Significance of the inflammatory-immune-nutritional (IINS) score on postoperative survival and recurrence in breast cancer patients: a retrospective study

Introduction

Breast cancer (BC) is the most prevalent malignant neoplastic disease affecting women globally (Zannetti, 2023). According to information on epidemiology, the disease is most common among Chinese women (Sung et al., 2021). Although the outlook for those diagnosed with breast cancer is relatively favorable in comparison to other forms of cancer (such as those affecting the gastrointestinal system or the lungs), the survival rates of patients with advanced or disseminated breast cancer remain poor (D’Eredita’ et al., 2001). At present, traditional prognostic indicators include the patient’s age, the TNM stage (tumor-lymph nodes-metastases), the histological grade, the estrogen receptor (ER), the progesterone receptor (PR), and the human epidermal growth factor 2 (HER2) status, all of which are employed as prognostic indicators for breast cancer (Xie et al., 2022). However, survival duration differs even among patients who are diagnosed at the same stage of disease and with the same causal kind of disease (Wang et al., 2023). Given the absence of an individualized assessment, our study employed a combination of validated biochemical indicators to examine their influence on the future prognosis of breast cancer patients (He et al., 2023).

In recent times, an increasing number of potential prognostic indicators that may be employed to forecast the prognosis of breast cancer have been identified and adopted in clinical practice (Liang et al., 2021). Prior research has unequivocally shown that dietary status and biomarkers reflecting systemic inflammatory responses are significant predictors of cancer prognosis (Cuk et al., 2023). Elements of systemic inflammation, such as platelets, lymphocytes and high-sensitivity C-reactive protein (hs-CRP), and biochemical markers in the blood, such as C-reactive protein levels and albumin levels, are valuable prognostic indicators for cancer, including breast cancer (Takamizawa et al., 2020). Currently, the platelet-to-lymphocyte ratio (PLR) and prognostic nutritional index (PNI) have been demonstrated to be reliable predictors for breast cancer patients undergoing surgical intervention, but it remains controversial as to whether they can be independent prognostic factors (Tiainen et al., 2021). In addition, the inflammation-immune-nutrition (IINS) value has been associated with the prognosis of hepatocellular carcinoma and colorectal carcinoma (Li et al., 2021). The predictive value of IINS in breast cancer has not been supported by any studies.

In order to determine the best independent prognostic markers, we retrospectively examined the progression-free survival (PFS) and overall survival (OS) of 200 breast cancer patients in relation to preoperative IINS, PLR, and PNI.

Materials and Methods

Definition

We used X-tile software version 3.6.1 (https://medicine.yale.edu/lab/rimm/research/software/, Yale University School of Medicine, New Haven, CT, USA) to select the optimal threshold values for high-sensitivity C-reactive protein (hs-CRP), lymphocytes (LYM), and albumin (ALB) based on the association of each metric with patient overall survival (Yeun & Kaysen, 1998). Three categories of hs-CRP were created based on the two critical values (score 0: ≤6 mg/L, score 1: >6 and ≤12 mg/L, and score 2: >12 mg/L); whereas LYM and ALB were categorized as follows: lym (score 0: >1.6 × 10⁹/L, score 1: >1.1 × 10⁹/L and ≤1.6 × 10⁹/L, and score 2: ≤1.1 × 10⁹/L); ALB (score 0: >38.4 g/L, score 1: >34.8 g/L and ≤38.4 g/L, score 2: ≤34.8 g/L). The IINS was then calculated by adding the scores for hs-CRP, LYM, and ALB. Given that the study’s median IINS was 2, an IINS of greater than 2 was considered to belong to the high IINS group. As an example, a patient’s preoperative hs-CRP, LYM, and ALB values were 14.0 mg/L, 1.5 × 10⁹/L, and 30.6 g/L. The hs-CRP, LYM, and ALB scores were then 2, 1, and 2, respectively. Then, the IINS score was 5 (high IINS) (Li et al., 2021).

To appraise the prognosis of IINS in comparison with other markers of prediction, we also looked at the prognostic manifestations of PLR and PNI, and the optimal thresholds for PLR and PNI that are derived from the subject’s work characterization (receiver operating characteristic, ROC) plots are shown in Table S1. PLR and PNI are defined as follows: PLR = platelet/lymphocyte count, PNI = albumin + 5 × lymphocyte count (Camp, Dolled-Filhart & Rimm, 2004).

Results

Prognostic value of IINS in progression-free survival

Table S1 shows the area under the ROC curve (AUC) of PFS for IINS, PLR and PNI. Results showed that IINS (AUC: 0.735; 95% CI [0.622–0.809]) predicted PFS better than PLR (AUC: 0.724; 95% CI [0.655–0.794]) and PNI (AUC: 0.694; 95% CI [0.619–0.769]). On the basis of the ROC curve, we found that the IINS had the best area under the curve with a value of 0.735 (As shown in Fig. 1). The Kaplan-Meier survival curves showed that patients in the low IINS group had a longer progression-free survival (Fig. 2). Integrating the results of area under the curve and multivariate Cox regression analyses, the study confirms that IINS is a novel prognostic indicator of progression-free survival in breast cancer patients.

Prognostic value of IINS in overall survival

Table S1 shows the area under the ROC curve (AUC) of OS for IINS, PLR and PNI. The findings revealed that IINS (AUC: 0.738; 95% CI [0.642–0.834]) was a better predictor of OS than PLR (AUC: 0.700; 95% CI [0.623–0.777]) and PNI (AUC: 0.713; 95% CI [0.615–0.811]) On the basis of the ROC curve, we found that the IINS had the best area under the curve with 0.738 points (as shown in Fig. 3). Similarly, the Kaplan-Meier survival curve showed that patients in the low IINS group had longer overall survival (Fig. 4). Integrating the area under the curve with the results of multivariate Cox regression analyses, the study confirms that IINS is also a novel prognostic indicator of overall survival in breast cancer patients.

Discussion

In this study, we revealed that IINS might function as a reliable predictive score for those who have gone through breast cancer surgery. The findings of this study indicate that IINS is a prognostic indicator affecting BC patients, with PFS and OS being considerably better in individuals with low IINS than in patients with high IINS. Additional comparisons revealed that IINS performed better in terms of prognosis than other indices including the PLR and PNI. To the greatest extent of our knowledge, this retrospective study is the first to appraise the predictive feasibility of the IINS in BC patients undergoing post-surgical treatment.

Blood and biochemical markers had been shown in a rising number of studies to be prognostic indicators for cancer (Wattacheril et al., 2023). The majority of present-day prognostic biomarkers, on the other hand, are various combinations of two markers in serum tests, which do not represent the immune and nutritional activities of the body, resulting in bias and poor prediction by default (De Larco, Wuertz & Furcht, 2004). A good prognostic indicator for resectable colorectal, hepatocellular, and endometrial cancers has been demonstrated to be the inflammation-immunity-nutrition score based on the preoperative hs-CRP, LYM, and ALB composite score (Antonio et al., 2015; Wang et al., 2024). The role of these indicators can also be used to explain the predictive value of IINS for breast cancer. Low immunological and nutritional status together with a strong inflammatory response are all indicators of high IINS, which is typically caused by lymphopenia, hypoalbuminemia, and elevated hs-CRP (Hua et al., 2020). Value-added, invasion, and metastasis of malignant tumors are strongly correlated with the inflammatory response that occurs throughout the human body and is mostly mediated by diet and immunology (Shankaran et al., 2001; Swierczak et al., 2015). Hypoalbuminemia weakens the immune system at large, which promotes the growth of tumor cells (Cong et al., 2020). IINS is also a pretty decent predictor of the prognostic value of breast cancer. Lymphocytes are the basis of the cell-mediated antitumor immune response, which inhibits tumor cell proliferation and metastasis (Muangto et al., 2022). Low lymphocyte counts are associated with a poor prognosis in a number of malignancies. Lymphocyte counts reduce immune surveillance against cancer (Zheng et al., 2020). Consequently, IINS may be a useful, efficient, and easily accessible clinical prognostic indication for people with breast cancer.

In a comparative ROC analysis of IINS, PLR, and PNI, it was found that all three metrics demonstrated significance both for PFS and OS. In order to further clarify the clinical application value of each metric, a comparison was conducted of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The results showed that the PPV and NPV assessed by IINS were 65% and 54% for PFS and 41% and 39% for OS. These PPV and NPV values for IINS were higher than those for PLR and PNI, a result that is potentially clinically important to facilitate personalized care for breast cancer (BC) patients and simplify follow-up. However, the PPV and NPV results of IINS are not ideal but only favorable to PLR and PNI. For this reason, IINS should only be used as a supplementary indicator in future clinical practice. The results of this study should also be viewed with caution.

Limitation

The key advantage of the current study is that we employed a newly developed indicator, IINS, which was based on hs-CRP, LYM, and ALB and may perform better than some of the conventional indicators generated from inflammatory, immunological, and nutritional components (Song et al., 2021). However, there are some limitations to our study. First, despite the fact that the IINS threshold value was determined from clinical reference values, there were variations in sample size and patient selection criteria across studies, which will inevitably bias the results (Wang et al., 2024). Additionally, while the system is uncomplicated and pragmatic in its categorization, it operates under the assumption of equal weighting, which may not fully capture the inherent biological complexity of the biomarkers in question. Consequently, the interpretation of results should be approached with a degree of circumspection (Cheng et al., 2025; Zhang et al., 2022).

Although we built a validation cohort for internal validation, the lack of external validation compromises the robustness and generalizability of the study. Secondly, this study involved a relatively small sample size and included patients from only one center, and the conclusions may be potentially biased. To confirm our findings, multicentre, large-scale prospective studies are needed. Thirdly, the relationship between postoperative IINS changes and the prognosis of these patients has not yet been investigated in our study, which focused on the prognostic significance of preoperative IINS. Longitudinal studies should be performed in the future to verify the prognostic significance of the fact that many patients received multiple treatments for tumor recurrence during the follow-up period, which also influenced the prognosis. Finally, our study included a small amount of clinical data that could be used in the future to characterize the dynamics of patients as their disease progresses by statistically analyzing their comorbidities and other biochemical data, and the results may be more instructive in the future.

Conclusion

According to our findings, preoperative IINS may be a potent prognostic predictor in patients with operable breast cancer. In the case of prognosis in particular, IINS is superior to PLR or PNI. Suggesting that it may give a straightforward way of identifying individuals with bad prognosis and the chance to lead therapy and follow-up efforts to improve their status.

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