Evidence map›Paper›PMID 35416993›Full record

ArticleJAMA network open2022

Evaluation of Information Theoretic Network Meta-analysis to Rank First-Line Anticancer Regimens for Hormone Receptor-Positive, ERBB2-Negative Metastatic Breast Cancer.

Xuanyi Li, Alicia Beeghly-Fadiel, Suresh K Bhavnani, Hossein Tavana, Samuel M Rubinstein, Bishal Gyawali, Irbaz Bin Riaz, H Deepika Fernandes, Jeremy L Warner

Open access · goldAbstract readNetwork Meta-Analysis
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 9 institutions in 2 countries.

Xuanyi LiDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Alicia Beeghly-FadielDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Suresh K BhavnaniDepartment of Biomedical Informatics, University of Texas Medical Branch, Galveston.
Hossein TavanaDepartment of Biomedical Engineering, University of Akron, Akron, Ohio.
Samuel M RubinsteinLineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill.
Bishal GyawaliDivision of Cancer Care and Epidemiology, Departments of Oncology and Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
Irbaz Bin RiazDepartment of Oncology, Dana Farber Cancer Institute, Boston, Massachusetts.
H Deepika FernandesEdith Sanford Breast Center at Sanford Health, Bismarck, North Dakota.
Jeremy L WarnerVanderbilt-Ingram Cancer Center, Nashville, Tennessee.
Mayo Clinic in Florida · USQueen's University · CASanford Health · USThe University of Texas Medical Branch at Galveston · USUniversity of Akron · USUniversity of North Carolina at Chapel Hill · USVanderbilt-Ingram Cancer CenterVanderbilt University · USVanderbilt University Medical Center · US

Funding

TrainingU54CA163072 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Karen Marie Winkfield · 2011 to 2026
$20.1M
Training and Mentoring CoreU54MD010722 · NIMHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WILKINS, CONSUELO HOPKINS · 2016 to 2020
$11.9M
Network Analysis for a Data-Driven Approach to Cancer CareU01CA231840 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WARNER, JEREMY LYLE · 2018 to 2020
$1.2M
NCI NIH HHS U01 CA231840NCI NIH HHS U54 CA163072NIMHD NIH HHS U54 MD010722
6 · The paper itself

Abstract

Importance: Hormone receptor-positive, ERBB2 (formerly HER2/neu)-negative metastatic breast cancer (HR-positive, ERBB2-negative MBC) is treated with targeted therapy, endocrine therapy, chemotherapy, or combinations of these modalities; however, evaluating the increasing number of treatment options is challenging because few regimens have been directly compared in randomized clinical trials (RCTs), and evidence has evolved over decades. Information theoretic network meta-analysis (IT-NMA) is a graph theory-based approach for regimen ranking that takes effect sizes and temporality of evidence into account. Objective: To examine the performance of an IT-NMA approach to rank HR-positive, ERBB2-negative MBC treatment regimens. Data Sources: HemOnc.org, a freely available medical online resource of interventions, regimens, and general information relevant to the fields of hematology and oncology, was used to identify relevant RCTs. Study Selection: All primary and subsequent reports of RCTs of first-line systemic treatments for HR-positive, ERBB2-negative MBC that were referenced on HemOnc.org and published between 1974 and 2019 were included. Additional RCTs that were evaluated by a prior traditional network meta-analysis on HR-positive, ERBB2-negative MBC were also included. Data Extraction and Synthesis: RCTs were independently extracted from HemOnc.org and a traditional NMA by separate observers. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline for NMA with several exceptions: the risk of bias within individual studies and inconsistency in the treatment network were not assessed. Main Outcomes and Measures: Regimen rankings generated by IT-NMA based on clinical trial variables, including primary end point, enrollment number per trial arm, P value, effect size, years of enrollment, and year of publication. Results: A total of 203 RCTs with 63 629 patients encompassing 252 distinct regimens were compared by IT-NMA, which resulted in 151 rankings as of 2019. Combinations of targeted and endocrine therapy were highly ranked, especially the combination of endocrine therapy with cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors. For example, letrozole plus palbociclib was ranked first and letrozole plus ribociclib, third. Older monotherapies that continue to be used in RCTs in comparator groups, such as anastrozole (251 of 252) and letrozole (252), fell to the bottom of the rankings. Many regimens gravitated toward indeterminacy by 2019. Conclusions and Relevance: In this network meta-analysis study, combination therapies appeared to be associated with better outcomes than monotherapies in the treatment of HR-positive, ERBB2-negative MBC. These findings suggest that IT-NMA is a promising method for longitudinal ranking of anticancer regimens from RCTs with different end points, sparse interconnectivity, and decades-long timeframes.

Indexed as

Breast NeoplasmsAromatase InhibitorsErb-b2 Receptor Tyrosine KinasesFemaleHumansLetrozoleRandomized Controlled Trials as TopicAromatase InhibitorsERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesLetrozole

Identifiers

PMID35416993
PMCPMC9008500
OpenAlexW4223438198

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.