Evidence map›Paper›PMID 33577928›Full record

ArticleAnnals of epidemiology2021

Neighborhood archetypes and breast cancer survival in California.

Salma Shariff-Marco, Mindy C DeRouen, Juan Yang, Jennifer Jain, David O Nelson, Margaret M Weden, Scarlett L Gomez

Abstract read
In one paragraph

Article in Annals of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  5. Article
  6. Review
  7. Article
  8. Article
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  12. Area-level Socioeconomic Disadvantage and Cancer Survival in Metropolitan Detroit.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  13. Article
  14. Breast Cancer Disparities and the Impact of Geography.Surgical oncology clinics of North America · 2022
    Review
  15. Evaluating the Impact of Social and Built Environments on Health-Related Quality of Life among Cancer Survivors.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  16. Integrating Electronic Health Record, Cancer Registry, and Geospatial Data to Study Lung Cancer in Asian American, Native Hawaiian, and Pacific Islander Ethnic Groups.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
    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

7 authors.

Salma Shariff-MarcoDepartment of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA. Electronic address: salma.shariff-marco@ucsf.edu.
Mindy C DeRouenDepartment of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA.
Juan YangDepartment of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA.
Jennifer JainDepartment of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA.
David O NelsonCancer Prevention Institute of California, Fremont, CA.
Margaret M WedenRAND Corporation, Santa Monica, CA.
Scarlett L GomezDepartment of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA.

Funding

Developing Neighborhood Archetypes for Understanding Disparities in CancerR21CA174469 · NCI · CANCER PREVENTION INSTIT OF CALIFORNIA · PI SHARIFF-MARCO, SALMA · 2014 to 2016
$396k
NCCDPHP CDC HHS NU58DP006344NCI NIH HHS HHSN261201800009CNCI NIH HHS HHSN261201800009INCI NIH HHS HHSN261201800015CNCI NIH HHS HHSN261201800015INCI NIH HHS HHSN261201800032CNCI NIH HHS HHSN261201800032INCI NIH HHS R21 CA174469
6 · The paper itself

Abstract

purposePrevious studies on neighborhoods and breast cancer survival examined neighborhood variables as unidimensional measures (e.g. walkability or deprivation) individually and thus cannot inform how the multitude of highly correlated neighborhood domains interact to impact breast cancer survival. Neighborhood archetypes were developed that consider interactions among a broad range of neighborhood social and built environment attributes and examine their associations with breast cancer survival.

methodsArchetypes were measured using latent class analysis (LCA) fit to California census tract-level data. Thirty-nine social and built environment attributes relevant to eight neighborhood domains (socioeconomic status (SES), urbanicity, demographics, housing, land use, commuting and traffic, residential mobility, and food environment) were included.  The archetypes were linked to cancer registry data on breast cancer cases (diagnosed 1996-2005 with follow-up through Dec 31, 2017) to evaluate their associations with overall and breast cancer-specific survival using Cox proportional hazards models. Analyses were stratified by race/ethnicity.

resultsCalifornia neighborhoods were best described by nine archetypal patterns that were differentially associated with overall and breast cancer-specific survival. The lowest risk of overall death was observed in the upper middle class suburb (reference) and high status neighborhoods, while the highest was observed among inner city residents with a 39% greater risk of death (95% CI = 1.35 to 1.44). Results were similar for breast cancer-specific survival. Stratified analyses indicated that differences in survival by neighborhood archetypes varied according to individuals' race/ethnicity.

conclusionsBy describing neighborhood archetypes that differentiate survival following breast cancer diagnosis, the study provides direction for policy and clinical practice addressing contextually-rooted social determinants of health including SES, unhealthy food environments, and greenspace.

Indexed as

Breast NeoplasmsCaliforniaEthnicityHumansResidence CharacteristicsSocial ClassSocioeconomic FactorsBreast cancerCancer survivalGeographic disparitiesLatent class analysisNeighborhood archetypesNeighborhood socioeconomic statusRacial/ethnic disparities

Identifiers

PMID33577928
PMCPMC8133764

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.