Evidence map›Paper›PMID 32968805›Full record

ArticleBiostatistics (Oxford, England)2022

The role of body mass index at diagnosis of colorectal cancer on Black-White disparities in survival: a density regression mediation approach.

Katrina L Devick, Linda Valeri, Jarvis Chen, Alejandro Jara, Marie-Abèle Bind, Brent A Coull

Open access · greenAbstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2022. 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
0.3field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  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 at 4 institutions in 2 countries.

Katrina L DevickDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 13400 E. Shea Blvd., Scottsdale, AZ 85259, USA.
Linda ValeriDepartment of Biostatistics, Columbia Mailman School of Public Health, 722 W. 168th Street, Room 612, New York, NY 10032, USA.
Jarvis ChenDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Landmark Center, Room 403-N, West Wing, Boston, MA 02215, USA.
Alejandro JaraDepartment of Statistics, Facultad de Matemáticas, Pontificia Universidad Católica de Chile, Casilla 306, Correo 22, Santiago, Chile and Millennium Nucleus Center for the Discovery of Structures in Complex Data, Faculty of Mathematics UC, Campus San Joaquin, Vicuña Mackenna 4860, Macul, Chile.
Marie-Abèle BindDepartment of Statistics, Harvard University, One Oxford Street, Suite 400, Cambridge, MA, USA.
Brent A CoullDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Building 2, 4th Floor, Boston, MA 02115, USA.
Harvard University · USColumbia University · USMayo Clinic in Arizona · USPontificia Universidad Católica de Chile · CL

Funding

Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI JAIME ELIZABETH HART · 1985 to 2026
$44.6M
GRADUATE TRAINING IN BIOSTATISTICST32ES007142 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Brent Andrew Coull · 1985 to 2026
$11.9M
Statistical Methods for the Spatio-Temporal Assessment of Social Disparities in CancerP01CA134294 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI DOMINICI, FRANCESCA, LIN, XIHONG · 2008 to 2017
$6.8M
Transporting established insights from classical experimental design to address causal questions in environmental epidemiology including the understanding of biological mediating mechanismsDP5OD021412 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI BIND, MARIE-ABELE CATHERINE · 2016 to 2020
$2.1M
Statistical methods for the assessment of social engagement in psychosis using digital technologiesK01MH118477 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI VALERI, LINDA · 2018 to 2021
$558k
NCI NIH HHS P01 CA134294NIEHS NIH HHS P30 ES000002NIEHS NIH HHS T32 ES007142NIH HHS DP5 OD021412NIMH NIH HHS K01 MH118477
6 · The paper itself

Abstract

The study of racial/ethnic inequalities in health is important to reduce the uneven burden of disease. In the case of colorectal cancer (CRC), disparities in survival among non-Hispanic Whites and Blacks are well documented, and mechanisms leading to these disparities need to be studied formally. It has also been established that body mass index (BMI) is a risk factor for developing CRC, and recent literature shows BMI at diagnosis of CRC is associated with survival. Since BMI varies by racial/ethnic group, a question that arises is whether differences in BMI are partially responsible for observed racial/ethnic disparities in survival for CRC patients. This article presents new methodology to quantify the impact of the hypothetical intervention that matches the BMI distribution in the Black population to a potentially complex distributional form observed in the White population on racial/ethnic disparities in survival. Our density mediation approach can be utilized to estimate natural direct and indirect effects in the general causal mediation setting under stronger assumptions. We perform a simulation study that shows our proposed Bayesian density regression approach performs as well as or better than current methodology allowing for a shift in the mean of the distribution only, and that standard practice of categorizing BMI leads to large biases when BMI is a mediator variable. When applied to motivating data from the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium, our approach suggests the proposed intervention is potentially beneficial for elderly and low-income Black patients, yet harmful for young or high-income Black populations.

Indexed as

Colorectal NeoplasmsAgedBayes TheoremBody Mass IndexHumansSocioeconomic FactorsUnited StatesAccelerated failure time modelCancer health disparitiesCausal inferenceDependent Dirichlet processNonparametric BayesianStochastic intervention

Identifiers

PMID32968805
PMCPMC9016785
OpenAlexW3088484455

What OpenQuestion holds

Textmetadata
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.