In a groundbreaking multi-center retrospective study published in BMC Cancer, researchers have unveiled compelling evidence supporting the use of a composite recurrence risk score (CR-score) model to guide ovarian function suppression (OFS) therapy in premenopausal women diagnosed with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer. This study is poised to transform current clinical decision-making by offering a validated, data-driven approach to personalize adjuvant therapy and improve patient outcomes.
Hormone receptor-positive, HER2-negative breast cancer constitutes a significant subset of early breast cancer cases in premenopausal women globally. The management of such cases has increasingly incorporated ovarian function suppression as a means to mitigate estrogen-driven tumor recurrence. However, the application of OFS, critical yet burdensome, lacks definitive, validated tools to identify patients who would gain the most benefit, often leading to either underuse or overtreatment.
This novel study builds upon the foundations laid by the seminal SOFT and TEXT clinical trials, which originally identified heterogeneity in treatment effects of OFS across patient subgroups. By employing the subgroup treatment effect pattern plot (STEPP) method, the researchers developed the CR-score model, incorporating nuanced patient and tumor characteristics to stratify recurrence risk and guide therapeutic choices. Yet, the key question remained—would this model hold predictive accuracy outside controlled trial settings?
Addressing this gap, the investigators retrospectively examined data from over 42 breast cancer centers across China, compiling patient records from January 2013 through December 2021. The multi-institutional nature of the cohort and the extensive timeframe provided a robust, real-world data landscape ideal for validating the CR-score’s clinical utility. The study cohort focused specifically on premenopausal women with HR+/HER2- early-stage breast cancer to maintain homogeneity and relevance to the population where OFS therapy is debated.
Advanced statistical techniques such as restricted cubic splines (RCS) were instrumental in this analysis, enabling the researchers to visualize continuous relationships between CR-scores and hazard ratios for breast cancer recurrence. This method illuminated the dynamic risk gradient with increasing CR-scores, providing insight into how incremental changes in patient-specific factors translate into significant prognostic differences.
Moreover, to address inevitable confounders inherent in observational data, propensity score matching (PSM) was utilized. This approach balanced baseline characteristics across patients receiving OFS versus those who did not, ensuring the observed survival differences were attributable to treatment effects rather than selection bias. Following PSM, Kaplan-Meier survival analyses were performed, revealing striking improvements in disease-free survival (DFS) among patients receiving OFS, particularly within the high CR-score subgroup.
The results were unequivocal: the hazard ratio for recurrence consistently rose with higher CR-scores, underscoring the model’s validity in capturing risk gradients. Notably, nearly 88% of patients who underwent OFS had a CR-score exceeding the threshold of 1.42, identifying them as high-risk candidates. Within this subgroup, OFS treatment conferred a substantial DFS benefit, with a hazard ratio of 0.571 (95% confidence interval: 0.403 to 0.809) and a highly significant p-value of 0.001.
Age-stratified analyses revealed that patients younger than 35 years derived even greater benefits from OFS. This subset, typically associated with more aggressive tumor biology and poorer prognosis, demonstrated significantly better outcomes when treated with OFS compared to their untreated counterparts. These findings reinforce the importance of incorporating age alongside the CR-score for nuanced risk stratification.
In addition to age, further subgroup assessments of patients receiving chemotherapy confirmed the significance of the CR-score in guiding OFS therapy. Even after adjusting for key variables such as tumor grade, estrogen receptor (ER) and progesterone receptor (PR) expression levels, and lymph node involvement, patients with higher CR-scores who received OFS experienced statistically significant improvements in DFS (p = 0.006). This multi-dimensional validation emphasizes the model’s robustness in complex clinical scenarios.
Intriguingly, the study also identified a subset of high-risk patients—those with elevated CR-scores but ER expression levels below 50%—who failed to benefit from OFS. This observation suggests that low ER expression might attenuate the efficacy of hormone-driven treatments like OFS, highlighting the need for tailored therapeutic strategies beyond the CR-score in certain biological contexts.
The clinical implications of this research are profound. By objectively quantifying recurrence risk and predicting who will benefit from adjuvant OFS, the CR-score model aids oncologists in avoiding unnecessary treatment in low-risk patients, sparing them potential side effects and preserving quality of life. Conversely, the tool ensures that high-risk patients receive optimal, evidence-backed care to minimize recurrence and improve long-term survival.
The integration of real-world evidence from diverse clinical settings across China further strengthens the generalizability of the CR-score model. Its adoption could streamline treatment protocols internationally, harmonizing the approach to premenopausal HR+/HER2- breast cancer management and sparking further research into personalized adjuvant therapies.
Looking ahead, future prospective studies and randomized trials could expand upon these findings by incorporating genomic data, exploring the biological underpinnings of differential OFS response, and refining the CR-score with emerging biomarkers. Additionally, longitudinal assessments may illuminate the impact of tailored OFS on overall survival and patient-reported outcomes, deepening our understanding of comprehensive breast cancer care.
In an era where precision medicine is revolutionizing oncology, this study exemplifies the power of data-driven models to translate complex trial findings into actionable clinical tools. It marks a pivotal step toward individualized treatment paradigms that balance efficacy with tolerability, ensuring that breakthrough interventions reach those most likely to benefit.
As breast cancer treatment paradigms evolve, the validated CR-score model offers hope for more rational, patient-centric strategies. For premenopausal women grappling with the uncertainty of adjuvant therapy decisions, this tool provides clarity and confidence grounded in rigorous science. It is a beacon of progress illuminating the path toward better outcomes and improved quality of life.
In summary, the validation of the CR-score for guiding ovarian function suppression in premenopausal women with HR+/HER2- early breast cancer heralds a new chapter in adjuvant therapy. It underscores the necessity of integrating sophisticated risk models in clinical workflows and epitomizes the marriage of clinical trial data with real-world applicability. This advancement is a testament to the relentless pursuit of precision oncology aimed at delivering the right treatment, to the right patient, at the right time.
Subject of Research: Adjuvant ovarian function suppression in premenopausal women with hormone receptor-positive, HER2-negative early breast cancer using a composite recurrence risk score model.
Article Title: Adjuvant ovarian function suppression in premenopausal women with hormone receptor-positive, human epidermal growth factor receptor 2–negative early breast cancer: a multi-center retrospective study.
Article References:
Lian, W., Li, L., Chen, D. et al. Adjuvant ovarian function suppression in premenopausal women with hormone receptor-positive, human epidermal growth factor receptor 2–negative early breast cancer: a multi-center retrospective study. BMC Cancer 25, 723 (2025). https://doi.org/10.1186/s12885-025-14120-0
Image Credits: Scienmag.com
