Our analysis is in line with previously reported studies showing that markers relatively easily obtained from peripheral blood samples might be important factors for prediction of DFS and OS17,18. However, it is important to determine which of the blood markers measured at the beginning of treatment have independent predictive power, and whether consideration of blood parameters during chemotherapy provides more information for this purpose. NLR measured before the start of neoadjuvant chemotherapy (NLR1) was the only independent prognostic serologic marker for prediction of survival. In previous neoadjuvant studies it has not been shown unequivocally that in TNBC NLR1 is an independent factor predicting survival (both DFS and OS) 9,11,14,19,20,21,22,23,24,25; however, a recent analysis of Bae et colleagues presented on a greater cohort this independent association13 (Table 6).
Table 6
Prognostic value of baseline neutrophil-to lymphocyte ratio (NLR1) in triple-negative breast cancer (TNBC) patients treated with neoadjuvant chemotherapy.
Reference | N | Neoadjuvant (%) | Adjuvant (%) | significant in MVA | non-significant in MVA |
---|
Losada et al.23 | 25 | 100 | | (DFS, OS)* | |
Asano et al.24 | 61 | 100 | | | DFS |
Goto et al.25 | 83 | 100 | | | DFS, OS |
Chae S. et al.9 | 87 | 100 | | pCR | DFS, OS |
Patel et al.11 | 126 | 36.5 | 52.4 | OS | DFS |
Our study | 137 | 100 | | DFS, OS | |
Liu C et al.14 | 161 | 18 | 81 | DFS, OS | |
Muñoz-Montaño et al.20 | 261 | 100 | | DFS, OS | |
Ren K et al.22 | 281 | 21 | 79 | DFS, OS | |
Lee J.et al.21 | 358 | 14 | 86 | OS | DFS |
Qiu X. et al.19 | 406 | 21.2 | 78.8 | DFS, OS | |
Bae SJ et al.13 | 459 | 100 | | DFS, OS | |
* MVA not performed. |
DFS, disease-free survival; MVA, multivariate analysis; OS, overall survival; pCR, pathologic complete remission. |
It was suggested that incorporating PLR may also be important predicting survival26,27. Some reports concluded that the use of SII, which incorporates NLR and PLR, may better predict the efficacy of chemotherapy, compared to either factor separately. This hypothesis has not been investigated specifically in TNBC population treated with neoadjuvant chemotherapy28,29. In our analysis PLR and also SII were prognostic in the univariate analysis for DFS and OS, but these associations were less pronounced compared to NLR. In addition, there was a strong correlation with NLR; consequently, these parameters were not included in the multivariate analysis. This observation is consistent with a recent meta-analysis summarizing 39 studies which include also neoadjuvant studies and TNBC patients. This analysis shows that NLR can predict DFS and OS, but PLR has prognostic role only for OS with less statistical power than NLR30.
Interestingly, in our analysis Ki67 value and pathological stage had independent prognostic value, but with different cut-offs, than usually applied. Tumors with Ki67 value over 50% had significantly worse survival; however, in clinical practice the 14% or 30% are used as cut-offs5. A question is raised whether a 50% cut-off should be applied for TNBC. For cases where pCR was not reached, the relapse rate is much higher and additional chemotherapy is frequently indicated. However, in our study, the survival rate of patients with minimal residual disease (Ia) was similar to that of patients with pCR.This observation reflects the results of Symmans et al31.
The temporal change and serial measurement during neoadjuvant therapy of these markers may also be important. They could reflect treatment efficacy, change in biological behavior of the tumor or host immune reactions. The prognostic value of markers before the 3rd cycle in general was not as pronounced as NLR at the baseline and did not add prognostic information to baseline values in our analysis. There are data showing that NLR value measured in different time-points during neoadjuvant treatment may have a role in survival prediction11. Choi and colleagues reported that change in NLR from baseline to a sample taken shortly before the 3rd cycle ((NLR3-NLR1)/NLR1, with the cut-off level of 0.1258) was predictive for survival15. In our analysis this value and a cut-off level calculated by ROC analysis resulted in a non-significant difference of DFS curves (data not shown). The discrepancy can be explained by the fact that the proportion of TNBC patients in the Choi study was only 25%, and as a result, 54% of patients received postoperative hormonal therapy.The blood immune-markers have to be standardized for clinical use. In clinical studies cited in this work the cut-off values of NLR varies between 1.34–4, and PLR varies between 185–292. In the meta-analysis of Guo et al. the cut-off values of NLR under and above 3.0 equally produced significant results30. In the case of PLR their results were inconclusive, but PLR above 185 may be more suitable. In our analysis the cut-off for NLR was 2.76 and for PLR 118.4. In ROC analysis the best threshold for NLR3 was 3.27 and for PLR3 225. However, these were not significant factors and not justifiable to use different thresholds at different time points. It seems reasonable to follow the method of Vernieri and colleagues to set the cut-off for NLR at a certain point for clinical purpose and for standardization32.
In a recent meta-analysis of 52 neoadjuvant studies, pCR rate was 21.1% overall and 30% in TNBC. Pathological complete response was associated with significantly reduced disease recurrence (HR 0.31). This effect was more pronounced in TNBC (HR 0.18). The five-year event-free survival was 88% for those with pCR and was similar with and without adjuvant chemotherapy. The authors stated that attaining pCR after neoadjuvant chemotherapy is likely to reflect tumor biology and highlights the need for further research to evaluate clinical utility of escalation/de-escalation strategies in the adjuvant setting based on neoadjuvant response for patients with localized breast cancer2. In our analysis, the pCR rate (28%) was lower than expected which could be explained by the use of older and less effective chemotherapeutic regimes available at that time. The relapse after pCR had no association with NLR or other investigated biomarkers which is in line with the results of Bae et al13. The relapse rate after pCR was higher than in the above mentioned meta-analysis which has several causes. It could be partly explained with patient selection. Our center is a national center receiving patients from all regions of Hungary where the medical therapies can vary significantly. In many cases our patients faced problems reaching the oncological centers. Therefore, the OS can be adversely affected by regional differences in access to care. In many cases, the original treatment plan in our cohort was to use chemotherapy both pre- and postoperatively. It is not proven that the same survival results can be achieved by shorter neoadjuvant therapy producing pCR, but without adjuvant treatment than with full chemotherapy. Lastly, no standardized staging was compulsory before starting therapy in that time. However, all these considerations draw attention to the importance of the standardization of oncological care through our country.
Our analysis has some limitations. The data collection took place retrospectively in one institution. The chemotherapy did not follow a uniform scheme, and approximately half of the patients were treated without taxane. Paired data of pathologic prognostic factors in core and surgery specimens were not available in all cases and therefore the change in these factors could not be examined. In this analysis not all previously reported blood markers were considered (e.g. monocyte-to-lymphocyte ratio), although the most relevant parameters found in the literature were included. The tumor infiltrating lymphocyte ratio (TILs) and PD-L1 expression were not measured, though they have predictive and prognostic significance in several investigations and may also have associations with blood immune-markers21. Other parameters, which may also influence the OS (e.g. first and further treatment lines of relapsed patients, further surgery or irradiation, etc.) were not recorded.
In this investigation a broad spectrum of characteristics were investigated, among them several common hematological parameters, not just once but at two time-points. From easily accessible putative blood immune-markers NLR at baseline proved to have the strongest prognostic significance. Our search for new blood markers suggests that other markers may also be useful for prognosis prediction beyond wildly accepted prognostic factors such as stage and pCR in triple-negative breast cancer. In our view it is worth exploring the role of such serologic markers also at different time points in a prospective trial, which may help identify patients who potentially benefit from treatment change, de-escalation or escalation.