Evidence map›Paper›PMID 32889829›Full record

ArticleAmerican journal of clinical oncology2020

Development and Validation of an Individualized Nomogram for Predicting Overall Survival in Patients With Typical Lung Carcinoid Tumors.

Shenghua Dong, Jun Liang, Wenxin Zhai, Zhuang Yu

Open access · hybridAbstract readValidation Study
In one paragraph

Article in American journal of clinical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 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

4 authors at 3 institutions in 1 country.

Shenghua DongDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province.
Jun LiangDepartment of Oncology, Peking University International Hospital, Beijing, China.
Wenxin ZhaiDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province.
Zhuang YuDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province.
Affiliated Hospital of Qingdao University · CNPeking University · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aim to develop and validate an effective nomogram prognostic model for patients with typical lung carcinoid tumors using a large patient cohort from the Surveillance, Epidemiology, and End Results (SEER) database. MATERIALS AND

methodsData from patients with typical lung carcinoid tumors between 2010 and 2015 were selected from the SEER database for retrospective analysis. Univariate and multivariate Cox analysis was performed to clarify independent prognostic factors. Next, a nomogram was formulated to predict the probability of 3- and 5-year overall survival (OS). Concordance indexes (c-index), receiver operating characteristic analysis and calibration curves were used to evaluate the model.

resultsThe selected patients were randomly divided into a training and a validation cohort. A nomogram was established based on the training cohort. Cox analysis results indicated that age, sex, T stage, N stage, surgery, and bone metastasis were independent variables for OS. All these factors, except surgery, were included in the nomogram model for predicting 3- and 5-year OS. The internally and externally validated c-indexes were 0.787 and 0.817, respectively. For the 3-year survival prediction, receiver operating characteristic analysis showed that the areas under the curve in the training and validation cohorts were 0.824 and 0.795, respectively. For the 5-year survival prediction, the area under the curve in the training and validation cohorts were 0.812 and 0.787, respectively. The calibration plots for probability of survival were in good agreement.

conclusionThe nomogram brings us closer to personalized medicine and the maximization of predictive accuracy in the prediction of OS in patients with typical lung carcinoid tumors.

Indexed as

NomogramsAgedAge FactorsBone NeoplasmsCarcinoid TumorFemaleForecastingHumansLung NeoplasmsMaleMiddle AgedNeoplasm StagingProbabilityPrognosisProportional Hazards ModelsRetrospective Studies

Identifiers

PMID32889829
PMCPMC7515482
OpenAlexW3030920224

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.