Evidence map›Paper›PMID 32988850›Full record

ArticleBMJ open diabetes research & care2020

Improving the American Diabetes Association Framework for individualizing treatment in older adults: evaluating life expectancy.

Alexandra K Lee, Michael A Steinman, Sei J Lee

Open access · goldAbstract read
In one paragraph

Article in BMJ open diabetes research & care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Alexandra K LeeDivision of Geriatrics, University of California San Francisco, San Francisco, California, USA alexandra.lee@ucsf.edu.ORCID 0000-0001-9525-3833
Michael A SteinmanDivision of Geriatrics, University of California San Francisco, San Francisco, California, USA.
Sei J LeeDivision of Geriatrics, University of California San Francisco, San Francisco, California, USA.
University of California, San Francisco · US

Funding

VARC CoreP30AG044281 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Alexander Keliimoeanu Smith · 2013 to 2026
$19.9M
Unnecessary and Harmful Medication Use in Older Adults with DementiaP01AG066605 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MELISSA Diane ALDRIDGE · 2020 to 2026
$17.7M
U.S. Deprescribing Research NetworkR24AG064025 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI BOYD, CYNTHIA MELINDA, STEINMAN, MICHAEL A. · 2019 to 2023
$9.9M
RESEARCH TRAINING IN GERIATRIC MEDICINET32AG000212 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Alexander Keliimoeanu Smith · 1991 to 2026
$7.7M
Prescribing cascades in older adults with and without dementiaK24AG049057 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEINMAN, MICHAEL A. · 2015 to 2025
$1.8M
Developing prognostic models for life expectancy and geriatric outcomesR01AG047897 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI LEE, SEI, SMITH, ALEXANDER KELIIMOEANU · 2015 to 2018
$1.7M
Prognostic calculators for patients with Alzheimers disease and related dementiasR01AG057751 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI LEE, SEI, SMITH, ALEXANDER KELIIMOEANU · 2018 to 2021
$1.5M
HSRD VA I01 HX002135NIA NIH HHS K24 AG049057NIA NIH HHS P01 AG066605NIA NIH HHS P30 AG044281NIA NIH HHS R01 AG047897NIA NIH HHS R01 AG057751NIA NIH HHS R24 AG064025NIA NIH HHS T32 AG000212
6 · The paper itself

Abstract

introductionFor older adults with type 2 diabetes, the American Diabetes Association (ADA) Framework uses comorbidities and functional status to categorize patients by estimated life expectancy to guide individualization of glycemic treatment. We evaluated whether modifying the ADA Framework by removing three comorbidities and incorporating age could improve life expectancy stratification and better identify patients likely to benefit from intensive treatment. RESEARCH DESIGN AND

methodsWe examined 3166 Health and Retirement Study participants aged ≥65 with diabetes from 1998 to 2004, using a prospective cohort design with mortality follow-up through 2016. We classified participants into one of three ADA Framework categories: Healthy, Intermediate Health, and Poor Health. We created modified categories by excluding comorbidities weakly associated with mortality (hypertension, arthritis, and incontinence). Using Gompertz regression, we estimated life expectancy across age strata for both original and modified ADA Framework categories.

resultsThe original ADA Framework classified 34% as Healthy (likely to benefit from intensive treatment), 50% as Intermediate Health, and 16% as Poor Health (unlikely to benefit from intensive treatment). Our comorbidity modification reclassified 20% of participants from Intermediate Health to Healthy. Using the modified ADA Framework, median life expectancy of the Healthy varied greatly by age (aged 65-69: 16.3 years; aged ≥80: 7.6 years), indicating differing likelihood of benefit. Additionally, age ≥80 made extended life expectancy unlikely (median life expectancy for Healthy 7.6 years, Intermediate Health 5.9 years, Poor Health 2.5 years), suggesting adults ≥80 are unlikely to benefit from intensive treatment.

conclusionsModifying the ADA Framework by incorporating age and focusing on comorbidities associated with mortality improved life expectancy stratification, resulting in different treatment recommendations for many older adults.

Indexed as

Diabetes Mellitus, Type 2Life ExpectancyAdolescentAgedBlood GlucoseChildComorbidityHumansProspective StudiesUnited StatesBlood Glucoseageingdiabetes mellitusepidemiologylife expectancytype 2

Identifiers

PMID32988850
PMCPMC7523213
OpenAlexW3090037986

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.