Evidence map›Paper›PMID 33960711›Full record

ArticleCancer medicine2021

Competing-risks nomograms for predicting cause-specific mortality in parotid-gland carcinoma: A population-based analysis.

Fengshuo Xu, Xiaojie Feng, Fanfan Zhao, Qiao Huang, Didi Han, Chengzhuo Li, Shuai Zheng, Jun Lyu

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.6field-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

8 citing papers in PubMed, 21 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

8 authors at 2 institutions in 1 country.

Fengshuo XuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
Xiaojie FengDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
Fanfan ZhaoDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
Qiao HuangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei Province, China.ORCID 0000-0002-3566-1023
Didi HanDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.ORCID 0000-0002-6975-2783
Chengzhuo LiDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
Shuai ZhengDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
Jun LyuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.ORCID 0000-0002-2237-8771
First Affiliated Hospital of Jinan University · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionParotid-gland carcinoma (PGC) is a relatively rare tumor that comprises a group of heterogeneous histologic subtypes. We used the Surveillance, Epidemiology, and End Results (SEER) program database to apply a competing-risks analysis to PGC patients, and then established and validated predictive nomograms for PGC.

methodsSpecific screening criteria were applied to identify PGC patients and extract their clinical and other characteristics from the SEER database. We used the cumulative incidence function to estimate the cumulative incidence rates of PGC-specific death (GCD) and other cause-specific death (OCD), and tested for differences between groups using Gray's test. We then identified independent prognostic factors by applying the Fine-Gray proportional subdistribution hazard approach, and constructed predictive nomograms based on the results. Calibration curves and the concordance index (C-index) were employed to validate the nomograms.

resultsWe finally identified 4,075 eligible PGC patients who had been added to the SEER database from 2004 to 2015. Their 1-, 3-, and 5-year cumulative incidence rates of GCD were 10.1%, 21.6%, and 25.7%, respectively, while those of OCD were 2.9%, 6.6%, and 9.0%. Age, race, World Health Organization histologic risk classification, differentiation grade, American Joint Committee on Cancer (AJCC) T stage, AJCC N stage, AJCC M stage, and RS (radiotherapy and surgery status) were independent predictors of GCD, while those of OCD were age, sex, marital status, AJCC T stage, AJCC M stage, and RS. These factors were integrated for constructing predictive nomograms. The results for calibration curves and the C-index suggested that the nomograms were well calibrated and had good discrimination ability.

conclusionWe have used the SEER database to establish-to the best of our knowledge-the first competing-risks nomograms for predicting the 1-, 3-, and 5-year cause-specific mortality in PGC. The nomograms showed relatively good performance and can be used in clinical practice to assist clinicians in individualized treatment decision-making.

Indexed as

Cause of DeathNomogramsAdultAgedAge DistributionAnalysis of VarianceCalibrationFemaleHumansIncidenceMaleMiddle AgedParotid NeoplasmsRisk AssessmentSEER ProgramSex Distributioncause-specific mortalitycompeting-risks analysisnomogramparotid-gland carcinomaSEER

Identifiers

PMID33960711
PMCPMC8178487
OpenAlexW3158776968

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LicenceCC BY
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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.