Neutrophil/lymphocyte ratio predicts chemotherapy outcomes in patients with advanced colorectal cancer

ABSTRACT BACKGROUND: Advances in the treatment of metastatic colorectal cancer (mCRC) in the last decade have significantly improved survival; however, simple biomarkers to predict response

or toxicity have not been identified, which are applicable to all community oncology settings worldwide. The use of inflammatory markers based on differential white-cell counts, such as the

neutrophil/lymphocyte ratio (NLR), may be simple and readily available biomarkers. METHODS: Clinical information and baseline laboratory parameters were available for 349 patients, from two

independent cohorts, with unresectable mCRC receiving first-line palliative chemotherapy. Associations between baseline prognostic variables, including inflammatory markers such as the NLR

and tumour response, progression and survival were investigated. RESULTS: In the training cohort, combination-agent chemotherapy (_P_=0.001) and NLR⩽5 (_P_=0.003) were associated with

improved clinical benefit. The ECOG performance status ⩾1 (_P_=0.002), NLR>5 (_P_=0.01), hypoalbuminaemia (_P_=0.03) and single-agent chemotherapy (_P_<0.0001) were associated with

increased risk of progression. The ECOG performance status ⩾1 (_P_=0.004) and NLR>5 (_P_=0.002) predicted worse overall survival (OS). The NLR was confirmed to independently predict OS in

the validation cohort (_P_<0.0001). Normalisation of the NLR after one cycle of chemotherapy in a subset of patients resulted in improved progression-free survival (_P_=0.012).

CONCLUSION: These results have highlighted NLR as a potentially useful clinical biomarker of systemic inflammatory response in predicting clinically meaningful outcomes in two independent

cohorts. Results of this study have also confirmed the importance of a chronic systemic inflammatory response influencing clinical outcomes in patients with mCRC. SIMILAR CONTENT BEING

VIEWED BY OTHERS THE PROGNOSTIC AND DIAGNOSTIC SIGNIFICANCE OF THE NEUTROPHIL-TO-LYMPHOCYTE RATIO IN HEPATOCELLULAR CARCINOMA: A PROSPECTIVE CONTROLLED STUDY Article Open access 14 June 2021

CLINICAL SIGNIFICANCE OF BASELINE PAN-IMMUNE-INFLAMMATION VALUE AND ITS DYNAMICS IN METASTATIC COLORECTAL CANCER PATIENTS UNDER FIRST-LINE CHEMOTHERAPY Article Open access 27 April 2022 THE

COMBINATION OF PRE-NEOADJUVANT CHEMORADIOTHERAPY INFLAMMATION BIOMARKERS COULD BE A PROGNOSTIC MARKER FOR RECTAL CANCER PATIENTS Article Open access 11 March 2022 MAIN Colorectal cancer

(CRC) is the third leading cause of worldwide cancer mortality after lung and stomach cancer and is responsible for 639 000 deaths or 1.1% of total deaths (World Health Organisation, 2004).

There have been major advances in the treatment of metastatic CRC (mCRC) in the last 10–15 years, involving the introduction of new cytotoxic and molecular targeted therapies. However, use

of these newer treatments result in increased toxicities and are prohibitively expensive. Hence, there is a need for accurate predictors of outcomes from treatment, in particular, in

identifying those patients who are more likely to benefit by being assisted in rationalising increasingly expensive treatments, especially in under-resourced communities. Tumour development

and growth occurs as a result of interactions among the tumour, host-derived stromal tissues including blood vessels and host immune/inflammatory cells (see Figure 1), with chronic

inflammation having an important role in cancer development and progression (Balkwill and Mantovani, 2010; Coussens and Werb, 2002). Lymphocytic infiltration in primary colorectal tumour

tissue with different lymphocyte subpopulations has been investigated as potential prognostic factors (Pagès et al, 2005; Galon et al, 2006). This chronic inflammatory state also has effects

on normal tissues, including the liver, resulting in an ongoing release of ‘acute-phase proteins’ that may be used to monitor this process. Current prognostication in advanced CRC, as in

other malignancies, involves a poorly defined combination of clinical experience with the use of relatively crude and subjective covariates, such as performance status, with few markers in

clinical practice apart from the use of _k-ras_ mutation status and treatment with epidermal growth-factor receptor inhibitors (Bokemeyer et al, 2009; Koopman et al, 2009; Van Cutsem et al,

2009; Chua et al, 2010). Over the last 10 years, laboratory markers of a systemic inflammatory response, including plasma C-reactive protein concentration (CRP), hypoalbuminaemia and Glasgow

Prognostic Score (GPS, which combines CRP and albumin), and absolute white cell or its components (neutrophils, neutrophil/lymphocyte ratios (NLRs) and platelet/lymphocyte ratios (PLRs))

have been investigated as prognostic and predictive markers in different cancer populations, with the best evidence for their use demonstrated in surgical patients with CRC (Roxburgh and

McMillan, 2010). Emerging evidence suggests that elevated baseline levels of CRP (Hilmy et al, 2005; Crumley et al, 2006a; Mitsuru et al, 2009; Johnson et al, 2010), abnormal GPS scores

(Forrest et al, 2003; Crumley et al, 2006b; McMillan, 2009) and elevated NLR (Yamanaka et al, 2007; Halazun et al, 2008, 2009; Liu et al, 2010) or PLR (Smith et al, 2009) are not only

negatively correlated with outcome after surgical resection but also in those with inoperable cancers. These inflammation scores based on readily available and inexpensive tests could

potentially be ideal biomarkers of outcome in patients with mCRC. Evidence for the use of these inflammatory markers as direct predictors of outcome in patients with advanced malignancy

receiving first-line chemotherapy is lacking. Two recent studies have highlighted the use of the systemic inflammatory response in predicting survival (Teramukai et al, 2009) and toxicity

(Arieta et al, 2010) in patients receiving chemotherapy for advanced non-small-cell lung cancer. Neutrophilia has been shown to be an adverse prognostic factor in patients receiving

first-line oxaliplatin-based chemotherapy for CRC (Michael et al, 2006). An elevated NLR in CRC patients with liver-only colorectal metastases receiving neoadjuvant chemotherapy before

surgical resection of liver metastases predicted worse survival (Kishi et al, 2009). In addition, those patients in whom NLR normalised after chemotherapy had significantly improved 1-, 3-

and 5-year survival similar to patients with NLR⩽5 at baseline. These data suggest that NLR may be a readily available and useful biomarker for monitoring early response and prognosis with

chemotherapy for CRC (Kishi et al, 2009). The aims of the current study were to investigate (1) NLR in predicting treatment response, toxicity and survival in medical patients receiving

first-line chemotherapy for advanced CRC in a training set; (2) validating the results from the training cohort in a separate community patient cohort; and (3) assessing the impact of

normalisation of NLR for monitoring early response during chemotherapy. PATIENTS AND METHODS STUDY POPULATION In total, there were 349 patients with available clinical information and

baseline laboratory parameters. The training set consisted of 171 patients enrolled in first-line chemotherapy trials at the Sydney Cancer Centre for advanced CRC between 1999 and 2007. The

independent validation set included 178 patients from a community-based clinical database in the province of Alberta and included patients referred to medial oncology units at the Cross

Cancer Institute who received first-line chemotherapy for advanced CRC between 2004 and 2007 (Prado et al, 2008). Table 1 lists the comparative baseline clinical information and laboratory

parameters for both cohorts before chemotherapy commencement. METHODS Baseline clinical information and biochemical evaluation, including full blood count (neutrophils, lymphocytes,

haemoglobin and platelets) and albumin before chemotherapy commencement, were collected in a database for patients in both the training and validation sets. Alkaline phosphatase was also

collected in the training set. Prognostic variables with >10% missing data were not included in the analysis. Differential white-cell counts (neutrophils and lymphocytes) were also

collected for patients before cycle 2 of chemotherapy. Response rates, dates of progression and survival were available for patients in the training set; however, only survival data were

available for patients in the validation cohort. Dates of death were followed up by the investigators through hospital records, local Cancer Registries or phone contact through patient

relatives, local medical practitioners and palliative-care services. Patients were consented to undergo analyses before commencing chemotherapy, and the study was approved by institutional

research ethics committees in both Sydney and Edmonton. STATISTICAL ANALYSIS Statistical analyses were performed using SPSS Graduate Version 17.0 (IBM Corporation 2010, Somers, NY, USA).

Response rates were determined according to criteria determined by individual clinical trials, RECIST criteria. Clinical response was defined as either complete or partial response and

non-response as either stable or progressive disease. Clinical benefit was defined as complete response, partial response and stable disease and no benefit as progressive disease alone.

Progression-free survival (PFS) was defined as the date of commencing protocol treatment to the date of first progression or death from any cause without progression. Overall survival (OS)

was defined as the date from the date of commencing protocol treatment to the date of death from any cause. The _χ_2-tests were used to test associations between variables of interest

(grouped using standard thresholds) and clinical response or benefit. Multivariate modelling was used for calculation of hazard ratios and clinical response and benefit. The follow-up period

commenced at the start of chemotherapy with the censor date of January 2010. Survival analysis was performed using the Kaplan–Meier method with log-rank test in univariate analyses. Cox

regression analysis was used for multivariate survival analysis and for calculation of hazard ratios. RESULTS PATIENT CHARACTERISTICS Baseline clinical demographics and laboratory values for

both training and validation sets are presented in Table 1. There were no differences in age and gender between the two cohorts. However, a significantly higher proportion of patients in

the validation cohort had rectal cancer as the primary tumour site and had ECOG PS⩾1. The majority of patients in both cohorts received combination chemotherapy±a biological agent.

PROGNOSTIC VARIABLES IN TRAINING SET Table 2 shows the univariate analyses between prognostic variables of interest and clinical benefit, PFS and OS in the training set. At the time of

analysis, all patients had progressed on chemotherapy and 169 patients were deceased. The overall clinical response (complete response and partial response) was 55% (93 out of 168 evaluable

patients) and clinical benefit (complete response, partial response and stable disease) was 75% (128 out of 168 evaluable patients). The median PFS was 6.7 months (95% CI 5.6–7.8 months) and

OS was 15.3 months (95% CI 12.4–18.2). CLINICAL BENEFIT AND RESPONSE Younger age (⩽65 years old), ECOG performance status 0, absence of hypoalbuminaemia, normal alkaline phosphatase, low or

normal neutrophil counts and NLR⩽5 were associated with improved clinical benefit (Table 2). Similarly, younger age (⩽65 years old), ECOG performance status 0 and NLR⩽5 were associated with

improved clinical response. In addition, combination-agent chemotherapy was also associated with improved clinical response. PFS AND OS Variables predicting improved PFS included younger

age, ECOG performance status 0, combination-agent chemotherapy, single site of metastasis, absence of neutrophilia or hypoalbuminaemia and NLR⩽5 (Table 2 and Figure 2A). The following

variables were associated with improved OS: younger age, ECOG PS 0, combination-agent chemotherapy, absence of neutrophilia or anaemia. Hypoalbuminaemia, elevated alkaline phosphatase and

NLR>5 were also significantly associated with worse OS (Table 2 and Figure 2B). MULTIVARIATE ANALYSIS In multivariate analysis performed in the training set (Table 3), combination-agent

chemotherapy and NLR⩽5 were associated with improved clinical benefit. The ECOG performance status ⩾1, NLR>5, hypoalbuminaemia and single-agent chemotherapy were associated with increased

risk of progression. The ECOG performance status ⩾1 and NLR>5 predicted worse OS. PROGNOSTIC VARIABLES ACCORDING TO NLR Table 4 summarises analysis of baseline characteristics and

prognostic variables according to NLR groups. Patients with NLR>5 were more likely to suffer from hypoalbuminaemia (_P_-level <0.0001) and elevated alkaline phosphatase (_P_-level

0.008). The association between NLR and gender (_P_-level 0.06) and number of metastatic sites (_P_-level 0.05) approached statistical significance. NLR IN VALIDATION COHORT At the time of

analysis, 82% (146 out of 178) of patients were deceased. The median OS in this cohort was 16.8 months (95% CI 13.1–20.4 months). Independent predictors of survival from the training cohort

(ECOG performance status and NLR) were tested in the validation cohort. The NLR was statistically significantly associated with OS (_P_-level <0.0001). Patients with NLR⩽5 had median OS

of 19.1 months (95% CI 15.3–22.8) compared with patients with NLR>5 (median OS 11.3 months; 95%CI 8.3–14.3; Figure 2C). The ECOG performance status was not predictive of survival in this

cohort (median OS for ECOG 0 was 21.5 months (95% CI 4.1–38.9) and PS⩾1 15.7 months (95% CI 13.1–18.3; _P_-level 0.15)). NORMALISATION OF NLR PRE-CYCLE 2 AND CORRELATION WITH PFS AND OS

(TRAINING COHORT) Patients were categorised into the following categories: (1) patients with NLR⩽5 at baseline (_n_=120; cohort 1), (2) NLR>5 at baseline and before cycle 2 of

chemotherapy (_n_=21; cohort 2) and (3) NLR>5 at baseline with normalisation of NLR⩽5 before cycle 2 of chemotherapy (_n_=21; cohort 3). Patients with normalisation of NLR before cycle 2

of chemotherapy (cohort 3) had an improved PFS of 5.8 months (95% CI 4.1–7.5) compared with patients without normalisation of NLR pre-cycle 2 (cohort 2; median PFS 3.7 months; 95% CI 0.6–6.8

months; _P_-level 0.012; Figure 3A). Normalisation of NLR improved median OS from 9.4 months (cohort 2; 95% CI 3.2–15.5) to 12.1 months (cohort 3; 95% CI 7.3–16.8) in patients with a

persistently elevated NLR, although this did not reach statistical significance (_P_-level 0.053; Figure 3B). Patients with normalised NLR before cycle 2 of chemotherapy (cohort 3) did not

have significantly different median PFS (5.8 months (95% CI 4.1–7.5) _vs_ 8.0 months (95% CI 6.9–9.0); _P_-level 0.37) or OS (12.1 months (95% CI 7.3–16.8) _vs_ 18.3 months (95% CI

16.2–20.4); _P_-level 0.77) in comparison with patients with NLR⩽5 before chemotherapy commencement (cohort 1; Figures 3A and B). Normalisation of NLR before cycle 2 of chemotherapy was not

performed in the validation cohort, as there was >10% of missing data for this patient group. DISCUSSION This is the first study, to our knowledge, to describe the use of NLR in a

non-selected unresectable mCRC setting for patients receiving first-line palliative chemotherapy to provide useful information regarding prognostication, and the data have been validated in

an independent community-based cohort. These results support the use of NLR as a marker of systemic inflammatory response and as an independent predictor of clinical benefit, progression and

survival in patients receiving chemotherapy for mCRC. An NLR cutoff >5 was able to identify a subset of patients least likely to respond to chemotherapy (40 _vs_ 16%) and those at higher

risk of progression and death (HR 1.6 and 1.7, respectively). A cutoff score of 5 was chosen on the basis of previous studies (Halazun et al, 2008, 2009; Kishi et al, 2009) and this

represents a simple measurement to use in clinical practice, although other cutoffs have been used (Duffy et al, 2006; Cho et al, 2009). This identifies ∼30% of CRC patients with a raised

NLR receiving first-line chemotherapy in both cohorts and associated with shorter survival of up to 8 months. These results are highly clinically relevant in this increasingly common

malignancy. In addition, evidence for significantly improved outcomes with normalisation of NLR after the first cycle is promising for possible manipulation of the systemic inflammatory

response through targeted anti-inflammatory mediators such as IL-6 blocking antibodies. If the use of NLR and normalistion of NLR after cycle 1 are confirmed, this would provide additional

prognostic information for clinicians at an earlier time point before conventional staging with computed tomography scans and potentially identify a proportion of patients in whom further

treatment may be futile. For example, in the training cohort, there was NLR normalisation after one cycle of chemotherapy in 50% (21 out of 42) of evaluable patients, which resulted in a

2-month PFS improvement (5.8 _vs_ 3.7 months) compared with patients without NLR normalisation. These data will permit not only retrospective evaluations of established large cohorts with

known outcome data to corroborate these findings but also to undertake correlation with molecular characteristics, such as microsatellite instability and _B-raf_ mutations, which are

associated with worse cancer outcomes. The strengths in our training cohort were that patient data were retrospectively analysed from robust prospectively collected data through entry into

clinical trials. As the patients were eligible for enrolment in a clinical trial, it is highly unlikely that the elevated NLR was due to other active inflammatory diseases or infection or

were requiring high doses of steroids; however, these issues should be specifically assessed in future studies. Other independent predictive variables identified from the training cohort,

such as performance status, use of combination chemotherapy and hypoalbuminaemia, have also been reported from previous studies and strengthens the case for this cohort being representative

of a palliative mCRC population. The median OS in both cohorts (15.3 and 16.8 months in training and validation cohorts, respectively) are shorter than those reported using modern

combination chemotherapy regimens, which have median OS upwards of 24 months. However, a significant proportion of the patients in both cohorts received single-agent chemotherapy, with

patients enrolled in chemotherapy trials from as early as 1999. There were also significant baseline differences in the types of chemotherapy regimens between the Australian and Canadian

cohorts. In the Canadian cohort, up to 29% of patients did not have the type of chemotherapy specified, which may account for some of the survival difference between the two cohorts. The

validation cohort in this study failed to identify performance status as an independent prognosticator, which, although surprising, may reflect the community-based origins of this group.

However, in both cohorts, the proportion of patients with NLR>5 was surprisingly consistent between the two cohorts (29 and 31%). In spite of differences between the cohorts, NLR remained

an independent prognosticator and may reflect that it is an even more robust and accurate prognosticator than performance status alone. The heterogeneity of treatment regimens used could be

criticised; however, this is probably more reflective of day-to-day clinical practice. The NLR is a simple, readily available and robust laboratory variable. Other authors have advocated

the use of GPS or a modified GPS, based on albumin and CRP levels, and validated its use as a prognostic variable particularly in the pre-operative setting. Two studies have reported the use

of GPS in patients receiving chemotherapy for mCRC and gastro-oesophageal malignancies (Crumley et al, 2008; Ishizuka et al, 2009). However, this assessment is complicated by the

requirement for an additional blood test to measure CRP levels, which may not be readily available as was in the case of both our training and validation sets. The NLR, as a continuous

variable, may also be a more accurate and dynamic variable reflecting acute changes in the inflammatory state of a patient rather than GPS, which is applied as a static, categorical

variable. The NLR and GPS have not been compared in the same population in CRC patients, and this comparison should be undertaken to discern whether these two indices are overlapping or

additive as indicators of cancer-associated inflammation. In CRC, the use of NLR has previously been confirmed as an independent prognostic factor in a cohort of patients with liver-only

colorectal metastases, the majority of whom proceeded to hepatic resection post chemotherapy (Kishi et al, 2009). Although this is an important subset of patients with mCRC, these patients

would have been highly selected for surgical intervention and not representative of the majority of patients with mCRC. The findings in our study are not only consistent with this earlier

report but also supports the use of NLR in a more generalised patient population receiving first-line chemotherapy both in a clinical trial and community setting. Although elevated NLR was

correlated with the presence of hypoalbuminaemia and elevated alkaline phosphatase in this study (Table 4), other prognostic variables, such as performance status, site or extent of disease,

were relatively well-balanced between the high- and low-NLR groups, suggesting that NLR provides additional information than these other variables. The association of both raised NLR and

hypoalbuminaemia is likely because of its role as a marker of systemic inflammation. The reasons for the correlation between alkaline phosphatase and NLR are unclear. Alkaline phosphatase

may be a more accurate marker of the extent of liver involvement or indirectly related to systemic inflammation. The NLR has also been previously shown to independently predict outcomes in

non-malignant disease, such as post-ST-segment elevation myocardial infarction (Núñez et al, 2008) and percutaneous coronary intervention (Duffy et al, 2006) in which the systemic

inflammation response has been implicated as a major contributing factor. This adds credibility for the use of NLR as a potential biomarker of the systemic inflammatory response. In recent

years, there have been significant developments and discoveries in cancer genomics. The development of gene-expression-based arrays or examining germline single-nucleotide polymorphisms for

defining prognosis or predicting response to therapy has limited clinical application even in the two most common malignancies, lung and breast cancers (Hartman et al, 2010; Subramanian and

Simon, 2010). For example, Wacholder et al (2010) discovered that the inclusion of 10 common breast cancer genetic variants only modestly improved the performance of existing risk-assessment

models in >11 000 patients, with little change in the predicted breast-cancer risk among most women, using currently available genetic information. These tests are also expensive and

confined to use in developed countries, with limited application in under-resourced communities. A useful biomarker needs to be not only accurate and reproducible but also easily accessible.

The prognostic importance of the systemic reaction to tumours has been relatively ignored in the quest for tumour-based molecular assessments of outcome. These data will encourage a

re-evaluation of that approach. These results have highlighted the use of a potential clinical biomarker of systemic inflammatory response in predicting clinically meaningful outcomes in two

independent cohorts. In addition, results of the study have also confirmed the importance of a chronic systemic inflammatory response influencing clinical outcomes in patients with mCRC.

Validation of these results in larger patient populations will allow many potential applications in the treatment of mCRC, a major cause of morbidity worldwide. Clinical applications include

(1) prognostication and in-patient stratification in clinical trials, (2) as a marker of response to chemotherapy treatment and, more excitingly, (3) in identifying patients for possible

interventions with anti-inflammatory mediators. The results of this study, we believe, strongly support the use of NLR in these settings, and more importantly, as a dynamic marker of

interactions among tumour, host and the systemic inflammatory response. CHANGE HISTORY * _ 29 MARCH 2012 This paper was modified 12 months after initial publication to switch to Creative

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Scholar  Download references ACKNOWLEDGEMENTS We thank Jenny Peat for assistance with statistical analysis. Wei Chua was supported by a NSW Cancer Institute Fellowship (Australia) and a

Pfizer Australia Cancer Research Grant. The research was facilitated by a Translational Colorectal Cancer Research Grant from the NSW Cancer Institute. This study was funded by the Canadian

Institute of Health Research. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Sydney Cancer Centre, Concord Repatriation General Hospital, Hospital Road, Concord, 2139, New South Wales,

Australia W Chua & S J Clarke * Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia W Chua & S J Clarke * School of Medical Sciences (Pharmacology) and

Bosch Institute, University of Sydney, Sydney, New South Wales, Australia K A Charles * Department of Oncology, University of Alberta, Edmonton, Alberta, Canada V E Baracos Authors * W Chua

View author publications You can also search for this author inPubMed Google Scholar * K A Charles View author publications You can also search for this author inPubMed Google Scholar * V E

Baracos View author publications You can also search for this author inPubMed Google Scholar * S J Clarke View author publications You can also search for this author inPubMed Google Scholar

CORRESPONDING AUTHOR Correspondence to S J Clarke. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no conflict of interest. RIGHTS AND PERMISSIONS From twelve months after its

original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit

http://creativecommons.org/licenses/by-nc-sa/3.0/ Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Chua, W., Charles, K., Baracos, V. _et al._ Neutrophil/lymphocyte ratio

predicts chemotherapy outcomes in patients with advanced colorectal cancer. _Br J Cancer_ 104, 1288–1295 (2011). https://doi.org/10.1038/bjc.2011.100 Download citation * Received: 01

December 2010 * Revised: 15 February 2011 * Accepted: 25 February 2011 * Published: 29 March 2011 * Issue Date: 12 April 2011 * DOI: https://doi.org/10.1038/bjc.2011.100 SHARE THIS ARTICLE

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by the Springer Nature SharedIt content-sharing initiative KEYWORDS * colorectal cancer * prognosis * neutrophil/lymphocyte ratio * cancer-associated inflammation