Introduction

Breast cancer remains the most frequently diagnosed malignancy and the leading cause of cancer‑related morbidity among women worldwide. Despite significant advances in early detection and therapeutic strategies, chemotherapy continues to play a central role in the management of both early‑stage and advanced breast cancer. However, interindividual variability in treatment response and toxicity highlights the need for reliable prognostic and predictive markers to optimize patient outcomes. 

Among various laboratory parameters, routine liver and renal function tests increasingly recognized as potential indicators of prognosis in oncology practice (1). Chemotherapy agents commonly used in breast cancer, including anthracyclines, taxanes, cyclophosphamide, and platinum‑based compounds, metabolized and excreted primarily through hepatic and renal pathways.  Consequently, baseline organ function and chemotherapy‑induced alterations in liver and kidney parameters may significantly influence drug pharmacokinetics, treatment tolerability, and therapeutic efficacy. Understanding the prognostic implications of these laboratory tests is therefore clinically relevant (2). The liver plays a pivotal role in drug metabolism, protein synthesis, and systemic inflammatory regulation. Abnormalities in liver function tests such as alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, bilirubin, and serum albumin have been associated with disease burden, metastatic involvement, and systemic inflammation in cancer patients. These parameters may reflect both tumor biology and host response, making them potential prognostic indicators (3). Hypoalbuminemia, in particular, has been consistently associated with poor outcomes across multiple malignancies, including breast cancer. Serum albumin reflects nutritional status, hepatic synthetic capacity, and systemic inflammatory activity. Low albumin levels have been linked to increased chemotherapy toxicity, reduced treatment adherence, and inferior survival, underscoring its prognostic significance (4).

Renal function is equally critical in oncology care. Parameters such as serum creatinine, blood urea nitrogen, and estimated glomerular filtration rate are routinely used to assess kidney performance. Impaired renal function can limit chemotherapy dosing, increase the risk of adverse effects, and compromise overall treatment efficacy. Moreover, renal dysfunction may reflect underlying comorbidities that adversely affect cancer prognosis (5). Emerging evidence suggests that subtle changes in renal function tests, even within clinically accepted normal ranges, may have prognostic implications in patients receiving systemic anticancer therapy. Reduced glomerular filtration rate has been associated with increased mortality, treatment discontinuation, and hospitalizations among cancer patients, highlighting the importance of careful renal assessment (6). Beyond their role in drug handling, liver and kidney function tests may also serve as surrogate markers of systemic inflammation and metabolic dysregulation. Cancer‑related inflammation can alter hepatic protein synthesis and renal perfusion, leading to measurable laboratory abnormalities. These changes may precede overt clinical deterioration, offering an opportunity for early risk stratification (7).

Several retrospective studies have explored the association between liver or renal dysfunction and survival outcomes in breast cancer patients. However, the majority of these studies were limited by heterogeneous populations, retrospective designs, or a focus on advanced metastatic disease. Prospective data specifically evaluating the prognostic value of routine liver and renal function tests during chemotherapy remain scarce (8). In clinical practice, laboratory biomarkers that are inexpensive, widely available, and routinely measured are particularly attractive. Liver and renal function tests meet these criteria and are already integrated into standard oncologic care. Identifying their prognostic relevance could enhance clinical decision‑making without imposing additional diagnostic burden (9). Chemotherapy‑induced hepatotoxicity and nephrotoxicity represent significant challenges in breast cancer management. Elevations in liver enzymes or declines in renal function during treatment may necessitate dose reductions, treatment delays, or discontinuation, potentially compromising oncologic outcomes. Understanding whether these laboratory changes also predict long‑term prognosis is of considerable interest (10).

Prospective evaluation allows for systematic monitoring of laboratory parameters before, during, and after chemotherapy, enabling temporal associations between organ function and clinical outcomes to be assessed. Such an approach minimizes bias and enhances the validity of prognostic analyses compared with retrospective studies (11). In addition, breast cancer is a biologically heterogeneous disease, with prognosis influenced by tumor subtype, stage, molecular characteristics, and patient‑related factors. Integrating laboratory‑based prognostic markers with established clinical and pathological variables may improve risk stratification and personalized treatment planning (12). The potential role of liver and renal function tests as predictive markers of chemotherapy response is also noteworthy. Patients with preserved organ function may tolerate full‑dose chemotherapy and achieve better tumor control, whereas those with compromised function may experience suboptimal dosing and reduced efficacy (13). Despite the clinical relevance of these considerations, there is a lack of consensus regarding the prognostic thresholds and clinical interpretation of liver and renal function abnormalities in breast cancer patients undergoing chemotherapy. This uncertainty underscores the need for well‑designed prospective studies focusing specifically on these parameters (14). Furthermore, most existing studies have examined composite prognostic scores or inflammatory indices, while fewer have evaluated conventional liver and kidney tests independently. Clarifying the individual prognostic contributions of these routine parameters may facilitate their integration into everyday clinical assessment (15). Therefore, the present prospective study aims to evaluate the prognostic value of liver and renal function tests in breast cancer patients receiving chemotherapy.

Material and methods

Study Design: This study is designed as a prospective cohort study conducted to evaluate the prognostic value of liver and renal function tests in patients with breast cancer undergoing chemotherapy. The study follows newly diagnosed patients longitudinally from baseline assessment prior to chemotherapy initiation through the completion of treatment and subsequent follow‑up. Data collection and patient monitoring were performed over a 12‑month recruitment period, with extended outcome follow‑up to assess survival endpoints.

Sample Size Estimation and Sampling Method: A total of 150 patients with breast cancer were enrolled in the study. The sample size was determined based on feasibility considerations, patient availability during the study period, and consistency with similar prospective oncologic cohort studies. Convenience sampling was applied, whereby all eligible patients presenting to the radiotherapy and chemotherapy outpatient clinics during the recruitment period were invited to participate until the target sample size was reached.

Inclusion and Exclusion Criteria: Eligible participants were adult female patients with histologically confirmed breast cancer stages I to III, who were candidates for chemotherapy, including adjuvant or neoadjuvant regimens. Patients were required to have classification into one of the recognized molecular subtypes, including Luminal A, Luminal B, HER2‑positive, or Basal‑like, and to provide informed consent prior to enrollment. Exclusion criteria included evidence of metastatic (stage IV) disease, prior chemotherapy or radiotherapy for breast cancer, known chronic liver or kidney disease unrelated to malignancy, concurrent malignancies, active infectious or inflammatory conditions affecting laboratory parameters, pregnancy or lactation, and incomplete baseline laboratory data.

Study Procedures: At baseline, prior to the initiation of chemotherapy, comprehensive demographic and clinical data were collected, including age, tumor stage, molecular subtype, and treatment plan. Blood samples were obtained to assess baseline laboratory parameters, including liver function tests (alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total bilirubin, and serum albumin) and renal function tests (serum creatinine, blood urea nitrogen, and estimated glomerular filtration rate). Additional laboratory markers, including inflammatory markers, tumor markers, and anemia‑related indices, were also recorded.

During the chemotherapy course, patients were prospectively followed with periodic reassessment of laboratory parameters to monitor dynamic changes in liver and renal function. Treatment‑related adverse effects, chemotherapy dose modifications, and clinical responses were systematically documented. Patients were followed until the completion of chemotherapy, and treatment response was evaluated according to standard clinical and radiologic criteria. Long‑term follow‑up continued for up to two years to assess clinical outcomes, including overall survival (OS) and progression‑free survival (PFS).

Statistical Analysis: Statistical analyses were performed using appropriate statistical software. Continuous variables were expressed as mean ± standard deviation or median with interquartile range, depending on data distribution, while categorical variables were reported as frequencies and percentages. Comparisons between groups were conducted using independent‑sample t‑tests or Mann–Whitney U tests for continuous variables and chi‑square or Fisher’s exact tests for categorical variables. Survival outcomes were analyzed using the Kaplan–Meier method, with differences assessed by the log‑rank test. Multivariable Cox proportional hazards regression models were applied to identify independent prognostic factors. A two‑sided P value <0.05 was considered statistically significant.

Ethical Considerations: The study protocol was reviewed and approved by the Ethics Committee of Tabriz University of Medical Sciences (Ethics Code: IR.TBZMED.FMD.REC.1404.297). All procedures were conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment. Patient confidentiality was strictly maintained, and all data were anonymized and used exclusively for research purposes.

Results

Patients receiving neoadjuvant chemotherapy were significantly younger than those treated in the adjuvant setting (49.6 ± 9.8 vs. 54.1 ± 11.1 years, P=0.012) and more frequently presented with stage III disease (P<0.001). Basal‑like and HER2‑positive subtypes were more prevalent in the neoadjuvant group (P=0.021), whereas Luminal A tumors were predominant among adjuvant patients (P=0.034). Baseline liver function parameters, including ALT and AST, did not differ significantly between groups (P>0.05). However, serum albumin levels were modestly lower in the neoadjuvant group (3.91 ± 0.44 vs. 4.09 ± 0.39 g/dL, P=0.018). Renal function indices, including serum creatinine and eGFR, were comparable between groups (P>0.05), indicating similar baseline renal status prior to chemotherapy initiation (table 1).

Table 1. Baseline Demographic, Clinical, and Laboratory Characteristics of the Study Population (n=150)

Multivariable Cox regression analysis demonstrated that advanced tumor stage was a strong independent predictor of poorer overall survival, with stage III disease conferring a significantly higher risk compared with stages I-II (HR=2.41, P<0.001). Older age was also associated with increased mortality risk (HR per 10‑year increase = 1.28, P=0.014). Compared with Luminal A tumors, HER2‑positive (HR=1.94, P=0.011) and basal‑like subtypes (HR=2.63, P<0.001) showed significantly worse survival, whereas Luminal B subtype was not independently associated with outcome (P=0.152). Patients receiving neoadjuvant chemotherapy experienced a higher mortality risk than those treated in the adjuvant setting (HR=1.46, P=0.043). Higher baseline serum albumin levels were significantly protective (HR=0.58, P=0.006), while preserved renal function, reflected by higher eGFR, was associated with improved survival (HR=0.82, P=0.017). In contrast, baseline ALT levels were not significantly associated with overall survival (P=0.183) (table 2).

 Table 2. Multivariable Cox Proportional Hazards Analysis of Prognostic Factors for Overall Survival

Figure 1 summarizes the multivariable Cox regression analysis for overall survival, demonstrating clear between‑group differences across clinic pathological and biochemical factors. Patients with stage III disease exhibited a significantly higher mortality risk compared with those with stage I-II tumors (P<0.001). Increasing age was associated with worse survival (P=0.014). When molecular subtypes were compared with Luminal A tumors, both HER2‑positive (P=0.011) and basal‑like subtypes (P<0.001) showed significantly poorer outcomes, whereas no significant difference was observed for Luminal B tumors (P=0.152). Patients treated with neoadjuvant chemotherapy had inferior survival compared with those receiving adjuvant therapy (P=0.043). In contrast, higher serum albumin levels were associated with significantly improved survival (P=0.006), and better renal function, reflected by higher eGFR, was likewise protective (P=0.017). Baseline ALT levels did not differ significantly between survival outcomes (P=0.183).

Figure 1. Forest Plot of Multivariable Cox Regression for Overall Survival

Figure 2 illustrates the Kaplan Meier analysis of overall survival stratified by tumor stage, revealing a pronounced divergence between the two groups over time. Patients diagnosed with stage III breast cancer experienced significantly poorer overall survival compared with those with stage I-II disease (log‑rank test, P<0.001). The survival curves separated early during follow‑up and continued to diverge throughout the observation period, indicating a persistent adverse effect of advanced stage on mortality risk. In contrast, patients with early‑stage tumors maintained higher survival probabilities across all time points, underscoring the prognostic advantage of earlier disease stage.

Figure 2. Kaplan Meier Overall Survival Curves According to Tumor Stage

 Discussion