ArticleBMJ open2019
Ethical and social implications of using predictive modeling for Alzheimer's disease prevention: a systematic literature review protocol.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- "I Want to Know Everything ... ": The Return of Research Results and the Importance of Transparency in the Acceptability of Lumbar Punctures for African American Older Adults.Journal of Alzheimer's disease : JAD · 2023Article
- Dementia Risk Score for a Population in Southern Europe Calculated Using Competing Risk Models.Journal of Alzheimer's disease : JAD · 2022Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe therapeutic paradigm in Alzheimer's disease (AD) has shifted towards secondary prevention, defined as an intervention aiming to prevent or delay disease onset in pre-symptomatic individuals at risk of developing dementia due to AD. The key feature of AD prevention is the need to treat years or even decades before the onset of cognitive, behavioural or functional decline. Prediction of AD risk and evaluation of long-term treatment outcomes in this setting requires predictive modelling and is associated with ethical concerns and social implications. The objective of this review is to identify and elucidate them, as presented in the literature. METHODS AND ANALYSIS: A systematic literature review was conducted in Medline, Embase, PsycInfo and Scopus, and was complemented with a grey literature search. All searches were conducted between March and July 2018. Two reviewers independently assessed each study for inclusion and disagreements were adjudicated by a third reviewer. Data are now being extracted using an extraction sheet developed within the group of reviewers, based on an initial sample of three manuscripts, but allowing for inclusion of newly identified data items (ethical arguments). Data will be analysed qualitatively using a thematic analysis technique. Potential biases in selection and interpretation of extracted data are mitigated by the fact that reviewers come from a range of different scientific backgrounds and represent different types of stakeholders in this ethical discussion (academia, industry, patient advocacy groups). ETHICS AND DISSEMINATION: The study does not require ethical approval. The findings of the review will be disseminated in a peer-reviewed journal and presented at conferences. They will also be reported through the Innovative Medicine Initiative project: Real World Outcomes Across the AD Spectrum for Better Care: Multi-modal Data Access Platform (IMI: ROADMAP). TRIAL REGISTRATION NUMBER: CRD42018092205.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.