A new model combining erythrocyte levels with nutritional scores has emerged as a promising tool for predicting disease-free survival (DFS) outcomes among breast cancer patients post-surgery. This groundbreaking research, conducted at Shaoxing People’s Hospital, analyzed data from 536 female patients with invasive ductal carcinoma who underwent surgical treatment from January 2012 to December 2018.
Breast cancer remains the most prevalent malignancy among women, and its high mortality rate is often linked to distant metastasis or recurrent disease following surgery. Despite advancements in treatment strategies, it is imperative to identify accurate biomarkers for predicting potential recurrence to tailor more aggressive treatment approaches for at-risk patients.
The study set out to compare existing nutritional and inflammatory measures—known for their relevance to cancer prognosis—and their efficacy in predicting disease outcomes. Among the indicators evaluated was the Controlling Nutritional Status (CONUT) score, which assesses nutritional health based on albumin, lymphocyte count, and cholesterol levels. Findings indicated the CONUT score had the highest area under the curve (AUC) value of 0.667 for predicting DFS.
Interestingly, when erythrocyte levels were modified and integrated with the CONUT score to develop the new model—dubbed the Erythrocyte modified Controlling Nutritional Status (ECONUT)—the predictive power increased significantly, achieving an AUC of 0.722. Researchers concluded this model effectively identifies patients who may experience poorer postoperative outcomes.
Through the Kaplan-Meier survival analysis, patients with high ECONUT scores were observed to have markedly poorer DFS compared to those with lower scores. The study demonstrated high ECONUT scores stand as independent risk factors for postoperative recurrence, confirming their relevance through statistical analyses.
With nearly 30% of study participants diagnosed at pathological stage I and 59% at stage II, the results highlight the necessity of effective nutritional and inflammatory assessments among various breast cancer subtypes, particularly as the majority of participants were classified as Luminal B breast cancer patients.
The research advocates the incorporation of the ECONUT model within clinical practice as it has the potential to greatly improve the way clinicians evaluate postoperative prognosis and personalize treatment plans for breast cancer patients. By addressing the underlying nutritional status and its impact on patient health, the ECONUT score could pave the way for enhanced survival outcomes.
Despite its promising findings, the study acknowledges limitations such as its single-center retrospective design and calls for larger, multicenter studies for external validation of the ECONUT model. The authors also pointed out the need to explore the biochemical mechanisms connecting erythrocyte levels and nutritional variables to recurrence risks comprehensively.
Overall, the findings signify a significant advancement in using nutritional status as part of the prognostic assessment for breast cancer patients, emphasizing how integrating erythrocyte levels can refine predictive measures and potentially improve patient management following surgery.