Comparison of Nottingham Prognostic Index, PREDICT and PrognosTILs in Triple Negative Breast Cancer –a Retrospective Cohort Study

The Nottingham Prognostics Index (NPI) is a prognostics measure that predicts operable primary breast cancer survival. The NPI value is calculated based on the size of the tumor, the number of lymph nodes, and the tumor grade. Next-generation sequencing advancements have led to measuring different biological indicators called multi-omics data. The availability of multi-omics data triggered the challenge of integrating and analyzing these various biological measures to understand the progression of the diseases. High-dimensional embedding techniques are incorporated to present the features in the lower dimension, i.e., in a 2-dimensional map. The dataset consists of three -omics: gene expression, copy number alteration (CNA), and mRNA from 1885 female patients. The model creates a gene similarity network (GSN) map for each omic using t-distributed stochastic neighbor embedding (t-SNE) before being merged into the residual neural network (ResNet) classification model. The aim of this work was to (i) extract multi-omics biomarkers that are associated with the prognosis and prediction of breast cancer survival; and (ii) build a prediction model for multi-class breast cancer NPI classes. We evaluated this model and compared it to different high-dimensional embedding techniques and neural network combinations. The proposed model outperformed the other methods with an accuracy of 98.48%, and the area under the curve (AUC) equals 0.9999. The findings in the literature confirm associations between some of the extracted omics and breast cancer prognosis and survival including CDCA5, IL17RB, MUC2, NOD2 and NXPH4 from the gene expression dataset; MED30, RAD21, EIF3H and EIF3E from the CNA dataset; and CENPA, MACF1, UGT2B7 and SEMA3B from the mRNA dataset.

Section: Introductionmentioning

confidence: 99%

“…The study compared three prognostics models that are NPI, PREDICT [ 13 ] and PrognosTILs [ 14 ]. None of the three models are inferior to the others; however, NPI outperforms the others in the area under the curve (AUC) prediction measurement [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network

Zhou

Rueda

Alkhateeb

2022

“…However, due to its frequent association with high histological grade and aggressive biological behaviour, the management of TNBC is a major focus in the field of medical oncology due to the lack of options for targeted therapy [ 12 ]. Although the prognosis of non-metastatic TNBC is influenced by a number of variables besides the triple negative phenotype [ 13 , 14 , 15 ], it is not an unexceptional practice to recommend adjuvant systemic chemotherapy (CT) to (nearly) all patients with TNBC to improve survival.…”

Section: Introductionmentioning

confidence: 99%

Triple-Negative Breast Cancer Histological Subtypes with a Favourable Prognosis

Cserni

Quinn

Foschini

et al. 2021

Self Cite

Triple-negative breast cancers (TNBC), as a group of tumours, have a worse prognosis than stage-matched non-TNBC and lack the benefits of routinely available targeted therapy. However, TNBC is a heterogeneous group of neoplasms, which includes some special type carcinomas with a relatively indolent course. This review on behalf of the European Working Group for Breast Screening Pathology reviews the literature on the special histological types of BC that are reported to have a triple negative phenotype and indolent behaviour. These include adenoid cystic carcinoma of classical type, low-grade adenosquamous carcinoma, fibromatosis-like metaplastic carcinoma, low-grade mucoepidermoid carcinoma, secretory carcinoma, acinic cell carcinoma, and tall cell carcinoma with reversed polarity. The pathological and known molecular features as well as clinical data including treatment and prognosis of these special TNBC subtypes are summarised and it is concluded that many patients with these rare TNBC pure subtypes are unlikely to benefit from systemic chemotherapy. A consensus statement of the working group relating to the multidisciplinary approach and treatment of these rare tumour types concludes the review.

“…The second evaluation with an external independent database of a certified breast center reproduced again highly significant outcomes and the initial prognostic value of our model. Time dependent ROCs were calculated and compared to published ROC results by Sejben et al [39]. The authors determined for TNBC the ROC for the NPI, PrognosTILs and Predict model.…”

Section: Discussionmentioning

confidence: 99%

BRENDA-Score, a Highly Significant, Internally and Externally Validated Prognostic Marker for Metastatic Recurrence: Analysis of 10,449 Primary Breast Cancer Patients

Wischnewsky

Schwentner

Diessner

et al. 2021

Background Current research in breast cancer focuses on individualization of local and systemic therapies with adequate escalation or de-escalation strategies. As a result, about two-thirds of breast cancer patients can be cured, but up to one-third eventually develop metastatic disease, which is considered incurable with currently available treatment options. This underscores the importance to develop a metastatic recurrence score to escalate or de-escalate treatment strategies. Patients and methods Data from 10,499 patients were available from 17 clinical cancer registries (BRENDA-project [1]. In total, 8566 were used to develop the BRENDA-Index. This index was calculated from the regression coefficients of a Cox regression model for metastasis-free survival (MFS). Based on this index, patients were categorized into very high, high, intermediate, low, and very low risk groups forming the BRENDA-Score. Bootstrapping was used for internal validation and an independent dataset of 1883 patients for external validation. The predictive accuracy was checked by Harrell’s c-index. In addition, the BRENDA-Score was analyzed as a marker for overall survival (OS) and compared to the Nottingham prognostic score (NPS). Results: Intrinsic subtypes, tumour size, grading, and nodal status were identified as statistically significant prognostic factors in the multivariate analysis. The five prognostic groups of the BRENDA-Score showed highly significant (p < 0.001) differences regarding MFS:low risk: hazard ratio (HR) = 2.4, 95%CI (1.7–3.3); intermediate risk: HR = 5.0, 95%CI.(3.6–6.9); high risk: HR = 10.3, 95%CI (7.4–14.3) and very high risk: HR = 18.1, 95%CI (13.2–24.9). The external validation showed congruent results. A multivariate Cox regression model for OS with BRENDA-Score and NPS as covariates showed that of these two scores only the BRENDA-Score is significant (BRENDA-Score p < 0.001; NPS p = 0.447). Therefore, the BRENDA-Score is also a good prognostic marker for OS. Conclusion: The BRENDA-Score is an internally and externally validated robust predictive tool for metastatic recurrence in breast cancer patients. It is based on routine parameters easily accessible in daily clinical care. In addition, the BRENDA-Score is a good prognostic marker for overall survival. Highlights: The BRENDA-Score is a highly significant predictive tool for metastatic recurrence of breast cancer patients. The BRENDA-Score is stable for at least the first five years after primary diagnosis, i.e., the sensitivities and specificities of this predicting system is rather similar to the NPI with AUCs between 0.76 and 0.81 the BRENDA-Score is a good prognostic marker for overall survival.