Evidence map›Paper›PMID 37090814›Full record

ArticleMethodology : European journal of research methods for the behavioral & social sciences2023

Using Pointwise Mutual Information for Breast Cancer Health Disparities Research With SEER-Medicare Claims.

Brian L Egleston, Ashis Kumar Chanda, Tian Bai, Carolyn Y Fang, Richard J Bleicher, Slobodan Vucetic

Abstract read
In one paragraph

Article in Methodology : European journal of research methods for the behavioral & social sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Using Pointwise Mutual Information for Breast Cancer Health Disparities Research With SEER-Medicare Claims.Methodology : European journal of research methods for the behavioral & social sciences · 2023
    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.

Brian L EglestonBiostatistics and Bioinformatics Facility, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA.ORCID 0000-0002-1633-799X
Ashis Kumar ChandaDepartment of Computer and Information Sciences, Temple University, Philadelphia, PA, USA.ORCID 0000-0002-0118-8901
Tian BaiDepartment of Computer and Information Sciences, Temple University, Philadelphia, PA, USA.ORCID 0000-0001-9482-5553
Carolyn Y FangCancer Prevention and Control, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA.ORCID 0000-0002-0575-3867
Richard J BleicherDepartment of Surgical Oncology, Fox Chase Cancer Center, Temple University Health System, Philadelphia, PA, USA.ORCID 0000-0001-7343-932X
Slobodan VuceticDepartment of Computer and Information Sciences, Temple University, Philadelphia, PA, USA.ORCID 0000-0001-5884-6293

Funding

WORD PROCESSING CENTER--COREP30CA006927 · NCI · RESEARCH INST OF FOX CHASE CAN CTR · PI Dietmar J Kappes · 1985 to 2026
$138.8M
TUFCCC/HC Regional Comprehensive Cancer Health PartnershipU54CA221705 · NCI · TEMPLE UNIV OF THE COMMONWEALTH · PI Xavier Grana · 2018 to 2026
$16.3M
Deep learning for representation of codes used for SEER-Medicare claims researchR21CA202130 · NCI · RESEARCH INST OF FOX CHASE CAN CTR · PI EGLESTON, BRIAN L, VUCETIC, SLOBODAN · 2016 to 2017
$398k
NCI NIH HHS P30 CA006927NCI NIH HHS R21 CA202130NCI NIH HHS U54 CA221705
6 · The paper itself

Abstract

Identification of procedures using International Classification of Diseases or Healthcare Common Procedure Coding System codes is challenging when conducting medical claims research. We demonstrate how Pointwise Mutual Information can be used to find associated codes. We apply the method to an investigation of racial differences in breast cancer outcomes. We used Surveillance Epidemiology and End Results (SEER) data linked to Medicare claims. We identified treatment using two methods. First, we used previously published definitions. Second, we augmented definitions using codes empirically identified by the Pointwise Mutual Information statistic. Similar to previous findings, we found that presentation differences between Black and White women closed much of the estimated survival curve gap. However, we found that survival disparities were completely eliminated with the augmented treatment definitions. We were able to control for a wider range of treatment patterns that might affect survival differences between Black and White women with breast cancer.

Indexed as

breast cancerhealth disparitiesmachine learningpointwise mutual informationSEER-Medicare claims

Identifiers

PMID37090814
PMCPMC10121207

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.