Abstract 4337: Identifying risk subgroups of invasive prostate cancer surgical delay using a person-centered approach: The constellation of health determinants using latent class analysis on cancer registry data

2020 ◽  
Author(s):  
Francisco Alejandro Montiel Ishino ◽  
Xiaohui Liu ◽  
Bonita Salmeron ◽  
Rina Das ◽  
Faustine Williams
Keyword(s):  
Prostate Cancer ◽  
Latent Class Analysis ◽  
Cancer Registry ◽  
Latent Class ◽  
Registry Data ◽  
Health Determinants ◽  
Class Analysis ◽  
Surgical Delay ◽  
Cancer Registry Data ◽  
Person Centered Approach

scholarly journals Identifying Risk Profiles of Malignant Prostate Cancer Surgical Delay Using a Person-Centered Approach to Understand Prostate Cancer Disparities: The Constellation of Health Determinants Using Latent Class Analysis on Cancer Registry Data

2020 ◽  
Vol 14 (6) ◽  
pp. 155798832098428
Author(s):  
Francisco A. Montiel Ishino ◽  
Claire Rowan ◽  
Rina Das ◽  
Janani Thapa ◽  
Ewan Cobran ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Health Insurance ◽  
Latent Class Analysis ◽  
Cancer Registry ◽  
High Probability ◽  
Private Health Insurance ◽  
Latent Class ◽  
Class Analysis ◽  
Risk Profiles ◽  
Surgical Delay

Surgical prostate cancer (PCa) treatment delay (TD) may increase the likelihood of recurrence of disease, and influence quality of life as well as survival disparities between Black and White men. We used latent class analysis (LCA) to identify risk profiles in localized, malignant PCa surgical treatment delays while assessing co-occurring social determinants of health. Profiles were identified by age, marital status, race, county of residence (non-Appalachian or Appalachian), and health insurance type (none/self-pay, public, or private) reported in the Tennessee Department of Health cancer registry from 2005 to 2015 for adults ≥18 years ( N = 18,088). We identified three risk profiles. The highest surgical delay profile (11% of the sample) with a 30% likelihood of delaying surgery >90 days were young Black men, <55 years old, living in a non-Appalachian county, and single/never married, with a high probability of having private health insurance. The medium surgical delay profile (46% of the sample) with a 21% likelihood of delay were 55–69 years old, White, married, and having private health insurance. The lowest surgical delay profile (42% of the sample) with a 14% likelihood of delay were ≥70 years with public health insurance as well as had a high probability of being White and married. We identified that even with health insurance coverage, Blacks living in non-Appalachian counties had the highest surgical delay, which was almost double that of Whites in the lowest delay profile. These disparities in PCa surgical delay may explain differences in health outcomes in Blacks who are most at-risk.

scholarly journals A primer to latent profile and latent class analysis

2021 ◽  
Author(s):  
Johannes Bauer
Keyword(s):  
Individual Differences ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Class Analysis ◽  
Class Membership ◽  
External Variables ◽  
Response Profiles ◽  
Person Centered Approach ◽  
Conceptual Overview ◽  
Latent Profile

This chapter gives an applied introduction to latent profile and latent class analysis (LPA/LCA). LPA/LCA are model-based methods for clustering individuals in unobserved groups. Their primary goals are probing whether and, if so, how many latent classes can be identified in the data, and to estimate the proportional size and response profiles of these classes in the population. Moreover, latent class membership can serve as predictor or outcome for external variables. Substantively, LPA/LCA adopt a person-centered approach that is useful for analyzing individual differences in prerequisites, processes, or outcomes of learning. The chapter provides a conceptual overview of LPA/LCA, a nuts-and-bolts discussion of the steps and decisions involved in their application, and illustrative examples using freely available data and the R statistical environment.

Using Latent Class Analysis to Explore Subtypes of Youth Who Have Committed Sexual Offenses

2018 ◽  
Vol 17 (4) ◽  
pp. 413-430 ◽  
Author(s):  
Adam Brown
Keyword(s):  
Young People ◽  
Latent Class Analysis ◽  
Sexual Behaviors ◽  
Latent Class ◽  
Individual Factors ◽  
Class Analysis ◽  
Male Youth ◽  
Direct Practice ◽  
Sexual Offenses ◽  
Person Centered Approach

Attempts to identify typologies of youth who have committed sexual offenses have been challenged by their overlapping characteristics with youth who have committed nonsexual crimes, as well as methodological limitations that make the results difficult to translate into direct practice. In the current study, a technical new way of identifying subtypes of these young people was proposed using latent class analysis, a person-centered approach that allows categorical subtypes to be revealed by the data rather than hypothesized differences based on individual factors. The indicators included in this analysis were sexual behaviors only, thereby eliminating any overlap with general delinquents. In a sample of 573 male youth between the ages of 11 and 20 ( M = 16.75, SD = 1.72), four unique classes were identified. Research implications are offered.

scholarly journals Spatial patterns in prostate Cancer-specific mortality in Pennsylvania using Pennsylvania Cancer registry data, 2004–2014

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ming Wang ◽  
Emily Wasserman ◽  
Nathaniel Geyer ◽  
Rachel M. Carroll ◽  
Shanshan Zhao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Spatial Patterns ◽  
Cancer Registry ◽  
Registry Data ◽  
Cancer Registry Data ◽  
Specific Mortality ◽  
Cancer Specific Mortality

scholarly journals Prostate Cancer Overall Survival: Multilevel Analysis of A Population-Based Cancer Registry Data

2014 ◽  
Vol 17 (7) ◽  
pp. A733
Author(s):  
H Xiao ◽  
F Tan ◽  
G Adunlin ◽  
AA Ali ◽  
P Goovaerts ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Multilevel Analysis ◽  
Cancer Registry ◽  
Population Based ◽  
Registry Data ◽  
Cancer Registry Data

scholarly journals Discerning the survival advantage among patients with prostate cancer who undergo radical prostatectomy or radiotherapy: The limitations of cancer registry data

Cancer ◽  
2017 ◽  
Vol 123 (9) ◽  
pp. 1617-1624 ◽  
Author(s):  
Stephen B. Williams ◽  
Jinhai Huo ◽  
Karim Chamie ◽  
Marc C. Smaldone ◽  
Christopher D. Kosarek ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Radical Prostatectomy ◽  
Cancer Registry ◽  
Survival Advantage ◽  
Registry Data ◽  
Cancer Registry Data
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