Evidence map›Paper›PMID 33517494›Full record

ArticleActa diabetologica2021

Targeting of the diabetes prevention program leads to substantial benefits when capacity is constrained.

Natalia Olchanski, David van Klaveren, Joshua T Cohen, John B Wong, Robin Ruthazer, David M Kent

Open access · greenAbstract read
In one paragraph

Article in Acta diabetologica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors at 1 institution in 1 country.

Natalia OlchanskiInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA. nolchanski@tuftsmedicalcenter.org.ORCID http://orcid.org/0000-0002-9983-8166
David van KlaverenInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA.
Joshua T CohenInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA.
John B WongInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA.
Robin RuthazerInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA.
David M KentInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, 800 Washington Street #63, Boston, MA, 02111, USA.
Tufts Medical Center · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Value of Personalized Risk InformationU01NS086294 · NINDS · TUFTS MEDICAL CENTER · PI KENT, DAVID M, NEUMANN, PETER · 2013 to 2017
$2.6M
Tufts Clinical and Translational Research InstituteTL1TR001062 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2013 to 2017
$2.1M
NCATS NIH HHS TL1 TR001062NIDDK NIH HHS P30 DK092926NIH HHS U01 NS086294NINDS NIH HHS U01 NS086294
6 · The paper itself

Abstract

objectiveApproximately 84 million people in the USA have pre-diabetes, but only a fraction of them receive proven effective therapies to prevent type 2 diabetes. We estimated the value of prioritizing individuals at highest risk of progression to diabetes for treatment, compared to non-targeted treatment of individuals meeting inclusion criteria for the Diabetes Prevention Program (DPP).

methodsUsing microsimulation to project outcomes in the DPP trial population, we compared two interventions to usual care: (1) lifestyle modification and (2) metformin administration. For each intervention, we compared targeted and non-targeted strategies, assuming either limited or unlimited program capacity. We modeled the individualized risk of developing diabetes and projected diabetic outcomes to yield lifetime costs and quality-adjusted life expectancy, from which we estimated net monetary benefits (NMB) for both lifestyle and metformin versus usual care.

resultsCompared to usual care, lifestyle modification conferred positive benefits and reduced lifetime costs for all eligible individuals. Metformin's NMB was negative for the lowest population risk quintile. By avoiding use when costs outweighed benefits, targeted administration of metformin conferred a benefit of $500 per person. If only 20% of the population could receive treatment, when prioritizing individuals based on diabetes risk, rather than treating a 20% random sample, the difference in NMB ranged from $14,000 to $20,000 per person.

conclusionsTargeting active diabetes prevention to patients at highest risk could improve health outcomes and reduce costs compared to providing the same intervention to a similar number of patients with pre-diabetes without targeted selection.

Indexed as

Patient SelectionPrimary PreventionAdultCohort StudiesCost-Benefit AnalysisDiabetes Mellitus, Type 2FemaleHealth Services AccessibilityHumansHypoglycemic AgentsLife ExpectancyLife StyleMaleMetforminMiddle AgedPrediabetic StateHypoglycemic AgentsMetforminDiabetes preventionEconomic analysisHeterogeneity of treatment effectLifestyle modificationRisk basedType 2 diabetesValue

Identifiers

PMID33517494
PMCPMC8276501
OpenAlexW3127824896

What Socratic holds

Texttitle and abstract
LicenceTDM
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 Socratic graph.