Evidence map›Paper›PMID 36718941›Full record

ArticleThe clinical respiratory journal2023

Clinicopathological features and prognostic nomogram of giant cell carcinoma of the lung: A population-based study.

Jiang He, Jin-Ping Ni, Guang-Bin Li, Jie Yao, Bin Ni

Open access · goldAbstract read
In one paragraph

Article in The clinical respiratory journal, 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
0.8field-weighted citation impact, top 26% 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, 3 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

5 authors at 2 institutions in 1 country.

Jiang HeDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Jin-Ping NiSuzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China.
Guang-Bin LiDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Jie YaoDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Bin NiDepartment of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China.
Soochow University · CNKowloon Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to its rarity, the features and prognosis of giant cell carcinoma of the lung (GCCL) are not well defined. The present study aimed to describe the clinicopathological features and prognostic analysis of this rare disease, compare it with lung adenocarcinoma (LAC), further determine the prognostic factors and establish a nomogram.

methodsPatients diagnosed with GCCL and LAC were identified from the SEER database between 2004 and 2016. The features and survival between GCCL and LAC were compared in the unmatched and matched cohorts after propensity score matching (PSM) analysis. Univariate and multivariate Cox analyses were used to identify the prognostic factors, and a nomogram was constructed. Area under the curve (AUC), C-index, calibration curve and decision curve analysis (DCA) were used to confirm the established nomogram.

resultsA total of 295 patient diagnosed with GCCL and 149 082 patients with LAC were identified. Compared with LAC, patients with GCCL tend to be younger, male, black and have pathological Grade III/IV GCCL, more proportion of AJCC-TNM-IV, T3/T4 and distant metastases. The 1-, 2- and 5-year OS rates of the patients with GCCL were 21.7%, 13.4% and 7.9%, respectively. The median OS and CSS were 3 and 4 months, respectively. Patients with GCCL had significantly shorter OS and CSS than those with LAC in the unmatched and matched cohorts after PSM. Multivariate Cox analysis demonstrated that T, N and M stages and use of chemotherapy and surgery were independent of survival. Furthermore, we constructed a prognostic nomogram for OS and CSS by using independent prognostic factors. The C-index of OS-specific nomogram is 0.78 (0.74-0.81), and the C-index of CSS-specific nomogram is 0.77 (0.73-0.80). The calibration curve and ROC analysis showed good predictive capability of these nomograms. DCA showed that the nomogram had greater clinical practical value in predicting the OS and CSS of GCCL than TNM staging.

conclusionGCCL have distinct clinicopathological characteristics and significantly worse clinical outcomes. Prognostic nomograms for overall survival (OS) and CSS were constructed.

Indexed as

Adenocarcinoma of LungCarcinoma, Giant CellCarcinoma, Non-Small-Cell LungLung NeoplasmsHumansLungMaleNeoplasm StagingNomogramsPrognosisgiant cell carcinoma of the lungnomogrampropensity score matching analysisSEER database

Identifiers

PMID36718941
PMCPMC9978898
OpenAlexW4318671049

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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.