Evidence map›Paper›PMID 30677255›Full record

ArticleCancer medicine2019

Development and validation of nomograms integrating immune-related genomic signatures with clinicopathologic features to improve prognosis and predictive value of triple-negative breast cancer: A gene expression-based retrospective study.

Kang Wang, Hai-Lin Li, Yong-Fu Xiong, Yang Shi, Zhu-Yue Li, Jie Li, Xiang Zhang, Hong-Yuan Li

Abstract read
In one paragraph

Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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.

Kang WangDepartment of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.ORCID 0000-0001-7415-5134
Hai-Lin LiDepartment of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
Yong-Fu XiongDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
Yang ShiDivision of Biostatistics and Data Science, Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, Georgia.
Zhu-Yue LiInstitute of Hospital Management, West China Hospital, Sichuan University, Chengdu, China.
Jie LiDepartment of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
Xiang ZhangDepartment of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.
Hong-Yuan LiDepartment of the Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccumulating evidence indicated that triple-negative breast cancer (TNBC) can stimulate stronger immune responses than other subtypes of breast cancer. We hypothesized that integrating immune-related genomic signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system.

methodsTen signatures that reflect specific immunogenic or immune microenvironmental features of TNBC were identified and re-analyzed using bioinformatic methods. Then, clinically annotated TNBC (n = 711) with the corresponding expression profiles, which predicted a patient's probability of disease-free survival (DFS) and overall survival (OS), was pooled to evaluate their prognostic values and establish a clinicopathologic-genomic nomogram. Three and two immune features were, respectively, selected out of 10 immune features to construct nomogram for DFS and OS prediction based on multivariate backward stepwise Cox regression analyses.

resultsBy integrating the above immune expression signatures with prognostic clinicopathologic features, clinicopathologic-genomic nomograms were cautiously constructed, which showed reasonable prediction accuracies (DFS: HR, 1.79; 95% CI, 1.46-2.18, P < 0.001; AUC, 0.71; OS: HR, 1.96; 95% CI, 1.54-2.49; P < 0.001; AUC, 0.73). The nomogram showed low-risk subgroup had higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4, LAG-3) expression and benefited from radiotherapy (HR, 0.2, 95% CI, 0.05-0.89; P = 0.034) rather than chemotherapy (HR, 1.26, 95% CI, 0.66-2.43; P = 0.485).

conclusionsThese findings offer evidence that immune-related genomic data provide independent and complementary prognostic information for TNBC, and the nomogram might be a practical predictive tool to identify TNBC patients who would benefit from chemotherapy, radiotherapy, and upcoming popularity of immunotherapy.

Indexed as

Gene Expression Regulation, NeoplasticAdultAgedGene Expression ProfilingGenomicsHumansMiddle AgedNomogramsPrognosisTriple Negative Breast Neoplasmsimmune-related genomic signaturesnomogramtriple-negative breast

Identifiers

PMID30677255
PMCPMC6382728

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.