Multi-gene assays: effect on chemotherapy use, toxicity and cost in estrogen receptor-positive early stage breast cancer

Hochheiser, Louis I.; Hornberger, John; Turner, Michelle; Lyman, Gary H.

doi:10.2217/cer-2018-0137

Cited by 11 publications

(18 citation statements)

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“…EndoPredict offers a risk score of recurring as distant metastasis for early-stage breast cancer patients with Estrogen-Receptor (ER) positive and HER2 negative [81]. Activities of 12 genes are profiled in breast cancer cells to calculate the risk score and the threshold 3.3287 is optimized to discriminate the patients with higher than 10% risks [82].…”

Section: F Comparison With the Existing Gene Panels For Breast Cancersmentioning

confidence: 99%

Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall

Liu

Zheng

et al. 2021

IEEE Access

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Breast cancer is one of main causes of death for women. Most of the existing survival analyses focus on the features' associations with whether the patients may survive five years or not. The personalized question remains largely unresolved about how long a breast cancer patient will live. This study aims to predict the patient-specific survival time of breast cancer patients. It formulates the personalized question into two machine learning problems. The first problem is the binary classification of whether a patient will live longer than five years or not. The second one is to build a regression model to predict the patient's survival time within five years. The methylome of a breast cancer patient is used for the prediction. A new algorithm Crystall is presented to find the methylomic features for this regression model. Our models perform well in the above two problems, and achieve the mean absolute error (MAE) of about 1 month for predicting how long a breast cancer patient will live within five years. The detected biomarker genes demonstrate close connections with breast cancers.

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Section: F Comparison With the Existing Gene Panels For Breast Cancersmentioning

confidence: 99%

Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall

Liu

Zheng

et al. 2021

IEEE Access

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“…We applied almost the same incidence as recently reported by Hannouf et al, which had a monthly incidence of 0.15%, computing into a 16.1% incidence at 10 years assuming a constant hazard rate [12]. Our meta-analyses systematically summarized the published evidence on how physicians use multigene assays to affect chemotherapy recommendations and decisions [13]. Fallowfield et al is the only published study of effects of EPclin on real-world decision making [14].…”

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confidence: 99%

Letter in reply

et al. 2019

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We appreciate the comments from Hannouf et al. that allow for elaboration on the analyses and implications. Several queries concern the incidence of distant recurrence among women not prescribed chemotherapy, clinically referred to as prognosis. Across multiple large-cohort studies and control arms of clinical trials of chemotherapy, the average 10-year incidence of distant recurrence in node-negative tumors for all women receiving endocrine therapy varies between 6.4 and 14.8% [1][2][3][4][5][6][7][8][9][10]. The Early Breast Cancer Trialists' Collaborative Group (EBCTCG) reported a 10-year incidence of distant recurrence of 11% among a cohort of women with node-negative tumors in whom 32% underwent chemotherapy (Table 1 & Figure 2A in [11]); they remark that ". . . the risk of recurrence after 5 years may well be somewhat lower in women who receive contemporary chemotherapy than among those in our study" [11]. Based on these data, we assumed across all multigene assays an average 10-year incidence equal to 11% if a woman receives endocrine therapy alone.The EndoPredict R (EP) assay uses 12-genes to derive a risk score; EPclin also incorporates nodal status and tumor size to compute a risk score between 0 and 15. The incidence of distant recurrence stratified by risk score was reported for EP and EPclin in 2016, showing EPclin had a higher 10-year incidence for high-risk patients relative to EP [10]. We applied almost the same incidence as recently reported by Hannouf et al., which had a monthly incidence of 0.15%, computing into a 16.1% incidence at 10 years assuming a constant hazard rate [12]. Our meta-analyses systematically summarized the published evidence on how physicians use multigene assays to affect chemotherapy recommendations and decisions [13]. Fallowfield et al. is the only published study of effects of EPclin on real-world decision making [14]. In seven hospitals in the UK, EPclin increased the use of chemotherapy from 61 to 62 patients among 149 tested patients. Moreover, axiomatically (adhering to mathematical consistency), a higher incidence of distant recurrence results in more distant recurrences overall, unless there is an offsetting chemobenefit among women with high-risk versus low-risk tumors. Chemobenefit has only been demonstrated for the 21-gene Oncotype DX Breast Recurrence Score R test (see below for more details). A higher incidence also correlates with more resources to manage metastatic disease and higher costs. Due to the high cost of managing metastatic cancer, applying the higher incidence rate increases the cost -relative to no testing -from $41M with EP to more than $100M with EPclin. Even if physicians exhibited greater confidence to prescribe chemotherapy only to women with a high-risk score by EPclin, it would not offset its lack of proven chemobenefit. Notably, NCCN Guidelines R refer to '12-gene (EndoPredict)' assay, but also cite the cutpoint associated with EPclin; by contrast, the American Society of Clinical Oncology (ASCO) guidelines refer to '12-gene risk score' o...

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“…

We read with interest the recent article by Hochheiser et al regarding the economic impact of four multi-gene assays (MGAs) used to make decisions regarding chemotherapy use in women with newly diagnosed estrogen receptor-positive, HER2-negative breast cancer: 21-gene recurrence score (Oncotype DX R ), 70-gene signature (MammaPrint R ), PAM50 (commercial; Prosigna R ) and 12-gene molecular score (EndoPredict R ) [1]. We wish to highlight several deficiencies in the study design and the resultant conclusions.The authors described the variables that were utilized in their cost-effectiveness model, which included two elements related to the risk of distant recurrence according to MGA risk stratification: the 10-year probability of recurrence without chemotherapy (i.e., prognostic performance) and the 10-year relative risk of recurrence with and without chemotherapy (i.e., predictive performance).

…”

mentioning

confidence: 99%

“…These values were then applied to decision-impact data (i.e., how testing with each MGA impacted chemotherapy treatment decisions) to model the cost-effectiveness of each MGA. Hochheiser et al [1] followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to compile all available and applicable decision-impact literature for the four MGAs. However, the authors did not use this same approach to compile literature reporting on the ability of the MGAs to stratify the 10-year risk of distant recurrence.There are several significant issues regarding the values for the prognostic performance of the MGAs that the authors used as inputs to their model.…”

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confidence: 99%

“…However, the authors did not use this same approach to compile literature reporting on the ability of the MGAs to stratify the 10-year risk of distant recurrence.There are several significant issues regarding the values for the prognostic performance of the MGAs that the authors used as inputs to their model. Hochheiser et al [1] cite a meta-analysis from the Early Breast Cancer Trialists' Collaborative Group [2] as the source of the input prognostic values for the 12-gene molecular score and PAM50 (commercial) score. The authors state that this meta-analysis "provided commonly cited rates for distant recurrence"; however, this citation predates the MGAs and does not contain any molecular data.…”

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Letter to the Editor

et al. 2019

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We read with interest the recent article by Hochheiser et al. regarding the economic impact of four multi-gene assays (MGAs) used to make decisions regarding chemotherapy use in women with newly diagnosed estrogen receptor-positive, HER2-negative breast cancer: 21-gene recurrence score (Oncotype DX R ), 70-gene signature (MammaPrint R ), PAM50 (commercial; Prosigna R ) and 12-gene molecular score (EndoPredict R ) [1]. We wish to highlight several deficiencies in the study design and the resultant conclusions.The authors described the variables that were utilized in their cost-effectiveness model, which included two elements related to the risk of distant recurrence according to MGA risk stratification: the 10-year probability of recurrence without chemotherapy (i.e., prognostic performance) and the 10-year relative risk of recurrence with and without chemotherapy (i.e., predictive performance). These values were then applied to decision-impact data (i.e., how testing with each MGA impacted chemotherapy treatment decisions) to model the cost-effectiveness of each MGA. Hochheiser et al. [1] followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to compile all available and applicable decision-impact literature for the four MGAs. However, the authors did not use this same approach to compile literature reporting on the ability of the MGAs to stratify the 10-year risk of distant recurrence.There are several significant issues regarding the values for the prognostic performance of the MGAs that the authors used as inputs to their model. Hochheiser et al. [1] cite a meta-analysis from the Early Breast Cancer Trialists' Collaborative Group [2] as the source of the input prognostic values for the 12-gene molecular score and PAM50 (commercial) score. The authors state that this meta-analysis "provided commonly cited rates for distant recurrence"; however, this citation predates the MGAs and does not contain any molecular data. Therefore, it is not possible to use this meta-analysis to obtain input values for the probability of recurrence without chemotherapy according to MGA risk group for the 12-gene or PAM50 (commercial) scores if the MGAs themselves did not exist yet. As such, the base prognostic variables used for these MGAs are questionable and may be invalid and, by association, so are any conclusions drawn from them.The EndoPredict test result is a combined clinico-molecular score (EPclin) that incorporates tumor size and nodal status with a 12-gene molecular score. Hochheiser et al. [1], used decision-impact data for the EPclin score in their model; however, the base case variables used for the prognostic and predictive performance appear to be for the 12-gene molecular score and not the EPclin score. This is inappropriate for two reasons. First, there is inconsistency within the authors' model regarding the use of the 12-gene molecular score and EPclin score. Second, the EPclin score is the actual test result provided to clinicians for use in treatment decisions and would have ...

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Multi-gene assays: effect on chemotherapy use, toxicity and cost in estrogen receptor-positive early stage breast cancer

Cited by 11 publications

References 45 publications

Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall

Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall

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Letter to the Editor

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