Evidence map›Paper›PMID 32813682›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

A Predictive Nomogram for Early Mortality in Stage IV Gastric Cancer.

Yuqian Feng, Kaibo Guo, Huimin Jin, Yuying Xiang, Yiting Zhang, Shanming Ruan

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. 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
–field-weighted citation impact
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.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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

6 authors.

Yuqian FengThe First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).
Kaibo GuoThe First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).
Huimin JinThe First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).
Yuying XiangThe First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).
Yiting ZhangThe First Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).
Shanming RuanDepartment of Medical Oncology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The study was intended to establish predictive nomogram models for predicting total early mortality (the probability of surviving less than or equal to 3 months) and cancer-specific early mortality in patients with stage IV gastric cancer. This was the first study to establish prognostic survival in patients with stage IV gastric cancer. MATERIAL AND METHODS Patients from the SEER database were identified using inclusion and exclusion criteria. Their clinical characteristics were statistically analyzed. The Kaplan-Meier method and the log-rank test were used to compare the influences of different factors on survival time. Logistic regression models were conducted to explore the correlative factors of early mortality. A nomogram was established based on factors significant in the logistic regression model and an internal validation was performed. RESULTS Of the 11,036 eligible patients included in the study, 4932(44.7%) patients resulted in total early death (42.6% died of the cancer and 2.1% died of other reasons). Larger tumor size, poor differentiation, and liver metastasis were positively related to cancer-specific early mortality. Surgery was negatively related to total early mortality and cancer-specific early mortality, while cardia was only negatively associated with total early death. Predictive nomogram models for total early mortality and cancer-specific early mortality have been validated internally. The areas under the receiver operating characteristics curve were 73.5%, and 68.0%, respectively, and the decision curve analysis also proved the value of the models. CONCLUSIONS The nomogram models proved to be a suitable tool for predicting the early mortality in stage IV gastric cancer.

Indexed as

NomogramsAgedAged, 80 and overFemaleHumansMaleMiddle AgedNeoplasm MetastasisPrognosisSEER ProgramStomach NeoplasmsSurvival Analysis

Identifiers

PMID32813682
PMCPMC7453749

What OpenQuestion holds

Textmetadata
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.