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Randomized Controlled Trial
. 2021 Dec 6;11(1):23509.
doi: 10.1038/s41598-021-02992-8.

A nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer

Young Joo Lee  1 , Young Sol Hwang  2 , Junetae Kim  3 , Sei-Hyun Ahn  4 , Byung Ho Son  4 , Hee Jeong Kim  4 , Beom Seok Ko  4 , Jisun Kim  4 , Il Yong Chung  4 , Jong Won Lee  4 , Sae Byul Lee  5
Affiliations
Randomized Controlled Trial

A nomogram for predicting probability of low risk of MammaPrint results in women with clinically high-risk breast cancer

Young Joo Lee et al. Sci Rep. .

Abstract

We aimed to develop a prediction MammaPrint (MMP) genomic risk assessment nomogram model for hormone-receptor positive (HR+) and human epidermal growth factor receptor-2 negative (HER2-) breast cancer and minimal axillary burden (N0-1) tumors using clinicopathological factors of patients who underwent an MMP test for decision making regarding adjuvant chemotherapy. A total of 409 T1-3 N0-1 M0 HR + and HER2- breast cancer patients whose MMP genomic risk results and clinicopathological factors were available from 2017 to 2020 were analyzed. With randomly selected 306 patients, we developed a nomogram for predicting a low-risk subgroup of MMP results and externally validated with remaining patients (n = 103). Multivariate analysis revealed that the age at diagnosis, progesterone receptor (PR) score, nuclear grade, and Ki-67 were significantly associated with MMP risk results. We developed an MMP low-risk predictive nomogram. With a cut off value at 5% and 95% probability of low-risk MMP, the nomogram accurately predicted the results with 100% positive predictive value (PPV) and negative predictive value respectively. When applied to cut-off value at 35%, the specificity and PPV was 95% and 86% respectively. The area under the receiver operating characteristic curve was 0.82 (95% confidence interval [CI] 0.77 to 0.87). When applied to the validation group, the nomogram was accurate with an area under the curve of 0.77 (95% CI 0.68 to 0.86). Our nomogram, which incorporates four traditional prognostic factors, i.e., age, PR, nuclear grade, and Ki-67, could predict the probability of obtaining a low MMP risk in a cohort of high clinical risk patients. This nomogram can aid the prompt selection of patients who does not need additional MMP testing.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Nomogram to predict a MammaPrint low risk. Age, Progesterone receptor, nuclear grade, and Ki-67 levels were finally selected to develop the model.
Figure 2
Figure 2
Receiver operating characteristic curve of nomogram. (a) Training group of 312 patients. (b) Validation group of 97 patients.
Figure 3
Figure 3
Automatic calculator using Microsoft Excel worksheets. (a) 95% probability of low Mammaprint risk with age 67, strong PR (8), low Ki67 (5%) and tumor grade 2. (b) 4% probability of low Mammaprint risk with age 52, intermediate PR (5), high Ki67 (40%) and high tumor grade.
See this image and copyright information in PMC

References

    1. Rosenberg J, Chia YL, Plevritis S. The effect of age, race, tumor size, tumor grade, and disease stage on invasive ductal breast cancer survival in the US SEER database. Breast Cancer Res. Treat. 2005;89:47–54. doi: 10.1007/s10549-004-1470-1. - DOI - PubMed
    1. Koscielny S, et al. Breast cancer: Relationship between the size of the primary tumour and the probability of metastatic dissemination. Br. J. Cancer. 1984;49:709–715. doi: 10.1038/bjc.1984.112. - DOI - PMC - PubMed
    1. Fisher B, et al. Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update. Cancer. 1983;52:1551–1557. doi: 10.1002/1097-0142(19831101)52:9<1551::AID-CNCR2820520902>3.0.CO;2-3. - DOI - PubMed
    1. Baak JP, et al. Proliferation is the strongest prognosticator in node-negative breast cancer: Significance, error sources, alternatives and comparison with molecular prognostic markers. Breast Cancer Res. Treat. 2009;115:241–254. doi: 10.1007/s10549-008-0126-y. - DOI - PubMed
    1. Nice.org.uk, National Institute for Health Care and Excellence. Tumour profiling tests to guide adjuvant chemotherapy decisions in early breast cancer. Diagnostic Guidance DG34. https://www.nice.org.uk/guidance/dg34/resources/tumour-profiling-tests-t... (2018).

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