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Development and internal validation of a prognostic model for 15-year risk of Alzheimer dementia in primary care patients

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Abstract

Background

The exploitation of routinely collected clinical health information is warranted to optimize the case detection and diagnostic workout of Alzheimer’s disease (AD). We aimed to derive an AD prediction score based on routinely collected primary care data.

Methods

We built a cohort selecting 199,978 primary care patients 60 + part of the Health Search Database between January 2002 and 2009, followed up until 2019 to detect incident AD cases. The cohort was randomly divided into a derivation and validation sub-cohort. To identify AD and non-AD cases, we applied a clinical algorithm that involved two clinicians. According to a nested case–control design, AD cases were matched with up to 10 controls based on age, sex, calendar period, and follow-up duration. Using the derivation sub-cohort, 32 potential AD predictors (sociodemographic, clinical, drug-related, etc.) were tested in a logistic regression and selected to build a prediction model. The predictive performance of this model was tested on the validation sub-cohort by mean of explained variation, calibration, and discrimination measurements.

Results

We identified 3223 AD cases. The presence of memory disorders, hallucinations, anxiety, and depression and the use of NSAIDs were associated with future AD. The combination of the predictors allowed the production of a predictive score that showed an explained variation (pseudo-R2) for AD occurrence of 13.4%, good calibration parameters, and an area under the curve of 0.73 (95% CI: 0.71–0.75). In accordance with this model, 7% of patients presented with a high-risk score for develo** AD over 15 years.

Conclusion

An automated risk score for AD based on routinely collected clinical data is a promising tool for the early case detection and timely management of patients by the general practitioners.

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Funding

The study was sponsored by Roche S.p.A.. The corresponding author had full access to all the data in the study and has final responsibility for the decision to submit it for publication.

Author information

Authors and Affiliations

  1. Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden

    Giulia Grande & Davide L. Vetrano

  2. Health Search, Italian College of General Practitioners and Primary Care, Via del Sansovino 179, 50141, Florence, Italy

    Ettore Marconi, Elisa Bianchini, Iacopo Cricelli & Francesco Lapi

  3. Roche S.P.A, Monza, Italy

    Valeria Lovato & Luisa Guglielmini

  4. Italian College of General Practitioners and Primary Care, Florence, Italy

    Daiana Taddeo & Claudio Cricelli

  5. ICoN Center, University Institute for Advanced Studies IUSS Pavia, Pavia, Italy

    Stefano F. Cappa

  6. IRCCS Mondino Foundation, Pavia, Italy

    Stefano F. Cappa

Authors
  1. Giulia Grande
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  2. Davide L. Vetrano
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  3. Ettore Marconi
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  4. Elisa Bianchini
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  6. Valeria Lovato
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  7. Luisa Guglielmini
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  8. Daiana Taddeo
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  9. Stefano F. Cappa
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  10. Claudio Cricelli
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  11. Francesco Lapi
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Contributions

FL contributed to the conception and design of the study and conducted the statistical analyses. All the authors contributed to the interpretation of the results. GG and DLV drafted the first version of the manuscript. All the authors critically revised the manuscript for important intellectual content. All the authors made a significant contribution to the research and the development of the manuscript and approved the final version for publication.

Corresponding author

Correspondence to Francesco Lapi.

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Ethical approval

According to a by-law on the classification and implementation of observational drug-related research, as issued by the Italian Medicines Agency, the present study does not require approval by an ethics committee.

Conflict of interest

FL, EM, EB and IC provided consultancies in protocol preparation for epidemiological studies and data analyses for Roche and Abbvie; DT and CC provided clinical consultancies for Roche, Abbvie and Viatris; VL and LG are employees of Roche S.p.A., Monza, Italy; the other co-authors have no conflict of interest to diclose.

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Grande, G., Vetrano, D.L., Marconi, E. et al. Development and internal validation of a prognostic model for 15-year risk of Alzheimer dementia in primary care patients. Neurol Sci 43, 5899–5908 (2022). https://doi.org/10.1007/s10072-022-06258-7

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