Evidence map›Paper›PMID 32644137›Full record

ArticleJAMA network open2020

Association of Independent Prognostic Factors and Treatment Modality With Survival and Recurrence Outcomes in Breast Cancer.

Dat Nguyen, John Yu, William C Reinhold, Sherry X Yang

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 15% of its field
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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  6. Observational
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  11. The Role of the 21-Gene Recurrence ScoreCurrent oncology (Toronto, Ont.) · 2022
    Review
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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

4 authors at 2 institutions in 1 country.

Dat NguyenNational Clinical Target Validation Laboratory, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland.
John YuDSC, Inc, Reston, Virginia.
William C ReinholdLaboratory of Pharmacology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.
Sherry X YangNational Clinical Target Validation Laboratory, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland.
National Cancer Institute · USCenter for Cancer Research · US

Funding

Comparison of molecular factors to drug activities.ZICBC011509 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI REINHOLD, WILLIAM · 2013 to 2025
$1.4M
6 · The paper itself

Abstract

Importance: It is not well understood whether prognostic factors in breast cancer are affected by specific treatment and vary by clinical outcome type compared with untreated patients. Objective: To identify independent clinical and molecular measurements associated with overall survival (OS) and recurrence-free survival (RFS) by homogeneous treatment in women with breast cancer. Design, Setting, and Participants: This prognostic study included 956 patients diagnosed with invasive breast cancer from hospital centers across 4 geographical regions of the United States who participated in the accreditation program of the Commission on Cancer of the American College of Surgeons from 1985 to 1997. The duration of follow-up ranged from 1 to 282 months. The study analysis was conducted from June 10, 2019, to March 18, 2020. Main Outcomes and Measures: Analysis of OS and RFS in patients who underwent chemotherapy, radiotherapy, or endocrine therapy alone compared with no systemic or locoregional therapy. Cox proportional hazards regression models were used to estimate independent performance and 95% CI of age, tumor size, number of positive nodes (nodal status), tumor grades 2 and 3, p53 status, estrogen receptor (ER) status, and ERBB2 (formerly HER2) status. Results: Among 956 participants, median age was 61 (range, 25-96) years. Age (adjusted hazard ratio [AHR], 2.24; 95% CI, 1.27-3.94; P = .01) and high grade (AHR, 2.05; 95% CI, 1.09-3.86; P = .02), in addition to nodal status and tumor size, were independently associated with OS and RFS, respectively, in untreated patients. p53 status (AHR, 2.11; 95% CI, 1.07-4.18; P = .03) and ER status (AHR, 0.46; 95% CI, 0.23-0.92; P = .03) were associated with higher and lower risks of death, respectively, whereas nodal status (AHR, 1.13; 95% CI, 1.06-1.20; P < .005), high grade (AHR, 4.01; 95% CI, 1.51-10.70; P = .01), and ERBB2 positivity (AHR, 2.67; 95% CI, 1.25-5.70; P = .01) were associated with the risk of recurrence after endocrine therapy. Tumor size (AHR for OS, 2.76 [95% CI, 1.79-4.31; P < .005]; AHR for RFS, 2.27 [95% CI, 1.23-4.18; P = .01]) and ERBB2 status (AHR for OS, 5.35 [95% CI, 1.31-21.98; P = .02]; AHR for RFS, 6.05 [95% CI, 1.48-24.78; P = .01]) were independently associated with radiotherapy outcomes, and nodal status was significantly associated with chemotherapy outcomes (AHR for OS, 1.06 [95% CI, 1.02-1.09; P < .005]; AHR for RFS, 1.05 [95% CI, 1.01-1.09; P = .01]). Conclusions and Relevance: In this study, independent prognostic factors were associated with specific treatment and weighted by the outcome category with reference to untreated patients within biological and clinical contexts.

Indexed as

Breast NeoplasmsBiomarkers, TumorDisease-Free SurvivalErb-b2 Receptor Tyrosine KinasesFemaleHumansKaplan-Meier EstimateMiddle AgedNeoplasm Recurrence, LocalNeoplasm StagingOutcome Assessment, Health CarePatient Care ManagementPrognosisReceptors, EstrogenTumor BurdenBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, Estrogen

Identifiers

PMID32644137
PMCPMC7348688
OpenAlexW3041866451

What OpenQuestion holds

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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.