Responses

PDF
Research paper
Models for predicting risk of dementia: a systematic review
Compose Response

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Statement of Competing Interests

PLEASE NOTE:

  • Responses are moderated before posting and publication is at the absolute discretion of BMJ, however they are not peer-reviewed
  • Once published, you will not have the right to remove or edit your response. Removal or editing of responses is at BMJ's absolute discretion
  • If patients could recognise themselves, or anyone else could recognise a patient from your description, please obtain the patient's written consent to publication and send them to the editorial office before submitting your response [Patient consent forms]
  • By submitting this response you are agreeing to our full [Response terms and requirements]

Vertical Tabs

Other responses

Jump to comment:

  • Published on:
    Models for predicting risk of dementia: improvement still needed
    • Silvan Licher, PhD Student Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
    • Other Contributors:
      • Pinar Yilmaz, PhD Student
      • Maarten J.G. Leening, Post-doc Preventive Cardiology and Cardiovascular Epidemiology
      • M. Kamran Ikram, Neurologist and Associate Professor Neuro-epidemiology
      • M. Arfan Ikram, Professor and Chair Epidemiology

    Hou et al. are to be commended for an in-depth systematic review of currently available dementia risk models that quantify the probability of developing dementia, covering both studies on community-dwelling individuals as well as clinic-based MCI studies.1 One of the key conclusions was that “the predictive ability of existing dementia risk models is acceptable, but the lack of validation limited the extensive application of the models for dementia risk prediction in general population or across subgroups in the population.” Based on recent insights, we believe that the discriminative ability of existing dementia prediction models in the general population is currently not acceptable for clinical use.

    We recently validated four promising dementia risk models (CAIDE, ANU-ADRI, BDSI, and DRS).2 In addition to external validation of these models in the Dutch general population, we also sought to investigate how these models compared to predicting dementia based on the age component of these models only. We found that full models do not have better discriminative properties than age alone. As such, we would like to make three suggestions to establish a reliable dementia prediction model.

    First, prediction models typically only report model performance on the basis of a full model.1-4 For dementia risk, however, age plays a pivotal role. Therefore, any new model should compare its predictive accuracy to age alone.

    Second, the setting in which a prediction...

    Show More
    Conflict of Interest:
    None declared.