A comparative analysis of recurrence risk predictions in ER+/HER2- early breast cancer using NHS Nottingham Prognostic Index, PREDICT, and CanAssist Breast

Performance of a novel spectroscopy-based tool for adjuvant therapy decision-making in hormone receptor-positive breast cancer: a validation study

PURPOSE

Digistain Index (DI), measured using an inexpensive mid-infrared spectrometer, reflects the level of aneuploidy in unstained tissue sections and correlates with tumor grade. We investigated whether incorporating DI with other clinicopathological variables could predict outcomes in patients with early breast cancer.

METHODS

DI was calculated in 801 patients with hormone receptor-positive, HER2-negative primary breast cancer and ≤ 3 positive lymph nodes. All patients were treated with systemic endocrine therapy and no chemotherapy. Multivariable proportional hazards modeling was used to incorporate DI with clinicopathological variables to generate the Digistain Prognostic Score (DPS). DPS was assessed for prediction of 5- and 10-year outcomes (recurrence, recurrence-free survival [RFS] and overall survival [OS]) using receiver operating characteristics and Cox proportional hazards regression models. Kaplan-Meier analysis evaluated the ability of DPS to stratify risk.

RESULTS

DPS was consistently highly accurate and had negative predictive values for all three outcomes, ranging from 0.96 to 0.99 at 5 years and 0.84 to 0.95 at 10 years. DPS demonstrated statistically significant prognostic ability with significant hazard ratios (95% CI) for low- versus high-risk classification for RFS, recurrence and OS (1.80 [CI 1.31-2.48], 1.83 [1.32-2.52] and 1.77 [1.28-2.43], respectively; all P < 0.001).

CONCLUSION

DPS showed high accuracy and predictive performance, was able to stratify patients into low or high-risk, and considering its cost and rapidity, has the potential to offer clinical utility.

Prediction of the Nottingham prognostic index and molecular subtypes of breast cancer through multimodal magnetic resonance imaging

PURPOSE

To explore the ability of intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and background parenchyma enhancement (BPE) to predict the Nottingham prognostic index (NPI) and molecular subtypes of breast cancer (BC).

MATERIALS AND METHODS

In this study, 93 patients with BC were included, and they all underwent DKI, IVIM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations. The corresponding mean kurtosis value (MK), pure diffusion (MD), perfusion fraction (f), pseudo diffusion coefficient (D*), true diffusion coefficient (D), and BPE were measured. We used logistic regression analysis to investigate the relevance between the NPI, molecular subtypes and variables. The diagnostic efficacy was analyzed using receiver operating characteristic curves (ROC).

RESULTS

The MD and D values of the high-level NPI group were significantly lower than those of the low-level NPI group (p < 0.01), and the f value of the high-level NPI group was obviously higher than that of low-level NPI group (p < 0.001). The area under curve (AUC) of the combined model (f + D) was 0.824. Comparing with non-Luminal subtypes, the Luminal subtypes showed obviously lower MK, f and D*, and the AUC of the combined model (MK + f + D*) was 0.785. In comparison to other subtypes, the MK and D* values of triple-negative subtype were higher than other subtypes, and the combined model (MK + D*) represented an AUC of 0.865.

CONCLUSION

The quantitative parameters of DKI and IVIM have vital value in predicting the NPI and molecular subtypes of BC, while BPE could not provide additional information. Besides, these combined models can obviously improve the prediction performance.

The usefulness of CanAssist Breast over Ki67 in breast cancer recurrence risk assessment

BACKGROUND

Assessment of Ki67 by immunohistochemistry (IHC) has limited utility in clinical practice owing to analytical validity issues. According to International Ki67 Working Group (IKWG) guidelines, treatment should be guided by a prognostic test in patients expressing intermediate Ki67 range, >5%-<30%. The objective of the study is to compare the prognostic performance of CanAssist Breast (CAB) with that of Ki67 across various Ki67 prognostic groups.

METHODS

The cohort had 1701 patients. Various risk groups were compared for the distant relapse-free interval (DRFi) derived from Kaplan-Meier survival analysis. As per IKWG, patients are categorized into three risk groups: low-risk (<5%), intermediate risk (>5%-<30%), and high-risk (>30%). CAB generates two risk groups, low and high risk based on a predefined cutoff.

RESULTS

In the total cohort, 76% of the patients were low risk (LR) by CAB as against 46% by Ki67 with a similar DRFi of 94%. In the node-negative sub-cohort, 87% were LR by CAB with a DRFi of 97% against 49% by Ki67 with a DRFi of 96%. In subgroups of patients with T1 or N1 or G2 tumors, Ki67-based risk stratification was not significant while it was significant by CAB. In the intermediate Ki67 (>5%-<30%) category up to 89% (N0 sub-cohort) were LR by CAB and the percentage of LR patients was 25% (p < 0.0001) higher compared to NPI or mAOL. In the low Ki67 (≤5%) group, up to 19% were segregated as high-risk by CAB with 86% DRFi suggesting the requirement of chemotherapy in these low Ki67 patients.

CONCLUSION

CAB provided superior prognostic information in various Ki67 subgroups, especially in the intermediate Ki67 group.