Abstract
Objective:
Previous studies focused on the prognostic significance of the pre- or post-operative neutrophil–lymphocyte ratio (NLR); the significance of combined pre- and post-operative NLR (PP-NLR) remains unknown. Therefore, we investigated the value of PP-NLR for predicting prognosis after radiofrequency ablation (RFA) in patients with hepatocellular carcinoma (HCC) to improve treatment and prolong survival.
Methods:
We investigated pre- and post-operative NLR and PP-NLR in predicting prognosis after RFA in patients with HCC. Optimal thresholds for leukocytes, lymphocytes, neutrophils, and NLR before and after RFA were retrospectively assessed in patients with HCC who had undergone RFA between January 2018 and June 2019 in Harbin Medical University Cancer Hospital. Risk factors for early HCC recurrence and those affecting recurrence-free survival (RFS) were analyzed.
Results:
The respective pre- and post-operative optimal thresholds were as follows: neutrophils, 3.431 and 4.975; leukocytes, 5.575 and 6.61; lymphocytes, 1.455 and 1.025; and NLR, 1.53 and 4.36. Univariate analysis revealed tumor number; alpha-fetoprotein level; post-operative leukocytes, lymphocytes, NLR, and neutrophils; pre-operative neutrophils and NLR; and PP-NLR as factors influencing early recurrence and RFS. Multivariate analysis indicated PP-NLR as an independent risk factor for poor RFS and early recurrence.
Conclusion:
PP-NLR was more effective for predicting prognosis than pre- or post-operative NLR alone for patients with HCC.
Advances in knowledge:
The novelty of this study lies in the combination of pre- and post-operative NLR, namely PP-NLR, to study its prognostic value for HCC patients after RFA, which has not been found in previous studies. The contribution of our study is that PP-NLR can provide clinicians with a new reference index to judge the prognosis of patients and make timely treatment to help patients improve their prognosis.
Introduction
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third leading cause of cancer-related death. 1 HCC accounted for more than three-quarters of liver cancer cases in 2018. Treatments for HCC include surgery, minimally invasive procedures, and liver transplantation. 2 Radiofrequency ablation (RFA) is recommended for early HCC. 3 Although treatments for HCC continue to improve, the 5-year recurrence rate remains high at 43%. 4 HCC is divided into early and late recurrence stages, often negatively affecting patient survival time and prognosis.
Tumor diameter and number, vascular invasion are reportedly associated with the early recurrence of HCC, 5,6 but these require imaging and are subjective. Levels of alpha-fetoprotein (AFP), a clinical tumor biomarker, are associated with early recurrence; however, only 50% of patients with HCC secrete AFP, 7 and bile duct stones, pregnancy, and other factors can also lead to elevated AFP. 8 Therefore, accurately judging prognosis and recurrence using AFP is clinically challenging. Serum indicators such as AFP-L3, Golgi glycoprotein 73, and osteopontin also have certain predictive significance for HCC prognosis. 9,10 However, using these indicators for prediction, the accuracy cannot meet the clinical needs. Therefore, a laboratory test index with strong specificity, high sensitivity, and easy detection is urgently needed to improve HCC diagnosis and prognosis.
Many inflammation-related components (including macrophages, lymphocytes, inflammatory cytokines, and interleukin-6 [IL-6]) are involved in promoting tumor growth and spread. 11 Inflammatory marker levels are independent risk factors for tumor survival. 12 Among them, the neutrophil–lymphocyte ratio (NLR) is commonly used and provides easy detection and good reproducibility. 13 High pre-operative NLR is seen in various malignant tumors with poor prognosis. 14 Higher post-operative NLR adversely affects recurrence-free survival (RFS) and overall survival in patients with upper urothelial carcinoma and is an independent risk factor. Previous studies focused only on the prognostic significance of pre- or post-operative NLR 14–16 ; few studies have investigated the clinical significance of combined pre- and post-operative NLR (PP-NLR). Therefore, we investigated the value of pre-operative NLR, post-operative NLR, and PP-NLR for predicting prognosis after RFA in patients with HCC to improve treatment and prolong survival.
Methods and materials
Patients
This study was reviewed and approved by the Ethics Committee of Harbin Medical University Cancer Hospital (approval number: KY2022-628) and was in accordance with the Declaration of Helsinki. All patients signed informed consent.
The participants of this cohort study were 199 patients with HCC who underwent RFA in department of ultrasound of Harbin Medical University Cancer Hospital from January 2018 to June 2019. The HCC diagnostic criteria referred to the guidelines of the American Association for the Study of Liver Diseases. The imaging diagnosis criteria were rapid enhancement and clearance of arterial and/or delayed blood flow signals on contrast-enhanced MRI (CE-MRI), CEUS, and contrast-enhanced CT (CE-CT). Lesion tissue for pathological diagnosis was obtained by ultrasound-guided needle biopsy. Study inclusion criteria were: (1) complete patient clinical data; (2) no serious heart or lung disease; (3) no metastasis outside the liver; (4) platelet count ≥6×109 l−1 and prothrombin activity ≥50%; and (5) lesions met criteria for pathological or imaging diagnosis. The exclusion criteria were: (1) prior treatment for HCC, or RFA was not the first treatment modality; (2) patient lost to follow-up or death after RFA; (3) lesions did not meet imaging or pathology diagnostic criteria; (4) concomitant malignancy or previous malignancies; (5) autoimmune disease or treatment affecting immune function; and (6) contraindications for CEUS/CECT/CEMRI. A total of 108 patients with HCC were analyzed (Figure 1).
Figure 1.
Flow chart for screening patients. HCC, hepatocellular carcinoma; RFA, radiofrequency ablation
Patient data
Patient data included age, drinking history, sex, liver cirrhosis history, maximum diameter of lesions, body mass index, number of lesions, AFP level, aspartate transaminase, alanine transaminase, total bilirubin, albumin, Child-Pugh grade, and absolute values of leukocytes, lymphocytes, and neutrophils before and after RFA. Blood samples for detecting AFP levels and cell counts before and after RFA were collected at most 3 days before and 3 days after RFA, respectively. NLR was calculated using the absolute value of neutrophils and lymphocytes. Except for blood parameters, all data were collected 1 week before RFA.
Ultrasound-guided RFA
First, the patient lay flat on the operating table, and electrode patches were attached to the upper and lower sides of the base of the thighs on both sides. Subsequently, midazolam (0.075 mg/kg) and fentanyl (0.1 mg/kg) were administered as general anesthesia, and blood pressure, blood oxygen, and heart rate were monitored. According to the pre-operative ultrasound, MRI, and other examinations, the location of the lesion was comprehensively considered, and the needle insertion position was determined. Ultrasound-guided needle biopsies were performed on patients who consented to needle biopsy before the initiation of RFA, followed by the insertion of an RFA needle into the center of the lesion and heating. The number of RFA needles used for treatment and the number of heating times were determined according to the size and location of the lesion; each heating period was 12 min. Sometimes, two or more RFA needles were used simultaneously for larger lesions. The area of RFA should be >0.5 cm from the tumor margin. To ensure safety in difficult cases, artificial ascites was required before RFA. After ablation, to avoid hemorrhage, tumor implantation, or metastasis, the needle and needle track were heated during needle extraction. After RFA, CEUS (convex array C51 probe, mechanical index = 0.06, transducer frequency = 1–5 MHz; EPIQ7 ultrasonic machine; Philips, Amsterdam, Netherlands) was performed to detect residual disease with a second-generation ultrasound contrast agent (SonoVue hexafluoride microbubbles; 5 mg ml−1; SonoVue, Bracco, Italy). When abnormally enhanced blood flow signal was seen in the target area in the arterial phase, additional ablation was required.
Patient follow-up
Patients underwent CEUS, CE-CT, and CE-MRI 30 days after RFA to determine the effects of treatment and whether complete ablation was achieved. The standard for complete ablation was no abnormal blood flow signal in the ablation area of the original lesion. Checks were performed every 3 months for the first year after RFA and every 6 months for the second year until tumor recurrence. The items of each regular examination included CEUS, CE-MRI, liver and kidney function, routine blood tests, and tumor markers (carbohydrate antigen 19–9, AFP, carcinoembryonic antigen). Local HCC intrahepatic recurrence was defined as viable tumor within or near the ablation target detected within the first month after the end of RFA. Distant HCC intrahepatic recurrence was defined as a surviving tumor within the liver outside the RFA area during post-operative follow-up on any post-operative imaging modality. Herein, HCC recurrence within 24 months after RFA was defined as early recurrence.
There are many treatments for HCC recurrence, such as systemic chemotherapy, transarterial chemoembolization, re-RFA, and surgical resection, depending on the location, size, and number of lesions and the general physical condition of the patient. The follow-up period refers to the end of RFA to December 31, 2021, or the discovery of recurrence. The main measurement result was RFS, defined as the time from RFA to the detection of recurrence.
Statistical analyses
SPSS (v. 21.0; IBM Corp., Armonk, NY) software was used for data processing and statistical analysis. Normally distributed quantitative variables are expressed as the mean ± standard deviation, and an independent-sample t-test was used for comparison between two groups; one-way analysis of variance was used for comparison of more than two groups. Non-normally distributed quantitative variables are represented by median (interquartile range); for comparisons between two groups, the Mann–Whitney U test was used, and for comparisons of more than two groups, the Kruskal–Wallis test was used. Qualitative variables were tested using the χ2 test.
The optimal threshold values of leukocytes, lymphocytes, neutrophils, and NLR before and after RFA were analyzed using receiver operating characteristic (ROC) curves and grouped by cut-off values. An NLR below the critical value was scored as 0 points; one point for NLR above the critical value. PP-NLR was the combination of NLR before and after RFA; there were three possible values: PP-NLR = 0, PP-NLR = 1, and PP-NLR = 2. A univariate Cox regression analysis was performed on the collected clinical data, and statistically significant factors were further analyzed using a multivariate Cox proportional hazards model (p < 0.05). Kaplan–Meier survival curves were drawn, and the log-rank test was used to examine differences between comparison groups. p < 0.05 was considered statistically significant.
Results
Thresholds and grouping
ROC curves were established by extracting the data of neutrophils, lymphocytes, leukocytes, and NLR before and after RFA treatment and were used to find the critical values of these indicators. The optimal cut-off was defined as that with maximum sensitivity and specificity. The results are shown in Table 1 and Figures 2–5 (AB).
Table 1.
Critical value
| Factor | AUC | Standard error | p-value | 95% CI | Critical value | Sensitivity | Specificity |
|---|---|---|---|---|---|---|---|
| Pre-operative NLR | 0.682 | 0.053 | 0.001 | 0.578–0.785 | 1.53 | 0.765 | 0.614 |
| Post-operative NLR | 0.787 | 0.046 | 0.000 | 0.697–0.876 | 4.36 | 0.765 | 0.772 |
| Pre-operative leukocytes | 0.502 | 0.057 | 0.966 | 0.392–0.613 | 5.575 | 0.392 | 0.719 |
| Post-operative leukocytes | 0.655 | 0.053 | 0.006 | 0.552–0.758 | 6.61 | 0.667 | 0.614 |
| Pre-operative lymphocytes | 0.507 | 0.056 | 0.895 | 0.398–0.617 | 1.455 | 0.608 | 0.439 |
| Post-operative lymphocytes | 0.678 | 0.054 | 0.001 | 0.573–0.783 | 1.025 | 0.647 | 0.737 |
| Pre-operative neutrophils | 0.657 | 0.053 | 0.005 | 0.554–0.761 | 3.431 | 0.471 | 0.842 |
| Post-operative neutrophils | 0.764 | 0.046 | 0.000 | 0.675–0.854 | 4.975 | 0.686 | 0.789 |
AUC, area under curve; CI, confidence interval; NLR, neutrophil to lymphocyte ratio.
Figure 2.
(A) ROC curves for pre-operative neutrophils critical value. (B) ROC curves for post-operative neutrophils critical value. ROC, receiver operating characteristic.
Figure 3.
(A) ROC curves for pre-operative lymphocytes critical value. (B) ROC curves for post-operative lymphocytes critical value. ROC, receiver operating characteristic.
Figure 4.
(A) ROC curves for pre-operative leukocytes critical value. (B) ROC curves for post-operative leukocytes critical value. ROC, receiver operating characteristic.
Figure 5.
(A) ROC curves for pre-operative NLR critical value. (B) ROC curves for post-operative NLR critical value. NLR, neutrophil to lymphocyte ratio; ROC, receiver operating characteristic.
Clinical characteristics of patients
Table 2 lists the clinical data of all patients. 48 patients had HCC recurrence within 24 months after RFA.
Table 2.
Basic characteristics of clinical data of patients
| Factor | Group | All patients |
|---|---|---|
| Age, years(x ± s） | 56.73 ± 9.192 | |
| BMI, kg/m2(median(Interquartile range)） | 24.5150 (4.77) | |
| Gender (n, %） | Male | 79 (73.1%） |
| Female | 29 (26.9%） | |
| Number of lesions (n, %） | Multiple | 23 (21.3%） |
| Single | 85 (78.7%） | |
| Maximum diameter of lesions, mm (n, %） | ≥20 | 89 (82.4%） |
| ＜20 | 19 (17.6%） | |
| Liver cirrhosis history (n, %） | Yes | 96 (88.9%） |
| No | 12 (11.1%） | |
| Drinking history (n, %） | Yes | 21 (19.4%） |
| No | 87 (80.6%） | |
| AFP, ng/ml(n, %） | ≥400 | 17 (15.7%） |
| ＜400 | 91 (84.3%） | |
| Child-pugh grades | A | 100 (92.6%） |
| B | 8 (7.4%） | |
| ALT, U/L (n, %） | ≥40 | 32 (29.65%） |
| ＜40 | 76 (70.4%） | |
| AST, U/L (n, %） | ≥40 | 27 (25.0%） |
| ＜40 | 81 (75.0%） | |
| TBIL, μmol/L (n, %） | ≥34 | 3 (2.8%） |
| ＜34 | 105 (97.2%） | |
| ALB, G/L (n, %） | ≥35 | 87 (80.6%） |
| ＜35 | 21 (19.4%） | |
| Pre-operative leukocytes, x109/L (n, %） | ≥5.575 | 36 (33.3%） |
| ＜5.575 | 72 (66.7%） | |
| Post-operative leukocytes, x109/L (n, %） | ≥6.61 | 56 (51.9%） |
| ＜6.61 | 52 (48.1%） | |
| Pre-operative lymphocytes, x109/L (n, %） | ≥1.455 | 63 (58.3%） |
| ＜1.455 | 45 (41.7%） | |
| Postoperative lymphocytes,x109/L (n, %） | ≥1.025 | 60 (55.6%） |
| ＜1.025 | 48 (44.4%） | |
| Pre-operative neutrophils, x109/L (n, %） | ≥3.431 | 33 (30.6%） |
| ＜3.431 | 75 (69.4%） | |
| Post-operative neutrophils cells, x109/L (n, %） | ≥4.975 | 47 (43.5%） |
| ＜4.975 | 61 (56.5%） |
AFP, alpha-fetoprotein; ALB, albumin; ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; NLR, neutrophil to lymphocyte ratio; TBIL, total bilirubin.
Notes：The data are presented as a median(Interquartile range) or mean ± standard deviation. All other data are represented by n (%).
The PP-NLR groups of 0, 1, and 2 contained 36, 31, and 41 patients, respectively (Table 3). In the comparison between the three groups, alanine transaminase (p = 0.036), pre-operative neutrophils (p = 0.000), post-operative leukocytes (p = 0.023), post-operative neutrophils (p = 0.000), and post-operative lymphocytes (p = 0.000) were significantly different. Pre-operative neutrophils, post-operative leukocytes, and post-operative neutrophils of patients in the PP-NLR = 2 group were higher than those of the PP-NLR = 0 group, and post-operative lymphocytes in PP-NLR = 2 group were lower than those of the PP-NLR = 0 group.
Table 3.
Comparison between PP-NLR groups
| Factor | Group | PP-NLR(0） (n = 36） |
PP-NLR(1） (n = 31） |
PP-NLR(2） (n = 41） |
p value |
|---|---|---|---|---|---|
| Age, years (x ± s） | 56.73 ± 9.192 | 55.25 ± 10.402 | 57.23 ± 8.338 | 57.66 ± 8.728 | 0.491 |
| BMI, kg/m2 (median(Interquartile range)） | 24.5150 (4.77) | 25.4450 (4.13) | 23.9200 (5.08) | 24.3500 (4.70) | 0.258 |
| Gender | Male | 26 | 20 | 33 | 0.314 |
| Female | 10 | 11 | 8 | ||
| Number of lesions | Multiple | 4 | 7 | 12 | 0.149 |
| Single | 32 | 24 | 29 | ||
| Maximum diameter of lesions, mm | ≥20 | 32 | 23 | 34 | 0.287 |
| ＜20 | 4 | 8 | 7 | ||
| Liver cirrhosis history | yes | 30 | 29 | 37 | 0.390 |
| no | 6 | 2 | 4 | ||
| Drinking history | Yes | 4 | 6 | 11 | 0.221 |
| No | 32 | 25 | 30 | ||
| AFP, ng/ml | ≥400 | 5 | 5 | 7 | 0.927 |
| ＜400 | 31 | 26 | 34 | ||
| Child-pugh grades | A | 32 | 30 | 38 | 0.470 |
| B | 4 | 1 | 3 | ||
| ALT, U/L | ≥40 | 16 | 5 | 11 | 0.036 |
| ＜40 | 20 | 26 | 30 | ||
| AST, U/L | ≥40 | 13 | 4 | 10 | 0.091 |
| ＜40 | 23 | 27 | 31 | ||
| TBIL, μmol/L | ≥34 | 0 | 0 | 3 | 0.109 |
| ＜34 | 36 | 31 | 38 | ||
| ALB, G/L | ≥35 | 26 | 25 | 36 | 0.226 |
| ＜35 | 10 | 6 | 5 | ||
| Pre-operative leukocytes, x109/L (median(Interquartile range)） | 4.8250 (2.24) | 4.3700 (1.86) | 4.8800 (1.62) | 5.3000 (2.79) | 0.251 |
| Post-operative leukocytes, x109/L (median(Interquartile range)） | 6.7150 (2.73) | 6.4050 (2.12) | 5.8900 (2.93) | 7.3100 (3.27) | 0.023 |
| Pre-operative lymphocyte, x109/L s (median(Interquartile range)） | 1.5450 (0.89) | 1.7850 (0.69) | 1.4800 (0.95) | 1.4200 (0.96) | 0.079 |
| Post-operative lymphocytes, x109/L (median(Interquartile range)） | 1.0900 (0.63) | 1.3850 (0.61) | 1.1400 (0.77) | 0.8300 (0.32) | 0.000 |
| Pre-operative neutrophils, x109/L (median(Interquartile range)） | 2.5420 (2.02) | 1.9541 (0.97) | 2.6432 (1.96) | 3.7346 (2.52) | 0.000 |
| Post-operative neutrophils, x109/L (median(Interquartile range)） | 4.7400 (2.20) | 3.8300 (1.72) | 4.5700 (2.08) | 5.5200 (2.88) | 0.000 |
AFP, alpha-fetoprotein; ALB, albumin; ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; NLR, neutrophil to lymphocyte ratio; TBIL, total bilirubin.
Notes：The data are presented as a median(Interquartile range) or mean ± standard deviation. All other data are represented by n. One-way ANOVA and Kruskal–Wallis test were used to calculate p-value between three groups.
The pre-operative NLR was significantly different between the high (≥1.53) and low (<1.53) groups of alanine transaminase (p = 0.041), albumin (p = 0.048), pre-operative lymphocytes (p = 0.018), pre-operative neutrophils (p = 0.000), post-operative lymphocytes (p = 0.000), and post-operative neutrophils (p = 0.029). Moreover, the post-operative NLR was significantly different between the high (≥4.36) and low (<4.36) groups of pre-operative neutrophils (p = 0.005), tumor number (p = 0.005), post-operative leukocytes (p = 0.035), post-operative lymphocytes (p = 0.000), and post-operative neutrophils (p = 0.000) (Table 4).
Table 4.
Comparison between groups of pre- and post-operative NLR by various factors
| Factor | Group | Number | Pre-operative NLR | p- value | Post-operative NLR | p-value |
|---|---|---|---|---|---|---|
| Age, years | ≥65 | 22 | 1.7600 (1.37) | 0.251 | 4.3600 (7.00) | 0.647 |
| ＜65 | 86 | 1.6400 (1.25) | 4.1750 (3.32) | |||
| BMI, kg/m2 | ≥28 | 16 | 1.6350 (0.72) | 0.613 | 3.5200 (4.92) | 0.574 |
| ＜28 | 92 | 1.6500 (1.47) | 4.4150 (3.55) | |||
| Gender | Male | 79 | 1.6600 (1.47) | 0.462 | 4.4200 (3.96) | 0.577 |
| Female | 29 | 1.6200 (1.00) | 4.1400 (3.30) | |||
| Number of lesions | Multiple | 23 | 1.8000 (1.45) | 0.437 | 6.3100 (7.52) | 0.005 |
| Single | 85 | 1.6300 (1.36) | 3.9400 (2.71) | |||
| Maximum diameter of lesions, mm | ≥20 | 89 | 1.6200 (1.48) | 0.356 | 4.3100 (4.01) | 0.257 |
| ＜20 | 19 | 1.9200 (0.89) | 3.7500 (2.37) | |||
| Liver cirrhosis history | Yes | 96 | 1.6600 (1.39) | 0.622 | 4.3050 (3.62) | 0.996 |
| No | 12 | 1.3800 (1.73) | 3.8200 (6.04) | |||
| Drinking history | Yes | 21 | 1.7800 (2.03) | 0.364 | 4.9900 (8.45) | 0.060 |
| No | 87 | 1.6300 (1.28) | 4.1200 (3.20) | |||
| AFP, ng/ml | ≥400 | 17 | 1.9300 (1.69) | 0.604 | 4.9700 (6.56) | 0.610 |
| ＜400 | 91 | 1.6400 (1.44) | 4.2500 (3.32) | |||
| Child-pugh grades | A | 100 | 1.6650 (1.39) | 0.643 | 4.3050 (3.92) | 0.222 |
| B | 8 | 1.4850 (1.68) | 3.6450 (3.12) | |||
| ALT, U/L | ≥40 | 32 | 1.3300 (0.91) | 0.041 | 3.9450 (3.64) | 0.933 |
| ＜40 | 76 | 1.6750 (1.34) | 4.4250 (3.80) | |||
| AST, U/L | ≥40 | 27 | 1.3900 (1.07) | 0.253 | 3.5600 (4.63) | 0.305 |
| ＜40 | 81 | 1.6600 (1.48) | 4.4400 (3.35) | |||
| TBIL, μmol/L | ≥34 | 3 | 2.6300 (0.00) | 0.057 | 5.4700 (0.00) | 0.208 |
| ＜34 | 105 | 1.6400 (1.25) | 4.2100 (3.76) | |||
| ALB, G/L | ≥35 | 87 | 1.7500 (1.42) | 0.048 | 4.4400 (3.65) | 0.104 |
| ＜35 | 21 | 1.3700 (1.03) | 3.4200 (3.32) | |||
| Pre-operative leukocytes, x109/L | ≥5.575 | 36 | 1.8300 (1.26) | 0.097 | 4.7850 (6.87) | 0.093 |
| ＜5.575 | 72 | 1.5250 (1.03) | 3.9150 (3.13) | |||
| Post-operative leukocytes, x109/L | ≥6.61 | 56 | 1.7150 (1.37) | 0.259 | 4.5850 (4.96) | 0.035 |
| ＜6.61 | 52 | 1.5150 (1.21) | 3.7300 (2.51) | |||
| Pre-operative lymphocytes, x109/L | ≥1.455 | 63 | 1.4400 (1.12) | 0.018 | 3.7100 (4.28) | 0.313 |
| ＜1.455 | 45 | 1.8500 (1.44) | 4.7000 (2.76) | |||
| Post-operative lymphocytes, x109/L | ≥1.025 | 60 | 1.3400 (0.96) | 0.000 | 3.1050 (1.62) | 0.000 |
| ＜1.025 | 48 | 1.9800 (1.45) | 6.9550 (5.31) | |||
| Pre-operative neutrophils, x109/L | ≥3.431 | 33 | 2.6300 (1.63) | 0.000 | 5.5200 (7.12) | 0.005 |
| ＜3.431 | 75 | 1.3700 (0.79) | 3.8700 (2.50) | |||
| Post-operative neutrophils cells, x109/L | ≥4.975 | 47 | 1.8000 (1.25) | 0.029 | 6.3100 (6.00) | 0.000 |
| ＜4.975 | 61 | 1.4000 (1.14) | 3.4800 (2.41) |
AFP, alpha-fetoprotein; ALB, albumin; ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; NLR, neutrophil to lymphocyte ratio; TBIL, total bilirubin.
Notes：Pre- and post-operative NLR are expressed as median(Interquartile range). All other data are represented by n. Mann–Whitney U test was used to calculate p-value between two groups.
Univariate analysis
Univariate analysis was performed on all indicators using a Cox proportional hazards model, and tumor number (hazard ratio [HR]=0.320; 95% confidence interval [CI]: 0.180–0.569; p = 0.000), AFP level (HR = 0.523; 95% CI: 0.274–1.000; p = 0.043), post-operative leukocytes (HR = 0.438; 95% CI: 0.244–0.787; p = 0.004), post-operative lymphocytes (HR = 3.138; 95% CI: 1.758–5.602; p = 0.000), pre-operative neutrophils (HR = 0.366; 95% CI: 0.210–0.637; p = 0.000), post-operative neutrophils (HR = 0.250; 95% CI: 0.137–0.457; p = 0.000), post-operative NLR (HR = 0.289; 95% CI: 0.151–0.555; p = 0.000), post-operative NLR (HR = 0.183; 95% CI: 0.095–0.352; p = 0.000), and PP-NLR (HR = 3.091; 95% CI: 2.045–4.672; p = 0.000) were factors influencing the early recurrence of HCC and RFS (Table 5). Patients with multiple tumors, high AFP levels (≥400), high post-operative leukocytes (≥6.61), low post-operative lymphocytes (<1.025), high pre-operative neutrophils (≥3.431), high post-operative neutrophils (≥4.975), high pre-operative NLR (≥1.53), high post-operative NLR (≥4.36), and PP-NLR = 2 had a shorter median RFS (Table 6).
Table 5.
COX univariate analysis
| Factor | Group | Recurrence rate (%) | p-value | HR (95% CI) |
|---|---|---|---|---|
| Age, years | ≥65 | 50.0 | 0.424 | 0.765 (0.392–1.492） |
| ＜65 | 46.5 | |||
| BMI, kg/m2 | ≥28 | 56.3 | 0.550 | 0.806 (0.392–1.656） |
| ＜28 | 45.7 | |||
| Gender | Male | 51.9 | 0.158 | 0.615 (0.308–1.227） |
| Female | 34.5 | |||
| Number of lesions | Multiple | 82.6 | 0.000 | 0.320 (0.180–0.569） |
| Single | 37.6 | |||
| Maximum diameter of lesions, mm | ≥20 | 46.1 | 0.561 | 1.224 (0.613–2.444） |
| ＜20 | 52.6 | |||
| Liver cirrhosis history | Yes | 49.0 | 0.299 | 0.590 (0.212–1.638） |
| No | 33.3 | |||
| Drinking history | Yes | 61.9 | 0.106 | 0.602 (0.321–1.131） |
| No | 43.7 | |||
| AFP, ng/ml | ≥400 | 70.6 | 0.043 | 0.523 (0.274–1.000） |
| ＜400 | 42.9 | |||
| Child-pugh grades | A | 48.0 | 0.534 | 0.696 (0.217–2.235） |
| B | 37.5 | |||
| ALT, U/L | ≥40 | 46.9 | 0.972 | 0.989 (0.542–1.807） |
| ＜40 | 47.4 | |||
| AST, U/L | ≥40 | 44.4 | 0.976 | 1.010 (0.529–1.930） |
| ＜40 | 48.1 | |||
| TBIL, μmol/L | ≥34 | 66.7 | 0.383 | 0.542 (0.132–2.234） |
| ＜34 | 46.7 | |||
| ALB, G/L | ≥35 | 48.3 | 0.485 | 0.777 (0.378–1.597） |
| ＜35 | 42.9 | |||
| Pre-operative leukocytes, x109/L | ≥5.575 | 55.6 | 0.205 | 0.699 (0.398–1.228） |
| ＜5.575 | 43.1 | |||
| Post-operative leukocytes, x109/L | ≥6.61 | 60.7 | 0.004 | 0.438 (0.244–0.787） |
| ＜6.61 | 32.7 | |||
| Pre-operative lymphocytes, x109/L | ≥1.455 | 49.2 | 0.669 | 0.886 (0.505–1.555） |
| ＜1.455 | 44.4 | |||
| Post-operative lymphocytes, x109/L | ≥1.025 | 30.0 | 0.000 | 3.138 (1.758–5.602） |
| ＜1.025 | 68.8 | |||
| Pre-operative neutrophils, x109/L | ≥3.431 | 72.7 | 0.000 | 0.366 (0.210–0.637） |
| ＜3.431 | 36.0 | |||
| Post-operative neutrophils cells, x109/L | ≥4.975 | 74.5 | 0.000 | 0.250 (0.137–0.457） |
| ＜4.975 | 26.2 | |||
| Pre-operative NLR | ≥1.53 | 63.9 | 0.000 | 0.289 (0.151–0.555） |
| ＜1.53 | 25.5 | |||
| Post-operative NLR | ≥4.36 | 75.0 | 0.000 | 0.183 (0.095–0.352） |
| ＜4.36 | 21.4 | |||
| PP-NLR | 0 | 19.4 | 0.000 | 3.091 (2.045–4.672） |
| 1 | 32.3 | |||
| 2 | 82.9 |
AFP, alpha-fetoprotein; ALB, albumin; ALT, alanine transaminase; AST, aspartate transaminase; BMI, body mass index; CI, confidence interval; HR, hazard ratio; NLR, neutrophil to lymphocyte ratio; PP-NLR, pre-operative combined post-operative neutrophil to lymphocyte ratio; TBIL, total bilirubin.
Notes：The data are presented as hazard ratio (confidence interval 95%). p-values using the Log-rank test.
Table 6.
Median survival of significant factors in univariate analysis
| Factor | Group | Median survival |
|---|---|---|
| Number of lesions | Multiple | 19.609 |
| Single | 33.450 | |
| AFP, ng/ml | ≥400 | 22.941 |
| ＜400 | 31.889 | |
| Post-operative leukocytes, x109/L | ≥6.61 | 26.554 |
| ＜6.61 | 34.926 | |
| Post-operative lymphocytes, x109/L | ≥1.025 | 35.869 |
| ＜1.025 | 23.958 | |
| Pre-operative neutrophils, x109/L | ≥3.431 | 22.606 |
| ＜3.431 | 34.065 | |
| Post-operative neutrophils cells, x109/L | ≥4.975 | 22.255 |
| ＜4.975 | 36.613 | |
| Pre-operative NLR | ≥1.53 | 25.262 |
| ＜1.53 | 37.526 | |
| Post-operative NLR | ≥4.36 | 21.981 |
| ＜4.36 | 38.543 | |
| PP-NLR | 0 | 39.163 |
| 1 | 34.323 | |
| 2 | 19.244 |
AFP, alpha-fetoprotein; NLR, neutrophil to lymphocyte ratio; PP-NLR, pre-operative combined post-operative neutrophil to lymphocyte ratio.
Notes：The data are represented by median survival time.
Multivariate analysis
Statistically significant univariate analysis (p < 0.05) factors were included in the multivariate analysis to identify independent risk factors for early HCC recurrence and poor RFS after RFA. Recurrence during follow-up was a state variable, and tumor number, AFP level, post-operative leukocytes, post-operative lymphocytes, pre-operative neutrophils, post-operative neutrophils, pre-operative NLR, and post-operative NLR were included in the multivariate analysis as covariates; the results showed no significant differences (Table 7). When tumor number, AFP level, post-operative leukocytes, post-operative lymphocytes, pre-operative neutrophils, post-operative neutrophils, and PP-NLR were included in the multivariate analysis as covariates, only PP-NLR (HR = 1.869; 95% CI: 1.075–3.249; p = 0.027) was an independent risk factor for poor RFS and early recurrence in patients with primary HCC after RFA (Table 8).
Table 7.
COX multivariate analysis
| Factor | B | SE | WALD | p-value | HR (95% CI) |
|---|---|---|---|---|---|
| Number of lesions | −0.533 | 0.327 | 2.656 | 0.103 | 0.587 (0.309–1.114） |
| AFP | −0.414 | 0.362 | 1.305 | 0.253 | 0.661 (0.325–1.345） |
| Post-operative leukocytes | −0.448 | 0.491 | 0.833 | 0.361 | 0.639 (0.244–1.671） |
| Post-operative lymphocytes | 0.665 | 0.404 | 2.704 | 0.100 | 1.945 (0.880–4.296） |
| Pre-operative neutrophils | −0.293 | 0.344 | 0.725 | 0.395 | 0.746 (0.380–1.465） |
| Post-operative neutrophils cells | −0.319 | 0.513 | 0.387 | 0.534 | 0.727 (0.266–1.987） |
| Pre-operative NLR | −0.511 | 0.385 | 1.761 | 0.184 | 0.600 (0.282–1.276） |
| Post-operative NLR | −0.789 | 0.474 | 2.771 | 0.096 | 0.454 (0.179–1.150） |
AFP, alpha-fetoprotein; CI, confidence interval; HR, hazard ratio; NLR, neutrophil to lymphocyte ratio.
Notes：The data are presented as hazard ratio (confidence interval 95%). p-values using the log-rank test.
Table 8.
COX multivariate analysis
| Factor | B | SE | WALD | p-value | HR (95% CI) |
|---|---|---|---|---|---|
| Number of lesions | −0.536 | 0.325 | 2.719 | 0.099 | 0.585 (0.309–1.106） |
| AFP | −0.439 | 0.356 | 1.520 | 0.218 | 0.645 (0.321–1.295） |
| Post-operative leukocytes | −0.418 | 0.484 | 0.748 | 0.387 | 0.658 (0.255–1.698） |
| Post-operative lymphocytes | 0.726 | 0.383 | 3.591 | 0.058 | 2.066 (0.975–4.377） |
| Pre-operative neutrophils | −0.271 | 0.340 | 0.638 | 0.424 | 0.762 (0.392–1.483） |
| Post-operative neutrophils cells | −0.378 | 0.492 | 0.592 | 0.442 | 0.685 (0.261–1.795） |
| PP-NLR | 0.625 | 0.282 | 4.914 | 0.027 | 1.869 (1.075–3.249） |
AFP, alpha-fetoprotein; CI, confidence interval; HR, hazard ratio; PP-NLR, pre-operative combined post-operative neutrophil to lymphocyte ratio.
Notes：The data are presented as hazard ratio (confidence interval 95%). p-values using the log-rank test.
Survival curves
The survival curves of patients with pre-operative high and low NLR, posto-perative high and low NLR, and PP-NLR = 0, 1, and 2 (Figure 6A, B and C) were drawn by the Kaplan–Meier method. The 1- and 2-year RFS rates were 0.91 and 0.77 in patients with a pre-operative NLR<1.53 after RFA, while the 1- and 2-year RFS rates in patients with a pre-operative NLR≥1.53 decreased to 0.77 and 0.36, respectively (Table 9). The RFS rates 1 and 2 years after RFA were 0.91 and 0.80, respectively.
Figure 6.
(A) RFS survival curve of pre-operative high and low NLR. (B) RFS survival curve of post-operative high and low NLR. (C) RFS survival curve of PP-NLR 0 1 2. NLR, neutrophil to lymphocyte ratio; PP-NLR, pre-operative combined post-operative neutrophil to lymphocyte ratio; RFA, rdiofrequency ablation.
Table 9.
RFS rates of different groups of pre- and post-operative NLR, PP-NLR
| Factor | Group | 1-year RFS rates | 2-year RFS rates |
|---|---|---|---|
| Pre-operative NLR | ≥1.53 | 0.77 | 0.36 |
| ＜1.53 | 0.91 | 0.77 | |
| Post-operative NLR | ≥4.36 | 0.75 | 0.25 |
| ＜4.36 | 0.91 | 0.80 | |
| PP-NLR | 0 | 0.92 | 0.83 |
| 1 | 0.90 | 0.68 | |
| 2 | 0.71 | 0.17 |
NLR, neutrophil to lymphocyte ratio; PP-NLR, pre-operative combined post-operative neutrophil to lymphocyte ratio; RFS, recurrence-free survival.
Discussion
Pre-operative neutrophils and NLR, post-operative leukocytes, neutrophils, lymphocytes, and NLR, and PP-NLR, tumor number, and AFP level, were all associated with early HCC recurrence. Factors affecting RFS and leading to early recurrence were further analyzed using a Cox risk prediction model; compared with pre- or post-operative NLR and other indicators, PP-NLR was more effective in predicting prognosis. Moreover, PP-NLR was an independent risk factor for poor RFS and early recurrence.
Neutrophils collect inflamed cells at the inflamed site by secreting peroxidases, chemokines, and various proteases, forming an inflammatory microenvironment that is conducive to tumor growth. Here, vascular endothelial growth factor, tumor necrosis factors, and other cytokines can promote angiogenesis, and damage innate and adaptive immunity, weakening the antitumor immune response. 17,18 In addition, neutrophils can inhibit T lymphocyte activity by producing arginine, inducing a weakened lymphocyte-mediated immune response. 19 Activated inflammatory cells can cause DNA damage through reactive oxygen and nitrogen species, and the persistent stimulation of chronic inflammation may lead to immune tolerance to this. This is consistent with our results; in the univariate analysis, pre- and post-operative neutrophils were risk factors for poor RFS and early recurrence. Lymphocytes play an antitumor immune response through IL-2, IL-6, interferon γ, and tumor necrosis factor-α, inducing autoreactive T lymphocyte proliferation and other mechanisms leading to tumor necrosis and an antitumor immune response. 20,21 The mechanisms of the reduction of lymphocyte count mainly concern the following: lymphocytes are the main immune cells of the body and play a role in the antitumor response, and a decrease indicates severe immunosuppression; second, the secretion of transforming growth factor-β by tumor cells can also inhibit antigen-presenting cells, such as T lymphocytes, dendritic cells, and innate immune cells, causing further immunosuppression. 22 A retrospective analysis of 123 cases of cervical cancer hysterectomy showed that prognosis was related to the peripheral blood lymphocyte count. 23 Lymphocytes could also reflect tumor prognosis, and the higher the lymphocyte count, the better the immune response and prognosis. 24 A significant decrease in lymphocyte count after surgery is often associated with immunosuppression, and timely recovery of the lymphocyte count is associated with a good prognosis. 25 Herein, univariate analysis showed that post-operative lymphocytes influenced early HCC recurrence, consistent with the literature.
We also found higher leukocyte counts after RFA. The post-operative leukocyte counts were statistically significant in the univariate analysis, likely because the inflammatory response is dominant in early stages after RFA, while the immune response is relatively suppressed. Inflammatory factors accelerate the repair of liver tissue.
In diagnosing HCC and predicting recurrence, AFP is the most commonly used tumor marker. An increase in AFP level is related to tumor growth, including tumor invasion into adjacent vessels and malignant transformation. 26 An increase in AFP causes increased expression of metastasis-related proteins, leading to invasion of tissues surrounding the tumor. AFP has a unique role in the process of distant HCC metastasis; the AFP level can be used to predict the recurrence of HCC after treatment. 27 This is consistent with the results of the Cox univariate analysis herein showing that AFP is a factor leading to early recurrence of HCC and short RFS after RFA.
Herein, Cox univariate analysis showed that tumor number also affected RFS and early recurrence, consistent with previous studies. 28 This can be explained by the multicentric origin of HCC; patients with multiple HCC lesions are more likely to develop micrometastases than patients with only one lesion, and micrometastases from original lesions may cause early recurrence.
The inflammatory microenvironment is generally formed before carcinogenesis and provides a suitable environment for the occurrence, development, and metastasis of tumors. Inflammation promotes tumor development by promoting gene mutation, immortal proliferation of tumor cells, and angiogenesis. 29,30 NLR can effectively evaluate prognosis as an objective indicator to evaluate the relative levels of neutrophils and lymphocytes. 31 High NLR is related to poor prognosis in solid tumors, including liver cancer. 32,33 High pre-operative NLR (>2.31) is a poor predictor of survival after hepatectomy in patients with HCC and may become a new prognostic indicator for HCC after surgery. 34 Post-operative NLR is also an effective prognostic indicator. In a retrospective analysis 35 of clinical data from 3116 patients with breast cancer, NLR was an important prognostic factor. In 110 patients who underwent radical bladder cancer surgery, both pre- and post-operative NLR were associated with tumor recurrence. 36 However, the mechanism by which the NLR affects tumor prognosis is not fully understood. A high NLR reflects a disrupted balance between inflammatory and immune responses, with tumor-associated inflammatory responses predominating. Currently, few studies have combined the pre- and post-operative NLR to predict prognosis. However, the combination of these two reflects the balance between the immune system and the inflammatory response at different stages during treatment. Pre-operative NLR may reflect the balance between the body’s inflammatory response and immune status, whereas post-operative NLR may reflect residual immune activity. 37 The change rate of pre- and post-operative NLR in patients with clear cell renal cell carcinoma is an important prognostic factor affecting tumor recurrence. 38 NLR changes are an independent prognostic factor in patients with liver cancer; pre-operative NLR can be used to stratify patients before treatment, and post-operative NLR changes can be used to evaluate early treatment efficacy and predict survival. 39 PP-NLR combines the status of immune function of patients at different stages, more comprehensively predicting prognosis. This is consistent with the findings of the present study, where only PP-NLR was statistically significant in multivariate analysis. However, the mechanisms underlying pre- and post-operative NLR elevation and poor prognosis are unclear. The results herein showed that patients with primary liver cancer with a low NLR had longer RFS, regardless of pre- or post-operative measurements, indicating patients with a low NLR had relatively active immune systems and relatively suppressed inflammatory responses. Kim et al 40 collected clinical information of 1227 patients who underwent radical gastrectomy for gastric cancer, showing that persistently elevated pre- and post-operative NLR are an important poor prognostic factor.
Regarding the new findings of this retrospective study, PP-NLR (HR = 1.869; 95% CI: 1.075–3.249; p = 0.027) was an independent risk factor for early recurrence and shorter RFS after RFA. The combination of pre- and post-operative NLR was not available in previous studies, and it was easy to detect and did not bring any economic or physical burden to the patients. In terms of its clinical value, we believe that it can provide a new indicator, whether it is used as a single reference indicator or as a risk factor in models to predict the prognosis of HCC patients. If a prognostic model combined with other imaging or clinical indicators can be established and a nomogram can be constructed, it will provide the clinician with a convenient tool, because the nomogram can convert an abstract formula into a visual graph, and clinicians can judge the expected prognosis of patients as long as they collect the corresponding risk indicators of patients.
The study has several limitations. First, the number of patients was limited, and only patients from our Harbin Medical University Cancer Hospital were analyzed; thus, selection bias may affect the results. Second, the accuracy of the data processing cannot be guaranteed because ROC curves were used to calculate pre- and post-operative thresholds. Third, pre- and post-operative NLR were included in the multivariate Cox analysis, and the results showed no significant difference, indicating that these ratios were not independent risk factors. This may be because of the time at which peripheral blood samples were collected. In this study, blood samples used to calculate pre- and post-operative NLR were collected within three days of RFA. A previous study showed that NLR calculated 3–6 months after HCC resection had a better predictive value. 41 Fourth, another limitation could be an infectious disease. Finally, not all HCC diagnoses in this study were based on pathological diagnostic criteria, because some patients did not agree to the invasive examination. In future research, improvements should be made, such as including patients from multiple centers, increasing the study population, and adjusting the collection time of blood samples.
Conclusion
In conclusion, patients with a high pre-operative NLR, neutrophils, and AFP level; high post-operative NLR, neutrophils, and leukocytes, and low lymphocytes; and multiple tumors may have a shorter RFS and a higher possibility of early recurrence. In addition, the multivariate analysis revealed PP-NLR was an independent risk factor for early recurrence and poor RFS in patients with HCC after RFA. PP-NLR was more effective for predicting patient prognosis than pre- or post-operative NLR alone. NLR and, more specifically, PP-NLR have clinical application value for predicting patient prognosis.
Footnotes
Acknowledgments: The authors thank all those in the Ultrasound Department of the Cancer Hospital affiliated to Harbin Medical University who contributed to this article. Thanks to Editage (www.editage.cn) for polishing the English of this article.
Declarations of interest: The authors of this article declare that there is no potential conflict of interest with any organization or individual
Ethics approval: The study was reviewed and approved by the Ethics Committee of the Cancer Hospital Affiliated to Harbin Medical University, and was in line with the purpose of the Declaration of Helsinki. All patients signed informed consent.
Data availability statement: The data that support the findings of this study were available upon request from the corresponding author. The data were not publicly available due to privacy or ethical restrictions.
Contributor Information
ZiHao Ni, Email: 1070291639@qq.com.
BoLin Wu, Email: wubolin@hrbmu.edu.cn.
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