried us • Self-selection for treatment • “Recruitment bias” • Data reported (vs. data opportunity) • Outliers (e.g. PMA and PLS) • “Optimism bias” at treatment start

  23. What Mike (and PatientsLikeMe) can learn

  24. Conclusions • Savvy patients are using the internet in creative ways to understand and improve their health • Structured, self-reported patient data has profound value, despite being subject to bias (like all patient data!)

More Related