Evidence map›Paper›PMID 37848302›Full record

ArticleBMJ open2023

Survival analysis and nomogram for pulmonary sarcomatoid carcinoma: an SEER analysis and external validation.

Weishuai Wu, Lijing Zheng, Feng Li, Hongchao Chen, Chen Huang, Qianshun Chen, Yidan Lin, Xunyu Xu, Yongmei Dai

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 5 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

9 authors at 2 institutions in 1 country.

Weishuai Wu *Shengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China.ORCID 0000-0003-0874-5587
Lijing Zheng *Shengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China.
Feng Li *Shengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China.
Hongchao ChenDepartment of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, Fujian, China.
Chen HuangDepartment of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, Fujian, China.
Qianshun ChenDepartment of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, Fujian, China.
Yidan LinShengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China.
Xunyu XuShengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China 418536903@qq.com xunyux2019@163.com.
Yongmei DaiShengli Clinical Medical College of Fujian Medical University,Fujian Provinical Hospital, Fuzhou, Fujian, China 418536903@qq.com xunyux2019@163.com.
Fujian Medical University · CNFujian Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveUncommon and particularly deadly, pulmonary sarcomatoid carcinoma (PSC) is an aggressive type of lung cancer. This research aimed to create a risk categorisation and nomogram to forecast the overall survival (OS) of patients with PSC.

methodsTo develop the model, 899 patients with PSC were taken from the Surveillance, Epidemiology, and End Results database from the USA. We also used an exterior verification sample of 34 individuals with PSC from Fujian Provincial Hospital in China. The Cox regression hazards model and stepwise regression analysis were done to screen factors in developing a nomogram. The nomogram's ability to discriminate was measured employing the area under a time-dependent receiver operating characteristic curve (AUC), the concordance index (C-index) and the calibration curve. Decision curve analysis (DCA) and integrated discrimination improvement (IDI) were used to evaluate the nomogram to the tumour-node-metastasis categorisation developed by the American Joint Committee on Cancer (AJCC-TNM), eighth edition, and an additional sample confirmed the nomogram's accuracy. We further developed a risk assessment system based on nomogram scores.

resultsSix independent variables, age, sex, primary tumour site, pathological group, tumour-node-metastasis (TNM) clinical stage and therapeutic technique, were chosen to form the nomogram's basis. The nomogram indicated good discriminative ability with the C-index (0.763 in the training cohort and 0.746 in the external validation cohort) and time-dependent AUC. Calibration plots demonstrated high congruence between the prediction model and real-world evidence in both the validation and training cohorts. Nomogram outperformed the AJCC-TNM eighth edition classification in both DCA and IDI. Patients were classified into subgroups according to their risk ratings, and significant differences in OS were observed between them (p<0.001).

conclusionWe conducted a survival analysis and nomogram for PSC. This developed nomogram holds potential to serve as an efficient tool for clinicians in prognostic modelling.

Indexed as

CarcinomaLung NeoplasmsNomogramsHumansSurvival AnalysisONCOLOGYSarcomaThoracic medicine

Identifiers

PMID37848302
PMCPMC10583103
OpenAlexW4387709328

What OpenQuestion holds

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LicenceCC BY-NC
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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.