Evidence map›Paper›PMID 28931428›Full record

ArticleAlzheimer's research & therapy2017

Personalized predictive modeling for patients with Alzheimer's disease using an extension of Sullivan's life table model.

Eric Stallard, Bruce Kinosian, Yaakov Stern

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's research & therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 32% of its field
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

8 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
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  7. Validation and demonstration of a new comprehensive model of Alzheimer's disease progression.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2021
    Article
  8. Review
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

3 authors at 3 institutions in 1 country.

Eric StallardBiodemography of Aging Research Unit, Social Science Research Institute, Duke University, 2024 West Main Street, Room A102H, Durham, NC, 27708-0408, USA.
Bruce KinosianGeriatrics and Extended Care Data Analysis Center, Philadelphia VA Medical Center, 3900 Woodland Avenue, Philadelphia, PA, 19104, USA.
Yaakov SternCognitive Neuroscience Division, Department of Neurology, Columbia University College of Physicians and Surgeons, 630 West 168th Street, P&S Box 16, New York, NY, 10032-3702, USA. ys11@columbia.edu.ORCID http://orcid.org/0000-0001-7542-3241
Columbia University · USPhiladelphia VA Medical Center · USSocial Science Research Council · US

Funding

PREDICTORS OF SEVERITY IN ALZHEIMERS DISEASER01AG007370 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI STERN, YAAKOV · 1989 to 2021
$16.6M
STALLARD Admin Supp: Predicting Future Care Needs and Costs for Individual Medicare Enrollees with Incident Suspected Alzheimer's DiseaseP30AG034424 · NIA · DUKE UNIVERSITY · PI SCOTT M. LYNCH · 2009 to 2026
$12.2M
NIA NIH HHS P30 AG034424NIA NIH HHS R01 AG007370
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) progression varies substantially among patients, hindering calculation of residual total life expectancy (TLE) and its decomposition into disability-free life expectancy (DFLE) and disabled life expectancy (DLE) for individual patients with AD. The objective of the present study was to assess the accuracy of a new synthesis of Sullivan's life table (SLT) and longitudinal Grade of Membership (L-GoM) models that estimates individualized TLEs, DFLEs, and DLEs for patients with AD. If sufficiently accurate, such information could enhance the quality of important decisions in AD treatment and patient care.

methodsWe estimated a new SLT/L-GoM model of the natural history of AD over 10 years in the Predictors 2 Study cohort: N = 229 with 6 fixed and 73 time-varying covariates over 21 examinations covering 11 measurement domains including cognitive, functional, behavioral, psychiatric, and other symptoms/signs. Total remaining life expectancy was censored at 10 years. Disability was defined as need for full-time care (FTC), the outcome most strongly associated with AD progression. All parameters were estimated via weighted maximum likelihood using data-dependent weights designed to ensure that the estimates of the prognostic subtypes were of high quality. Goodness of fit was tested/confirmed for survival and FTC disability for five relatively homogeneous subgroups defined to cover the range of patient outcomes over the 21 examinations.

resultsThe substantial heterogeneity in initial patient presentation and AD progression was captured using three clinically meaningful prognostic subtypes and one terminal subtype exhibiting highly differentiated symptom severity on 7 of the 11 measurement domains. Comparisons of the observed and estimated survival and FTC disability probabilities demonstrated that the estimates were accurate for all five subgroups, supporting their use in AD life expectancy calculations. Mean 10-year TLE differed widely across subgroups: range 3.6-8.0 years, average 6.1 years. Mean 10-year DFLE differed relatively even more widely across subgroups: range 1.2-6.5 years, average 4.0 years. Mean 10-year DLE was relatively much closer: range 1.5-2.3 years, average 2.1 years.

conclusionsThe SLT/L-GoM model yields accurate maximum likelihood estimates of TLE, DFLE, and DLE for patients with AD; it provides a realistic, comprehensive modeling framework for endpoint and resource use/cost calculations.

Indexed as

Alzheimer DiseaseForecastingLife ExpectancyLife TablesModels, TheoreticalCohort StudiesFemaleHealth Status IndicatorsHumansMaleMental Status SchedulePopulation SurveillancePredictive Value of TestsAlzheimer’s diseaseDisability-free life expectancyDisabled life expectancyFull-time careGrade of MembershipLongitudinal data analysisMultidomain modelPrognostic subtype

Identifiers

PMID28931428
PMCPMC5607490
OpenAlexW2755089181

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.