Evidence map›Paper›PMID 31057324›Full record

ArticleCancer informatics2019

Development and Validation of a Nomogram Prognostic Model for Patients With Advanced Non-Small-Cell Lung Cancer.

Tao Wang, Rong Lu, Sunny Lai, Joan H Schiller, Fang Liz Zhou, Bo Ci, Stacy Wang, Xiaohan Gao, Bo Yao, David E Gerber and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Prognostic value of plasma circulating tumor DNA fraction across four common cancer types: a real-world outcomes study.Annals of oncology : official journal of the European Society for Medical Oncology · 2023
    Article
  8. Lung Cancer Computational Biology and Resources.Cold Spring Harbor perspectives in medicine · 2022
    Review
  9. Article
  10. Overall survival nomogram for patients with spinal bone metastases (SBM).Clinical and translational radiation oncology · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
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

13 authors at 2 institutions in 1 country.

Tao WangQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Rong LuQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Sunny LaiQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Joan H SchillerInova Schar Cancer Institute, Falls Church, VA, USA.
Fang Liz ZhouSanofi, Bridgewater, NJ, USA.
Bo CiQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Stacy WangQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Xiaohan GaoQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Bo YaoQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
David E GerberDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
David H JohnsonDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Guanghua XiaoQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Yang XieQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
The University of Texas Southwestern Medical Center · USSanofi (United States) · US

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
UT Southwestern Medical Center Simmons Comprehensive Cancer CenterP30CA142543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Sandi Leigh Pruitt · 2010 to 2026
$53.7M
Integrative Analysis to Identify Therapeutic Targets for Lung CancerR01CA172211 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2013 to 2017
$1.6M
Predicting Adjuvant Chemotherapy Response in Lung CancerR01CA152301 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI XIE, YANG · 2010 to 2014
$1.5M
Integrative Analysis to Identify Regulation Targets of RNA-Binding ProteinsR01GM115473 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIE, YANG · 2016 to 2019
$1.3M
Development of New Cancer Treatments and InvestigatorsK24CA201543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GERBER, DAVID ERIC · 2016 to 2020
$737k
NCI NIH HHS K24 CA201543NCI NIH HHS P30 CA142543NCI NIH HHS P50 CA070907NCI NIH HHS R01 CA152301NCI NIH HHS R01 CA172211NIGMS NIH HHS R01 GM115473
6 · The paper itself

Abstract

importanceNomogram prognostic models can facilitate cancer patient treatment plans and patient enrollment in clinical trials.

objectiveThe primary objective is to provide an updated and accurate prognostic model for predicting the survival of advanced non-small-cell lung cancer (NSCLC) patients, and the secondary objective is to validate a published nomogram prognostic model for NSCLC using an independent patient cohort.

design1817 patients with advanced NSCLC from the control arms of 4 Phase III randomized clinical trials were included in this study. Data from 524 NSCLC patients from one of these trials were used to validate a previously published nomogram and then used to develop an updated nomogram. Patients from the other 3 trials were used as independent validation cohorts of the new nomogram. The prognostic performances were comprehensively evaluated using hazard ratios, integrated area under the curve (AUC), concordance index, and calibration plots.

settingGeneral community. MAIN OUTCOME: A nomogram model was developed to predict overall survival in NSCLC patients.

resultsWe demonstrated the prognostic power of the previously published model in an independent cohort. The updated prognostic model contains the following variables: sex, histology, performance status, liver metastasis, hemoglobin level, white blood cell counts, peritoneal metastasis, skin metastasis, and lymphocyte percentage. This model was validated using various evaluation criteria on the 3 independent cohorts with heterogeneous NSCLC populations. In the SUN1087 patient cohort, the continuous risk score output by the nomogram achieved an integrated area under the receiver operating characteristics (ROC) curve of 0.83, a log-rank

conclusionsThis nomogram model based on basic clinical features and routine lab testing predicts individual survival probabilities for advanced NSCLC and exhibits cross-study robustness.

Indexed as

clinical trial data sharingnomogramnon-small-cell lung cancer

Identifiers

PMID31057324
PMCPMC6452590
OpenAlexW2926213406

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.