A Novel Prognostic Nomogram for 2-Year Survival in HER2-Positive Breast Cancer Patients

Background: Targeted therapies have largely improved prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Yet, disease can still progress rapidly for some patients in the rst two years after diagnosis. Our study aimed to establish a nomogram model to predict 2-year breast cancer-specic survival (BCSS) in early HER2-positive breast cancer patients. Methods: A total of 32,481 HER2-positive patients derived from Surveillance, Epidemiology, and End Results (SEER) database were included in the construction of nomogram. Concordance index (C-index) and calibration curve were used to evaluate the discrimination ability and predictive accuracy. We also tested the model in 804 patients from Shanghai Jiao Tong University Breast Cancer Data Base (SJTU-BCDB). Results: Age, estrogen receptor (ER) status, progesterone receptor (PR) status, histologic type, T stage and N stage were selected to construct the nomogram according to multivariable analysis. The 2-year BCSS rate was 95% and 60% for patients at low risk (<8 points) and high risk (>13 scores) respectively. The C-index of model derived from SEER database is 0.81 (95%CI 0.79-0.83). Sensitivity analysis was performed in patients undergoing breast surgeries with the C-index of 0.81 (95%CI 0.79-0.83). Validation in 804 patients from SJTU-BCDB showed respective C-index of 0.77 (95%CI, 0.62-0.92) in total population, 0.67 (95%CI 0.44-0.90) in patients receiving anti-HER2 therapy and 0.90 (95%CI 0.81-0.90) in those without targeted therapy. Conclusions: The novel nomogram can predict 2-year survival in HER2-positive patients and


Background
Breast cancer is a common type of malignant tumor among women worldwide. Human epidermal growth factor receptor 2 (HER2) was acknowledged to be one of the important predictors for breast cancer patients. HER2 positivity, de ned as HER2 overexpression or ampli cation, is associated with aggressive disease progression and poor clinical prognosis 1 and accounts for 15-20% of all breast cancers 2 . The emergence of several anti-HER2 agents has markedly improved the survival outcome of HER2 positive breast cancer patients 3 . Trastuzumab, a monoclonal antibody targeting against HER2 receptor 4 , was recommended to be used regularly combined with other necessary adjuvant therapies in HER2-positive diseases because of its validated therapeutic effect in a series of clinical trials 3,5 However, survival outcomes diverge in patients receiving trastuzumab. Treatment failures are common in HER2-positive breast cancer, especially in early phase of treatment. Evidence showed that cumulative breast cancer progression rate could come up to 10-15% in the rst two years under trastuzumab treatment and then reach a plateau of 20-25% gradually in the following years 3 , leading to more attention on insu cient treatment and primary drug resistance happened in early treatment.
Following the approval of trastuzumab, more anti-HER2 compounds, such as pertuzumab, lapatinib, neratinib and trastuzumab-DM1 (T-DM1) [6][7][8][9] , came into public for the intensi ed treatment of HER2positive breast cancer patients. Although these new drugs provided more available options, how to weigh against bene t, toxicity and cost remained di cult when clinicians made therapeutic decisions. Here, we performed a retrospective study and aimed to provide a new tool to predict the 2-year survival in nonmetastatic HER2-positive breast cancer patients, which may assist clinicians in selection between moderate and aggressive therapeutic strategies.

Statistical Analysis
Breast cancer-speci c survival (BCSS) and overall survival (OS) with corresponding 95% con dence interval (CI) was estimated by Kaplan-Meier method and 2-year BCSS was selected as the primary outcome based on which the nomogram was constructed. To identify potential predictors, we performed univariate and multivariate Cox proportional hazards model and factors with p-value > 0.05 were excluded. The package of rms on R Studio was used to construct the nomogram model. The discrimination ability and calibration of the nomogram was measured by Concordance index (C-index) and calibration plot respectively. We made sensitivity analysis in patients without any breast operation. External validation was performed in patients from SJTU-BCDB. All tests were performed using R Studio version 1.2.5019 based on R version 3.6.1.

Baseline Characteristics
Clinicopathologic features of primary cohort and validation cohort were presented in Table 1. 665 BCSS events happened in primary cohort and 9 in validation cohort. 1152 patients in primary set and 10 patients in validation set developed 2-year OS events respectively. Notably, 5.35% (n = 1,740) of patients in primary cohort didn't receive any surgery while all patients in validation cohort underwent breast operation.  Table 2. In addition, analysis of potential prognostic factors for 2-year OS showed similar outcomes (Table 3).

Nomogram Construction
According to the multivariable cox regression model, we constructed a prognostic nomogram using age, ER, PR, histologic type, T stage and N stage (Fig. 1). For an individual patient, each predictor is assigned with a speci c score according to the rst row of the nomogram. The total points of six predictors can be calculated to predict the probability of 2-year BCSS by locating points in the seventh row. In our nomogram, 89.2% of patients had total scores less than eight and the probability of 2-year BCSS were 95%. A total score of eight to thirteen was associated with a moderate 2-year BCSS (range 60%-80%). 29 patients had total scores more than thirteen, and they were at high risk with a 2-year BCSS of less than 60%. Statistical difference was observed among the three subgroups (log-rank p < 0.001).

Internal and External Validation
Internal validation showed a C-index of 0.81 (95%CI 0.79-0.83) for 2-year BCSS prediction. To avoid the potential disturbance of breast surgery, sensitivity analysis was performed in patients receiving operation. A C-index of 0.81 (95%CI 0.79-0.83) supported the universality of the novel nomogram in HER2-positive breast cancer patients with or without receiving breast surgery (Fig. 2). The calibration plots for prediction 2-year BCSS in primary cohort and sensitivity analysis showed good consistency between predicted probability and observed probability.
To evaluate the external applicability of the nomogram model, we validated it in the independent data derived from SJTU-BCDB.

Discussion
In the last two decades, the introduction of anti-HER2 agents had revolutionized the treatment of HER2positive breast cancer patients impressively 10 . Besides trastuzumab, addition or substitution of new novel anti-HER2 regimens were common in clinical practice, accompanied with increased cost and toxicity 11 . Therefore, it is important for clinicians to identify the HER2-positive patients at high risk of recurrence or death and monitor therapeutic strategies accordingly.
Our study discovered prognostic factors for 2-year survival outcome of HER2 + breast cancer patients based on which we built a prognostic model. Emerging evidence indicated that the rst two years were particularly important in HER2-positive breast cancer treatment. Although trastuzumab plus standard chemotherapy for early-stage HER2 positive breast cancer was recommended by National Comprehensive Cancer Network guideline 12 , new recurrences could be observed during or within 12 months after 1-year adjuvant trastuzumab treatment, which was de ned as trastuzumab resistance 13,14 . In clinical trials, the results showed that approximately 10-15% early HER2 positive breast cancer patients receiving trastuzumab treatment experienced disease progression in the rst two years and then the rate increased slowly and nally reached a plateau of 20-25% in the following years 3,5 . Different from HER2-positive subtype, the results of clinical trials showed that for triple-negative breast cancer, the DFS and OS rates remained high in the rst 12 months and then kept decreasing slowly in the following years 15,16 . Comparatively, patients with HR+/HER2-had high 5-year DFS or BCSS rates 17,18 though recurrences can occur even several decades later after primary diagnosis 18 . These data called for more attention to the prognosis in the rst two years of the treatment for HER2-positive early breast cancer patients.
Therefore, we chose to analyzed potential predictive factors for 2-year BCSS in HER2 + early breast cancer. Age, ER status, PR status, histologic type, T stage and N stage were found signi cantly associated with HER2 + breast cancer prognosis. ER and PR positivity were associated with better BCSS, which was in agreement with previous retrospective studies 19,20 . The favorable effects of ER or PR positivity on the survival outcome of HER2 + breast cancer patients were also observed when the OS or DFS rates were compared between HR positive and HR negative subgroups in clinical trials 3,5,6,8 . Grade was commonly recommended as a predictor for breast cancer prognosis 21 . However, our study showed that it might be less valuable when predicting the very early survival outcome of HER2 + subtype. The majority of HER2 + tumors presented with histologic grades of 2 or 3 and none statistically important impact of tumor grade on survival outcome of HER2 + patients was observed, which was concordant with previous knowledge 20 . The effect of different pathologic types on short-term survival outcome was generally overlooked before. Here, we found it necessary to classify the histologic type into two categories to improve the predictive ability.
Nomogram is a well-developed graphical model for cancer prognosis 22 . It emphasizes the magnitude of the effect of each predictor and makes the integration more convenient to read and use. Data source of our nomogram were derived from SEER database which covered about 34.6% of the U.S. population 23 , making the model more generalizable. All of the predictors in our nomogram model were basic clinicopathologic characteristics which could be collected easily during the process of diagnosis and treatment, so that it would be used conveniently in clinical practice. According to the nomogram, patients at high risk had increasing chances experiencing BCSS events and therapeutic escalation, such as concomitant trastuzumab and pertuzumab 6 or sequential trastuzumab and neratinib 7,24 might be considered. On the other hand, patients with low scores were less risky and proper de-escalated therapy, such as strategies in the APT trial, could lighten the nancial burdens for patients and avoid adverse effects without therapeutic effect compromise 25 .
We should admit that there were some limitations of the nomogram model. We could not obtain the details about whether patients derived from SEER database received anti-HER2 treatment and our model was based on the whole population without regard to anti-HER2 drug use. To solve this problem, we validated our model in patients from SJTU-BCDB. Although the number of 2-year DFS events was small in validation cohort, the nomogram model still showed good predictive ability. Because the validation was based on one single institution in China, whether the nomogram could be generally applied should be further investigated.

Conclusions
In conclusion, we constructed a novel nomogram with great potential to help clinicians with making therapeutic strategies for HER2-positive non-metastatic breast cancer patients. Still, our model needed to be tested in various populations to gain greater reliance.

Declarations
Ethics approval and consent to participate: Not applicable Consent for publication: Written informed consent for publication was obtained from all participants.
Availability of data and materials: