Evidence map›Paper›PMID 39002174›Full record

ArticleInternational journal of epidemiology2024

Bias due to coarsening of time intervals in the inference for the effectiveness of colorectal cancer screening.

Bikram Karmakar, Ann G Zauber, Anne I Hahn, Yan Kwan Lau, Chyke A Doubeni, Marshall M Joffe

Abstract read
In one paragraph

Article in International journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Bikram KarmakarDepartment of Statistics, College of Liberal Arts and Sciences, University of Florida, Gainesville, FL, USA.ORCID 0000-0002-9336-5062
Ann G ZauberDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Anne I HahnDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Yan Kwan LauDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-1612-9912
Chyke A DoubeniFamily and Community Medicine, Arthur G. James Cancer Hospital and Solove Research Institute, Columbus, OH, USA.
Marshall M JoffeDepartment of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, The University of Pennsylvania School of Medicine, Philadelphia, PA, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Effectiveness of screening for colorectal cancer in average risk adults: Colonoscopy vs. FITR01CA213645 · NCI · UNIVERSITY OF PENNSYLVANIA · PI CORLEY, DOUGLAS ALLEN, DOUBENI, CHYKE ABADAMA · 2017 to 2021
$3.2M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA213645NIH HHS R01CA213645
6 · The paper itself

Abstract

backgroundObservational studies are frequently used to estimate the comparative effectiveness of different colorectal cancer (CRC) screening methods due to the practical limitations and time needed to conduct large clinical trials. However, time-varying confounders, e.g. polyp detection in the last screening, can bias statistical results. Recently, generalized methods, or G-methods, have been used for the analysis of observational studies of CRC screening, given their ability to account for such time-varying confounders. Discretization, or the process of converting continuous functions into discrete counterparts, is required for G-methods when the treatment and outcomes are assessed at a continuous scale. DEVELOPMENT: This paper evaluates the interplay between time-varying confounding and discretization, which can induce bias in assessing screening effectiveness. We investigate this bias in evaluating the effect of different CRC screening methods that differ from each other in typical screening frequency. APPLICATION: First, using theory, we establish the direction of the bias. Then, we use simulations of hypothetical settings to study the bias magnitude for varying levels of discretization, frequency of screening and length of the study period. We develop a method to assess possible bias due to coarsening in simulated situations.

conclusionsThe proposed method can inform future studies of screening effectiveness, especially for CRC, by determining the choice of interval lengths where data are discretized to minimize bias due to coarsening while balancing computational costs.

Indexed as

BiasColorectal NeoplasmsEarly Detection of CancerConfounding Factors, EpidemiologicHumansMass ScreeningObservational Studies as TopicTime FactorsConfounding by indicationG-formulalongitudinal observational studyrandomization trialsequential screeningstructured tree graph

Identifiers

PMID39002174
PMCPMC11246168

What OpenQuestion holds

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Registered trials

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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.