Evidence map›Paper›PMID 29902534›Full record

ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2018

Development and Validation of a Nomogram Prognostic Model for SCLC Patients.

Shidan Wang, Lin Yang, Bo Ci, Matthew Maclean, David E Gerber, Guanghua Xiao, Yang Xie

Abstract read
In one paragraph

Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers.

0numbers the graph read from it
0cells of the map it votes in
133citing 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

133 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Establishment of a mInternational journal of genomics · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Observational
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

73 more citing papers are in PubMed but not listed here.

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

7 authors.

Shidan WangQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Lin YangQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Pathology, National Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Bo CiQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Matthew MacleanQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
David E GerberDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas.
Guanghua XiaoQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas.
Yang XieQuantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas. Electronic address: yang.xie@utsouthwestern.edu.

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

introductionSCLC accounts for almost 15% of lung cancer cases in the United States. Nomogram prognostic models could greatly facilitate risk stratification and treatment planning, as well as more refined enrollment criteria for clinical trials. We developed and validated a new nomogram prognostic model for SCLC patients using a large SCLC patient cohort from the National Cancer Database (NCDB).

methodsClinical data for 24,680 SCLC patients diagnosed from 2004 to 2011 were used to develop the nomogram prognostic model. The model was then validated using an independent cohort of 9700 SCLC patients diagnosed from 2012 to 2013. The prognostic performance was evaluated using p value, concordance index and integrated area under the (time-dependent receiver operating characteristic) curve (AUC).

resultsThe following variables were contained in the final prognostic model: age, sex, race, ethnicity, Charlson/Deyo score, TNM stage (assigned according to the American Joint Committee on Cancer [AJCC] eighth edition), treatment type (combination of surgery, radiation therapy, and chemotherapy), and laterality. The model was validated in an independent testing group with a concordance index of 0.722 ± 0.004 and an integrated area under the curve of 0.79. The nomogram model has a significantly higher prognostic accuracy than previously developed models, including the AJCC eighth edition TNM-staging system. We implemented the proposed nomogram and four previously published nomograms in an online webserver.

conclusionsWe developed a nomogram prognostic model for SCLC patients, and validated the model using an independent patient cohort. The nomogram performs better than earlier models, including models using AJCC staging.

Indexed as

AgedFemaleHumansLung NeoplasmsMaleNomogramsPrognosisSmall Cell Lung CarcinomaNomogram prognostic modelPatient prognosisSCLC

Identifiers

PMID29902534
PMCPMC7678404

What OpenQuestion holds

Textmetadata
LicenceTDM
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.