Evidence map›Paper›PMID 36440188›Full record

ArticleFrontiers in endocrinology2022

Risk stratification system and visualized dynamic nomogram constructed for predicting diagnosis and prognosis in rare male breast cancer patients with bone metastases.

Bing Gao, Xiao-Lan Ou, Mu-Feng Li, Meng-Die Wang, Fei Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

2 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.

Bing GaoDepartment of Orthopedics, China-Japan Union Hospital of Jilin University, Changchun, China.
Xiao-Lan OuDepartment of Hand Surgery, The Second Hospital of Jilin University, Changchun, China.
Mu-Feng LiDepartment of Orthopedics, The Second Hospital of Jilin University, Changchun, China.
Meng-Die WangDepartment of Neurology, China-Japan Union Hospital of Jilin University, Changchun, China.
Fei HuangDepartment of Orthopedics, China-Japan Union Hospital of Jilin University, Changchun, China.
Jilin University · CNSecond Affiliated Hospital of Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bone metastases (BM) from malignant tumors could disrupt the balance between osteoclasts and osteoblasts and affect bone homeostasis. Malignant breast cancer (BC) is rare in male patients, and co-occurrence of BM is even rarer. Given its low incidence, there is limited research evaluating risk and prognosis. Despite the widespread application of nomograms to predict uncommon malignancies, no studies have constructed predictive models focusing on the diagnosis and prognosis of male breast cancer with bone metastases (MBCBM). Methods: This study selected all male breast cancer patients (MBC) between 2010 and 2019 in the Surveillance, Epidemiology, and End Results (SEER) database. We used simple and multivariate Logistic regression analyses to identify independent risk factors for BM in MBC patients. Then simple and multivariate Cox regression analyses were employed to determine the independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in MBCBM patients. We established and validated three new nomograms based on these independent factors. Result: A total of 4187 MBC patients were included, with 191 (4.56%) having bone metastases at the time of diagnosis. The independent risk factors of BM in MBC patients included age, tumor size, marital status, T stage, and N stage. In MBCBM patients, independent prognostic factors for OS and CSS were both age, T stage, ER status, PR status, and surgery. The concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic curve (ROC), the calibration curve, and the decision curve analysis (DCA) confirmed that these three nomograms could accurately predict the diagnosis and prognosis of MBCBM patients with excellent discrimination and clinical utility superior to the TNM staging system. We then established two prognostic-based risk stratification systems and three visualized dynamic nomograms that could be applied in clinical practice. Conclusion: In conclusion, this study aimed to establish and validate an accurate novel nomogram to objectively predict the diagnosis and prognosis of MBCBM patients. On this basis, prognostic-based risk stratification systems and visualized dynamic nomograms were constructed to facilitate doctors and patients to quantify individual BM risk probability and survival probability to assist in personalized risk assessment and clinical decision-making.

Indexed as

Bone NeoplasmsBreast Neoplasms, MaleFemaleHumansMaleNomogramsPrognosisRisk AssessmentSEER Programbone homeostasisbone metastasisbreast cancercancer-specific survivaldynamic nomogrammaleoverall survivalrisk stratification

Identifiers

PMID36440188
PMCPMC9691876
OpenAlexW4308801777

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LicenceCC BY
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Registered trials

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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.