Evidence map›Paper›PMID 34253442›Full record

ArticleThe Journal of arthroplasty2021

Immortal Time Bias in the Analysis of Time-to-Event Data in Orthopedics.

Dirk R Larson, Cynthia S Crowson, Katrina L Devick, David G Lewallen, Daniel J Berry, Hilal Maradit Kremers

Open access · greenAbstract read
In one paragraph

Article in The Journal of arthroplasty, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Survival analyses and their applications in orthopaedics.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2023
    Review
  6. Article
  7. Living With Survival Analysis in Orthopedics.The Journal of arthroplasty · 2021
    Article
  8. Article
  9. 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 at 2 institutions in 1 country.

Dirk R LarsonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Cynthia S CrowsonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Division of Rheumatology, Mayo Clinic, Rochester, MN.
Katrina L DevickDepartment of Quantitative Health Sciences, Mayo Clinic, Scottsdale, AZ.
David G LewallenDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, MN.
Daniel J BerryDepartment of Orthopedic Surgery, Mayo Clinic, Rochester, MN.
Hilal Maradit KremersDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN.
Mayo Clinic in Arizona · USMayo Clinic in Florida · US

Funding

Resource CoreP30AR076312 · NIAMS · MAYO CLINIC ROCHESTER · PI Daniel Berry · 2019 to 2026
$5.5M
NIAMS NIH HHS P30 AR076312
6 · The paper itself

Abstract

Many outcomes in arthroplasty research are analyzed as time-to-event outcomes using survival analysis methods. When comparison groups are defined after a time-delayed exposure or intervention, a period of immortal time arises and can lead to biased results. In orthopedics research, immortal time bias often arises when a minimum amount of follow-up is required for study inclusion or when comparing outcomes in staged bilateral vs unilateral arthroplasty patients. We present an explanation of immortal time and the associated bias, describe how to correctly account for it using proper data preparation and statistical techniques, and provide an illustrative example using real-world arthroplasty data. We offer practical guidelines for identifying and properly handling immortal time to avoid bias. Please visit the followinghttps://youtu.be/58p8w5o-ci4for a video that explains the highlights of the paper in practical terms.

Indexed as

OrthopedicsBiasHumansSurvival AnalysisTime Factorscensoringimmortal time biassurvival analysistime-to-eventtotal joint arthroplasty

Identifiers

PMID34253442
PMCPMC8478821
OpenAlexW3174923429

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.