Evidence map›Paper›PMID 35702631›Full record

ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2021

A simple framework to identify optimal cost-effective risk thresholds for a single screen: Comparison to Decision Curve Analysis.

Hormuzd A Katki, Ionut Bebu

Abstract read
In one paragraph

Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. Evaluating Risk Prediction with Data Collection Costs: Novel Estimation of Test Tradeoff Curves.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    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

2 authors.

Hormuzd A KatkiDivision of Cancer Epidemiology and Genetics, US National Cancer Institute, NIH/DHHS, Rockville MD, USA.
Ionut BebuBiostatistics Center, George Washington University, Rockville MD, USA.

Funding

Limited Competition for the Continuation of Epidemiology of Diabetes Interventions and Complications (EDIC) Study Clinical Research Center (Collaborative U01)U01DK094157 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI Ionut Bebu, Barbara Halina Braffett · 2011 to 2026
$97.6M
Epidemiology of Diabetes Interventions and Complications Data Coordinating CenterU01DK094176 · NIDDK · GEORGE WASHINGTON UNIVERSITY · PI BEBU, IONUT, BRAFFETT, BARBARA HALINA · 2012 to 2022
$30.8M
Intramural NIH HHS Z99 CA999999NIDDK NIH HHS U01 DK094157NIDDK NIH HHS U01 DK094176
6 · The paper itself

Abstract

Decision Curve Analysis (DCA) is a popular approach for assessing biomarkers and risk models, but does not require costs and thus cannot identify optimal risk thresholds for actions. Full decision analyses can identify optimal thresholds, but typically used methods are complex and often difficult to understand. We develop a simple framework to calculate the Incremental Net Benefit for a single-time screen as a function of costs (for tests and treatments) and effectiveness (life-years gained). We provide simple expressions for the optimal cost-effective risk-threshold and, equally importantly, for the monetary value of life-years gained associated with the risk-threshold. We consider the controversy over the risk-threshold to screen women for mutations in

Indexed as

AUCBRCA1BRCA2cost effectivenessdecision analysisDecision CurvesDiagnostic TestingIncremental Net BenefitNet Benefitrisk predictionROCScreeningYouden’s index

Identifiers

PMID35702631
PMCPMC9190212

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.