Evidence map›Paper›PMID 36684376›Full record

ArticleFrontiers in surgery2022

An effective tool for predicting survival in breast cancer patients with

WenYi Wang, JiaJing Liu, YuQiu Chen, XiaoFan Xu, LiQun Huo, XuLin Wang, Jun Gu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in surgery, 2022. 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
1.6field-weighted citation impact, top 15% 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, 7 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

7 authors at 3 institutions in 1 country.

WenYi WangResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
JiaJing LiuDepartment of General Surgery, Jinling Hospital, Nanjing Medical University, Nanjing, China.
YuQiu ChenResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
XiaoFan XuResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
LiQun HuoResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
XuLin WangResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
Jun GuResearch Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.
Nanjing General Hospital of Nanjing Military Command · CNNanjing Medical University · CNNanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & objectives: An effective tool for forecasting the survival of BCLM is lacking. This study aims to construct nomograms to predict overall survival (OS) and breast cancer-specific survival (BCSS) in breast cancer patients with Methods: We gathered clinical data of 2,537 patients with BCLM between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression analysis was employed to identify independent prognostic parameters for BCLM, which were integrated to establish nomograms by R software. The discriminative ability and predictive accuracy of the nomograms were assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots. Kaplan-Meier analyses were applied to evaluate the clinical utility of the risk stratification system and investigate the survival benefit of primary site surgery, chemotherapy, and radiotherapy for BCLM patients. Results: Two nomograms shared common prognostic indicators including age, marital status, race, laterality, grade, AJCC T stage, subtype, bone metastasis, brain metastasis, liver metastasis, surgery, and chemotherapy. The results of the C-index, ROC curves, and calibration curves demonstrated that the nomograms exhibited an outstanding performance in predicting the prognosis of BCLM patients. Significant differences in the Kaplan-Meier curves of various risk groups corroborated the nomograms' excellent stratification. Primary site surgery and chemotherapy remarkably improved OS and BCSS of BCLM patients whether the patients were at low-risk or high-risk, but radiotherapy did not. Conclusions: We successfully developed prognostic stratification nomograms to forecast prognosis in BCLM patients, which provide important information for indicating prognosis and facilitating individualized treatment regimens for BCLM patients.

Indexed as

breast cancer lung metastasisnomogramprognosisSEERsurvival

Identifiers

PMID36684376
PMCPMC9852616
OpenAlexW4313575496

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.