Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Wazir, Umar; Mokbel, Kinan; Carmichael, Amtul R.; Mokbel, Kefah

doi:10.1186/s11658-017-0049-x

Cited by 9 publications

(9 citation statements)

References 33 publications

(34 reference statements)

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“…The recognition of breast cancer as a diverse collection of diseases characterised by distinct molecular signatures has been an important recent development. This finding was the basis for the recent development of genomic assays for breast cancer, which have greatly improved prognostication and decision-making with regards to adjuvant chemotherapy (4). In addition, this highlights the potential role for tailored treatment of breast cancer on the basis of specific pathways which may be involved (5).…”

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confidence: 89%

Correlation of TERT and Stem Cell Markers in the Context of Human Breast Cancer

Wazir

Orakzai

Martin

et al. 2019

Cancer Genomics Proteomics

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Background: Telomerase reverse transcriptase (TERT) has a well-known role in carcinogenesis due to its functions in inducing cell immortality and preventing senescence. In this study, the relationships between TERT and a panel of known stem cell markers was examined in order to direct future enquiries into the role of 'stem-ness' in human breast cancer. Materials and Methods: Breast cancer tissues (n=124) and adjacent normal tissues (n=30) underwent reverse transcription and quantitative polymerase chain reaction. Transcript levels were analyzed for the correlation with that of TERT. Results: A significant direct correlation was found in cancerous tissue between TERT and BMI1 proto-oncogene polycomb ring finger 4 (BMI1; n=88, p<0.001), nestin (NES; n=88, p<0.001), POU domain, class 5, transcription factor 1 (POU5F1; n=88, p<0.001), aldehyde dehydrogenase 1 family member A2 (ALDH1A2; n=87, p=0.0298), cyclin-dependent kinase inhibitor 1A (CDKN1A; n=88, p<0.001), integrin subunit beta 1 (ITGNB1; n=88, p<0.001), integrin subunit alpha 6 (ITGA6; n=88, p<0.001), cluster of differentiation antigen 24 (CD24; n=88, p=0.0114), n=78, p<0.001) and noggin (NOG; n=88, p<0.001). Conclusion: The evidence presented in this article of possible interactions between TERT and a discrete subset of known stem cell markers would significantly contribute to further enquiries regarding clonal dynamics in the context of human breast cancer.Wazir et al: TERT and Markers of 'Stem-ness'

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confidence: 89%

Correlation of TERT and Stem Cell Markers in the Context of Human Breast Cancer

Wazir

Orakzai

Martin

et al. 2019

Cancer Genomics Proteomics

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“…The literature which compares and contrasts available CDSSs for breast cancer treatment is very limited to the best of our knowledge. Initially, a total of nine reviews on general CDSSs were selected, using a systematic search explained in Section 2.2.1, to contextualise the study [8,[19][20][21][22][23][24][25][26]. The focus of reviewing these papers was to assess and characterise CDSSs in a general context.…”

Section: Related Work and Needs For The Reviewmentioning

confidence: 99%

Clinical Decision Support Systems in Breast Cancer: A Systematic Review

Mazo

Kearns

Mooney

et al. 2020

Cancers

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Breast cancer is the most frequently diagnosed cancer in women, with more than 2.1 million new diagnoses worldwide every year. Personalised treatment is critical to optimising outcomes for patients with breast cancer. A major advance in medical practice is the incorporation of Clinical Decision Support Systems (CDSSs) to assist and support healthcare staff in clinical decision-making, thus improving the quality of decisions and overall patient care whilst minimising costs. The usage and availability of CDSSs in breast cancer care in healthcare settings is increasing. However, there may be differences in how particular CDSSs are developed, the information they include, the decisions they recommend, and how they are used in practice. This systematic review examines various CDSSs to determine their availability, intended use, medical characteristics, and expected outputs concerning breast cancer therapeutic decisions, an area that is known to have varying degrees of subjectivity in clinical practice. Utilising the methodology of Kitchenham and Charter, a systematic search of the literature was performed in Springer, Science Direct, Google Scholar, PubMed, ACM, IEEE, and Scopus. An overview of CDSS which supports decision-making in breast cancer treatment is provided along with a critical appraisal of their benefits, limitations, and opportunities for improvement.

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“…Although all of the models (including St Gallen, Adjuvant! Online, Nottingham Prognostic Index, Magee equations, and NHS Predict) have their own limitations, they all result in reduced use of chemotherapy . In addition, surrogate models for estimating ODX have been developed including Magee Equations, Gage et al, and Tang et al All these equations use ER and PR status along with different combinations of grade, proliferation indices (Ki67 and mitotic rate), HER2 status, and tumour size .…”

Section: Discussionmentioning

confidence: 99%

Does integration of Magee equations into routine clinical practice affect whether oncologists order the Oncotype DX test? A prospective randomized trial

Robertson

Ibrahim

Stober

et al. 2019

Evaluation Clinical Practice

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Objective: The three Magee Equations provide an estimate of the Oncotype DX recurrence score using commonly available clinicopathologic information (tumour size, grade, oestrogen receptor, progesterone receptor, HER2, and Ki67). We assessed whether integration of Magee Equations into routine clinical practice affected the frequency of Oncotype DX requests.Methods: Patients with newly diagnosed, node negative, hormone receptor positive, and HER2 negative invasive breast cancer were randomized to undergo a Magee calculation or not. At the first clinic assessment, the oncologist was provided with all routinely available clinicopathologic information (including Ki67) either with or without the results of Magee Equations. Primary outcome was frequency of Oncotype DX ordering. Secondary outcomes included frequency of chemotherapy use, time to commencement of radiotherapy, or systemic therapy. Physician comfort with systemic therapy choices and the use of Ki67 and Magee Equations was also assessed.Results: Data from 175 randomized patients was available, 84 patients (48%) with and 91 (52%) without calculated Magee Equations. Oncotype DX was ordered in 10 (12.05%) and 13 (14.44%) (RR 0.83, 0.39-1.80; P = 0.64) in the Magee and no Magee groups, respectively. There were no statistically or clinically significant differences between the randomized groups for any of the secondary outcomes. Availability of both Ki67 and Magee Equations was associated with increased physician comfort around systemic treatment decisions. Conclusions:In a practice where Ki67 is routinely available, addition of Magee Equations into routine clinic practice was not associated with a reduction in Oncotype DX use. Availability of both Ki67 and Magee Equations did however increase physician comfort with systemic therapy decisions. KEYWORDS breast cancer, Magee equations, Oncotype DX 2 | METHODS | DesignA two-arm, single-centre, open label randomized controlled trial. | Study populationPatients with newly diagnosed early stage (I-III) breast cancer who had surgery at the Ottawa General Hospital (Ottawa, Canada) were eligible for this prospective, open label, randomized trial. Eligibility criteria included histologically confirmed primary breast cancer, no prior chemotherapy, tumour size greater than 0.2 cm, ER positive, PR positive or negative, HER2 negative, and lymph node negative breast cancer. Exclusion criteria included invasive lobular cancers, neoadjuvant treatment (including window of opportunity trials), presence of micrometastatic disease in lymph nodes, recurrent breast cancer, solid papillary and encapsulated papillary carcinoma, and specimens with only microinvasive disease. The study was approved by the Ottawa Health Science Network Research Ethics Board. | Study proceduresIf a patient's pathology results met the inclusion criteria, Ki67 analysis was performed, and the patient was randomized to either have Magee Equations calculated or not. At the patient's initial medical oncology consultation visit, the oncologist was provided with all ...

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Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Cited by 9 publications

References 33 publications

Correlation of TERT and Stem Cell Markers in the Context of Human Breast Cancer

Correlation of TERT and Stem Cell Markers in the Context of Human Breast Cancer

Clinical Decision Support Systems in Breast Cancer: A Systematic Review

Does integration of Magee equations into routine clinical practice affect whether oncologists order the Oncotype DX test? A prospective randomized trial

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