Evidence map›Paper›PMID 26992235›Full record

Trial reportOncotarget2016

Development and validation of a prognostic nomogram based on the log odds of positive lymph nodes (LODDS) for breast cancer.

Jiahuai Wen, Feng Ye, Xiaofang He, Shuaijie Li, Xiaojia Huang, Xiangsheng Xiao, Xiaoming Xie

Abstract readRandomized Controlled TrialValidation Study
In one paragraph

Trial report in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
–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

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Jiahuai WenDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Feng YeDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiaofang HeDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Shuaijie LiDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiaojia HuangDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiangsheng XiaoDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
Xiaoming XieDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo evaluate the prognostic effect of log odds of positive lymph nodes (LODDS) and develop a nomogram for survival prediction in breast cancer patients at the time of surgery.

resultsLODDS was an independent risk factor for cancer-related death in breast cancer (hazard ratio: 1.582, 95%CI: 1.190-2.104). Menopausal status, tumor size, pathological lymph node staging, estrogen receptor status and human epidermal growth factor receptor-2 status were also included in the nomogram. The calibration plots indicated optimal agreement between the nomogram prediction and actual observation. Discrimination of nomogram was superior to the seventh edition TNM staging system [C-index: 0.745 vs. 0.721 (p = 0.03) in training cohort; 0.796 vs. 0.726 (p < 0.01) in validation cohort].

methodsWe retrospectively evaluated 2023 breast cancer patients from Jan 2002 to Dec 2008 at our center. The cohort was randomly divided into training cohort and validation cohort. Univariate and multivariate analyses were performed to identify prognostic factors, and nomogram was established using Cox regression model in training cohort. External validation of the nomogram was performed in the validation cohort.

conclusionsThe LODDS is an independent prognostic indicator in breast cancer and the novel nomogram can provide individual prediction of cancer-specific survival and help prognostic assessment for breast cancer patients.

Indexed as

NomogramsAdultAgedAged, 80 and overBiomarkers, TumorBreast NeoplasmsFemaleFollow-Up StudiesHumansLymph NodesMiddle AgedNeoplasm StagingPrognosisRetrospective StudiesSurvival RateYoung AdultBiomarkers, Tumorbreast cancerLODDSnomogramprognosissurgery

Identifiers

PMID26992235
PMCPMC4991511

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.