Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Predicting Complete Pathological Response in Rectal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy

Introduction

Colon and rectal cancers together are the third most common malignancy among men and the second among women [1]. Colorectal cancer affects approximately 150 000 estimated new patients in the United States per year and of these cases 30% are due to rectal cancer [2]. While these cancers are reported as the third leading cause of cancer-related deaths in both men and women, determining mortality due to rectal cancer alone is difficult due to the large number of deaths from rectal cancer being misclassified as colon cancer [2,3]. After pathologic confirmation and careful staging, there are strong recommendations for neoadjuvant therapy in stage II (T3 or T4 node-negative) and stage III (node-positive) so-called locally advanced disease [3]. Pathologic response after the neoadjuvant approach has been shown to reduce recurrence and improve survival in patients with locally advanced rectal cancer [4]. However, the response to neoadjuvant therapy is highly variable among patients, making it crucial to identify specific biomarkers that can predict which patients are likely to benefit and which are not.

Recent evidence increasingly recognizes cancer-associated systemic inflammation as a significant determinant of survival [5]. Various studies have demonstrated that the neutrophil-to-lymphocyte ratio (NLR), a hematologic inflammatory marker, could be a predictive marker for oncological outcomes and response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer [6–9]. In a recent meta-analysis of 22 studies comprising 6316 patients, elevated pre-nCRT NLR was found to be strongly associated with worse treatment outcomes in patients with rectal cancer [10]. Although many studies have explored the correlation between NLR and outcome, few have examined the relationship between NLR and pathologic responses. Therefore, this retrospective study from a single center in Turkey included 187 patients with rectal cancer who underwent nCRT, and aimed to evaluate the association between NLR and pathologic response as well as outcome.

Material and Methods

ETHICS STATEMENT:

The study was conducted according to the standards of the Helsinki Declaration and approval was obtained from the Health Sciences University Antalya Training and Research Hospital’s clinical research ethics committee on 30.09.2021, with decision number 15/19.

PATIENTS:

Our study included 187 patients with rectal cancer treated at the medical oncology department of the Health Sciences University Antalya Training and Research Hospital between 2016 and 2020. All patients had histologically confirmed stage III rectal adenocarcinoma and underwent surgery after approximately 4 to 6 weeks of nCRT followed by a 4-to-8-week interval.

DATA COLLECTION:

Demographic, clinicopathologic, and laboratory data of the patients were retrospectively recorded using archival files and hospital database. Absolute neutrophil (normal: 2–7.15×10³/mm³) and lymphocyte (normal: 1.16–3.18×10³/mm³) values were extracted from hospital computer system complete blood count results within 2 weeks before nCRT initiation and after surgery. NLR was calculated as the absolute number of neutrophils divided by the absolute number of lymphocytes. Postoperative pathology reports were also evaluated from archive files to record pathologic response to nCRT.

PATHOLOGIC RESPONSE CRITERIA AND STUDY OUTCOMES:

The degree of primary tumor regression was assessed in 4 categories using the modified RYAN scheme, as recommended by the College of American Pathologists [11]: complete response (no viable cancer cells), near-complete response (single cells or rare small groups of cancer cells), partial response (residual cancer with evident tumor regression, but more than single cells or rare small groups of cancer cells), and poor or no response (extensive residual cancer with no evident tumor regression). Progression-free survival (PFS) was calculated from surgery to local or distant failure or death. Overall survival (OS) was defined as the time from initial diagnosis to death from any cause or date of last known contact.

STATISTICAL ANALYSIS:

For categorical variables, descriptive statistics are presented as frequency (n) and percentage (%), and for continuous variables as mean, standard deviation (SD), median, and interquartile range (IQR: 25^th–75^th percentile). Relationships between categorical variables were examined using the Pearson chi-square test and Fisher’s exact test. The assumption of normal distribution was checked with the Shapiro-Wilk test. Non-parametric comparisons of continuous variables between independent groups were analyzed using the Mann-Whitney U test and Kruskal-Wallis test, while parametric comparisons were conducted with the independent t test and one-way ANOVA. In all post hoc comparisons, Bonferroni correction was applied.

To differentiate among patients based on NLR values and to determine a cut-off point in predicting progression, receiver operating characteristic (ROC) analysis was conducted. The results of the analysis were presented with the area under the curve (AUC), cut-off points, sensitivity and specificity values, and 95% confidence intervals (CI). The optimal cut-off point for NLR was calculated using the Youden index.

Survival curves were generated using the Kaplan-Meier method, and OS and PFS rates according to NLR groups were compared using the log-rank test. Factors affecting OS and PFS were evaluated using univariate and multivariate Cox regression analyses. Variables with a P<0.1 in univariate analysis were used to build a multivariate model. The results are presented with hazard ratios (HR) and 95% CI.

The study sample size was calculated using the G*Power 3.1.9 program based on the effect size determined from the study of Kim et al [9]. All statistical analyses were performed using IBM SPSS 23.0 software package (IBM Corp., Armonk, NY) and P values less than 0.05 were considered statistically significant.

Results

PATIENT CHARACTERISTICS AND TREATMENT:

The demographic, clinicopathological data, and treatment responses of the patients are summarized in Table 1. The study included 187 patients with an average age of 64.59±11.19, of which 65.8% were male. During chemoradiotherapy, 51.3% of the patients received capecitabine. The most common surgical procedure performed was low anterior resection (LAR) (82.4%), and pathological complete response was achieved in 34 patients (18.2%) after nCRT.

PRE-NCRT AND POSTOPERATIVE LABORATORY PARAMETERS:

Descriptive statistics for the biochemical parameters of the patients at diagnosis and in the postoperative period are provided in Table 2.

ROC CURVE FOR RECURRENCE PREDICTION AND PATIENT CHARACTERISTICS ACCORDING TO NLR CUT-OFF:

In the ROC analysis conducted to determine the discriminative performance of the NLR parameter at diagnosis in predicting progression, the cut-off value was determined to be 3.63 (AUC=0.609 [95% CI: 0.535–0.679]; P=0.011) (Figure 1). Having an NLR threshold level >3.63 at diagnosis could predict PFS with 39.44% sensitivity and 81.9% specificity.

The general characteristics of the patients divided into 2 groups according to the NLR cut-off value are compared in Table 3. When the treatment response rates of the 2 groups were analyzed, the near-complete response rate was higher in patients with NLR <3.63 (38% vs 18%; P=0.035). The poor response rate was significantly higher in the group with NLR >3.63 (64% vs 43.8%; P=0.014).

PATIENT CHARACTERISTICS ACCORDING TO PATHOLOGICAL RESPONSE:

Table 4 compares the general characteristics of patients according to pathologic response after treatment. There was no significant difference between the hemoglobin (P=0.247), neutrophil (P=0.198), lymphocyte (P=0.580), platelet (P=0.903), and lactate dehydrogenase (LDH) (P=0.756) values at the time of diagnosis. Although NLR values were higher in patients with partial response and patients with no response, this difference was not statistically significant (P=0.127). The rate of NLR >3.63 in patients with no response to treatment (41.7%) was significantly higher than in patients with near-complete response (14.8%) (P=0.040).

PROGNOSTIC FACTORS:

A multivariate logistic regression analysis was performed to determine the risk factors independently associated with poor pathologic response in the patients included in the study, and the results are presented in Table 5. Poor pathological response was found to be associated with younger ages (P=0.006) and with NLR >3.63 at diagnosis (P=0.012).

The 5-year PFS rate was 63.6% in the NLR <3.63 group and 40.1% in the NLR >3.63 group. PFS rates were significantly lower in the group with NLR >3.63 (P=0.007) (Figure 2). The 5-year OS rate was 72.3% in the NLR <3.63 group and 63.1% in the NLR >3.63 group. Although the OS rates were lower in the NLR >3.63 group, this difference was not statistically significant (P=0.077) (Figure 3).

The risk factors affecting PFS in patients were evaluated by univariate and multivariate Cox regression analysis and are shown in Table 6. According to univariate analysis, PFS was associated with sex, the type of chemotherapy drug used, and NLR >3.63 at the time of diagnosis. Multivariate analysis showed that the risk of poor PFS was higher in patients who received 5-Fluorouracil (5-FU) as a chemotherapy agent (P=0.011).

The results of univariate and multivariate Cox regression analysis to determine the risk factors affecting OS in patients are presented in Table 7. In univariate analyses, age, chemotherapy agent used, and type of surgery were associated with OS, while decreasing age (P=0.017), 5-FU use (P=0.020), and MILES operation (P=0.025) negatively affected OS.

Discussion

Neoadjuvant therapy for rectal cancer is used to down-stage tumors, reduce local recurrences, and improve survival. Pathologic response after nCRT has been shown to reduce recurrence and improve survival in patients [4,12]. Inflammatory response plays a significant role in tumor development, progression, immune surveillance, and response to treatment. NLR is a cost-effective, easily accessible inflammatory parameter derived from peripheral blood count, which can predict prognosis, unlike traditional risk markers. The prognostic role of NLR has been demonstrated in many solid tumors, as shown in a recent meta-analysis including 100 studies [13]. Pre-treatment high NLR has been correlated with poor response to treatment, adverse pathological outcomes, and poor survival [14]. In our study, low preoperative NLR (<3.63) was found to be a good prognostic factor in indicating pathological response, and high NLR (>3.63) was associated with worse PFS.

In our study of 187 patients receiving nCRT, the mean age was 64.59±11.19 years, and 65.8% were male. In a study conducted by Nagasaki et al involving 201 patients, 52.2% were over 60 years old and 68.9% were male [15]. The sex and average age of patients in our study are consistent with the literature.

Regarding the chemotherapy agent used during nCRT, Kim et al [9] reported that 31.3% of patients received capecitabine, while Nagasaki et al [15] included only patients receiving 5-FU. Our study is more suitable for comparing responses to both chemotherapy agents.

Similar to the rate of complete responders in our study, in the study by Nagasaki et al [15], 26 patients (12.9%) had complete response and 175 patients (87.1%) were non-responsive.

The NLR cut-off value in our study is consistent with previous studies in the literature [9,15,16]. The variation in NLR values within a certain range can be attributed to the different patient numbers included in the studies and the inclusion of patients with different stages of rectal cancer. In our study, consistent with the literature [15,17], patients with high NLR were significantly older than those with low NLR. The literature shows that high NLR is generally associated with older average age. In the study by Nagasaki et al [15], similar to our study, the high NLR group had a higher proportion of male patients, while Dimitriou et al [17] included more patients and found an equal sex distribution in the high NLR group, contrary to our findings.

In our study addressing the relationship between NLR and pathological response, patients were categorized into 4 groups: complete response, near-complete response, partial response, and no response. Examining the treatment response rates according to NLR groups, a higher rate of near-complete response was observed in patients with NLR <3.63 (38% vs 18%; P=0.035). A significantly higher rate of poor response was found in the group with NLR >3.63 (64% vs 43.8%; P=0.014). In contrast, Nagasaki et al [15] examined the pathological response in 2 groups (complete response or no response) based on NLR and, unlike our findings, reported a higher rate of poor response in both groups with NLR <3.00 and NLR ≥3.00 (86% vs 90.9%; P=0.458). Similar to our results, Dimitriou et al found a higher rate of near-complete response in the low NLR group [17]. The larger patient cohort in Dimitriou’s study and its analysis of pathological responses in 4 groups, akin to our study, makes it more aligned with our findings. Other studies in the literature predominantly found that low NLR was associated with good prognosis and high NLR was associated with poor prognosis, suggesting that a high neutrophil count can promote tumor development in the tumor microenvironment.

No significant difference was observed between the age averages (P=0.188) and sex distributions (P=0.292) of patients when categorized according to pathological response. The study by Kim et al [9] also reported similar findings regarding the age averages (P=0.386) and sex distributions (P=0.379) of the groups. In our study analyzing pathological response in 4 groups, there were more patients who received capecitabine in both the complete and near-complete response groups (55.9% and 57.4%, respectively). However, Kim et al [9] reported a higher percentage of patients receiving 5-FU among those with a good pathological response (61.4%). In our study, there were more patients receiving 5-FU in the partial response and non-response groups (52.9% and 58.3%, respectively). Similarly, in the study by Kim et al [9], there were more patients who received 5-FU (73.6%) in the poor response group. Nonetheless, akin to our study and Kim et al’s study, the chemotherapy agent used was not associated with pathological response (P=0.463 and P=0.089, respectively).

In our study and in the study conducted by Kim et al [9], no significant differences were found in the hemoglobin (P=0.247 and P=0.276, respectively) or neutrophil (P=0.198 and P=0.90, respectively) values of patients according to pathological response at the time of diagnosis. In our study, no significant difference was found in lymphocyte (P=0.580) or platelet (P=0.903) values according to pathological response, whereas Kim et al found a significant difference in lymphocyte (P=0.025) and platelet (P=0.002) values.

In our study, the proportion of patients with NLR >3.63 was significantly higher in the group without treatment response (41.7%) compared to the group with near-complete response (14.8%) (P=0.040). Similarly, in a study by Kim et al [9], NLR values were significantly higher in the poor response group compared to the good response group (P=0.001). Consistent with the study by Kim et al [9], our multivariate logistic regression analysis indicated that having an NLR at time of diagnosis above the cut-off value increased the risk of poor pathological response.

In our study, the 5-year PFS was significantly lower in the group with NLR >3.63 (P=0.007). Unlike our study, Nagasaki et al [15] did not find a significant relationship between NLR and PFS (NLR <3.0: 75.8% and NLR ≥3.0: 75.8%; P=0.8437); however, Kim et al [9] found significantly lower PFS rates in the NLR ≥2.0 group, similar to our findings (NLR <2.0: 86.8% and NLR ≥2.0: 70.7%; P=0.014).

In univariate analyses, sex (P=0.040), chemotherapy agent used (P=0.006), and NLR >3.63 at diagnosis (P=0.008) were identified as risk factors affecting PFS. In contrast, Nagasaki et al [15] found no significant relationship of sex and NLR value with PFS (P=0.553 and P=0.843, respectively). Yoshida et al [16] also found that sex was not associated with progression, while an NLR value of ≥2.58 was associated with PFS (P=0.018). Dimitriou et al [17] found no significant relationship between sex and PFS, but found a significant association between NLR >4.7 and survival (P=0.207 and P=0.014, respectively). Multivariate analyses in our study determined that patients treated with 5-FU had a higher risk of poor PFS (P=0.011). Since no study demonstrating the relationship between chemotherapy agent and PFS was found in the literature, a comparison with our study could not be made. In their multivariate model, Nagasaki [15] did not include the same parameters as our study, so no comparison could be made. Kim et al [9] did not examine the effect of sex and chemotherapy agent used on PFS in their multivariate analysis, preventing comparisons with the present study, although they found a significant relationship between NLR <2.0 and PFS (P=0.014). Both Yoshida et al and Dimitriou et al found a significant association between high NLR and PFS in their multivariate analyses, differing from our study (P=0.001 and P=0.048, respectively) [16,17].

In our study, although the OS rates were lower in the group with NLR >3.63, this difference was not statistically significant (P=0.077). Similarly, in the study by Nagasaki et al [15], OS rates were lower in the high NLR group, but this difference was statistically significant (NLR <3.0: 92.5% and NLR ≥3.0: 80.5%; P=0.0108). Conversely, in the study conducted by Kim et al [9], OS rates in the NLR ≥2.0 group were significantly higher (NLR <2.0: 71.9% and NLR ≥2.0: 92.4%; P=0.027).

Univariate analyses conducted to identify risk factors affecting patients’ OS revealed that age (P=0.027), chemotherapy agent used (P=0.024), and type of surgery (P=0.009) were associated with OS. In Nagasaki et al’s study [15], age (P=0.407) and type of surgery (P=0.067) were not found to be related to OS, and, unlike our study, NLR value (P=0.015) was found to be related to poor survival. A lack of additional studies examining the relationship between chemotherapy agent and OS precluded a comparison with our study.

In the multivariate analysis for OS, younger age (P=0.017), the use of 5-FU (P=0.020), and the MILES operation (P=0.025) were found to adversely affect OS. In Nagasaki et al’s study [15], variables with P<0.1 in univariate analyses were not the same as in our study and could not be included in the multivariate model for decreasing age and 5-FU use. Only the MILES operation was included in the multivariate model, but its effect on OS could not be demonstrated, contrary to our study (P=0.521). In the study by Dimitriou et al [17], contrary to our study, older age was found to adversely affect OS (P=0.002). The inclusion of different parameters in all these studies in the literature has created limitations in terms of comparison.

A limitation of the present study is that it was a retrospective, single-center study, but its strengths include having a sample size similar to those of other studies and the comparison of factors that were not compared in similar studies in the literature (comparison of patients according to hemoglobin, platelet, and LDH values according to NLR groups). To the best of our knowledge, there have been no previous studies that evaluated the distribution of comorbid diseases and the relationship between the type of operation and pathological response.

Conclusions

In our study, a higher rate of near-complete response was observed in rectal cancer patients with NLR <3.63 receiving nCRT. This supports, in line with the literature, that a low preoperative NLR ratio is a good prognostic factor in indicating pathological response.