To Study the Neutrophil Lymphocyte Ratio As a Predictive Marker of Response to Neoadjuvant Chemotherapy in Locally Advanced Triple-Negative Breast Cancer

Abstract

Introduction

Triple-negative breast cancer (TNBC) is the most aggressive form of invasive breast cancer. A key predictor of positive outcomes is achieving a pathological complete response (pCR) following neoadjuvant chemotherapy (NACT). This study aims to evaluate the role of pre-chemotherapy neutrophil-to-lymphocyte ratio (NLR) as a predictive marker of pCR.

Objective

The aim of the study is to study the pCR rate after NACT in relation to NLR in patients with locally advanced TNBC.

Materials and Methods

This prospective study enrolled 120 consecutive female patients with locally advanced TNBC who were planned for NACT at the Kidwai Memorial Institute of Oncology from July 2022 to July 2024. Peripheral blood samples were collected before treatment to calculate NLR. The predictive value of NLR for pCR was assessed using descriptive statistics, Chi-square tests, and receiver operating characteristic (ROC) curve analysis.

Results

The final analysis included 101 patients. Thirty-one patients (30.7%) achieved pCR. Patients with pCR had a significantly lower mean NLR (2.29 ± 1.21) than the non-pCR group (2.85 ± 1.34). The optimal NLR cut-off for predicting pCR was 2.18. Low NLR (≤2.18) was significantly associated with higher pCR rates (67.74 vs. 32.25% for high NLR, p <0.05).

Conclusion

Pre-chemotherapy NLR is a potential predictive marker for pCR in locally advanced TNBC. Patients with a lower NLR were more likely to achieve pCR, suggesting its potential utility in risk stratification.

Keywords

triple-negative breast cancer - neutrophil lymphocyte ratio - pathological complete response - neoadjuvant chemotherapy - inflammatory markers

Introduction

Breast cancer is the leading malignancy affecting women globally, representing approximately 25% of all female cancer diagnoses and ranking among the top causes of cancer-related mortality.[1] Several factors influence patient outcomes, including age, tumor stage, ethnicity, molecular characteristics of the tumor, and biomarker expression particularly estrogen receptor (ER), progesterone receptor (PR), and HER2 status. Triple-negative breast cancer (TNBC), which constitutes 20% of cases, lacks these receptors and is characterized by aggressive behavior and a lack of targeted therapies.[2]

Neoadjuvant chemotherapy (NACT) is a standard treatment for locally advanced breast cancer, enhancing tumor response and improving the chances of breast-conserving surgery. Achieving pathological complete response (pCR) post-NACT is a key prognostic marker, particularly in TNBC where pCR rates exceed 50%.[3] [4] Recent research suggests inflammation plays a critical role in the development of cancer and its progression, with inflammatory cells generating reactive oxygen species that contribute to DNA damage and tumor growth.[5] [6] [7] [8] [9] Neutrophils suppress T-cell activity, promoting tumor invasion, while tumor-infiltrating lymphocytes are linked to better chemotherapy responses and improved prognosis.[10] [11] [12] [13] [14] [15]

Currently, predictors of response to NACT in breast cancer include traditional factors such as tumor grade, nodal status, receptor subtype, and radiological response (e.g., RECIST [response evaluation criteria in solid tumors] criteria on MRI). However, radiological assessment alone cannot reliably rule out residual disease. Emerging approaches focus on advanced imaging (e.g., computer-extracted MRI features for tumor biology insights) and liquid biopsies (e.g., ctDNA analysis for real-time tumor dynamics).[16] [17] [18] [19] [20] [21] Peripheral inflammatory markers like the neutrophil to lymphocyte ratio (NLR) may offer a simple, inexpensive means of predicting response to NACT and disease prognosis. Elevated NLR reflects systemic inflammation and has been correlated with poor outcomes in various cancers, though evidence in breast cancer remains limited.[22] [23] [24] [25] [26] [27] [28] [29] NLR is an easily available, reproducible, and inexpensive biomarker of inflammation. Our study enrolled only one subgroup of breast cancer that is non-metastatic locally advanced TNBC. It is one of the very few prospective study that can be found in the literature. This study aims to evaluate the predictive role of pre-chemotherapy NLR in relation to pCR in patients with locally advanced TNBC.

Materials and Methods

Study Design and Patient Population

This was a prospective, observational study. A total of 120 consecutive female patients with newly diagnosed, locally advanced TNBC planned for NACT were recruited between July 2022 and July 2024. [Fig. 1] (CONSORT Flowchart) illustrates the patient screening and recruitment process.

Fig. 1 Receiver Operating Characteristic (ROC) curve for the predictive model. The Area Under the Curve (AUC) is 0.67 (95% CI: 0.55 – 0.79), indicating moderate discriminatory power.

Data Collection

The study was approved by institutional ethical committee. Clinicopathological data were collected including age, menopausal status, clinical stage (AJCC 8th edition), histological type, grade, proliferation index (ki67), ECOG performance status, chemotherapy regimen, and NLR. All patients recruited in the study were pathologically diagnosed with invasive breast carcinoma, with immunohistochemistry (IHC) suggestive of ER-negative/PR-negative/ HER2-negative as per American Society of Clinical Oncology-College of American Pathologist guidelines, 2018.[30] Pre NACT complete blood count was performed from a peripheral venous blood sample drawn within 1 week prior to the initiation of the first cycle of chemotherapy. Absolute neutrophil and lymphocyte count were documented to calculate NLR. NLR is defined as absolute neutrophil count divided by absolute lymphocyte count.

Treatment

After pathological diagnosis, patients received standardized NACT. Those with ECOG performance status 0–1 received either:

1. Dose-dense chemotherapy, as per the CALGB 9741 trial protocol, consisted of Adriamycin (60 mg/m²) and cyclophosphamide (600 mg/m²) administered every 2 weeks for four cycles, followed by paclitaxel (175 mg/m²) every 2 weeks for another four cycles with growth factor support as show in [Table 1].[31]

2. FEC-D regimen: 5-Fluorouracil, Epirubicin, and cyclophosphamide followed by docetaxel. Patients with ECOG PS 2, as determined by the treating physician based on comorbidities and functional status, received the FEC-D regimen (non-dose-dense), due to better tolerability. A small number of patients (n = 6) received docetaxel plus cyclophosphamide (TC) based on physician discretion in specific clinical scenarios (e.g., pre-existing cardiac contraindications to anthracyclines). Following NACT, patients underwent surgical resection, with subsequent radiotherapy and hormone therapy administered as indicated based on receptor status. pCR was strictly defined as the absence of invasive tumor in both breast tissue (ypT0/Tis) and lymph nodes (ypN0) upon postoperative histopathological examination.

Table 1 Chemotherapy regimens

Regimen	Drugs and dosage	Frequency	Cycles
(1) FEC-D	5-Fluorouracil 500 mg/m2, Epirubicin 100 mg/m2, cyclophosphamide 500 mg/m2 (FEC)	Every 3 wk	3 FEC
	Followed by docetaxel 100 mg/m2	Every 3 wk	3 Docetaxel
(2) Dose-Dense AC-T	Adriamycin 60 mg/m2, cyclophosphamide 600 mg/m2 (AC)	Every 2 wk	4 AC
	Followed by paclitaxel 175 mg/m2	Every 2 wk	4 Paclitaxel
(3) TC	Docetaxel 75 mg/m2, cyclophosphamide 600 mg/m2	Every 3 wk	4 TC

Abbreviations: AC-T, Adriamycin, cyclophosphamide followed by paclitaxel; FEC-D, 5-fluorouracil, Epirubicin, cyclophosphamide followed by docetaxel; TC, docetaxel, cyclophosphamide.

Inclusion and Exclusion Criteria

The following inclusion criteria were used to select patient population (1) age >18 years, (2) ECOG 0–2, (3) biopsy-proven locally advanced TNBC. The exclusion criteria were: (1) recurrent breast cancer; (2) metastatic disease; (4) diagnosis of ductal carcinoma in situ; (5) hormone receptor positive or Her2-neu receptor positive breast cancer; (6) patient with impaired hepatic and renal function or cardiovascular disease, as they are less likely to tolerate full-dose chemotherapy and may require frequent dose reductions or treatment interruptions, which can delay treatment and affect outcomes; (7) active infection or inflammatory conditions.

Primary outcome: The primary aim is to study the pCR rate after NACT in relation to neutrophil lymphocyte ratio (NLR) in patients with locally advanced TNBC.

Sample Size Consideration

Given the exploratory nature of this study to determine an NLR cut-off value in a specific population, a formal sample size calculation was not performed a priori. The sample of 120 patients was based on the expected patient accrual over the 2-year study period at our institute. We acknowledge this as a limitation, particularly for the receiver operating characteristic (ROC) analysis, and the results should be interpreted as generating hypothesis for future validation in larger, powered studies.

Statistical Analysis

Statistical analysis was conducted using Python 3.7. Descriptive statistics (means, standard deviations, and percentages) summarized demographic and clinical data. The Chi-square test evaluated associations between clinicopathological factors (including NLR) and NACT response. ROC curve analysis assessed NLR's predictive ability for pCR, while binary logistic regression identified significant predictors (p <0.05 considered statistically significant). The multivariate model included age, menopausal status, clinical stage, tumor grade, K_i-67, lymphovascular invasion, chemotherapy regimen, and NLR.

Ethical Approval

All patient who gave written informed consent were included in the study. Ethical committee of Kidwai memorial institute of oncology has approved the study. Registration no: KMIO/MEC/2022/07/PG/MO/19. This study was conducted in compliance with institutional ethical guidelines and adhered to the principles of the 1964 Helsinki Declaration (including subsequent amendments).

Results

Patient Characteristics

As detailed in the CONSORT flowchart ([Fig. 1]), 120 patients were enrolled. Of these, 16 were lost to follow-up. Three patients developed distant metastasis during NACT and were excluded from the primary pCR analysis. We acknowledge that excluding these patients, who had high NLR values (mean NLR = 3.4), may introduce a bias; however, for the specific outcome of pCR (a pathological state assessed at surgery), these patients were not evaluable. Their outcomes can be analyzed separately in the context of the secondary survival outcomes. The final analysis for the primary endpoint (pCR) included 101 patients. The baseline characteristics of the 101 patients are summarized in [Table 2]. The median age was 49 (24–83) years. The majority of patients (93.1%) had an ECOG performance status of 0 to 1. The predominant histopathology was invasive ductal carcinoma (99.0%). Most tumors were high grade (Grade 2: 55.4%; Grade 3: 42.6%). Regarding chemotherapy regimens, 82 (81.2%) patients received FEC-D, 13 (12.9%) received dose-dense chemotherapy, and six (5.9%) received TC. The majority of patients (98.0%) underwent modified radical mastectomy. pCR was achieved in 31 patients (30.7%).

Table 2 Baseline clinical and pathological characteristics of the study population (n = 101)

Characteristic	Level	Frequency (n)	Percentage (%)
Age (years)	Median (range)	49 (24–83)	−
Menopausal status	Premenopausal	55	54.5
	Postmenopausal	46	45.5
ECOG performance status	0–1	94	93.1
	2	7	6.9
Clinical stage	Stage II	45	44.6
	Stage III	56	55.4
Histopathology	Invasive ductal carcinoma	100	99.0
	Other (metaplastic, poorly diff.)	2	2.0
Tumor grade	1	2	2.0
	2	56	55.4
	3	43	42.6
Chemotherapy regimen	FEC-D	82	81.2
	Dose-dense AC-T	13	12.9
	TC	6	5.9
Type of surgery	Breast conserving surgery (BCS)	2	2.0
	Modified radical mastectomy (MRM)	99	98.0

Abbreviation: ECOG, Eastern Cooperative Oncology Group; FEC-D, 5-fluorouracil, Epirubicin, and cyclophosphamide followed by docetaxel.

Note: Percentages may not sum to 100% due to rounding. The “Histopathology” category allows for patients with non-ductal histology to be represented.

Treatment Response and NLR

The mean NLR for the entire cohort was 2.68. Patients who achieved pCR had a significantly lower mean NLR (2.29 ± 1.21) compared with the non-pCR group (2.85 ± 1.34). The optimal NLR threshold for predicting pCR was 2.18 (AUC = 0.67, sensitivity 67.74%, specificity 67.14%) ([Table 3], [Fig. 2]). The cohort was divided into high NLR (>2.18; n = 57) and low NLR (≤2.18; n = 44) groups. pCR rates were significantly higher in the low NLR group (67.74 vs. 32.25%, p <0.05). This association is detailed in the 2 × 2 contingency table ([Table 4]). Of the three patients who developed metastasis during NACT and were excluded from the pCR analysis, all had an NLR above the 2.18 cut-off (values: 3.1, 3.5, 3.6). When considering “non-response” as either residual disease or disease progression, the association between high NLR and treatment failure is further strengthened. NLR showed no significant association with baseline characteristics like age or tumor grade ([Table 5]) but correlated with adverse pathological features (LVI, PNI) in non-responders.

Table 3 Pathological response and tumor characteristics post-NACT

Characteristic	Level	Frequency (n)	Percentage (%)
Pathological response	Complete response (pCR)	31	30.7
	Non-complete response (Non-pCR)	70	69.3
Residual cancer burden (RCB)	RCB-0 (pCR)	31	30.7
	RCB-1	13	12.9
	RCB-2	22	21.8
	RCB-3	35	34.7
Lymphovascular invasion (LVI)	Negative	56	55.4
	Positive	45	44.6
Perineural invasion (PNI)	Negative	86	85.1
	Positive	15	14.9
Ductal carcinoma in situ (DCIS)	Negative	79	78.2
	Positive	22	21.8
Extranodal extension	Negative	82	81.2
	Positive	19	18.8

Abbreviations: NACT, neoadjuvant chemotherapy; pCR, pathological complete response; RCB, residual cancer burden.

Fig. 2 ROC curve with AUC and 95% CI. AUC, area under the curve; CI, confidence intervals.

Table 4 ROC curve analysis for pretreatment NLR predicting pCR

AUC (95% CI)	Optimal cut-off	Sensitivity	Specificity	PPV	NPV
0.67 (0.55 − 0.79)	2.18	67.74%	67.14%	47.73%	82.46%

Abbreviations: AUC, area under the curve; CI, confidence interval; NLR, neutrophil-to-lymphocyte ratio; NPV, negative predictive value; pCR, pathological complete response; PPV, positive predictive value; ROC, receiver operating characteristic.

Table 5 Association between pretreatment NLR group and pathological complete response

NLR group	pCR (n = 31)	Non-pCR (n = 70)	Total (n = 101)	p-Value
Low NLR (≤2.18)	21 (67.7%)	23 (32.9%)	44	<0.05
High NLR (>2.18)	10 (32.3%)	47 (67.1%)	57
Total	31	70	101

Abbreviations: NLR, neutrophil-to-lymphocyte ratio; pCR, pathological complete response.

Note: p-Value calculated using Chi-square test.

Multiple (Binary) Logistic Regression Analysis

A multivariate binary logistic regression was performed to identify independent predictors of pCR. The model included age, menopausal status, clinical stage, tumor grade, K_i-67, lymphovascular invasion, chemotherapy regimen, and NLR. As shown in [Table 6] and [Table 7], a low pre-treatment NLR (≤2.18) remained a significant independent predictor of achieving pCR (odds ratio: 4.27, 95% CI: 1.46 − 12.48, p = 0.008). No other variables in the model showed a statistically significant association with pCR.

Table 6 Association of baseline characteristics with NLR (mean NLR comparison)

Variable	Level	N	Mean NLR	Standard deviation	p-Value[a]
Age	≤50 y	56	2.66	1.28	0.896
	>50 y	45	2.72	1.41
Menopausal status	Premenopausal	55	2.73	1.28	0.546
	Postmenopausal	46	2.62	1.38
Clinical stage	Stage II	45	2.63	1.30	0.629
	Stage III	56	2.72	1.37
Tumor grade	1 or 2	58	2.73	1.54	0.648
	3	43	2.60	0.97
Ki-67 index	≤20%	14	3.13	1.91	0.433
	>20%	87	2.59	1.20

Abbreviation: NLR, neutrophil-to-lymphocyte ratio.

^a p-Value calculated using Mann-Whitney U test.

Discussion

pCR after NACT is the most important goal in TNBC. Failure to reach the endpoint of a pCR is associated with poor clinical outcomes. Hence, it is crucial to identify the patients with higher likelihood of achieving pCR after NACT and further long-term outcomes. NLR is one of those systemic inflammatory markers which can be easily accessed and correlated with aggressive breast cancer outcome specifically TNBC.[32] [33] [34] Pre-chemotherapy NLR was assessed in 101 TNBC patients. The result suggests that a lower NLR has high rates of pCR than those with high NLR (67.8 vs. 32.2%, respectively). It is known that the higher NLR is associated with adverse prognosis and thus chances of achieving pCR are unlikely. Our findings align with previous research, including a study by Li et al that examined the relationship between NLR and breast cancer prognosis, particularly its impact on NACT response and survival outcomes. Their results demonstrated that a low pretreatment NLR (specifically <1.8) served as a favorable prognostic marker, correlating with both a higher pCR rate and improved long-term survival.[35] It is reported that patients with NLR of less than 1.8 have a high chance of pCR and overall survival. Similarly, another study showed that high NLR values above 3 resulted in poor disease-free survival DFS and overall survival (OS) status.[36]

Another study found that worse DFS and OS could be predicted by a pretreatment NLR >2.[37] In our study, the optimal cutoff point for NLR was determined to be 2.18, with a sensitivity of 67.74% and a specificity of 67.14%. This differs from cutoff points reported in the literature, likely due to variations in patient demographics, such as age, ethnicity, menopausal status, or overall health. Our study is the first from the Asian subcontinent correlating NLR with pCR in TNBC patients. Furthermore, the retrospective nature of many published studies, leading to different cutoff values for defining high or low NLR along with individual variations in immune response, genetic factors, and other biological factors, could also contribute to the observed differences.

The significance of pCR in TNBC is as an indirect parameter for survival benefit. Higher NLR has been associated with poor prognosis which includes increased rates of recurrence and reduced overall survival.[13] [14] [38] Similarly, a meta-analysis reported that high NLR was linked with poor DFS and OS across all breast cancer subtypes, including TNBC.[15] A study from Australia also showed that low NLR is predictive of pCR and is associated with better DFS and OS.[39] [40]

In this population, the proportion of patients achieving pCR was 30.7%, comparable to study conducted in Korea, where the figure was 28.7%. In our multivariate logistic regression analysis, low NLR remained the only significant independent predictor for pCR (odds ratio: 4.274; p = 0.008). This highlights the importance of NLR as an indicator of treatment response in TNBC. Recent advances in neoadjuvant therapy for locally advanced TNBC include pembrolizumab-based regimens (KEYNOTE-522 trial), which significantly improve pCR and survival when combined with chemotherapy and radiotherapy.[41] For patients with residual disease, extended adjuvant capecitabine enhances outcomes while germline BRCA-mutated patients benefit from adjuvant olaparib, reducing recurrence risk.[42] [43]

Limitations

Our study has several limitations. First, it is a single-center study with a modest sample size. The lack of a prespecified sample size calculation for the ROC analysis is a constraint, and the identified cut-off of 2.18 requires external validation in larger, multi-institutional cohorts. Second, NLR was measured only once before treatment; serial measurements during and after therapy could provide dynamic insights. Third, the exclusion of three patients who progressed during chemotherapy, while necessary for the pathological pCR endpoint, may have biased our results by removing clear non-responders with high NLR. Finally, the use of multiple chemotherapy regimens, although reflective real-world practice, introduces potential confounding.

Conclusion

This prospective study identifies pre-treatment NLR as a potential biomarker for NACT response in locally advanced TNBC. We observed a significant association between low NLR (≤2.18) and improved pCR rates, suggesting that NLR is a promising, cost-effective, and readily available biomarker for predicting response to NACT in locally advanced TNBC, offering a practical and economical approach to risk stratification and treatment planning. Future large-scale, multicenter studies are warranted to validate these findings and standardize the NLR cut-off value.

Table 7 Univariate and multivariate (binary) analysis of factors predicting pathological complete response (pCR)

Variable	Level	Univariate analysis p-Value[a]	Multivariate analysis[b]
			Odds ratio (OR)	95% CI for OR	p-Value
NLR	Low (≤2.18) vs. high (>2.18)	<0.001	4.27	1.46 − 12.48	0.008
Age	>50 vs. ≤50 y	1.000	0.75	0.28 − 2.01	0.57
Menopausal status	Post vs. premenopausal	0.869	1.12	0.40 − 3.15	0.83
Clinical stage	III vs. II	0.507	0.64	0.24 − 1.71	0.37
Tumor grade	3 vs. ½	0.239	1.89	0.68 − 5.26	0.22
Ki-67 index	>20% vs. ≤20%	0.215	1.54	0.29 − 8.21	0.61
Lymphovascular invasion	Positive vs. negative	<0.001 [a]	0.56	0.21 − 1.50	0.25
Chemotherapy regimen	(Reference: FEC-D)	−	−	−	−
	Dose − dense vs. FEC-D	0.344[c]	1.92	0.50 - 7.34	0.34
	TC vs. FEC-D	0.699[c]	1.15	0.18 − 7.26	0.88

Abbreviations: CI, confidence interval; FEC-D, 5-fluorouracil, Epirubicin, and cyclophosphamide followed by docetaxel; LVI, lymphovascular invasion; NLR, neutrophil-to-lymphocyte ratio.

^a p-Value from Chi-square test, unless otherwise indicated. LVI could not be included in the multivariate model due to quasi-complete separation (0 pCR events in the LVI-positive group).

^b Multivariate analysis performed using binary logistic regression.

^c p-Value from Fisher's exact test due to small cell counts.

Conflict of Interest

None declared.

Authors' Contributions

D.A., L.K.N., P.K.S.K., and M.C.S.B. contributed toward study design, critical revision, and supervision. R.A.H. and R.L.K. collected the data, drafted and revised the manuscript. S.C.S. analyzed the data and edited the manuscript.

• References

• 1 Faria SS, Fernandes PC, Silva MJB. et al. The neutrophil-to-lymphocyte ratio: a narrative review. E Cancer Med Sci 2016; 10: 702
• 2 Gao S, Tang W, Zuo B, Mulvihill L, Yu J, Yu Y. The predictive value of neutrophil-to-lymphocyte ratio for overall survival and pathological complete response in breast cancer patients receiving neoadjuvant chemotherapy. Front Oncol 2023; 12: 1065606
• 3 Cortazar P, Geyer Jr CE. Pathological complete response in neoadjuvant treatment of breast cancer. Ann Surg Oncol 2015; 22 (05) 1441-1446
• 4 Cortazar P, Zhang L, Untch M. et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 2014; 384 (9938): 164-172
• 5 Fernandes JV, Cobucci RN, Jatobá CA, Fernandes TA, de Azevedo JW, de Araújo JM. The role of the mediators of inflammation in cancer development. Pathol Oncol Res 2015; 21 (03) 527-534
• 6 Bremnes RM, Al-Shibli K, Donnem T. et al. The role of tumor-infiltrating immune cells and chronic inflammation at the tumor site on cancer development, progression, and prognosis: emphasis on non-small cell lung cancer. J Thorac Oncol 2011; 6 (04) 824-833
• 7 Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011; 144 (05) 646-674
• 8 Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and cancer. Cell 2010; 140 (06) 883-899
• 9 Greten FR, Grivennikov SI. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity 2019; 51 (01) 27-41
• 10 Ou Q, Cheng J, Zhang L, Wang H, Wang W, Ma Y. The prognostic value of pretreatment neutrophil-to-lymphocyte ratio in breast cancer: deleterious or advantageous?. Tumour Biol 2017; 39 (06) 1010428317706214
• 11 Jablonska J, Leschner S, Westphal K, Lienenklaus S, Weiss S. Neutrophils responsive to endogenous IFN-beta regulate tumor angiogenesis and growth in a mouse tumor model. J Clin Invest 2010; 120 (04) 1151-1164
• 12 Denkert C, Loibl S, Noske A. et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 2010; 28 (01) 105-113
• 13 Moldoveanu D, Pravongviengkham V, Best G. et al. Dynamic neutrophil-to-lymphocyte ratio: a novel prognosis measure for triple-negative breast cancer. Ann Surg Oncol 2020; 27 (10) 4028-4034
• 14 Savioli F, Morrow ES, Dolan RD. et al. Prognostic role of preoperative circulating systemic inflammatory response markers in primary breast cancer: meta-analysis. Br J Surg 2022; 109 (12) 1206-1215
• 15 Liu X, Qu JK, Zhang J. et al. Prognostic role of pretreatment neutrophil to lymphocyte ratio in breast cancer patients: a meta-analysis. Medicine (Baltimore) 2017; 96 (45) e8101
• 16 Lo Gullo R, Eskreis-Winkler S, Morris EA, Pinker K. Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy. Breast 2020; 49: 115-122
• 17 Cain EH, Saha A, Harowicz MR, Marks JR, Marcom PK, Mazurowski MA. Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set. Breast Cancer Res Treat 2019; 173 (02) 455-463
• 18 Hylton NM, Blume JD, Bernreuter WK. et al; ACRIN 6657 Trial Team and I-SPY 1 TRIAL Investigators. Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy—results from ACRIN 6657/I-SPY TRIAL. Radiology 2012; 263 (03) 663-672
• 19 Cavallone L, Aguilar-Mahecha A, Lafleur J. et al. Prognostic and predictive value of circulating tumor DNA during neoadjuvant chemotherapy for triple negative breast cancer. Sci Rep 2020; 10 (01) 14704
• 20 Rothé F, Silva MJ, Venet D. et al. Circulating tumor DNA in HER2-amplified breast cancer: a translational research substudy of the NeoALTTO phase III trial. Clin Cancer Res 2019; 25 (12) 3581-3588
• 21 Magbanua MJM, Swigart LB, Wu HT. et al. Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival. Ann Oncol 2021; 32 (02) 229-239
• 22 Mallappa S, Sinha A, Gupta S, Chadwick SJ. Preoperative neutrophil to lymphocyte ratio >5 is a prognostic factor for recurrent colorectal cancer. Colorectal Dis 2013; 15 (03) 323-328
• 23 Cho H, Hur HW, Kim SW. et al. Pre-treatment neutrophil to lymphocyte ratio is elevated in epithelial ovarian cancer and predicts survival after treatment. Cancer Immunol Immunother 2009; 58 (01) 15-23
• 24 Gondo T, Nakashima J, Ohno Y. et al. Prognostic value of neutrophil-to-lymphocyte ratio and establishment of novel preoperative risk stratification model in bladder cancer patients treated with radical cystectomy. Urology 2012; 79 (05) 1085-1091
• 25 An X, Ding PR, Li YH. et al. Elevated neutrophil to lymphocyte ratio predicts survival in advanced pancreatic cancer. Biomarkers 2010; 15 (06) 516-522
• 26 Ohno Y, Nakashima J, Ohori M. et al. Clinical variables for predicting metastatic renal cell carcinoma patients who might not benefit from cytoreductive nephrectomy: neutrophil-to-lymphocyte ratio and performance status. Int J Clin Oncol 2014; 19 (01) 139-145
• 27 Forget P, Bentin C, Machiels JP, Berliere M, Coulie PG, De Kock M. Intraoperative use of ketorolac or diclofenac is associated with improved disease-free survival and overall survival in conservative breast cancer surgery. Br J Anaesth 2014; 113 (Suppl. 01) i82-i87
• 28 Dirican A, Kucukzeybek BB, Alacacioglu A. et al. Do the derived neutrophil-to-lymphocyte ratio and the neutrophil-to-lymphocyte ratio predict prognosis in breast cancer?. Int J Clin Oncol 2014; 19 (03) 512-521
• 29 Chen J, Deng Q, Pan Y. et al. Prognostic value of neutrophil-to-lymphocyte ratio in breast cancer. FEBS Open Bio 2015; 5: 502-507
• 30 Lee J, Kim DM, Lee A. Prognostic role and clinical association of tumor-infiltrating lymphocyte, programmed death ligand-1 expression with neutrophil-lymphocyte ratio in locally advanced triple-negative breast cancer. Cancer Res Treat 2019; 51 (02) 649-663
• 31 Citron ML, Berry DA, Cirrincione C. et al. Randomized trial of dose-dense versus conventionally scheduled and sequential versus concurrent combination chemotherapy as postoperative adjuvant treatment of node-positive primary breast cancer: first report of Intergroup Trial C9741/Cancer and Leukemia Group B Trial 9741. J Clin Oncol 2003; 21 (08) 1431-1439
• 32 Matsumoto H, Koo SL, Dent R, Tan PH, Iqbal J. Role of inflammatory infiltrates in triple negative breast cancer. J Clin Pathol 2015; 68 (07) 506-510
• 33 Chen P, Zhao T, Bi Z. et al. Laboratory indicators predict axillary nodal pathologic complete response after neoadjuvant therapy in breast cancer. Future Oncol 2021; 17 (19) 2449-2460
• 34 Gasparri ML, Albasini S, Truffi M. et al. Low neutrophil-to-lymphocyte ratio and pan-immune-inflammation-value predict nodal pathologic complete response in 1274 breast cancer patients treated with neoadjuvant chemotherapy: a multicenter analysis. Ther Adv Med Oncol 2023; 15: 17 588359231193732
• 35 Li X, Tan Q, Li H, Yang X. Predictive value of pretreatment peripheral neutrophil-to-lymphocyte ratio for response to neoadjuvant chemotherapy and breast cancer prognosis. Cancer Manag Res 2021; 13: 5889-5898
• 36 Pistelli M, De Lisa M, Ballatore Z. et al. Pre-treatment neutrophil to lymphocyte ratio may be a useful tool in predicting survival in early triple negative breast cancer patients. BMC Cancer 2015; 15: 195
• 37 Bozkurt O, Karaca H, Berk V. et al. Predicting the role of the pretreatment neutrophil to lymphocyte ratio in the survival of early triple-negative breast cancer patients. J Balkan Union Oncol 2015; 20 (06) 1432-1439
• 38 Kim JH, Son NH, Lee JS. et al. Time-sequencing of the neutrophil-to-lymphocyte ratio to predict prognosis of triple-negative breast cancer. Cancers (Basel) 2021; 13 (14) 3472
• 39 Chae S, Kang KM, Kim HJ. et al. Neutrophil-lymphocyte ratio predicts response to chemotherapy in triple-negative breast cancer. Curr Oncol 2018; 25 (02) e113-e119
• 40 Shi K, Westhuyzen J, Shakespeare TP, Aherne NJ. Prognostic value of the neutrophil-lymphocyte ratio in triple-negative breast cancer patients. Clin Breast Cancer 2021; 21 (06) e667-e674
• 41 Schmid P, Cortes J, Pusztai L. et al; KEYNOTE-522 Investigators. Pembrolizumab for early triple-negative breast cancer. N Engl J Med 2020; 382 (09) 810-821
• 42 Caparica R, Lambertini M, Pondé N, Fumagalli D, de Azambuja E, Piccart M. Post-neoadjuvant treatment and the management of residual disease in breast cancer: state of the art and perspectives. Ther Adv Med Oncol 2019; 11: 1758835919827714
• 43 Tutt ANJ, Garber JE, Kaufman B. et al. Adjuvant olaparib for patients with BRCA1- or BRCA2-mutated breast cancer. N Engl J Med 2021; 384 (25) 2394-2405

Publication History

Article published online:
10 February 2026