Exploring the Data:

Demographic Disparities in Early-Stage Detection of Breast Cancer

Erin McLeod | IDSN 530 - 02a | 01.27.26

SUMMARY

The research described on this page is a deep dive into available data analytics on early-stage breast cancer detection. As you explore this page, you'll see that by focusing not just on cancer incidence alone, but on stage of detection segmented by demographics, survival outcomes could be improved by placing more focus and investment on increased screening access in underserved areas.

Research Domain

Incidence of Breast Cancer

Data Discovery

Stage at Diagnosis (0, I, II, III, IV)

Focused Sub-Domain

Demographic Disparities in Early-Stage Detection

RAW DATA

PUBLISHED DATA EXAMPLES

NIH Logo
Stage Distribution: Percent of Cases by Ethnicity
NIH: Stage Distribution by Ethnicity
Stage Distribution: Percent of Cases by Age
NIH: Stage Distribution by Age
State Cancer Profiles Logo
Breast Cancer Screening Rates by State
Screening by State
CDC Logo
Stage Distribution
CDC: Stage Distribution

From 2018 to 2022, about 2 in 3 female breast cancer cases were diagnosed at a localized stage, meaning the cancer had not spread outside the breast. About 1 in 4 female breast cancers were found at a regional stage (the cancer had spread to nearby lymph nodes, tissues, or organs), and 6% were found at a distant stage (the cancer had spread to distant parts of the body).

LCP logo
Non-Hispanic White Late Stage Diagnosis Percentage (%) For All Ages During 2016-2020 (Parish-level Breakdown)
Non-Hispanic White Late Stage Diagnosis
Non-Hispanic Black Late Stage Diagnosis Percentage (%) For All Ages During 2016-2020 (Parish-level Breakdown)
Non-Hispanic Black Late Stage Diagnosis

INSIGHTS EXTRACTED

  1. Early detection is unevenly distributed
    • Charts show that a large percentage of breast cancer cases are detected at a localized (early) stage
    • Data segmented by race shows the proportion of early-stage detection differs across groups
  2. Aggregated data obscures high-risk subpopulations
    • National-level summaries suggest strong early detection
    • Race and age segments show consistently lower early-stage diagnosis rates
  3. Published visualizations describe disparities but don't offer interactive outputs for decision-making
    • National-level summaries suggest strong early detection
    • Race and age segments show consistently lower early-stage diagnosis rates

ACTIONS

These action items highlight the need for visualization tools that not only describe disparities, but actively support exploration, prioritization, and intervention.

Screening Interventions

Available data can address screening disparities in under-detected populations by identifying who is being detected late and where they might be located. Policymakers and institutions should deploy targeted screening programs rather than replying on standard national screening recommendations.

Reframe National Metrics

Supplementing national metrics with “equity indicators” like minimum screening rates changes early-detection success criteria focus from performance average to missing demographics.

Targeted Investments

Screening maps identify where gaps exist, and stage-at-diagnosis data shows consequences of those gaps. Funding and infrastructure should be allocated to regions with low screening and high late-stage diagnosis rates.

IMPROVED OUTPUTS

A greater variety of tools are needed that enable viewers to explore early-stage detection by:

Demographic Explorer

Instead of static charts, users can identify populations with layered disadvantage.

Screening Access vs. Detection Maps

By visualizing access and outcomes geographically, intervention resources can be allocated in high-risk zones.

Equity Performance Dashboard

Health Administrators and Policymakers can ask equity-focused questions of the data to address accountability issues.

A Note on Sourcing:

All logos and images used in this document are sourced from their respective organizations and are used here for illustrative purposes only.