Evidence map›Paper›PMID 25884399›Full record

ArticleBMC cancer2015

Effects of payer status on breast cancer survival: a retrospective study.

Runhua Shi, Hannah Taylor, Jerry McLarty, Lihong Liu, Glenn Mills, Gary Burton

Abstract read
In one paragraph

Article in BMC cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. The Efficacy of Direct Mail, Patient Navigation, and Incentives for Increasing Mammography and Colonoscopy in the Medicaid Population: A Randomized Controlled Trial.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018
    Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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.

Runhua ShiDepartment of Medicine & Feist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. rshi@lsuhsc.edu.
Hannah TaylorFeist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. htayl2@lsuhsc.edu.
Jerry McLartyDepartment of Medicine & Feist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. jmclar@lsuhsc.edu.
Lihong LiuDepartment of Medicine & Feist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. lliu1@lsuhsc.edu.
Glenn MillsDepartment of Medicine & Feist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. gmills@lsuhsc.edu.
Gary BurtonDepartment of Medicine & Feist-Weiller Cancer Center, LSU Health Shreveport, 1501 Kings Hwy, Shreveport, LA, 71103, USA. gburto@lsuhsc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer outcomes are influenced by multiple factors including access to care, and payer status is a recognized barrier to treatment access. To further define the influence of payer status on outcome, the National Cancer Data Base data from 1998-2006 was analyzed.

methodData was analyzed from 976,178 female patients diagnosed with breast cancer registered in the National Cancer Data Base. Overall survival was the primary outcome variable while payer status was the primary predictor variable. Secondary predictor variables included stage, age, race, Charlson Comorbidity index, income, education, distance travelled, cancer program, diagnosing/treating facility, and treatment delay. Multivariate Cox regression was used to investigate the effect of payer status on overall survival while adjusting for secondary predictive factors.

resultsUninsured (28.68%) and Medicaid (28.0%) patients had a higher percentage of patients presenting with stage III and stage IV cancer at diagnosis. In multivariate analysis, after adjusting for secondary predictor variables, payer status was a statistically significant predictor of survival. Patients with private, unknown, or Medicare status showed a decreased risk of dying compared to uninsured, with a decrease of 36%, 22%, and 15% respectively. However, Medicaid patients had an increased risk of 11% compared to uninsured. The direct adjusted median overall survival was 14.92, 14.76, 14.56, 13.64, and 12.84 years for payer status of private, unknown, Medicare, uninsured, and Medicaid respectively.

conclusionWe observed that patients with no insurance or Medicaid were most likely to be diagnosed at stage III and IV. Payer status showed a statistically significant relationship with overall survival. This remained true after adjusting for other predictive factors. Patients with no insurance or Medicaid had higher mortality.

Indexed as

Insurance, HealthAdultAgedBreast NeoplasmsDatabases, FactualFemaleHealth Services AccessibilityHumansMiddle AgedNeoplasm StagingPatient Outcome AssessmentProportional Hazards ModelsRetrospective StudiesUnited States

Identifiers

PMID25884399
PMCPMC4383189

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.