Evidence map›Paper›PMID 20433705›Full record

ArticleBMC medical informatics and decision making2010

Modeling screening, prevention, and delaying of Alzheimer's disease: an early-stage decision analytic model.

Nicolas M Furiak, Robert W Klein, Kristin Kahle-Wrobleski, Eric R Siemers, Eric Sarpong, Timothy M Klein

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia.International journal of environmental research and public health · 2020
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nicolas M FuriakMedical Decision Modeling Inc., Indianapolis, IN, USA. nf@mdm-inc.com
Robert W Klein
Kristin Kahle-Wrobleski
Eric R Siemers
Eric Sarpong
Timothy M Klein

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development.

methodsA time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age > or =55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death.

resultsThe base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90).

conclusionsThis study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.

Indexed as

Computer SimulationDecision Support TechniquesAgedAged, 80 and overAlgorithmsAlzheimer DiseaseFemaleHumansLinear ModelsMaleMass ScreeningMiddle AgedSensitivity and Specificity

Identifiers

PMID20433705
PMCPMC3152764

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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.