Evidence map›Paper›PMID 33120801›Full record

ArticleMedicine2020

A nomogram for determining the disease-specific survival in invasive lobular carcinoma of the breast: A population study.

Rong Fu, Jin Yang, Hui Wang, Lin Li, Yuzhi Kang, Rahel Elishilia Kaaya, ShengPeng Wang, Jun Lyu

Abstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Nomogram for Prediction of Diabetic Retinopathy Among Type 2 Diabetes Population in Xinjiang, China.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022
    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

8 authors.

Rong FuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province.
Jin YangDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province.
Hui WangDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province.
Lin LiShaanxi Cancer Hospital.
Yuzhi KangShaanxi Cancer Hospital.
Rahel Elishilia KaayaSchool of Public Health, Xi'an Jiaotong University Health Science Center.
ShengPeng WangCardiovascular Research Center, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center.
Jun LyuDepartment of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to establish and validate a nomogram for predicting the disease-specific survival of invasive lobular carcinoma (ILC) patients.The Surveillance, Epidemiology, and End Results program database was used to identify ILC from 2010 to 2015, in which the data was extracted from 18 registries in the US. Multivariate Cox regression analysis was performed to identify independent prognostic factors and a nomogram was constructed to predict the 3-year and 5-year survival rates of ILC patients based on Cox regression. Predictive values were compared between the new model and the American Joint Committee on Cancer staging system using the concordance index, calibration plots, integrated discrimination improvement, net reclassification improvement, and decision-curve analyses.In total, 4155 patients were identified. After multivariate Cox regression analysis, nomogram was established based on a new model containing the predictive variables of age, the primary tumor site, histology grade, American Joint Committee on Cancer TNM (tumor node metastasis) stages II, III, and IV, breast cancer subtype, therapy modality (surgery and chemotherapy). The concordance index for the training and validation cohorts were higher for the new model (0.781 and 0.832, respectively) than for the old model (0.733 and 0.779). The new model had good performance in the calibration plots. Net reclassification improvement and integrated discrimination improvement were also improved. Finally, decision-curve analyses demonstrated that the nomogram was clinically useful.We have developed a reliable nomogram for determining the prognosis and treatment outcomes of ILC. The new model facilitates the choosing of superior medical examinations and the optimizing of therapeutic regimens with cooperation among oncologists.

Indexed as

NomogramsAdultAgedAged, 80 and overAge FactorsBreast NeoplasmsCarcinoma, LobularFemaleHumansMiddle AgedNeoplasm GradingNeoplasm InvasivenessNeoplasm StagingPrognosisRegression AnalysisReproducibility of Results

Identifiers

PMID33120801
PMCPMC7581138

What OpenQuestion holds

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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.