Breast cancer is a frequent entity whose management has evolved in recent years. Nowadays there is a tendency towards more conservative techniques. In the last decade of the 20th century, sentinel lymph node (SLN) biopsy replaced systematic axillary lymph node dissection (ALND), becoming the standard procedure for staging the axilla in breast cancer patients with clinically node-negative axilla [1, 2, 3, 4]. This caused a decrease of ALND rates [5] along with its associated comorbidity [6]. In aims to assess semiquantitatively the state of the SLN, the “One Step Nucleic Acid Amplification” (OSNA) method was proposed [7, 8, 9, 10, 11]. It is based on the quantification of Cytokeratin 19 (CK19) mRNA, which is expressed in more than 95% of breast cancer cases [12], and it is associated with total tumor load (TTL). The OSNA method shows a rentability comparable to conventional histologic techniques, and greatly benefit patients with clinically node-negative axilla [10, 11].

Determination of the different values of SLN TTL allows a different surgical approach to the axilla. In cases with an undetectable or low TTL, the ALND may be safely avoided [13, 14, 15]. Patients with detected micrometastasis in SLN have a disease-free and overall survival comparable to those who received an ALND [16]. Moreover, patients with a T1-2 tumor who had macrometastasis in two or less SLN and received conservative surgery, radiotherapy and adjuvant systemic therapy, showed similar results in terms of survival [13].

On the other hand, TTL of CK19 mARN correlates with the presence of metastasis in non-sentinel lymph nodes (NSLN), thus it is considered the most important predictive factor for the presence of metastasis in NSLN [17]. This is the reason why several cut-off points have been published for SLN TTL to determine when to perform an ALND [18, 19, 20]. Said cut-off points vary between 2150 copies, established by Terretano et al. [20], and 15,000 copies of CK19 mARN, defined by Peg et al. [19]. However, SNL TTL is not the only predictive factor for metastasis in NSLN. Previous studies tried to identify predictive factors for metastasis in NSLN in aims avoid ALND [21, 22, 23, 24]. Clinical and pathological factors have been described in aims to improve the predictive capability of SNL TTL. In this regard, we consider that a unique cut-off point of CK19 mARN copies would not be enough to predict the probabilities of metastasis in NSLN [25], given that there are other factors to be considered. Thus, our objective is to design a software-applied predictive model relating patients clinical and pathological traits associated with SNL TTL to individually establish the need to perform an ALND.

An observational retrospective study was carried out, including 127 patients with breast cancer in which a SLN biopsy was performed with the OSNA method and a subsequent ALND. Patients were consecutively recruited between October 1st 2010 and April 31st 2018.

Inclusion criteria were as follow: patients who had surgery for an invasive T1-3 breast carcinoma, which expressed CK19, with clinically node-negative axilla, and a normal preoperative axillar ultrasound or a lymph node biopsy with no evidence of metastasis. Patients with neoadjuvant chemotherapy treatment, previous ipsilateral axillary surgery, cancer recurrence or extensive in situ ductal carcinoma, were excluded from the study.

Variables studied were: age, menopausal status, menopause age, parity, number of births, ALND, tumor size, tumor histology type (ductal, lobular or others), multicentricity (presence of 2 or more tumor foci in different quadrants of the same breast or foci more than 5 centimeters from the primary focus), multifocality, lymphovascular invasion, tumor histological grade according to Modified Bloom-Richardson (tubules, nuclei and mitosis), estrogen receptors (ER), progesterone receptors (PR), y cHer-2 protein (HER2), Ki-67, SLN (macro or micrometastasis), NSLN (presence or absence of metastasis) and SLN TTL. Immunohistochemistry (IHC) classification was based in previously stablished criteria [26]: “Luminal A-like” (all of: ER and PR positive, HER2 negative and Ki-67 low); “Luminal B-like HER2 negative” (ER positive, HER2 negative and at least one of: Ki-67 high, PR negative or low); “Luminal B-like HER2 positive” (ER positive, HER2 over- expressed or amplified, any Ki-67, any PR); “HER2 positive non-luminal” (HER2 over- expressed or amplified, ER and PR absent); “Triple negative ductal” (ER and PR absent, HER2 negative).

Prior to surgery, and after the breast cancer diagnosis, all patients were assessed with an axillar ultrasound. Axillary lymph nodes suspicious for metastasis were those who shown cortical thickening of 2–3 mm, focal bulge, round shape, partial or complete absence of the fatty hilium, non-hiliar cortical blood flow, or a complete or partial replacement by tumoral tissue. A core needle biopsy was performed in patients with suspicious lymph-nodes. If the presence of metastasis was confirmed patients were excluded from the study.

During surgery, SLN biopsy was performed according to the established protocol in our unit, marking the node with a radiopharmaceutical and blue dye. The radiopharmaceutical used was 99mTc albumin nanocolloid, which was injected in the intradermic periareolar area a day prior to surgery. The dye used was methylene blue. Once the patient was under anesthesia, 2 mL of methylene blue was injected in the four quadrants of the periareolar area (0.5 mL per quadrant). Once the SLN was located and extirped, it was sent to the Anatomy Pathology unit for application of the OSNA method according to the existing literature [9]. The amplification rate was assessed by specthophotometry, and the number of CK19 mARN copies was calculated in relation to a standard curve. Macrometastasis were defined as the existence of more than 5000 copies/$\mu$L, micrometastasis as 250–5000 copies/$\mu$L, and absence of metastasis as less than 250 copies/$\mu$L [9].

Afterwards a Level II ALND was performed and NSLN were histologically assessed after being processed with a hematoxylin and eosin stain. Tissue blocks of NSLN were selected with a width of 3 microns, in a 200 microns interval, to determine the presence or absence of metastasis.

The main finding of our study is that a model based in the TTL, IHC, multicentricity and PR can predict 77% of patients with metastasis in NSLN. Given the simplicity of this model, which includes only 4 parameters (TTL, IHC, multicentricity an PR), it is easy to apply intraoperatively in any breast cancer unit. When applying this proposed predictive model, any breast surgeon can easily predict the probability of metastasis in NSLN and then decide whether to perform an ALND during the surgery act (Fig. 3).

Fig. 3.

Example of using the binary model based on total tumor load (TTL), IHC, MC and PR as a predictor for metastasis in non-sentinel lymph-nodes. PR (progesterone receptors): 0 = Presence of progesterone receptors; 1 = No presence of progesterone receptors. IHC (Immunohistochemistry): 0 = Luminal A-like; 1 = No Luminal A-like. MC (multicentricity): 0 = multicentric tumor; 1 = Non-multicentric tumor.

Up until recently, nomograms have been based in SLN TTL, establishing different AUC ranging between 0.66 and 0.86 [20, 27, 28, 29, 30, 31, 32, 33]. In our work, we described an AUC of 0.77 (95% CI, 0.688–0.852; p 0.0005), similar to those previously published, although we included clinical and pathological factors that may affect the probability of metastasis in NSLN. In a previous study, our group described an AUC of 0.651 using only the TTL, rising to 0.752 [25] when adding clinical and pathological factors (multicentricity, IHC and RP). Thus, we believe that clinical and pathological factors are of the utmost importance for the design of the presented model, for they allow us to individually assess each patient for the need of performing an ALND.

There have been publications of several cut-offs points for the copies of CK19 mARN in SLN TTL to decide on the ALND. Heilmann et al. [34] defined 7900 copies/$\mu$L as the cut-off point, with a sensibility of 91% and specificity of 61%. In their work, they combined histologic techniques and the OSNA method for the processing of SLN, which might alter the number of copies. In several other publications, we can observe that different cut-off points for the SLN TTL in the prediction of metastasis in NSLN have progressively decrease in recent years [18, 19, 20]. Peg et al. [19] defined in 2013 a high cut-off points of 15,000 copies (Sensibility: 76.7%, Specificity: 55%; Positive predictive value: 41.1%; Negative predictive value: 85.5%). Later, Ambrogio et al. [18] established a cut-off point of 7700 copies (Sensibility: 78%, Specificity: 57%; Positive predictive value: 50%; Negative predictive value: 83%), similar to the cut-off point of 7294 copies published by our group [25]. Terretano et al. [20] presented in 2017 the lowest cut-off point of 2150 copies sensibility: 94.9%, Specificity: 51.4%; Positive predictive value: 46.5%; negative predictive value: 95.8%). These variations among values of the SLN TTL for the prediction of metastasis in NSLN indicate that none of them are superior to the rest, and we should use other associated parameters. Thus, our model included the previously mentioned variables to individually assess the need of an ALND.

The association between clinical and pathological factors and the risk of metastasis in NSLN have been established in several studies, like the HER-2 status or the histological and nuclear grade described by Meretoja et al. [35]. Tumor size is also considered an important factor for metastasis in NSLN [36, 37, 38]. Furthermore, some factors have even been included in nomogram like the association of the TTL with tumor size, lymphovascular invasion, HER-2 status and number of metastatic SLN [28].

In contrast, Shimazu et al. [29] stated that nomograms using several pathological parameters are not practical for intraoperative decision-making. However, we consider that a simplify model like the one presented may be quite useful given the feasibility of use during surgery with a high predictive capacity.

We consider our study to have many strengths, one of them being the considerable sample size, with the inclusion of a representative sample of breast cancer patients undergoing ALND. Another notorious strength of our study is the fact that this proposed model allows for individual assessment of the need to perform ALND in the operating room, that can be made in a quick, effective and simple way without extending surgery time. Nonetheless, our study also has some limitations. We consider that a prospective design, along with the need for external validation might be considered for future studies. In addition, it would require an external validation to be able to apply it in routine practice.

In conclusion, the combination of TTL, IHC, multicentricity and PR can predict 77% of patients with metastasis in NSLN and said prediction may be made intraoperatively in a feasible manner.

SLN, Sentinel lymph node; ALND, Axillary lymph node dissection; OSNA, One step nucleic acid amplification; CK19, Cytokeratin 19; TTL, Total tumor load; NSLN, Non-sentinel lymph nodes; IHC, Immunohistochemical; ER, Estrogen receptors; PR, Progesterone receptors; MC, Multicentricity.

JAGM and JAS designed the research study. RGJ performed the research. AFP analyzed the data. JAGM, MSS, RGJ, and JAS wrote the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.

All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki , and the protocol was approved (on January 29th 2019) by Andalucia’s Board of Biomedicine Ethics Committee (registration number: 1004-N-18).

Thanks to all the peer reviewers for their opinions and suggestions.

This research received no external funding.

The authors declare no conflict of interest.