Evidence map›Paper›PMID 39421446›Full record

ArticleFrontiers in oncology2024

Race- associated molecular differences in uterine serous carcinoma.

Olivia D Lara, Hannah Karpel, Steven Friedman, Kari E Hacker, Bhavana Pothuri

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Olivia D LaraDivision of Gynecologic Oncology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Hannah KarpelDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Laura and Isaac Perlmutter Cancer Center, New York University (NYU) Langone Health, New York, NY, United States.
Steven FriedmanDepartment of Population Health, New York University Langone Health, New York, NY, United States.
Kari E HackerDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Laura and Isaac Perlmutter Cancer Center, New York University (NYU) Langone Health, New York, NY, United States.
Bhavana PothuriDepartment of Obstetrics and Gynecology, Division of Gynecologic Oncology, Laura and Isaac Perlmutter Cancer Center, New York University (NYU) Langone Health, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Endometrial cancer (EMCA) is the most common gynecologic malignancy, and new diagnoses are increasing in the United States. Black patients are more likely to present with advanced stage, be diagnosed with high-risk uterine serous carcinoma (USC) and die of their cancer. Methods: Patients with endometrial adenocarcinoma who received tumor FoundationOne CDx testing at our institution between January 2017 and August 2022 were identified. Genomic alterations, demographic and clinical characteristics were collected. Descriptive statistics and Fisher's exact test were used to analyze data. Results: A total of 289 patients (29.4% Black and 52.6% White) with advanced or recurrent endometrial adenocarcinoma underwent FoundationOne CDx testing. USC comprised 26.3% (76 of 289) of tested tumors. Of USC tumors, 33 of 76 (44%) were of Black race. USC occurred more frequently in Black patients (33 of 85 [38.8%] Black patients compared to 30 of 152 [19.7%] White patients, p<0.05). Among USC, Conclusions: Black patients constituted 44% of patients with USC in our study and had an increased frequency of

Indexed as

gynecologic cancerhealth disparitiesracetargeted treatmentuterine cancer

Identifiers

PMID39421446
PMCPMC11484420

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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.