Abstract
Objective
This study aims to investigate the potential prognostic value of albumin-bilirubin (ALBI) score in breast cancer patients with liver metastasis after surgery.
Methods
This was a retrospective study of 178 breast cancer patients with liver metastasis after surgery. ALBI score was calculated by the following formula: (log10 bilirubin × 0.66) − (albumin × 0.085). The optimal cutoff value of ALBI score was assessed by X-tile. The clinical influence of ALBI score on survival outcomes using Kaplan-Meier method, Log-rank test, Cox proportional hazards regression model. The calibration curves, decision curve analysis and time-dependent ROC curve were used to assess the predictive performance of the nomogram's models.
Results
The classifications of 178 breast cancer patients with liver metastasis after surgery were as follows: low ALBI score group (＜−3.36) vs. high ALBI score group (≥−3.36). The Cox proportional hazards regression model indicated that ALBI score was a potential predictor. Kaplan-Meier survival curve performed that the median disease free survival (p = 0.0029) and overall survival (p＜0.0001) in low ALBI score group were longer than in high ALBI score group. The ALBI-based nomograms had good predictive performance.
Conclusions
The ALBI score has high prognostic ability for survival time in breast cancer with liver metastasis after surgery. These models will be valuable in discriminating patients at high risks of liver metastasis.
Keywords: Breast cancer, Albumin-bilirubin grade, Albumin, Bilirubin, Liver metastasis
1. Introduction
Breast cancer is an onerous public health burden and the leading cause of cancer-related deaths in females all over the world [1]. There is a wide variety of therapeutic options for patients with breast cancer, according to Tumor-Node-Metastasis (TNM) staging system and performance status [2]. Surgical operation is the unique potential therapeutic method. Unfortunately, more than half of breast cancer deaths are caused by distant metastasis [3]. Take into consideration of the high incidence rate and aggressive behavior, patients diagnosed with breast cancer need to be classified to comply with the severity of the disease. And this classification can direct patients to select the appropriate treatment method. In clinical practice, it is distinguished to employ the markers that are prone to measure by non-invasive techniques. Serum tumor markers are quite prone to determine, together with beneficial for diagnosis and prediction of survival. Currently, prognostic factors such as carbohydrate antigen 125 (CA125), carbohydrate antigen 15–3 (CA15-3), carcinoembryonic antigen (CEA) have been proposed to this aim [[4], [5], [6]]. However, these tumor markers can be found normal in a small portion of breast cancer patients. Hence, more sensitive and efficient markers are required to predict the prognosis of breast cancer patients.
In recent years, there has been increasing interest in creating predictive biomarkers for plethora cancers based on serological and hematological tests. Johnson PJ and colleagues reported the albumin-bilirubin (ALBI) grade, which was based on serum bilirubin and albumin levels, acted as a novel model for objective measure of liver function [7]. The ALBI grade was initially applied to evaluate the severity of liver dysfunction in liver cancer patients. Some studies have proved that ALBI grade could predict the prognosis in hepatocellular carcinoma patients with resectable, recurrence or locally advanced disease [[8], [9], [10]]. Moreover, recent studies have also indicated that ALBI grade had prognostic value in a plethora of cancers including non-small-cell lung cancer, pancreatic cancer, intrahepatic cholangiocarcinoma, advanced gastric cancer, colorectal cancer [[11], [12], [13], [14], [15]]. The breast cancer commonly proliferates to liver, lungs, brain and bone. The survival time of breast cancer patients with liver metastasis without treatment is usually less than 9 months [16]. To our knowledge, there is currently no research in the literature to demonstrate the practicality of ALBI grade in predicting the prognosis of breast cancer with liver metastasis after surgery. Therefore, we aim to explore the prognostic value of ALBI grade in breast cancer patients with liver metastasis after surgery.
2. Methods
2.1. Ethics approval and consent to participate
This retrospective single center study was conducted in accordance with the amended Declaration of Helsinki, and was approved by the ethics committee of Cancer Hospital Chinese Academy of Medical Sciences (Approved no.82173328). The enrolled patients provided written informed consent for using their data in this retrospective study. The individual patient information has been protected.
2.2. Patients and samples enrolled in this study
From our database, we retrospectively identified 178 breast cancer with liver metastasis after surgery. These patients were treated and followed up from 2000 through 2018 at Cancer Hospital Chinese Academy of Medical Sciences. We groped the clinical and pathological data according to the electronic medical records.
2.3. Inclusion criteria and exclusion criteria
Inclusion requirements were that: 1) breast cancer patients with liver metastasis after surgery when followed up; 2) medical records with complete data and follow-up information. Exclusion requirements were that: 1) breast cancer patients with multiple metastases, such as lungs, brain and bone; 2) missing data and lost to follow up.
2.4. Calculation of albumin-bilirubin (ALBI) score
The albumin-bilirubin (ALBI) score was an indicator that combined the albumin and direct bilirubin level. Serum albumin and direct bilirubin were detected centrally at study baseline in this research. ALBI score was calculated based on the following formula: (log10 bilirubin × 0.66) − (albumin × 0.085), where bilirubin was in μmol/L and albumin in g/L. The optimal cutoff value of ALBI score was assessed by X-tile. In this study, patients were then grouped into two categories based on the ALBI score as low ALBI score group (＜-3.36) vs. high ALBI score group (≥-3.36).
2.5. Follow-up
All patients had routine checkups with a physical examination, hematology examination, breast ultrasound, or CT every three months. Disease free survival (DFS) was defined as the time from surgery to progression with live metastasis. Overall survival (OS) was defined as the time from surgery to the date of death from any cause or last follow-up.
2.6. Statistical analysis
All statistical analyses were performed using the IBM SPSS Statistics (version 23.0; SPSS Inc., Chicago, IL, USA), GraphPad Prism software (version 8.0; GraphPad Inc., La Jolla, CA, USA), and R (version 4.2.2; Vienna, Austria. URL: http://www.R-project.org/). Categorical variables were presented as absolute values and percentages (%). The comparison of the rates between the groups were analyzed with Chi-square test or Fisher's exact test. The optimal cut-off value was calculated by X-tile. Survival analyses were performed using Kaplan-Meier method and Log-rank test. The potential factors were examined with Cox proportional hazards regression model analysis. Nomograms of the potential prognostic factors by the multivariate analysis for survival time were established with R software. The prediction accuracy was performed by time-dependent ROC curve, and area under the curve (AUC) for different survival time. The calibration curve and decision curve analysis (DCA) were generated comparing the observed results with the predicted results to assess the accuracy of predictive performance. A P-value of ＜0.05 indicated statistical significance.
3. Results
3.1. Clinical characteristics of the patients enrolled in this study
Of 178 breast cancer patients with liver metastasis after surgery, all patients were female, with a median age of 49 years (range: 21–78 years). According to the optimal cut-off value of ALBI score by X-tile, patients with low ALBI score were 129 cases, and patients with high ALBI score were 49 cases. Table 1 summarized the clinical and pathological data of the 178 breast cancer patients with liver metastasis enrolled in this study. We explored the relationship between ALBI score and clinicopathological data, and found that ALBI score was significantly associated with menopause (p = 0.004), histologic grade (p = 0.043), positive lymph nodes (p = 0.038), molecular subtype (p = 0.002).
Table 1.
Clinical characteristics of the breast cancer patients with liver metastasis after surgery according to ALBI score.
| Characteristic |
level |
Low ALBI |
High ALBI |
p |
|---|---|---|---|---|
| n | 129 | 49 | ||
| Age | ＜49 | 75 (58.1) | 23 (46.9) | 0.241 |
| ≥49 | 54 (41.9) | 26 (53.1) | ||
| Marital status | Married | 125 (96.9) | 49 (100.0) | 0.496# |
| Unmarried | 4 (3.1) | 0 (0.0) | ||
| BMI | ＜23.51 | 65 (50.4) | 24 (49.0) | 1.000 |
| ≥23.51 | 64 (49.6) | 25 (51.0) | ||
| Family history | No | 106 (82.2) | 34 (69.4) | 0.098 |
| Yes | 23 (17.8) | 15 (30.6) | ||
| Menarche age | ＜14 | 36 (27.9) | 14 (28.6) | 1.000 |
| ≥14 | 93 (72.1) | 35 (71.4) | ||
| Menopause | No | 85 (65.9) | 20 (40.8) | 0.004 |
| Yes | 44 (34.1) | 29 (59.2) | ||
| ABO blood type | A | 27 (20.9) | 9 (18.4) | 0.632# |
| B | 45 (34.9) | 20 (40.8) | ||
| O | 45 (34.9) | 18 (36.7) | ||
| AB | 12 (9.3) | 2 (4.1) | ||
| Type of surgery | Mastectomy | 120 (93.0) | 49 (100.0) | 0.130# |
| Breast-conserving surgery | 9 (7.0) | 0 (0.0) | ||
| Pathological tumor size | ≤2 cm | 45 (34.9) | 15 (30.6) | 0.394# |
| ＞2 and ≤5 cm | 69 (53.5) | 31 (63.3) | ||
| ＞5 cm | 15 (11.6) | 3 (6.1) | ||
| Histologic grade | I | 5 (3.9) | 6 (12.2) | 0.043 |
| II | 74 (57.4) | 31 (63.3) | ||
| III | 50 (38.8) | 12 (24.5) | ||
| Pathological T stage | T1 | 37 (28.7) | 11 (22.4) | 0.620# |
| T2 | 72 (55.8) | 32 (65.3) | ||
| T3 | 10 (7.8) | 2 (4.1) | ||
| T4 | 10 (7.8) | 4 (8.2) | ||
| Pathological N stage | N0 | 26 (20.2) | 7 (14.3) | 0.228 |
| N1 | 29 (22.5) | 7 (14.3) | ||
| N2 | 38 (29.5) | 14 (28.6) | ||
| N3 | 36 (27.9) | 21 (42.9) | ||
| Pathological TNM stage | I | 6 (4.7) | 5 (10.2) | 0.060 |
| II | 45 (34.9) | 9 (18.4) | ||
| III | 78 (60.5) | 35 (71.4) | ||
| Total lymph nodes (TLN) | ＜19 | 63 (48.8) | 23 (46.9) | 0.953 |
| ≥19 | 66 (51.2) | 26 (53.1) | ||
| Positive lymph nodes (PLN) | ＜5 | 69 (53.5) | 17 (34.7) | 0.038 |
| ≥5 | 60 (46.5) | 32 (65.3) | ||
| Molecular subtype | Luminal A | 3 (2.3) | 7 (14.3) | 0.002# |
| Luminal B HER2+ | 18 (14.0) | 13 (26.5) | ||
| Luminal B HER2- | 64 (49.6) | 13 (26.5) | ||
| HER2 enriched | 24 (18.6) | 9 (18.4) | ||
| Triple negative | 20 (15.5) | 7 (14.3) | ||
| ER | Negative | 43 (33.3) | 17 (34.7) | 1.000 |
| Positive | 86 (66.7) | 32 (65.3) | ||
| PR | Negative | 45 (34.9) | 15 (30.6) | 0.718 |
| Positive | 84 (65.1) | 34 (69.4) | ||
| HER2 | Negative | 86 (66.7) | 27 (55.1) | 0.209 |
| Positive | 43 (33.3) | 22 (44.9) | ||
| Ki67 | Negative | 38 (29.5) | 20 (40.8) | 0.206 |
| Positive | 91 (70.5) | 29 (59.2) | ||
| AR | Negative | 124 (96.1) | 48 (98.0) | 0.888# |
| Positive | 5 (3.9) | 1 (2.0) | ||
| CK5/6 | Negative | 113 (87.6) | 43 (87.8) | 1.000 |
| Positive | 16 (12.4) | 6 (12.2) | ||
| E-cad | Negative | 71 (55.0) | 27 (55.1) | 1.000 |
| Positive | 58 (45.0) | 22 (44.9) | ||
| EGFR | Negative | 118 (91.5) | 44 (89.8) | 0.955 |
| Positive | 11 (8.5) | 5 (10.2) | ||
| P53 | Negative | 73 (56.6) | 26 (53.1) | 0.799 |
| Positive | 56 (43.4) | 23 (46.9) | ||
| TOP2A | Negative | 91 (70.5) | 34 (69.4) | 1.000 |
| Positive | 38 (29.5) | 15 (30.6) | ||
| Lymph vessel invasion | Negative | 82 (63.6) | 36 (73.5) | 0.284 |
| Positive | 47 (36.4) | 13 (26.5) | ||
| Neural invasion | Negative | 118 (91.5) | 45 (91.8) | 1.000# |
| Positive | 11 (8.5) | 4 (8.2) | ||
| Postoperative chemotherapy | No | 28 (21.7) | 13 (26.5) | 0.629 |
| Yes | 101 (78.3) | 36 (73.5) | ||
| Postoperative radiotherapy | No | 34 (26.4) | 13 (26.5) | 1.000 |
| Yes | 95 (73.6) | 36 (73.5) | ||
| Postoperative endocrine therapy | No | 46 (35.7) | 23 (46.9) | 0.227 |
| Yes | 83 (64.3) | 26 (53.1) | ||
| Postoperative targeted therapy | No | 100 (77.5) | 40 (81.6) | 0.694 |
| Yes | 29 (22.5) | 9 (18.4) |
Abbreviation: BMI, body mass index; ER, estrogen receptor; PR, progesterone receptor; HER2, Human Epidermal Growth Factor Receptor 2; AR, androgen receptor; CK5/6, Cytokeratin 5/6; E-cad, E-cadherin; EGFR, Epidermal Growth Factor Receptor; TOP2A, topoisomerase 2A.
#Fisher's exact test.
3.2. Comparison of serological and hematological characteristics by ALBI score
The common serological and hematological makers were detected in breast cancer patients with liver metastasis after surgery. In this study, we choose the median value as the grouping criterion. The serological and hematological characteristics of patients by ALBI score were summarized in Table 2. ALBI score was significantly associated with albumin(ALB) (p＜0.001), cholesterol(CHOL) (p = 0.019), total protein(TP) (p = 0.005).
Table 2.
Comparison of serological and hematological characteristics based on ALBI score in breast cancer patients with liver metastasis after surgery.
| Characteristic |
level |
Low ALBI |
High ALBI |
p |
|---|---|---|---|---|
| n | 129 | 49 | ||
| Alanine aminotransferase (ALT) (U/L) | ＜17 | 61 (47.3) | 26 (53.1) | 0.603 |
| ≥17 | 68 (52.7) | 23 (46.9) | ||
| Aspartate aminotransferase (AST) (U/L) | ＜20 | 61 (47.3) | 27 (55.1) | 0.445 |
| ≥20 | 68 (52.7) | 22 (44.9) | ||
| Lactic dehydrogenase (LDH) (U/L) | ＜166 | 60 (46.5) | 23 (46.9) | 1.000 |
| ≥166 | 69 (53.5) | 26 (53.1) | ||
| γ-glutamyl transpeptidase (γ-GT) (U/L) | ＜17 | 53 (41.1) | 27 (55.1) | 0.131 |
| ≥17 | 76 (58.9) | 22 (44.9) | ||
| Albumin (ALB) (g/L) | ＜44.1 | 41 (31.8) | 42 (85.7) | ＜0.001 |
| ≥44.1 | 88 (68.2) | 7 (14.3) | ||
| Total bilirubin (TBIL) (μmol/L) | ＜8.60 | 66 (51.2) | 21 (42.9) | 0.411 |
| ≥8.60 | 63 (48.8) | 28 (57.1) | ||
| Direct bilirubin (DBIL) (μmol/L) | ＜2.75 | 70 (54.3) | 19 (38.8) | 0.093 |
| ≥2.75 | 59 (45.7) | 30 (61.2) | ||
| Indirect bilirubin (IBIL) (μmol/L) | ＜5.85 | 68 (52.7) | 21 (42.9) | 0.314 |
| ≥5.85 | 61 (47.3) | 28 (57.1) | ||
| Cholesterol (CHOL) (mmol/L) | ＜3.80 | 72 (55.8) | 17 (34.7) | 0.019 |
| ≥3.80 | 57 (44.2) | 32 (65.3) | ||
| Triglyceride (TG) (mmol/L) | ＜1.16 | 59 (45.7) | 28 (57.1) | 0.233 |
| ≥1.16 | 70 (54.3) | 21 (42.9) | ||
| Total protein (TP) (g/L) | ＜73.0 | 55 (42.6) | 33 (67.3) | 0.005 |
| ≥73.0 | 74 (57.4) | 16 (32.7) | ||
| Globulin(G) (g/L) | ＜29.0 | 62 (48.1) | 25 (51.0) | 0.853 |
| ≥29.0 | 67 (51.9) | 24 (49.0) | ||
| Albumin/Globulin (A/G) | ＜1.55 | 60 (46.5) | 28 (57.1) | 0.272 |
| ≥1.55 | 69 (53.5) | 21 (42.9) | ||
| Prealbumin (PAB) (mg/dl) | ＜27.0 | 63 (48.8) | 22 (44.9) | 0.763 |
| ≥27.0 | 66 (51.2) | 27 (55.1) | ||
| Carbohydrate antigen 125 (CA125) (U/ml) | ＜10.57 | 60 (46.5) | 29 (59.2) | 0.179 |
| ≥10.57 | 69 (53.5) | 20 (40.8) | ||
| Carbohydrate antigen 153 (CA153) (U/ml) | ＜13.01 | 64 (49.6) | 25 (51.0) | 1.000 |
| ≥13.01 | 65 (50.4) | 24 (49.0) | ||
| Carcinoembryonic antigen (CEA) (ng/ml) | ＜1.95 | 65 (50.4) | 24 (49.0) | 1.000 |
| ≥1.95 | 64 (49.6) | 25 (51.0) | ||
| D-Dimer (DD) (mg/L) | ＜0.21 | 67 (51.9) | 21 (42.9) | 0.360 |
| ≥0.21 | 62 (48.1) | 28 (57.1) | ||
| Fibrinogen (FIB) (g/L) | ＜2.75 | 64 (49.6) | 25 (51.0) | 1.000 |
| ≥2.75 | 65 (50.4) | 24 (49.0) | ||
| ABO blood type | A | 27 (20.9) | 9 (18.4) | 0.632a |
| B | 45 (34.9) | 20 (40.8) | ||
| O | 45 (34.9) | 18 (36.7) | ||
| AB | 12 (9.3) | 2 (4.1) | ||
| White blood cell ( × 109/L) | ＜5.45 | 64 (49.6) | 25 (51.0) | 1.000 |
| ≥5.45 | 65 (50.4) | 24 (49.0) | ||
| Neutrophils ( × 109/L) | ＜3.23 | 65 (50.4) | 23 (46.9) | 0.808 |
| ≥3.23 | 64 (49.6) | 26 (53.1) | ||
| Lymphocyte ( × 109/L) | ＜1.70 | 67 (51.9) | 21 (42.9) | 0.360 |
| ≥1.70 | 62 (48.1) | 28 (57.1) | ||
| Monocyte ( × 109/L) | ＜0.35 | 65 (50.4) | 24 (49.0) | 1.000 |
| ≥0.35 | 64 (49.6) | 25 (51.0) | ||
| Platelet ( × 109/L) | ＜233 | 62 (48.1) | 27 (55.1) | 0.502 |
| ≥233 | 67 (51.9) | 22 (44.9) |
Fisher's exact test.
4. The potential prognostic factors for DFS and OS
The prognostic factors for DFS according to the univariate and multivariate Cox proportional hazards regression model analyses were listed in Table 3. A multivariate analysis indicated that ALBI, Lactic dehydrogenase (LDH), Topoisomerase 2A (TOP2A) were the potential prognostic factors for DFS. The prognostic factors for OS based on the univariate and multivariate Cox proportional hazards regression model analyses were listed in Table 4. The multivariate analysis shown that ALBI, LDH, monocyte, ER, TOP2A were the potential prognostic factors for OS.
Table 3.
Univariate and multivariate survival analysis of disease free survival in breast cancer patients with liver metastasis after surgery.
| Characteristics |
Group |
Univariate |
95%CI |
Multivariate |
95%CI |
||||
|---|---|---|---|---|---|---|---|---|---|
| P | HR | Low | High | P | HR | Low | High | ||
| ALBI | Low | 1(Ref.) | 1(Ref.) | ||||||
| High | 0.028 | 2.601 | 1.109 | 6.101 | 0.000 | 2.637 | 1.709 | 4.067 | |
| Age | ＜49 | 1(Ref.) | |||||||
| ≥49 | 0.233 | 1.260 | 0.862 | 1.843 | |||||
| Marital status | Married | 1(Ref.) | |||||||
| Unmarried | 0.137 | 5.088 | 0.598 | 43.311 | |||||
| BMI | ＜23.51 | 1(Ref.) | |||||||
| ≥23.51 | 0.704 | 1.139 | 0.583 | 2.222 | |||||
| Family history | No | 1(Ref.) | |||||||
| Yes | 0.623 | 1.182 | 0.606 | 2.306 | |||||
| Menarche age | ＜14 | 1(Ref.) | |||||||
| ≥14 | 0.164 | 0.583 | 0.272 | 1.247 | |||||
| Menopause | No | 1(Ref.) | |||||||
| Yes | 0.661 | 1.091 | 0.739 | 1.609 | |||||
| Alanine aminotransferase (ALT) | ＜17 | 1(Ref.) | |||||||
| ≥17 | 0.890 | 0.944 | 0.414 | 2.153 | |||||
| Aspartate aminotransferase (AST) | ＜20 | 1(Ref.) | |||||||
| ≥20 | 0.549 | 1.305 | 0.547 | 3.111 | |||||
| Lactic dehydrogenase (LDH) | ＜166 | 1(Ref.) | 1(Ref.) | ||||||
| ≥166 | 0.041 | 2.081 | 1.029 | 4.205 | 0.005 | 1.864 | 1.204 | 2.887 | |
| γ-glutamyl transpeptidase (γ-GT) | ＜17 | 1(Ref.) | |||||||
| ≥17 | 0.413 | 0.755 | 0.385 | 1.479 | |||||
| Direct bilirubin (DBIL) | ＜2.75 | 1(Ref.) | |||||||
| ≥2.75 | 0.379 | 0.684 | 0.293 | 1.595 | |||||
| Cholesterol (CHOL) | ＜3.80 | 1(Ref.) | |||||||
| ≥3.80 | 0.458 | 1.332 | 0.625 | 2.840 | |||||
| Triglyceride (TG) | ＜1.16 | 1(Ref.) | |||||||
| ≥1.16 | 0.203 | 0.664 | 0.354 | 1.247 | |||||
| Total protein (TP) | ＜73.0 | 1(Ref.) | |||||||
| ≥73.0 | 0.488 | 0.734 | 0.306 | 1.760 | |||||
| Albumin (ALB) | ＜44.1 | 1(Ref.) | |||||||
| ≥44.1 | 0.111 | 0.442 | 0.162 | 1.207 | |||||
| Globulin (G) | ＜29.0 | 1(Ref.) | |||||||
| ≥29.0 | 0.146 | 2.094 | 0.774 | 5.667 | |||||
| Albumin/Globulin (A/G) | ＜1.55 | 1(Ref.) | |||||||
| ≥1.55 | 0.052 | 2.671 | 0.992 | 7.190 | |||||
| Prealbumin (PAB) | ＜27.0 | 1(Ref.) | |||||||
| ≥27.0 | 0.364 | 1.412 | 0.670 | 2.977 | |||||
| Carbohydrate antigen 125 (CA125) | ＜10.57 | 1(Ref.) | |||||||
| ≥10.57 | 0.461 | 1.326 | 0.626 | 2.811 | |||||
| Carbohydrate antigen 153 (CA153) | ＜13.01 | 1(Ref.) | |||||||
| ≥13.01 | 0.311 | 1.423 | 0.719 | 2.819 | |||||
| Carcinoembryonic antigen (CEA) | ＜1.95 | 1(Ref.) | |||||||
| ≥1.95 | 0.583 | 1.112 | 0.762 | 1.623 | |||||
| D-Dimer (DD) | ＜0.21 | 1(Ref.) | |||||||
| ≥0.21 | 0.715 | 0.886 | 0.464 | 1.693 | |||||
| Fibrinogen (FIB) | ＜2.75 | 1(Ref.) | |||||||
| ≥2.75 | 0.461 | 0.784 | 0.410 | 1.498 | |||||
| White blood cell | ＜5.45 | 1(Ref.) | |||||||
| ≥5.45 | 0.376 | 1.187 | 0.812 | 1.733 | |||||
| Neutrophils | ＜3.23 | 1(Ref.) | |||||||
| ≥3.23 | 0.062 | 1.437 | 0.981 | 2.103 | |||||
| Lymphocyte | ＜1.70 | 1(Ref.) | |||||||
| ≥1.70 | 0.812 | 1.097 | 0.511 | 2.357 | |||||
| Monocyte | ＜0.35 | 1(Ref.) | |||||||
| ≥0.35 | 0.356 | 1.361 | 0.707 | 2.622 | |||||
| Platelet | ＜233 | 1(Ref.) | |||||||
| ≥233 | 0.137 | 0.607 | 0.314 | 1.173 | |||||
| Type of surgery | Mastectomy | 1(Ref.) | |||||||
| Breast-conserving surgery | 0.894 | 1.106 | 0.252 | 4.843 | |||||
| Pathological tumor size | ≤2 cm | 1(Ref.) | |||||||
| ＞2 and ≤5 cm | 0.230 | 0.490 | 0.153 | 1.571 | |||||
| ＞5 cm | 0.721 | 0.727 | 0.127 | 4.177 | |||||
| Histologic grade | I | 1(Ref.) | |||||||
| II | 0.236 | 2.184 | 0.599 | 7.959 | |||||
| III | 0.287 | 2.124 | 0.531 | 8.501 | |||||
| Pathological T stage | T1 stage | 1(Ref.) | |||||||
| T2 stage | 0.122 | 3.012 | 0.744 | 12.197 | |||||
| T3 stage | 0.431 | 2.158 | 0.318 | 14.662 | |||||
| T4 stage | 0.370 | 2.202 | 0.392 | 12.380 | |||||
| Pathological N stage | N0 stage | 1(Ref.) | |||||||
| N1 stage | 0.460 | 1.515 | 0.503 | 4.560 | |||||
| N2 stage | 0.121 | 8.408 | 0.570 | 123.912 | |||||
| N3 stage | 0.018 | 32.925 | 1.825 | 594.084 | |||||
| Pathological TNM stage | I | 1(Ref.) | |||||||
| II | 0.195 | 6.986 | 0.369 | 132.221 | |||||
| III | 0.225 | 4.340 | 0.406 | 46.437 | |||||
| Total lymph nodes (TLN) | ＜19 | 1(Ref.) | |||||||
| ≥19 | 0.148 | 1.508 | 0.864 | 2.629 | |||||
| Positive lymph nodes (PLN) | ＜5 | 1(Ref.) | |||||||
| ≥5 | 0.070 | 3.077 | 0.913 | 10.365 | |||||
| Molecular subtype | Luminal A | 1(Ref.) | |||||||
| Luminal B HER2+ | 0.007 | 0.017 | 0.001 | 0.325 | |||||
| Luminal B HER2- | 0.617 | 1.454 | 0.336 | 6.296 | |||||
| HER2 enriched | 0.001 | 0.006 | 0.000 | 0.119 | |||||
| Triple negative | 0.411 | 0.427 | 0.056 | 3.255 | |||||
| ER | Negative | 1(Ref.) | |||||||
| Positive | 0.368 | 0.636 | 0.237 | 1.704 | |||||
| PR | Negative | 1(Ref.) | |||||||
| Positive | 0.139 | 2.091 | 0.788 | 5.548 | |||||
| HER2 | Negative | 1(Ref.) | |||||||
| Positive | 0.079 | 1.431 | 0.959 | 2.135 | |||||
| Ki67 | Negative | 1(Ref.) | |||||||
| Positive | 0.171 | 1.792 | 0.777 | 4.131 | |||||
| AR | Negative | 1(Ref.) | |||||||
| Positive | 0.292 | 3.635 | 0.329 | 40.135 | |||||
| CK5/6 | Negative | 1(Ref.) | |||||||
| Positive | 0.340 | 1.676 | 0.580 | 4.846 | |||||
| E-cad | Negative | 1(Ref.) | |||||||
| Positive | 0.245 | 1.705 | 0.694 | 4.191 | |||||
| EGFR | Negative | 1(Ref.) | |||||||
| Positive | 0.604 | 0.690 | 0.170 | 2.807 | |||||
| P53 | Negative | 1(Ref.) | |||||||
| Positive | 0.757 | 1.117 | 0.555 | 2.246 | |||||
| TOP2A | Negative | 1(Ref.) | 1(Ref.) | ||||||
| Positive | 0.027 | 3.293 | 1.146 | 9.460 | 0.000 | 3.380 | 1.937 | 5.901 | |
| Lymph vessel invasion | Negative | 1(Ref.) | |||||||
| Positive | 0.092 | 1.738 | 0.913 | 3.308 | |||||
| Neural invasion | Negative | 1(Ref.) | |||||||
| Positive | 0.455 | 1.299 | 0.654 | 2.581 | |||||
| Postoperative chemotherapy | No | 1(Ref.) | |||||||
| Yes | 0.071 | 2.466 | 0.925 | 6.568 | |||||
| Postoperative radiotherapy | No | 1(Ref.) | |||||||
| Yes | 0.103 | 0.495 | 0.213 | 1.153 | |||||
| Postoperative endocrine therapy | No | 1(Ref.) | |||||||
| Yes | 0.193 | 1.928 | 0.717 | 5.187 | |||||
| Postoperative targeted therapy | No | 1(Ref.) | |||||||
| Yes | 0.509 | 1.341 | 0.561 | 3.209 |
Abbreviation: BMI, body mass index; ER, estrogen receptor; PR, progesterone receptor; HER2, Human Epidermal Growth Factor Receptor 2; AR, androgen receptor; CK5/6, Cytokeratin 5/6; E-cad, E-cadherin; EGFR, Epidermal Growth Factor Receptor; TOP2A, topoisomerase 2A.
Table 4.
Univariate and multivariate survival analysis of overall survival in breast cancer patients with liver metastasis after surgery.
| Characteristics |
Group |
Univariate |
95%CI |
Multivariate |
95%CI |
||||
|---|---|---|---|---|---|---|---|---|---|
| P | HR | Low | High | P | HR | Low | High | ||
| ALBI | Low | 1(Ref.) | 1(Ref.) | ||||||
| High | 0.027 | 2.644 | 1.116 | 6.266 | 0.000 | 3.015 | 1.950 | 4.662 | |
| Age | ＜49 | 1(Ref.) | 1(Ref.) | ||||||
| ≥49 | 0.006 | 2.934 | 1.361 | 6.326 | 0.378 | 1.212 | 0.790 | 1.859 | |
| Marital status | Married | 1(Ref.) | |||||||
| Unmarried | 0.946 | 1.097 | 0.077 | 15.713 | |||||
| BMI | ＜23.51 | 1(Ref.) | |||||||
| ≥23.51 | 0.286 | 1.415 | 0.748 | 2.678 | |||||
| Family history | No | 1(Ref.) | |||||||
| Yes | 0.589 | 0.840 | 0.445 | 1.583 | |||||
| Menarche age | ＜14 | 1(Ref.) | 1(Ref.) | ||||||
| ≥14 | 0.035 | 2.216 | 1.055 | 4.651 | 0.002 | 2.116 | 1.324 | 3.382 | |
| Menopause | No | 1(Ref.) | |||||||
| Yes | 0.102 | 0.453 | 0.175 | 1.172 | |||||
| Alanine aminotransferase (ALT) | ＜17 | 1(Ref.) | |||||||
| ≥17 | 0.666 | 0.840 | 0.381 | 1.851 | |||||
| Aspartate aminotransferase (AST) | ＜20 | 1(Ref.) | |||||||
| ≥20 | 0.959 | 0.979 | 0.436 | 2.198 | |||||
| Lactic dehydrogenase (LDH) | ＜166 | 1(Ref.) | 1(Ref.) | ||||||
| ≥166 | 0.029 | 2.209 | 1.086 | 4.493 | 0.005 | 1.851 | 1.203 | 2.847 | |
| γ-glutamyl transpeptidase (γ-GT) | ＜17 | 1(Ref.) | |||||||
| ≥17 | 0.505 | 1.253 | 0.646 | 2.430 | |||||
| Direct bilirubin (DBIL) | ＜2.75 | 1(Ref.) | |||||||
| ≥2.75 | 0.475 | 0.761 | 0.359 | 1.612 | |||||
| Cholesterol (CHOL) | ＜3.80 | 1(Ref.) | |||||||
| ≥3.80 | 0.377 | 1.420 | 0.652 | 3.093 | |||||
| Triglyceride (TG) | ＜1.16 | 1(Ref.) | |||||||
| ≥1.16 | 0.162 | 0.650 | 0.355 | 1.190 | |||||
| Total protein (TP) | ＜73.0 | 1(Ref.) | |||||||
| ≥73.0 | 0.869 | 0.929 | 0.389 | 2.220 | |||||
| Albumin (ALB) | ＜44.1 | 1(Ref.) | |||||||
| ≥44.1 | 0.139 | 0.502 | 0.201 | 1.250 | |||||
| Globulin(G) | ＜29.0 | 1(Ref.) | |||||||
| ≥29.0 | 0.629 | 0.809 | 0.342 | 1.913 | |||||
| Albumin/Globulin (A/G) | ＜1.55 | 1(Ref.) | |||||||
| ≥1.55 | 0.491 | 1.349 | 0.576 | 3.158 | |||||
| Prealbumin (PAB) | ＜27.0 | 1(Ref.) | |||||||
| ≥27.0 | 0.622 | 1.193 | 0.591 | 2.408 | |||||
| Carbohydrate antigen 125 (CA125) | ＜10.57 | 1(Ref.) | |||||||
| ≥10.57 | 0.616 | 0.833 | 0.408 | 1.701 | |||||
| Carbohydrate antigen 153 (CA153) | ＜13.01 | 1(Ref.) | |||||||
| ≥13.01 | 0.531 | 1.233 | 0.640 | 2.373 | |||||
| Carcinoembryonic antigen (CEA) | ＜1.95 | 1(Ref.) | |||||||
| ≥1.95 | 0.369 | 0.741 | 0.386 | 1.424 | |||||
| D-Dimer (DD) | ＜0.21 | 1(Ref.) | |||||||
| ≥0.21 | 0.544 | 0.815 | 0.422 | 1.577 | |||||
| Fibrinogen (FIB) | ＜2.75 | 1(Ref.) | |||||||
| ≥2.75 | 0.298 | 0.723 | 0.392 | 1.333 | |||||
| White blood cell | ＜5.45 | 1(Ref.) | |||||||
| ≥5.45 | 0.119 | 1.356 | 0.925 | 1.989 | |||||
| Neutrophils | ＜3.23 | 1(Ref.) | 1(Ref.) | ||||||
| ≥3.23 | 0.030 | 1.527 | 1.042 | 2.237 | 0.722 | 1.082 | 0.702 | 1.667 | |
| Lymphocyte | ＜1.70 | 1(Ref.) | 1(Ref.) | ||||||
| ≥1.70 | 0.007 | 1.700 | 1.155 | 2.501 | 0.485 | 1.164 | 0.761 | 1.780 | |
| Monocyte | ＜0.35 | 1(Ref.) | 1(Ref.) | ||||||
| ≥0.35 | 0.019 | 1.583 | 1.077 | 2.326 | 0.015 | 1.670 | 1.105 | 2.524 | |
| Platelet | ＜233 | 1(Ref.) | |||||||
| ≥233 | 0.556 | 0.822 | 0.428 | 1.578 | |||||
| Type of surgery | Mastectomy | 1(Ref.) | |||||||
| Breast-conserving surgery | 0.997 | 0.997 | 0.210 | 4.727 | |||||
| Pathological tumor size | ≤2 cm | 1(Ref.) | |||||||
| ＞2 and ≤5 cm | 0.248 | 0.510 | 0.163 | 1.599 | |||||
| ＞5 cm | 0.856 | 1.172 | 0.212 | 6.473 | |||||
| Histologic grade | I | 1(Ref.) | |||||||
| II | 0.209 | 2.291 | 0.628 | 8.359 | |||||
| III | 0.613 | 1.441 | 0.350 | 5.935 | |||||
| Pathological T stage | T1 stage | 1(Ref.) | |||||||
| T2 stage | 0.275 | 2.135 | 0.547 | 8.322 | |||||
| T3 stage | 0.559 | 1.842 | 0.238 | 14.261 | |||||
| T4 stage | 0.013 | 8.755 | 1.587 | 48.307 | |||||
| Pathological N stage | N0 stage | 1(Ref.) | |||||||
| N1 stage | 0.228 | 1.969 | 0.655 | 5.920 | |||||
| N2 stage | 0.136 | 7.056 | 0.542 | 91.903 | |||||
| N3 stage | 0.025 | 25.620 | 1.513 | 433.911 | |||||
| Pathological TNM stage | I | 1(Ref.) | |||||||
| II | 0.102 | 9.057 | 0.648 | 126.674 | |||||
| III | 0.110 | 5.844 | 0.669 | 51.054 | |||||
| Total lymph nodes (TLN) | ＜19 | 1(Ref.) | |||||||
| ≥19 | 0.433 | 0.859 | 0.588 | 1.255 | |||||
| Positive lymph nodes (PLN) | ＜5 | 1(Ref.) | |||||||
| ≥5 | 0.335 | 1.834 | 0.534 | 6.295 | |||||
| Molecular subtype | Luminal A | 1(Ref.) | |||||||
| Luminal B HER2+ | 0.241 | 0.190 | 0.012 | 3.059 | |||||
| Luminal B HER2- | 0.592 | 1.505 | 0.338 | 6.701 | |||||
| HER2 enriched | 0.125 | 0.090 | 0.004 | 1.947 | |||||
| Triple negative | 0.968 | 1.042 | 0.146 | 7.406 | |||||
| ER | Negative | 1(Ref.) | 1(Ref.) | ||||||
| Positive | 0.002 | 10.058 | 2.271 | 44.549 | 0.001 | 3.272 | 1.649 | 6.494 | |
| PR | Negative | 1(Ref.) | |||||||
| Positive | 0.216 | 1.898 | 0.688 | 5.239 | |||||
| HER2 | Negative | 1(Ref.) | |||||||
| Positive | 0.209 | 5.440 | 0.388 | 76.259 | |||||
| Ki67 | Negative | 1(Ref.) | |||||||
| Positive | 0.849 | 1.083 | 0.475 | 2.469 | |||||
| AR | Negative | 1(Ref.) | |||||||
| Positive | 0.936 | 0.902 | 0.073 | 11.119 | |||||
| CK5/6 | Negative | 1(Ref.) | |||||||
| Positive | 0.491 | 1.461 | 0.498 | 4.287 | |||||
| E-cad | Negative | 1(Ref.) | |||||||
| Positive | 0.284 | 1.616 | 0.672 | 3.886 | |||||
| EGFR | Negative | 1(Ref.) | |||||||
| Positive | 0.601 | 0.671 | 0.151 | 2.988 | |||||
| P53 | Negative | 1(Ref.) | |||||||
| Positive | 0.069 | 1.952 | 0.948 | 4.018 | |||||
| TOP2A | Negative | 1(Ref.) | 1(Ref.) | ||||||
| Positive | 0.046 | 3.021 | 1.021 | 8.934 | 0.002 | 2.443 | 1.393 | 4.282 | |
| Lymph vessel invasion | Negative | 1(Ref.) | |||||||
| Positive | 0.318 | 1.385 | 0.731 | 2.626 | |||||
| Neural invasion | Negative | 1(Ref.) | |||||||
| Positive | 0.052 | 3.208 | 0.990 | 10.398 | |||||
| Postoperative chemotherapy | No | 1(Ref.) | |||||||
| Yes | 0.741 | 0.923 | 0.572 | 1.487 | |||||
| Postoperative radiotherapy | No | 1(Ref.) | |||||||
| Yes | 0.060 | 0.463 | 0.207 | 1.032 | |||||
| Postoperative endocrine therapy | No | 1(Ref.) | |||||||
| Yes | 0.784 | 1.146 | 0.431 | 3.049 | |||||
| Postoperative targeted therapy | No | 1(Ref.) | |||||||
| Yes | 0.826 | 0.912 | 0.401 | 2.073 |
Abbreviation: BMI, body mass index; ER, estrogen receptor; PR, progesterone receptor; HER2, Human Epidermal Growth Factor Receptor 2; AR, androgen receptor; CK5/6, Cytokeratin 5/6; E-cad, E-cadherin; EGFR, Epidermal Growth Factor Receptor; TOP2A, topoisomerase 2A.
4.1. Clinical impact of the ALBI grade on survival
Firstly, we explored the effects of the ALBI score on survival. Through the optimal cut-off value of ALBI score, 129 cases were in low ALBI score group, and 49 cases were in high ALBI score group. According to the ALBI score, median DFS was 45.80 months in low ALBI score group, 29.17 months in high ALBI score group (Log rank: p = 0.0029); median OS was 103.80 months in low ALBI score group, 55.77 months in high ALBI score group (Log rank: p＜0.0001) (Fig. 1A and B). According to the DFS, 1-year survival rate was 0.889 (95%CI, 0.835–0.945), 3-year survival rate was 0.560 (95%CI, 0.475–0.660), 5-year survival rate was 0.416 (95%CI, 0.326–0.530), 10-year survival rate was 0.181 (95%CI, 0.093–0.355), 15-year survival rate was 0.136 (95%CI, 0.057–0.328) in low ALBI score group; and 1-year survival rate was 0.809 (95%CI, 0.703–0.930), 3-year survival rate was 0.458 (95%CI, 0.330–0.634), 5-year survival rate was 0.206 (95%CI, 0.109–0.387), 10-year survival rate was 0.059 (95%CI, 0.011–0.307) in high ALBI score group. According to the OS, 1-year survival rate was 0.992 (95%CI, 0.977–1.000), 3-year survival rate was 0.836 (95%CI, 0.774–0.903), 5-year survival rate was 0.693 (95%CI, 0.617–0.778), 10-year survival rate was 0.484 (95%CI, 0.395–0.593), 15-year survival rate was 0.234 (95%CI, 0.138–0.395) in low ALBI score group; and 1-year survival rate was 0.980 (95%CI, 0.941–1.000), 3-year survival rate was 0.790 (95%CI, 0.682–0.915), 5-year survival rate was 0.425 (95%CI, 0.301–0.599), 10-year survival rate was 0.103 (95%CI, 0.034–0.317) in high ALBI score group.
Fig. 1.
Kaplan-Meier survival plots comparing disease free survival (DFS) and overall survival (OS) in breast cancer patients with liver metastasis after surgery (A for DFS, B for OS).
4.2. Establishment and validation of nomogram
Nomograms were considered a simple tool for providing personalized risk assessment for every enrolled patient. According to the potential prognostic factors discriminated in the multivariate analysis, we established two nomograms to individually predict different survival time of breast cancer patients with liver metastasis after surgery (Fig. 2A and B). The C-index for nomogram-based model by DFS was 0.611 (95%CI, 0.552–0.670) (Fig. S1A). And the C-index for nomogram-based model by OS was 0.721 (95%CI, 0.670–0.772) (Fig. S1B). Moreover, the calibration curves of DFS at 1-year, 3-year, and 5-year after surgery performed that the best consistency between the actual and predicted observations (Fig. 3A–C). And the calibration curves of OS at 1-year, 3-year, 5-year, and 10-year after surgery indicated that the best agreement between the actual and predicted observations (Fig. 3D–G). In addition, the decision curve analysis of DFS at 3-year after surgery demonstrated that the constructed nomograms had better predictive value than ALBI score (Fig. 4A–D). And the decision curve analysis of OS at 3-year, 5-year, and 10-year after surgery demonstrated that the established nomograms had better predictive value than ALBI score (Fig. 4E–H). Furthermore, time-dependent receiver operating characteristic (TDROC) analysis performed that the plots of area under the receiver operating characteristic curves (AUROCs) for ALBI score in breast cancer patients with liver metastasis after surgery for survival time from 1 year to 15 years after the start of follow-up. TDROC analysis indicated that the AUROCs at 1-year, 3-year, 5-year, and 10-year of DFS after surgery of follow-up were 0.573, 0.539, 0.574, 0.561 for the ALBI score; and 1-year, 3-year, 5-year, 10-year, and 15-year of OS after surgery of follow-up were 0.614, 0.535, 0613, 0.658, 0.644 for the ALBI score. The ALBI score indicated that the AUROCs for survival time had the highest value at 5-year point (95%CI: 49.17%–65.67 %) for DFS (Fig. 5A and B), and at 10-year point (95%CI, 59.20%–72.38 %) for OS (Fig. 5C and D).
Fig. 2.
The established of ALBI-based nomograms in breast cancer patients with liver metastasis after surgery (A, nomogram of disease free survival; B, nomogram of overall survival).
Fig. 3.
The calibration curves for ALBI-nomogram model in predicting different survival time. A) 1-year DFS, B) 3-year DFS, C) 5-year DFS, D) 1-year OS, E) 3-year OS, F) 5-year OS, G) 10-year OS.
Fig. 4.
The decision curve analysis for the ALBI-nomogram and ALBI score model in evaluating the benefits for different survival time. A) 1-year DFS, B) 3-year DFS, C) 5-year DFS, D) 10-year DFS, E) 3-year OS, F) 5-year OS, G) 10-year OS, H) 15-year OS.
Fig. 5.
Time-dependent receiver operating characteristic (TDROC) analyzed the plots of area under the receiver operating characteristic curves (AUROCs) for ALBI score in breast cancer patients with liver metastasis after surgery of followup. A) Time-dependent AUROCs for DFS, B) 95%CI changes of AUROCs for DFS, C) Time-dependent AUROCs for OS, D) 95%CI changes of AUROCs for OS.
4.3. Subgroup analyses to evaluate the effects of the ALBI score on survival
Then, we conducted subgroup analyses to evaluate the impacts of ALBI score on survival according to the menopause. Kaplan-Meier curves revealed that the ALBI score was associated with DFS (Log rank: p = 0.031) and OS (Log rank: p = 0.00024) in menopause status (Figs. S2A–B). The postmenopausal patients with breast cancer with high ALBI score had poor prognosis and survival time. Moreover, we also analyzed the effects of ALBI grade on survival according to the histological grade. Kaplan-Meier curves shown that the ALBI score was significantly associated with DFS (Log rank: p = 0.0033) and OS (Log rank: p = 0.00072) in different histological grade (Figs. S3A–B). The higher histological grade breast cancer patients with high ALBI score had worse prognosis and shorter survival time. In addition, we also compared the impacts of ALBI score on survival by molecular subtype. Kaplan-Meier curves indicated that the ALBI score was dramatically associated with DFS (Log rank: p = 0.00052) and OS (Log rank: p＜0.0001) in molecular subtype of breast cancer (Figs. S4A–B).
5. Discussion
Breast cancer primarily metastasizes to bone, lung, liver and brain by way of circulation; wherein, the liver is the third most usual distant metastasis site of breast cancer [17]. It is worth noting that the incidence of liver metastasis is second only to lung and bone metastasis in an autopsy study, and liver metastasis accounts for 20 %–35 % of the deaths of metastatic breast cancer patients [18]. In addition, liver metastasis can lead to treatment resistance and higher mortality rates. The breast cancer patients with liver metastasis have poor prognosis and short median survival time [19]. Studies have proved that the median survival time of these patients without any therapy was about 4–8 months compared to 13–31 months after systemic therapy [[20], [21], [22]]. At present, it is hard to accurately predict the occurrence of liver metastasis from breast cancer. Although several prognostic scores had been reported to be related to prognosis in breast cancer patients, it was still unclear whether these markers reflect prognosis in both the short-term and long-term [23,24].
Johnson and his colleagues inaugurated the ALBI grade to estimate liver function [7]. After being proven to have prognostic benefits for liver cancer patients in 2015, there is increasing interest in the prognostic role of ALBI grade [7,25,26]. The ALBI is composed of albumin and bilirubin, and is measured by routine blood test. Albumin is synthesized in the liver and the decline in its level indicates malnutrition and liver synthesis dysfunction [27]. Additionally, an increase in serum bilirubin concentration usually determines varying degrees of liver dysfunction [28]. Hiraoka A and his colleagues designed a multicenter study including 6649 liver cancer patients treated from 2000 to 2017 and found that ALBI grade had prognostic predictive value and stratification ability [29]. Of late, in a single-center study by Koh HH and his colleagues analyzing 1015 patients with colorectal cancer, the ALBI grade was a significant prognostic factor, and the combination of ALBI and myosteatosis shown additional value in judging the survival rate of CRC patients [30]. Moreover, Takada K and his colleagues had analyzed 452 patients with advanced or recurrent NSCLC who received anti-PD-1 therapy and found that the ALBI grade was an independent prognostic factor for progression-free survival and overall survival [11].
In the current study, we reported that the ALBI score was a potential predictor of DFS and OS in breast cancer patients with liver metastasis after surgery. The median DFS and OS in low ALBI score group were longer than in high ALBI score group. A pooled analysis of two randomized trials indicated that higher ALBI grade was related to worse PFS and OS among patients with colorectal liver metastases treated with first-line systemic therapy [31]. Another study pointed out that a higher pretreatment ALBI grade was associated with worse PFS and OS in pancreatic cancer patients with liver metastasis treated with chemotherapy in the first-line setting, and it could help the treatment outcomes [32]. Our findings were consistent with previous reports, and our study also explored the clinical impact of ALBI grade in breast cancer patients with liver metastasis after surgery.
In the current queue, the ALBI score was significantly associated with menopause, histologic grade, positive lymph nodes, molecular subtype, albumin, cholesterol, and total protein (Table 1, Table 2), suggesting that the ALBI score was related to a bias from these clinical factors. With regards to menopause, the post-menopausal estrone activates EMT genes to stimulate breast cancer metastasis [33]. In this study, the results also indicated that the postmenopausal patients with high ALBI score had worse prognosis and shorter survival time. A previous study noted that the histological grade was positively associated with the proliferation and metastasis ability of tumor cells, and the higher the histological grade of breast cancer, the higher the risk of metastasis [34]. The results in our study also indicated that ALBI score was significantly related to histological grade of breast cancer, and the higher the histological grade of breast cancer with high ALBI score had poor prognosis and survival by Kaplan-Meier curves. Another study suggested that the probability of liver metastasis in HER2 positive subtype and triple negative subtype were significantly higher than that in HR+/HER2 subtypes [35]. Our present results also proved that triple-negative subtype and HER2 enriched subtype patients with high ALBI group had shorter survival time, in accordance with this published study. In addition, the albumin, cholesterol and total protein often used to assess liver function and nutritional status [36,37]. The patients with low albumin or high cholesterol level usually had poor prognosis, consistent with previously published researches [38,39].
We established effective ALBI-based nomograms for individualized assessment of breast cancer patients with liver metastasis after surgery. These nomograms had distinctive characteristics that integrate ALBI, LDH, monocyte, ER, and TOP2A. The results of calibration curves and decision curve analysis shown that ALBI-based nomograms were repeatedly and reliably predict the prognosis of breast cancer patients with liver metastasis after surgery, and these models might assist in individualized risk stratification and the development of individualized follow-up and treatment strategies. ROC analysis is typically used to appraise the discriminant power of continuous variables on binary disease outcomes. Nevertheless, it is hard to contrast the prognosis determined applying ordinary ROC analysis because outcomes are time dependent [40]. The time-dependent ROC curves have been innovated for evaluating the predictive power of diagnostic markers for time dependent disease outcomes. In this study, the prognosis of breast cancer patients with liver metastasis after surgery was also performed by the time-dependent ROC analysis. The results indicated that the AUROCs for survival time by ALBI score had the highest value at 5-year point for DFS and at 10-year point for OS.
It is worth noting that this research also has several limitations. First, this was a single-center retrospective study, the number of patients was relatively small, which may have some selection bias. Secondly, these established nomograms were using retrospective data, thus prospective cohort studies should be performed for further validation. Finally, the ALBI score's suitability to predict the prognosis of breast cancer patients with liver metastasis after surgery who receive other therapy needs further study.
6. Conclusion
In summary, tumor metastasis after radical surgery for breast cancer is a critical and natural complication. Our study indicates that the ALBI score has high prognostic ability for DFS and OS in breast cancer with liver metastasis after surgery. Our findings suggest that the advantage of ALBI score is that objectivity, easy to implement, without invasive procedures. We also construct nomograms, which is a energetic tool to predict subsequent liver metastasis in breast cancer patients after surgery. These models will help us in discriminating patients at high risks of liver metastasis, thereupon then we can design relevant trials for these patients. However, larger studies are needed to determine whether our results can be applied to other subgroups of breast patients.
Funding
This research was supported by grants from the National Nature Science Foundation of China (No.82173328), Hubei Province Postdoctoral Innovation Research Post Fund Project (No.0106540096), Open Fund for the Key Laboratory of Organ Transplantation of Ministry of Education and National Health Commission (No.2021QYKF03), Tongji Hospital Cultivation Project (No.2022B03), Chen Xiao-ping Foundation for the Development of Science and Technology of Hubei province, Youth Science Special Fund (No.CXPJJH123001-2308).
This retrospective single center study was conducted in accordance with the amended Declaration of Helsinki, and was approved by the ethics committee of Cancer Hospital Chinese Academy of Medical Sciences (Approved no.82173328).
Informed consent statement
The enrolled patients provided written informed consent for using their data in this retrospective study.
Data availability statement
The material supporting the conclusion of this article has been included within the article.
CRediT authorship contribution statement
Li Chen: Writing – review & editing, Writing – original draft, Resources, Funding acquisition, Formal analysis. Chunlei Tan: Writing – review & editing, Investigation, Data curation. Qingwen Li: Writing – review & editing, Data curation. Zhibo Ma: Data curation. Meng Wu: Investigation. Xiaosheng Tan: Supervision, Methodology. Tiangen Wu: Formal analysis. Jinwen Liu: Conceptualization. Jing Wang: Resources, Project administration, Funding acquisition, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
No.
Footnotes
Institutional Review Board Statement.
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2023.e21772.
Contributor Information
Xiaosheng Tan, Email: txs900416@163.com.
Tiangen Wu, Email: wtg666@whu.edu.cn.
Jinwen Liu, Email: Liujinwen@tjh.tjmu.edu.cn.
Jing Wang, Email: wangjing@cicams.ac.cn.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
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