Evidence map›Paper›PMID 26884579›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2016

Improved Method to Stratify Elderly Patients With Cancer at Risk for Competing Events.

Ruben Carmona, Kaveh Zakeri, Garrett Green, Lindsay Hwang, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W Williamson, Daniel P Triplett, Brent S Rose and 4 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Nomogram to Predict the Benefit of Intensive Treatment for Locoregionally Advanced Head and Neck Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
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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

14 authors.

Ruben CarmonaRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Kaveh ZakeriRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Garrett GreenRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Lindsay HwangRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Sachin GulayaRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Beibei XuRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Rohan VermaRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Casey W WilliamsonRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Daniel P TriplettRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Brent S RoseRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Hanjie ShenRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Florin VaidaRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
James D MurphyRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA.
Loren K MellRuben Carmona, Kaveh Zakeri, Garrett Green, Sachin Gulaya, Beibei Xu, Rohan Verma, Casey W. Williamson, Daniel P. Triplett, Hanjie Shen, James D. Murphy, and Loren K. Mell, University of California, San Diego, La Jolla; Florin Vaida, University of California San Diego Medical Center, San Diego, CA; Lindsay Hwang, Case Western Reserve University, Cleveland, OH; and Brent S. Rose, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA. lmell@ucsd.edu.

Funding

Clinical Research Training-Students in Health Professions (RMI)T32RR023254 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KELLY, CAROLYN J · 2005 to 2009
$2.2M
UCSD Medical Student Summer Aging Research TrainingT35AG026757 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Benjamin Hyun Han, Ellen Eun-Ok Lee · 2005 to 2026
$2.2M
NCRR NIH HHS RR023254NCRR NIH HHS T32 RR023254NIA NIH HHS T35 AG026757
6 · The paper itself

Abstract

purposeTo compare a novel generalized competing event (GCE) model versus the standard Cox proportional hazards regression model for stratifying elderly patients with cancer who are at risk for competing events.

methodsWe identified 84,319 patients with nonmetastatic prostate, head and neck, and breast cancers from the SEER-Medicare database. Using demographic, tumor, and clinical characteristics, we trained risk scores on the basis of GCE versus Cox models for cancer-specific mortality and all-cause mortality. In test sets, we examined the predictive ability of the risk scores on the different causes of death, including second cancer mortality, noncancer mortality, and cause-specific mortality, using Fine-Gray regression and area under the curve. We compared how well models stratified subpopulations according to the ratio of the cumulative cause-specific hazard for cancer mortality to the cumulative hazard for overall mortality (ω) using the Akaike Information Criterion.

resultsIn each sample, increasing GCE risk scores were associated with increased cancer-specific mortality and decreased competing mortality, whereas risk scores from Cox models were associated with both increased cancer-specific mortality and competing mortality. GCE models created greater separation in the area under the curve for cancer-specific mortality versus noncancer mortality (P < .001), indicating better discriminatory ability between these events. Comparing the GCE model to Cox models of cause-specific mortality or all-cause mortality, the respective Akaike Information Criterion scores were superior (lower) in each sample: prostate cancer, 28.6 versus 35.5 versus 39.4; head and neck cancer, 21.1 versus 29.4 versus 40.2; and breast cancer, 24.6 versus 32.3 versus 50.8.

conclusionCompared with standard modeling approaches, GCE models improve stratification of elderly patients with cancer according to their risk of dying from cancer relative to overall mortality.

Indexed as

Models, StatisticalAgedAged, 80 and overBreast NeoplasmsCause of DeathFemaleHead and Neck NeoplasmsHumansMaleMedicareNeoplasmsProportional Hazards ModelsProstatic NeoplasmsRisk AssessmentRisk FactorsSEER Program

Identifiers

PMID26884579
PMCPMC5070568

What OpenQuestion holds

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Registered trials

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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.