Evidence map›Paper›PMID 28449457›Full record

ArticleJournal of thoracic disease2017

Nomogram prediction for the survival of the patients with small cell lung cancer.

Hui Pan, Xiaoshun Shi, Dakai Xiao, Jiaxi He, Yalei Zhang, Wenhua Liang, Zhi Zhao, Zhihua Guo, Xusen Zou, Jinxin Zhang and 1 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 7% 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

43 citing papers in PubMed, 3 syntheses or guidelines pooled it, 69 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Hui PanDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Xiaoshun ShiDepartment of Thoracic Surgery, Cancer Center of Guangzhou Medical University, Guangzhou 510095, China.
Dakai XiaoGuangzhou Institute of Respiratory Disease, Guangzhou 510120, China.
Jiaxi HeDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Yalei ZhangDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Wenhua LiangDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Zhi ZhaoSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Zhihua GuoDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Xusen ZouDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Jinxin ZhangSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Jianxing HeDepartment of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
State Key Laboratory of Respiratory Disease · CNGuangzhou Medical University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmall cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. In this study, we aimed to build a nomogram to predict the survival of individual with SCLC by incorporating significant clinical parameters.

methodsThe patients with SCLC were enrolled from the First Affiliated Hospital of Guangzhou Medical University (GMUFAH) between 2009 and 2013. We identified and incorporated the independent prognostic factors to build a nomogram to predict the survival of SCLC patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve. We also compared the accuracy of the built model with the 7

resultsA total of 275 patients with SCLC were included in the primary cohort, and seven independent prognostic factors were identified including age, N stage, metastasis status, histology, platelets to lymphocyte ratio (PLR), neuron specific enolase (NSE) and CYFRA21-1 as independent prognostic factors after using Cox regression model. A nomogram incorporating these prognostic factors was subsequently built. The calibration curves for possibilities of 1-, 2-year overall survival (OS) revealed optimal agreement between nomogram prediction and actual observation. The C-index of this nomogram was higher than that of TNM and VALSG staging system in both primary and validation cohort (nomogram

conclusionsIn this study, we established and validated a novel nomogram for the prediction of OS for the patients with SCLC. This model could provide more accurate individual prediction of survival probability of SCLC than the existing staging systems.

Indexed as

nomogrampredictionSmall cell lung cancer (SCLC)survival

Identifiers

PMID28449457
PMCPMC5394048
OpenAlexW2599415454

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.