A Comparison of the Performance of EndoPredict Clinical and NHS PREDICT in 120 Patients Treated for ER-positive Breast Cancer

Mokbel, Kinan; Wazir, Umar; Chehade, Hiba El Hage; Manson, Aisling; Choy, Christina; Moye, Victoria; Mokbel, Kefah

doi:10.21873/anticanres.12148

Cited by 2 publications

(3 citation statements)

References 40 publications

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“…Over time, computational algorithms, and mathematical equations have been developed using the clinical outcome data of various cancer registries. [ 3 , 4 ]. Nottingham prognostic index (NPI), Adjuvant, NHS PREDICT, IHC4, and CancerMath are the widely used freely available prognostic tools for ER+/HER2 neu negative early breast cancer patients [ 5 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

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

Gunda¹,

Eshwaraiah²,

Gangappa³

et al. 2022

Breast Cancer Res Treat

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Aims Clinicians use multi-gene/biomarker prognostic tests and free online tools to optimize treatment in early ER+/HER2− breast cancer. Here we report the comparison of recurrence risk predictions by CanAssist Breast (CAB), Nottingham Prognostic Index (NPI), and PREDICT along with the differences in the performance of these tests across Indian and European cohorts. Methods Current study used a retrospective cohort of 1474 patients from Europe, India, and USA. NPI risk groups were categorized into three prognostic groups, good (GPG-NPI index ≤ 3.4) moderate (MPG 3.41–5.4), and poor (PPG > 5.4). Patients with chemotherapy benefit of < 2% were low-risk and ≥ 2% high-risk by PREDICT. We assessed the agreement between the CAB and NPI/PREDICT risk groups by kappa coefficient. Results Risk proportions generated by all tools were: CAB low:high 74:26; NPI good:moderate:poor prognostic group- 38:55:7; PREDICT low:high 63:37. Overall, there was a fair agreement between CAB and NPI[κ = 0.31(0.278–0.346)]/PREDICT [κ = 0.398 (0.35–0.446)], with a concordance of 97%/88% between CAB and NPI/PREDICT low-risk categories. 65% of NPI-MPG patients were called low-risk by CAB. From PREDICT high-risk patients CAB segregated 51% as low-risk, thus preventing over-treatment in these patients. In cohorts (European) with a higher number of T1N0 patients, NPI/PREDICT segregated more as LR compared to CAB, suggesting that T1N0 patients with aggressive biology are missed out by online tools but not by the CAB. Conclusion Data shows the use of CAB in early breast cancer overall and specifically in NPI-MPG and PREDICT high-risk patients for making accurate decisions on chemotherapy use. CAB provided unbiased risk stratification across cohorts of various geographies with minimal impact by clinical parameters.

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Section: Introductionmentioning

confidence: 99%

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

Gunda¹,

Eshwaraiah²,

Gangappa³

et al. 2022

Breast Cancer Res Treat

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“…Multiple prognostic and predictive tools have been developed to guide the care of patients with newly diagnosed early-stage hormone receptor (HR)-positive and human epidermal growth factor receptor (HER2)-negative breast cancer [ 1 , 2 , 3 , 4 ]. These include free and publicly available algorithms (e.g., PREDICT 2.1 [ 5 ], Magee equations (1,2,3) [ 6 , 7 ], Gage [ 8 ], and University of Tennessee probability models [ 9 ]) and IHC4 that incorporates immuno-histochemical markers to more expensive molecular tests such as Oncotype DX, MammaPrint, PAM50, EndoPredict, and Breast Cancer Index [ 10 , 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…The PREDICT 2.1 model is an online tool available at (accessed on 22 February 2024) [ 16 ]. It uses readily available clinico-pathologic characteristics including age at diagnosis, number of lymph nodes involved, tumor size, histological grade, ER/Her2/Ki67 status, mode of detection (screening vs. clinical), and type of adjuvant systemic therapy (chemotherapy, trastuzumab, endocrine therapy, and bisphosphonate) [ 5 ]. The results of meta-analyses from Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) from different systemic therapy modalities provide an estimate of an individual patient’s overall survival (OS) at 5, 10, and 15 years with different adjuvant systemic treatments.…”

Section: Introductionmentioning

confidence: 99%

Does Pre-Emptive Availability of PREDICT 2.1 Results Change Ordering Practices for Oncotype DX? A Multi-Center Prospective Cohort Study

Awan,

Saunders,

Pond

et al. 2024

Current Oncology

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For early-stage hormone receptor (HR)-positive and HER2-negative breast cancer, tools to estimate treatment benefit include free and publicly available algorithms (e.g., PREDICT 2.1) and expensive molecular assays (e.g., Oncotype DX). There remains a need to identify patients who de-rive the most benefit from molecular assays and where this test may be of poor value. In this multicenter prospective cohort study, we evaluated whether use of PREDICT 2.1 would impact physician decision making. For the first 6 months of the study, data on physician use of both PREDICT 2.1 and Oncotype DX ordering were collected on all newly diagnosed patients eligible for molecular testing. After 6 months, an educational intervention was undertaken to see if providing physicians with PREDICT 2.1 results affects the frequency of Oncotype DX requests. A total of 602 patients across six cancer centers in Ontario, Canada were recruited between March 2020 and November 2021. Providing PREDICT 2.1 results and an educational intervention did not alter the ordering of an Oncotype DX. For patients with low clinical risk, either by clinico-pathologic features or by PREDICT 2.1, the probability of obtaining a high Oncotype DX recurrence score was substantially lower compared to patients with high-clinical-risk disease. The introduction of an educational intervention had no impact on molecular assay requests. However, routine ordering of molecular assays for patients with low-clinical-risk disease is of poor value.

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A Comparison of the Performance of EndoPredict Clinical and NHS PREDICT in 120 Patients Treated for ER-positive Breast Cancer

Cited by 2 publications

References 40 publications

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

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

Does Pre-Emptive Availability of PREDICT 2.1 Results Change Ordering Practices for Oncotype DX? A Multi-Center Prospective Cohort Study

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