Ki‐67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study

Zhang, Yanna; Zhou, Yidong; Mao, Feng; Yao, Ru; Sun, Qiang

doi:10.1002/cac2.12024

Cited by 26 publications

(28 citation statements)

References 40 publications

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“…Up to now, there were several models using clinical parameters to estimate the RS with TAILORx cutoffs [ 20 , 25 , 26 , 29 , 30 ]. Our nomogram has a similar discriminative ability with models developed by Lee et al [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

“…Meanwhile, Ki-67 was not regularly recorded in the NCDB thus was not incorporated into their model, whereas our study demonstrated the importance of this biomarker in predicting high-risk RS. Recently, Zhang et al developed a model by using the Ki-67 index, PR expression, tumor grade, and tumor size with a predictive accuracy of 86.5%, which also had prognostic value [ 30 ]. However, it’s hard to perform a direct comparison between our two models because of the decision tree method they used.…”

Section: Discussionmentioning

confidence: 99%

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A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

Huang

et al. 2021

J Transl Med

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Background The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients > 50 years with RS > 25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS. Methods We included patients diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative who underwent the 21-gene RS testing and aged > 50 years. The primary outcome was high-risk RS (> 25). Univariate and multivariate analyses were performed to identify significant predictors. A predictive nomogram based on logistic model was developed and evaluated with receiver operating characteristic (ROC) curves. The nomogram was internally validated for discrimination and calibration with bootstrapping method, and externally validated in another cohort. We then assessed the nomogram in different subgroups of patients and compared it with several published models. Results A total of 1100 patients were included. Five clinicopathological parameters were used as predictors of a high-risk RS, including tumor grade, histologic subtype, ER expression, PR expression, and Ki-67 index. The area under the curve (AUC) was 0.798 (95% CI 0.772–0.825) and optimism adjusted AUC was 0.794 (95% CI 0.781–0.822). External validation demonstrated an AUC value of 0.746 (95% CI 0.685–0.807), which had no significant difference with the training cohort (P = 0.124). Calibration plots indicated that the nomogram-predicted results were well fitted to the actual outcomes in both internal and external validation. The nomogram had better discriminate ability in patients who had tumors > 2 cm (AUC = 0.847, 95% CI 0.804–0.890). When compared with four other existing models, similar AUC was observed between our nomogram and the model constructed by discriminate Lee et al. Conclusions We developed a user-friendly nomogram to predict the high-risk RS in luminal breast cancer patients who were older than 50 years of age, which could guide treatment decision making for those who have no access to the 21-gene RS testing.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

Huang

et al. 2021

J Transl Med

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“…In general, patients with ER‐positive tumors are considered eligible for endocrine therapy. In contrast, patients with ER‐negative tumors are more likely to benefit from chemotherapy and usually have a worse outcome than the former [ 2 , 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Estrogen receptor‐low breast cancer: Biology chaos and treatment paradox

Cai

et al. 2021

Cancer Communications

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Hormone receptor testing mainly serves the purpose of guiding treatment choices for breast cancer patients. Patients with estrogen receptor (ER)-positive breast cancers show significant response to endocrine therapy. However, the methods to define ER status and eligibility for treatment remain controversial. Despite recent guidelines considering staining ≥1% of tumor nuclei by immunohistology as ER-positive, it has raised concerns on the benefit of endocrine therapy for tumors with ER 1%-10% expression, termed "ER-low positive". This subgroup accounts for 3% to 9% of all patients and is likely to have unique molecular features, and therefore distinct therapeutic response to endocrine therapy compared with ER-high positive tumors. The latest guidelines did not provide detailed descriptions for those patients, resulting in inconsistent treatment strategies. Consequently, we aimed to resolve this dilemma comprehensively. This review discusses molecular traits and recent ER-low positive breast cancer innovations, highlighting molecular-targeted treatment rather than traditional unified endocrine therapy for future basic and clinical research.

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“…Up to now, there were several models using clinical parameters to estimate the RS with TAILORx cutoffs (20,25,26,29,30). Our nomogram has a similar discriminative ability with models developed by Lee et al (20,25).…”

Section: Discussionmentioning

confidence: 54%

A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

Huang

et al. 2020

Preprint

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Background: The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients >50 years with RS >25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS.Methods: We included patients diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative who underwent the 21-gene RS testing and aged >50 years. The primary outcome was high-risk RS (>25). Univariate and multivariate analyses were performed to identify significant predictors. A predictive nomogram based on logistic model was developed and evaluated with receiver operating characteristic (ROC) curves. The nomogram was internally validated for discrimination and calibration with bootstrapping method. We then assessed the nomogram in different subgroups of patients and compared it with several published models.Results: A total of 1100 patients were included. Five clinicopathological parameters were used as predictors of a high-risk RS, including tumor grade, histologic subtype, ER expression, PR expression, and Ki-67 index. The area under the curve (AUC) was 0.798 (95% CI 0.772-0.825) and optimism adjusted AUC was 0.794 (95% CI, 0.781-0.822). Calibration plots indicated that the nomogram-predicted results were well fitted to the actual outcomes. The nomogram had better discriminate ability in patients who had tumors >2cm (AUC=0.847, 95% CI 0.804-0.890). When compared with four other existing models, similar AUC was observed between our nomogram and the model constructed by discriminate Lee et al.Conclusions: We developed a user-friendly nomogram to predict the high-risk RS in luminal breast cancer patients who were older than 50 years of age, which could guide treatment decision making for those who have no access to the 21-gene RS testing.

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Ki‐67 index, progesterone receptor expression, histologic grade and tumor size in predicting breast cancer recurrence risk: A consecutive cohort study

Cited by 26 publications

References 40 publications

A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

Estrogen receptor‐low breast cancer: Biology chaos and treatment paradox

A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

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