Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
European Radiology
Published in: European Radiology 10/2022

Open Access 27-06-2022 | Ultrasound | Breast

Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics

Authors: Dan-li Sheng, Xi-gang Shen, Zhao-ting Shi, Cai Chang, Jia-wei Li

Published in: European Radiology | Issue 10/2022

Login to get access

Abstract

Objective

This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC).

Methods

Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set.

Results

A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts.

Conclusions

Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC.

Key Points

• The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC.
• Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC.
• The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.
Appendix
Available only for authorised users
Literature
1.
Foulkes WD, Smith IE, Reis-Filho JS et al (2010) Triple-negative breast cancer. N Engl J Med 363:1938–1948PubMedCrossRef
2.
Gluz O, Liedtke C, Gottschalk N, Pusztai L, Nitz U, Harbeck N (2009) Triple-negative breast cancer--current status and future directions. Ann Oncol 20:1913–1927PubMedCrossRef
3.
Dent R, Trudeau M, Pritchard KI et al (2007) Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13:4429–4434PubMedCrossRef
4.
Li X, Yang J, Peng L et al (2017) Triple-negative breast cancer has worse overall survival and cause-specific survival than non-triple-negative breast cancer. Breast Cancer Res Treat 161:279–287PubMedCrossRef
5.
6.
Garrido-Castro AC, Lin NU, Polyak K et al (2019) Insights into molecular mlassifications of triple-negative breast cancer: improving patient selection for treatment. Cancer Discov 9:176–198PubMedPubMedCentralCrossRef
7.
Bai X, Ni J, Beretov J, Graham P, Li Y (2021) Triple-negative breast cancer therapeutic resistance: where is the Achilles’ heel? Cancer Lett 497:100–111PubMedCrossRef
8.
Hernandez-Aya LF, Chavez-Macgregor M, Lei X et al (2011) Nodal status and clinical outcomes in a large cohort of patients with triple-negative breast cancer. J Clin Oncol 29:2628–2634PubMedPubMedCentralCrossRef
9.
Steward L, Conant L, Gao F, Margenthaler JA (2014) Predictive factors and patterns of recurrence in patients with triple negative breast cancer. Ann Surg Oncol 21:2165–2171PubMedCrossRef
10.
Urru SAM, Gallus S, Bosetti C et al (2018) Clinical and pathological factors influencing survival in a large cohort of triple-negative breast cancer patients. BMC Cancer 18:56PubMedPubMedCentralCrossRef
11.
Ma D, Jiang YZ, Xiao Y et al (2020) Integrated molecular profiling of young and elderly patients with triple-negative breast cancer indicates different biological bases and clinical management strategies. Cancer 126:3209–3218PubMedCrossRef
12.
Jiang YZ, Ma D, Suo C et al (2019) Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell 35:428–440 e5
13.
Jiang YZ, Liu Y, Xiao Y et al (2021) Molecular subtyping and genomic profiling expand precision medicine in refractory metastatic triple-negative breast cancer: the FUTURE trial. Cell Res 31:178–186PubMedCrossRef
14.
Bae MS, Moon HG, Han W et al (2016) Early stage triple-negative breast cancer: imaging and clinical-pathologic factors associated with recurrence. Radiology 278:356–364PubMedCrossRef
15.
Park VY, Kim EK, Kim MJ, Yoon JH, Moon HJ (2016) Breast parenchymal signal enhancement ratio at preoperative magnetic resonance imaging: association with early recurrence in triple-negative breast cancer patients. Acta Radiol 57:802–808PubMedCrossRef
16.
Bae MS, Shin SU, Ryu HS et al (2016) Pretreatment MR imaging features of triple-negative breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival. Radiology 281:392–400PubMedCrossRef
17.
Kim SY, Han BK, Kim EK et al (2017) Breast cancer detected at screening US: survival rates and clinical-pathologic and imaging factors associated with recurrence. Radiology 284:354–364PubMedCrossRef
18.
Wang H, Zhan W, Chen W, Li Y, Chen X, Shen K (2020) Sonography with vertical orientation feature predicts worse disease outcome in triple negative breast cancer. Breast 49:33–40PubMedCrossRef
19.
Tsau HS, Yen AM, Fann JC et al (2015) Mammographic tumour appearance and triple-negative breast cancer associated with long-term prognosis of breast cancer death: a Swedish Cohort Study. Cancer Epidemiol 39:200–208PubMedCrossRef
20.
Li Y, Cao J, Zhou Y, Mao F, Shen S, Sun Q (2019) Mammographic casting-type calcification is an independent prognostic factor in invasive breast cancer. Sci Rep 9:10544PubMedPubMedCentralCrossRef
21.
van der Velden BH, Dmitriev I, Loo CE, Pijnappel RM, Gilhuijs KG (2015) Association between parenchymal enhancement of the contralateral breast in dynamic contrast-enhanced MR imaging and outcome of patients with unilateral invasive breast cancer. Radiology 276:675–685PubMedCrossRef
22.
Hammond ME, Hayes DF, Dowsett M et al (2010) American society of clinical oncology/college of american pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. Arch Pathol Lab Med 134:907–922PubMedPubMedCentralCrossRef
23.
Yang Y, Wang Y, Deng H et al (2019) Development and validation of nomograms predicting survival in Chinese patients with triple negative breast cancer. BMC Cancer 19:541PubMedPubMedCentralCrossRef
24.
Yu FH, Wang JX, Ye XH, Deng J, Hang J, Yang B (2019) Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer. Eur J Radiol 119:108658PubMedCrossRef
25.
Gipponi M, Fregatti P, Garlaschi A et al (2016) Axillary ultrasound and fine-needle aspiration cytology in the preoperative staging of axillary node metastasis in breast cancer patients. Breast 30:146–150PubMedCrossRef
26.
Li JW, Zhou J, Shi ZT, Li N, Zhou SC, Chang C (2020) Sonographic features of triple-negative breast carcinomas are correlated with mRNA-lncRNA signatures and risk of tumor recurrence. Front Oncol 10:587422PubMedCrossRef
27.
Li JW, Zhang K, Shi ZT et al (2018) Triple-negative invasive breast carcinoma: the association between the sonographic appearances with clinicopathological feature. Sci Rep 8:9040PubMedPubMedCentralCrossRef
28.
29.
Steenbruggen TG, van Werkhoven E, van Ramshorst MS et al (2020) Adjuvant chemotherapy in small node-negative triple-negative breast cancer. Eur J Cancer 135:66–74PubMedCrossRef
30.
Crozier JA, Pezzi TA, Hodge C et al (2020) Addition of chemotherapy to local therapy in women aged 70 years or older with triple-negative breast cancer: a propensity-matched analysis. Lancet Oncol 21:1611–1619PubMedCrossRef
31.
Spring LM, Fell G, Arfe A et al (2020) Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: a comprehensive meta-analysis. Clin Cancer Res 26:2838–2848PubMedPubMedCentralCrossRef
32.
Park JH, Jonas SF, Bataillon G et al (2019) Prognostic value of tumor-infiltrating lymphocytes in patients with early-stage triple-negative breast cancers (TNBC) who did not receive adjuvant chemotherapy. Ann Oncol 30:1941–1949PubMedCrossRef
33.
Leon-Ferre RA, Polley MY, Liu H et al (2018) Impact of histopathology, tumor-infiltrating lymphocytes, and adjuvant chemotherapy on prognosis of triple-negative breast cancer. Breast Cancer Res Treat 167:89–99PubMedCrossRef
34.
Yu F, Hang J, Deng J et al (2021) Radiomics features on ultrasound imaging for the prediction of disease-free survival in triple negative breast cancer: a multi-institutional study. Br J Radiol. 94:20210188PubMedCrossRef
35.
Beenken SW, Urist MM, Zhang Y et al (2003) Axillary lymph node status, but not tumor size, predicts locoregional recurrence and overall survival after mastectomy for breast cancer. Ann Surg 237:732–738PubMedPubMedCentralCrossRef
36.
Candelaria RP, Adrada BE, Hess K et al (2020) Axillary ultrasound during neoadjuvant systemic therapy in triple-negative breast cancer patients. Eur J Radiol 130:109170PubMedPubMedCentralCrossRef
37.
Chang JM, Leung JWT, Moy L, Ha SM, Moon WK (2020) Axillary nodal evaluation in breast cancer: state of the art. Radiology 295:500–515PubMedCrossRef
38.
Kumar P, Aggarwal R (2016) An overview of triple-negative breast cancer. Arch Gynecol Obstet 293:247–269PubMedCrossRef
39.
Pogoda K, Niwinska A, Murawska M, Pienkowski T (2013) Analysis of pattern, time and risk factors influencing recurrence in triple-negative breast cancer patients. Med Oncol 30:388PubMedPubMedCentralCrossRef
40.
Yao Y, Chu Y, Xu B, Hu Q, Song Q (2019) Risk factors for distant metastasis of patients with primary triple-negative breast cancer. Biosci. Rep 39:BSR20190288PubMedPubMedCentralCrossRef
41.
Aleskandarany MA, Sonbul SN, Mukherjee A, Rakha EA (2015) Molecular Mechanisms Underlying Lymphovascular Invasion in Invasive Breast Cancer. Pathobiology 82:113–123PubMedCrossRef
42.
Ejlertsen B, Jensen MB, Rank F et al (2009) Population-based study of peritumoral lymphovascular invasion and outcome among patients with operable breast cancer. J Natl Cancer Inst 101:729–735PubMedCrossRef
43.
Li JW, Li N, Jiang YZ et al (2020) Ultrasonographic appearance of triple-negative invasive breast carcinoma is associated with novel molecular subtypes based on transcriptomic analysis. Ann Transl Med 8:435PubMedPubMedCentralCrossRef
44.
Shaikh S, Rasheed A (2021) Predicting molecular subtypes of breast cancer with mammography and ultrasound findings: introduction of sono-mammometry score. Radiol Res Pract 2021:6691958PubMedPubMedCentral
45.
Elsawaf Z, Sinn HP, Rom J, Bermejo JL, Schneeweiss A, Aulmann S (2013) Biological subtypes of triple-negative breast cancer are associated with distinct morphological changes and clinical behaviour. Breast 22:986–992PubMedCrossRef
46.
Li JW, Cao YC, Zhao ZJ et al (2021) Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis. Eur Radiol 32:1590–1600
47.
Elfgen C, Varga Z, Reeve K et al (2019) The impact of distinct triple-negative breast cancer subtypes on misdiagnosis and diagnostic delay. Breast Cancer Res Treat 177:67–75PubMedCrossRef
Metadata
Title
Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics
Authors
Dan-li Sheng
Xi-gang Shen
Zhao-ting Shi
Cai Chang
Jia-wei Li
Publication date
27-06-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 10/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08910-4

Other articles of this Issue 10/2022

European Radiology 10/2022 Go to the issue

Neuro

The MRI enhancement ratio and plaque steepness may be more accurate for predicting recurrent ischemic cerebrovascular events in patients with intracranial atherosclerosis

Interventional

TIPS plus sequential systemic therapy of advanced HCC patients with tumour thrombus-related symptomatic portal hypertension

Interventional

Influence of angioplasty and stenting on intracranial artery stenosis: preliminary results of high-resolution vessel wall imaging evaluation

Neuro

Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma—a systematic review

Correction

Correction: Visualization of the morphological changes in the median nerve after carpal tunnel release using three-dimensional magnetic resonance imaging

Imaging Informatics and Artificial Intelligence

Deep learning–based atherosclerotic coronary plaque segmentation on coronary CT angiography