Evidence map›Paper›PMID 23093413›Full record

ArticleJournal of gastrointestinal cancer2013

Characteristics of colorectal cancer survival in an urban county hospital.

Vincent K Lam, An-Ting T Lu, Natalia Kouzminova, Albert Y Lin

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Article in Journal of gastrointestinal cancer, 2013. 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

4 authors.

Vincent K LamSanta Clara Valley Medical Center, San Jose, CA 95128, USA.
An-Ting T Lu
Natalia Kouzminova
Albert Y Lin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDisparities in colorectal cancer (CRC) survival have been associated with race/ethnicity, screening, and insurance status, but less is known about how geographic and socioeconomic heterogeneity may modulate these factors. We examined CRC outcomes in an urban underserved population with sociodemographic factors distinctly different than those previously studied.

methodsIn this 11-year retrospective study, the demographics and clinical features of 331 CRC patients from a Northern California urban county hospital were reviewed. Cox proportional hazards modeling was used to evaluate differences in 5-year mortality.

resultsThe study cohort consisted of 38 % Whites, 37 % Asians, 22 % Hispanics, and 4 % Blacks. Most of the patients either had government-sponsored insurance (62.5 %) or were uninsured (21.8 %). Compared to national SEER data, stage IV disease was more prevalent in our study cohort (37 vs 20 %) and the overall 5-year survival rate was worse (52.9 vs 64.3 %). CRC screening was associated with improved survival (hazard ratio (HR) 0.24, P=0.002), while insurance status was not. In the multivariate analysis, advanced age (HR 2.48, confidence interval (CI) 1.39-4.42, P=0.002) and late stage (stage IV: HR 32.46, CI 9.92-106.25, P<0.001) predicted worse outcomes. Contrary to some population-based studies, Hispanics in our cohort had significantly better overall mortality compared to Whites (HR 0.46, CI 0.29-0.74, P=0.001).

conclusionsDisparities in CRC outcomes for urban underserved populations persist. However, there is geographic and socioeconomic heterogeneity in factors that have been previously shown to contribute to mortality. Screening and therapeutic strategies formulated from larger population-based studies may not be generalizable to these unique subpopulations.

Indexed as

Healthcare DisparitiesCaliforniaColorectal NeoplasmsEthnicityFemaleFollow-Up StudiesHumansMaleMiddle AgedNeoplasm StagingPrognosisRetrospective StudiesRisk FactorsSEER ProgramSocioeconomic FactorsSurvival Rate

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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.