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Abstract 4137: Latent class model characterization of neighborhood SES

Publication ,  Conference
Palumbo, A; Michael, Y; Hyslop, T
Published in: Cancer Research
October 1, 2014

Background: Breast cancer is the most common cancer in women and a significant source of mortality. Neighborhood-level socioeconomic status (NSES) has been shown to play a key role in health; poorer health outcomes are observed in deprived neighborhoods even after controlling for individual level SES. Commonly used NSES indexes are difficult to interpret. The relative impact of different factors within the index cannot be evaluated. Latent class models, which use latent variables to create distinct classes, allow for characterization of NSES and estimation of the effects of specific neighborhood characteristics on cancer outcomes.Methods: We used data from women diagnosed with breast cancer from a teaching hospital in Philadelphia, PA. Census information at the Zip Code Tabulation Area (ZCTA) level was used to obtain NSES variables. Latent class analysis and comparisons of model fit statistics were used to determine the optimal number of classes.Results: Complete ZCTA-level data was available for 1,664 breast cancer patients. In this population, NSES was best represented by two separate latent variables, each with 2-classes (LC2). When the class variables were compared to a continuous NSES index (NSI), the correlation was 0.85. However, LC2 demonstrated stronger association with race, stage, disease subtype, tumor size, and histologic grade.Conclusions: We classified neighborhoods based on correlated socioeconomic census-level variables. Latent variables identify specific characteristics associated with living in a neighborhood with low versus high advantage and disadvantage and thus may improve our understanding of critical breast cancer prognostic factors and the targeting of cancer control efforts. Further research will provide overall structural latent models that incorporate information on tumor biology, prognostic variables and survival outcomes to aid in the identification of vulnerable populations.Table 1. Neighborhood latent class model (LC2) and SES Index (NSI)Table 1.Neighborhood latent class model (LC2) and SES Index (NSI)LC2 *ModelNSI Model *Prognostic Factor Stage24.5511.61 Race366.44331.01 Subtype18.4315.48 Size22.532.91* Chi-square statistic for association of Prognostic Factor with LC2 class or with NSI quartile. Higher number indicates higher strength of association.Citation Format: Aimee Palumbo, Yvonne Michael, Terry Hyslop. Latent class model characterization of neighborhood SES. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4137. doi:10.1158/1538-7445.AM2014-4137

Duke Scholars

Published In

Cancer Research

DOI

EISSN

1538-7445

ISSN

0008-5472

Publication Date

October 1, 2014

Volume

74

Issue

19_Supplement

Start / End Page

4137 / 4137

Publisher

American Association for Cancer Research (AACR)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 3101 Biochemistry and cell biology
  • 1112 Oncology and Carcinogenesis
 

Citation

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Palumbo, A., Michael, Y., & Hyslop, T. (2014). Abstract 4137: Latent class model characterization of neighborhood SES. In Cancer Research (Vol. 74, pp. 4137–4137). American Association for Cancer Research (AACR). https://doi.org/10.1158/1538-7445.am2014-4137
Palumbo, Aimee, Yvonne Michael, and Terry Hyslop. “Abstract 4137: Latent class model characterization of neighborhood SES.” In Cancer Research, 74:4137–4137. American Association for Cancer Research (AACR), 2014. https://doi.org/10.1158/1538-7445.am2014-4137.
Palumbo A, Michael Y, Hyslop T. Abstract 4137: Latent class model characterization of neighborhood SES. In: Cancer Research. American Association for Cancer Research (AACR); 2014. p. 4137–4137.
Palumbo, Aimee, et al. “Abstract 4137: Latent class model characterization of neighborhood SES.” Cancer Research, vol. 74, no. 19_Supplement, American Association for Cancer Research (AACR), 2014, pp. 4137–4137. Crossref, doi:10.1158/1538-7445.am2014-4137.
Palumbo A, Michael Y, Hyslop T. Abstract 4137: Latent class model characterization of neighborhood SES. Cancer Research. American Association for Cancer Research (AACR); 2014. p. 4137–4137.

Published In

Cancer Research

DOI

EISSN

1538-7445

ISSN

0008-5472

Publication Date

October 1, 2014

Volume

74

Issue

19_Supplement

Start / End Page

4137 / 4137

Publisher

American Association for Cancer Research (AACR)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 3101 Biochemistry and cell biology
  • 1112 Oncology and Carcinogenesis