Novel postoperative nomograms for predicting individual prognosis of hepatitis B-related hepatocellular carcinoma with cirrhosis

doi:10.21203/rs.3.rs-1711130/v1

Background

Liver cirrhosis is a well-known risk factor for carcinogenesis of hepetocellular carcinoma (HCC). The aim of present study is to construct individual prognostic models for HCC with cirrhosis.

Methods

The clinical differences between HCC patients with and without cirrhosis were compared using a large cohort containing 1003 cases. Then cirrhotic patients were randomly divided into training and validation cohorts according to a ratio of 2:1. Univariate and multivariate analyses were performed to reveal the independent risk factors for recurrence-free survival (RFS) and overall survival (OS). These factors were subsequently used to construct nomograms.

Results

Multivariate analyses revealed that five clinical variables (hepatitis B e antigen (HBeAg), alpha-fetoprotein (AFP), tumor diameter, microvascular invasion (MVI) and satellite lesion) and seven variables (HBeAg, AFP, tumor diameter, MVI, satellite lesion, gamma-glutamyl transpeptidase (GGT) and differentiation) were significantly associated with RFS and OS, respectively. The nomograms based on these parameters were established. In training cohort, the C-indices of the nomograms for RFS and OS were 0.739 (P < 0.001) and 0.789 (P < 0.001), respectively; in validation cohort, the C-indices of the nomograms for RFS and OS were 0.752 (P < 0.001) and 0.813 (P < 0.001), respectively, which were significantly higher than the C-indices derived from conventional staging systems (P < 0.001). The calibration plots showed optimal consistence in prognoses between the prediction by nomograms and actual observation.

Conclusions

Presents nomograms showed good performance in predicting prognoses of HCC patients with hepatitis B virus associated cirrhosis.

Hepatocellular carcinoma

Cirrhosis

Hepatitis B virus

Prognosis

Nomogram

Hepatocellular carcinoma (HCC) is the most common pathological type of liver cancer and is a huge medical burden all over the world.[1, 2] Globally, approximately 782 000 new cases were diagnosed as HCC and about 746 000 deaths were caused by HCC each year.[1] More than half of new cases and deaths were happened in China due to the high prevalence of hepatitis B virus (HBV).[3–5] HCC has been ranked as the sixth most common malignancy and the third leading cause of cancer-related death worldwide.[1, 2] Owing to the lack of regular surveillance and asymptomatic characteristic of early-stage HCC, only 5–10% of HCC patients are the candidates for curative resection according to the Barcelona Clinic Liver Cancer (BCLC) staging system.[2, 6] Unfortunately, nearly 70% of HCC patients develop recurrence within 5 years after curative resection.[7] Therefore, developing new treatment strategies and regularly postoperative surveillance are imperative for increasing long-term survival of HCC patients.

Cirrhosis is a well-demonstrated risk factor for HCC. Almost 70% of patients with HCC have a background of cirrhosis.[2, 8] The annual incidence of HCC arising from established cirrhotic state ranges from 2.5–6.6%,[9–11] which was 2.79 - to 45.0 – fold higher than non-cirrhotic state, irrespective of the etiology of liver disease.[12] The carcinogenesis of HCC in patients with cirrhosis often is related to the sequential progression of regenerative nodules to dysplastic nodules to well-differentiated HCC.[13] Additionally, there are multiple clinical differences between the patients with and without cirrhosis. A recent study enrolled patients from Japan and America revealed that cirrhotic patients with HCC were more likely to have high level of HBV or HCV load, increased AFP level, poor liver function, low density of platelets, good pathologic differentiation and unfavorable postoperative prognosis when compared with non-cirrhotic patients with HCC.[14] Meanwhile, the probability of postoperative recurrence for patients with cirrhosis was about 6–15% higher per year than the patients without cirrhosis.[14] Furthermore, patients with cirrhosis were more likely to occur decompensated cirrhosis with symptoms including ascites, variceal bleeding, encephalopathy and/or jaundice post surgery.[15, 16] In this context, prognostic predictive models are imperative in designation of personalized surveillance strategies and adjuvant therapies for this subset of HCC patients. Unfortunately, such predictive models in cirrhotic patients with HCC have not been established specifically.

Nomogram has been accepted by abundant investigators in predicting outcomes of various diseases.[17–19] It is constructed based on the independent risk factors of special endpoints and showed more accurate than commonly used staging systems.[20] In this study, using a large cohort of HCC patients without macrovascular invasion, we firstly compared the clinical characteristics between cirrhotic and non-cirrhotic HCC patients. Then, nomograms were constructed for predicting individual recurrence-free survival (RFS) and overall survival (OS) of cirrhotic patients with HCC, respectively. In addition, the accuracy between these nomograms and conventional staging systems were compared.

Study population

The patients who underwent curative-intent resection for HCC from June 2006 to March 2015 in West China hospital, Sichuan University were retrospectively screened in this study. The inclusion criteria are (1) age not less than 18 years; (2) pathologically diagnosed as hepatocellular carcinoma; (3) positive hepatitis B surface antigen (HBsAg); (4) capable liver reserve function (Child-Pugh grade A or B); (5) treated curative hepatectomy initially; The exclusion criteria include (1) mixed with cholangiocarcinoma or other tumor types; (2) macrovascular invasion; (3) lymph node metastasis confirmed by pathology; (4) died in hospital or lost to follow-up within 3 months post surgery; (5) lack of important clinical variables such as tumor diameter, HBV-DNA load and pathological results. Finally, a total of 1003 patients who fulfilled the inclusion and exclusion criteria were including in this study. Written informed consent were obtained from all patients for their data to be used for clinical trials. This study was approved by ethics committee of West China Hospital, Sichuan University.

Baseline and clinical variables

The demographic characteristics and clinicopathologic variables of each patients were extracted from the hospital digital health care system of West China Hospital, Sichuan University. Demographic characteristics included age, sex, underlying liver diseases, hypertension and diabetes mellitus. Preoperative variables included Child-pugh grading, coagulation function, HBV-DNA loading, α-fetoprotein (AFP) level, portal hypertension, concentration of white blood cell (WBC), neutrophil (NEU), lymphocyte (LYM), and platelet (PLT), gamma-glutamyl transpeptidase (GGT) level. Imageology variables included tumor location/diameter/number and major vascular invasion, which were determined by three-phase-enhanced computed tomography (CT) or magnetic resonance imaging (MRI) scans. Intraoperative variables contained resection type, blood loss and transfusion. The histological diagnosis of each patient was made by two professional pathologists who were blinded to clinical information and laboratory findings of each patients. The differentiation grade was determined according to the criteria of the Edmondson-Steiner classification.[21] Microvascular invasion (MVI) was defined as tumor embolus detected by microscopy in small vessels of surgical samples.[22] Satellite lesions were termed as separate nodules less than 2 cm in diameter around the main tumor.[23] Fibrosis was staged according to the Ishak fibrosis scale of 0 to 6.[24] Patients with Ishak score of 5 (incomplete cirrhosis) or 6 (definite cirrhosis) were allocated into cirrhosis group, remaining patients were stratified into non-cirrhosis group.

Follow-up

A regular follow-up strategy was carried out for all patients after discharge from hospital. Serum AFP level, HBV-DNA load, liver function, routine blood test, and abdominal ultrasonography, CT or MRI scan were routinely performed at the first postoperative month, at 3-month intervals thereafter for the next 3 postoperative years, and every half year subsequently. For patients with positive HBV-DNA before surgery or during follow-up, antiviral therapy (entecavir or lamivudine) was administered immediately. If indicated, bone scan or positron emission tomography were employed to confirm distant metastasis. Tumor recurrence was determined by at least two radiological examinations showing new lesions with typical appearance of HCC in remnant liver, extrahepatic tissues or organs. After diagnosis of recurrence, optimum treatments including radiofrequency ablation (RFA), rehepatectomy, salvage liver transplantation, transarterial chemoembolization (TACE), sorafenib or best care support were performed. Recurrence-free survival (RFS) was defined as the time interval between the operation and the first diagnosis of recurrence. Overall survival (OS) was defined as the time interval between the operation and death or last follow-up. The follow-up was censored in August 2018.

Statistical analysis

Categorical variables were expressed as number or percentage and compared using Pearson Chi-Square or Fisher’s exact test. Continuous variables with a normal distribution were expressed as mean (standard deviation, SD) and analyzed using Student’s t test or Mann-Whitney U test. Univariate and multivariate analyses were performed using Cox proportional hazard model. Significant variables in univariate analysis were integrated into multivariate analysis to identify independent risk factors. All cirrhosis patients were randomly classified into training and validation cohorts based on a ratio of 2: 1.

The construction of nomograms was based on all independent risk factors derived from multivariate analyses in training cohort. The predictive accuracy of the nomograms was measured by Harrell’s concordance index (C-index) and assessed by calibration. A larger C-index value represents more accurate prognostic prediction. For internal validation, total points of each patient in the validation cohort were calculated using established nomograms, then the total points was treated as a new factor to calculate the C-index and depict calibration curve. If there is no significant difference of C-index and calibration between training and validation cohorts, stable performance of nomograms was considered. In addition, the predictive accuracy between the present nomograms and other conventional staging systems were compared using the rcorrp.cens package.[17]

All statistical analysis were performed in SPSS version 24.0 (IBM SPSS Inc, Chicago, IL) and R software version 3.5.0 with the rms package (http://www.r-project.org/). A two-tailed p-value less than 0.05 was considered as statistically significant.

The fibrosis status of all included patients

A total of 1003 HBV-related patients with HCC who underwent curative liver resection between June 2006 to March 2015 were included in this study. The fibrosis extent of each patients was evaluated using Ishak staging system. As shown in Fig. 1, only 3 patients (0.3%) had fibrosis score of 0 which means no fibrosis; 3 patients (0.3%) had fibrosis score of 1 which means fibrous expansion of some portal areas, with or without short fibrous septa; 30 patients (3.0%) had fibrosis score of 2 which means fibrous expansion of most portal areas, with or without short fibrous septa; 144 patients (14.4%) had fibrosis score of 3 which means fibrous expansion of most portal areas with occasional portal-to-portal bridging; 148 patients (14.8%) had fibrosis score of 4 which means fibrous expansion of most portal areas with marked bridging (both portal-to-portal and portal-to-central); 199 patients (19.8%) had fibrosis score of 5 which means incomplete cirrhosis characterized by marked bridging and occasional nodules; remaining 476 patients (47.5%) had fibrosis score of 6 which means probable or definite cirrhosis. In present study, we classified patients with Ishak score of 5 or 6 into cirrhosis group (675, 67.3%), the rest of patients were stratified into non-cirrhosis group (328, 32.7%).

Clinical differences between cirrhosis and non-cirrhosis groups

The clinical characteristics in cirrhosis and non-cirrhosis groups were listed in Table 1. Compared with non-cirrhosis group, higher percentage of patients in cirrhosis group had high HBV-DNA load, positive HBeAg, elevated AFP level, decreased concentration of WBC, NEU and PLT, prolonged prothrombin time (PT), increased international normalized ratio (INR), decreased fibrinogen (Fib) and elevated total bilirubin (TBIL). However, lower percentage of patients in cirrhosis group had age older than 60 years when compared with non-cirrhosis group. With respected to the tumor characteristics, the mean tumor diameter in cirrhosis group was significantly smaller than that in non-cirrhosis group. However, higher percentage of patients in cirrhosis group had multiple tumor nodules when compared with non-cirrhosis group. In cirrhosis group, the percentage of patients who underwent anatomical liver resection was 42.5%, which was significantly lower than that in non-cirrhosis group of 56.9%. No other significant differences were observed between cirrhosis and non-cirrhosis groups.

Follow-up results and independent prognostic factors in cirrhotic patients with HCC

The median follow-up time for all cirrhotic patients with HCC was 39 months (range, 1-120 months), the median RFS time was 25 months (range, 1-116 months). During the follow-up, a total of 429 out of 675 patients suffer from recurrence. Among them, 80 patients (18.6%) received repeat liver resection, 10 patients (2.3%) received salvage liver transplantation, 65 patients (15.2%) received radio frequency ablation, 181 patients (42.2%) received TACE, 5 patients (1.2%) received sorafenib, and remaining patients (20.5%) received best care support. The postoperative 1, 3, and 5-year RFS and OS rates were 64.42%, 43.61%, 31.97% and 88.79%, 63.15%, and 50.90%, respectively.

Based on a ratio of 2:1, cirrhotic patients with HCC was randomly divided into training cohort (n=450) and validation cohort (n=225), which were used to construct and validate prognostic models, respectively. As shown in table 2, except platelet-to-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), aspartate aminotransferase (AST) and the presence of MVI, no other significant differences were existed between cohorts. As listed in table 3, univariate analysis in training cohort revealed that HBV-DNA, HBeAg, AFP, NEU, LYM, NLR, PLR, GGT, tumor diameter, tumor number, hystologic differentiation, MVI, and satellite lesion were significantly associated with RFS; parameters which were significantly associated with OS included HBV-DNA, HBeAg, AFP, NEU, LYM, PLT, PLR, AST, GGT, tumor diameter, hystologic differentiation, MVI, satellite lesion, and type of hepatectomy. Subsequently, these variables were chosen for multivariate analyses. The results showed that positive HBeAg (HR 1.426, 95% confidence interval (CI) 1.085-1.874, P = 0.011), elevated AFP (HR 1.576, 95% CI 1.237-2.008, P < 0.001), large tumor diameter (HR 1.358, 95% CI 1.060-1.739, P = 0.015), the presence of MVI (HR 1.943, 95% CI 1.527-2.471, P < 0.001), and the presence of satellite lesion (HR 1.794, 95% CI 1.305-2.467, P < 0.001) were the independent risk factors for RFS; and positive HBeAg (HR 1.517, 95% CI 1.105-2.081, P = 0.01), elevated AFP (HR 1.477, 95% CI 1.113-1.960, P < 0.001), large tumor diameter (HR 1.383, 95% CI 1.024-1.868, P = 0.035), the presence of MVI (HR 2.113, 95% CI 1.594-2.802, P < 0.001), and the presence of satellite lesion (HR 1.509, 95% CI 1.050-2.167, P = 0.026), increased GGT (HR 1.416, 95% CI 1.051-1.907, P = 0.022) and poor hystologic differentiation (HR 1.411, 95% CI 1.078-1.847, P = 0.012) were the independent risk factors for OS.

Construction and validation of prognostic nomograms for cirrhotic patients with HCC

Above independent risk factors were used to generate nomograms for RFS and OS respectively (Fig. 2). The nomograms showed promising accuracy in predicting prognoses, with the bootstrap-corrected C-index for RFS and OS prediction in training cohort were 0.739 (95% CI 0.709-0.769, P < 0.001) and 0.789 (95% CI: 0.759-0.819, P < 0.001), respectively. The calibration plots of training cohort graphically showed optimal consistency of the 3 and 5- year RFS (Fig. 3a and 3b) and OS (Fig. 3c and 3d) between the prediction by nomograms and actual observation. For clinical use of present nomograms, the projection on the point scale meant score of each variable, total point was calculated by summing the scores of all variables, the projection of total point on the prognostic scales represented the individual probability for 3- and 5-year RFS or OS rate.

For internal validation of these nomograms, the total point of each patient in validation cohort was calculated by above nomograms. Then the total point was treated as a new factor to calculate the C-indices and depict calibration curves of RFS and OS, respectively. The results showed the C-indices for RFS and OS prediction in validation cohort were 0.752 (95% CI: 0.712-0.792, P < 0.001) and 0.813 (95% CI: 0.775-0.851, P < 0.001), respectively, which were comparable with the C-indices in training cohort. The calibration plots of validation cohort also showed good agreement of the 3 and 5- year RFS (Fig. 3e and 3f) and OS (Fig. 3g and 3h) between the prediction by nomograms and actual observation. These results indicted that present nomograms had promising performance in predicting the prognoses of cirrhotic patients with HCC.

Comparison of predictive accuracy between the present nomograms and conventional staging systems

To compare the superiority between our nomograms and conventional staging systems in predicting prognoses of cirrhotic patients with HCC, four routinely used staging systems (Barcelona Clinic Liver Cancer staging system (BCLC), the eighth version of American Joint Committee on Cancer (AJCC^8th), the Japan Integrated Staging Score (JIS score), the Hong Kong Liver Cancer prognostic classification scheme (HKLC)) were selected and the discriminatory capacity of each prognostic system was compared by means of Harrel’s C-index, as shown in Table 4. In training cohort, the C-index of the nomogram for RFS was 0.739, which was significantly higher (p<0.001) than the BCLC, AJCC^8th, JIS score and HKLC systems; the C-index of the nomogram for OS was 0.789, which was also significantly higher (p<0.001) than the BCLC, AJCC^8th, JIS score and HKLC systems. Similar results were also observed in validation cohort. These data suggesting that our nomograms are more feasible than conventional staging systems in predicting the prognoses of cirrhotic patients with HCC.

In this study, the fibrosis extent of included patients was evaluated according to the Ishak staging system. Ishak staging system is a modified version of Knodell system and has seven stages of fibrosis (0–6), which was effective in distinctions of fibrosis and architectural remodeling.[24] In recent years, Ishak staging system has been widely used in clinical trials and was recommended as a tool in Grading of Chronic Virus Hepatitis by World Health Organization (WHO).[25, 26] The percentage of cirrhosis in our cohort was 67.3%, which was in line with previous studies.[2, 8] To the best of our knowledge, present study firstly compared the clinical characteristics between cirrhotic and non-cirrhotic HCC using a large sample size of HBV-related patients. The results showed that HCC patients in cirrhosis group were more likely to have younger age, elevated AFP level, decreased concentration of WBC, NEU and PLT, poor coagulation function, smaller tumor size and multiple tumor number, some of which were in line with a recent study which included Japanese and American patients with background etiologies containing HBV (32.5%), HCV (58.7%), alcohol abuse (3.7%) and others (5.1%).[14] These evidence indicated that the patients with cirrhosis had heavier burden of hepatitis infection, poorer coagulation function, more advanced tumor stage than the patients without cirrhosis. Therefore, this study concentrated on the prognosis of this subgroup of patients with HCC.

Using univariate and multivariate analyses, five RFS associated risk factors and seven OS associated risk factors were identified. Based on these factors, individual nomograms for RFS and OS were established, respectively. The C-index and calibration plots showed promising accuracy and optimal consistence of these nomograms. Internal validation also suggested ideal performance of these prediction models. After comparing with four conventional staging systems, we found that present nomograms were more superior in predicting the prognoses of cirrhotic patients with HCC. The results of this study further demonstrated that nomograms were more suitable in predicting individual clinical events than commonly used staging systems.[20]

Compared with routinely used staging systems, some new prognosis-related elements including AFP, HBeAg, GGT, MVI, satellite lesion and hystologic differentiation were integrated into present nomograms. Serum AFP is the most common biomarker in diagnosing HCC with capable sensitivity and specificity.[27, 28] Preoperative serum AFP level was normally treated as an indicator for tumor burden and an predictor for prognosis of HCC after hepatectomy.[29, 30] Serum HBeAg positive means active viral replication and is associated with deterioration of HCC.[31, 32] A recent propensity score matching study found that positive serum HBeAg was an independent risk factor of RFS and OS for patients with HCC after curative surgery.[33] GGT could be abundantly produced by HCC cells and is a valuable biomarker in diagnosis of HCC with a low serum AFP level.[34–36] Higher serum GGT levels were associated with larger tumor size, presence of vascular invasion, and advanced tumor stage.[37, 38] In consistent with present study, numerous studies have been reported that elevated GGT level was significantly associated with unfavorable prognosis of HCC patients after curative liver resection.[39, 40] MVI was an established risk factor of early recurrence and poor survival for patients with HCC after liver resection,[22, 41, 42] the incidence of MVI was positively associated with tumor size and number.[41] The presence of satellite lesion indicates intrahepatic dissemination,[23, 43, 44] which is a dangerous signal of early recurrence and short survival time for patients with HCC after hepatectomy.[45, 46] Poor hystologic differentiation was normally considered as an aggressive property of HCC lesions.[47] Poor differentiation is normally associated with larger tumor size, up-regulated AFP level, presence of MVI and unfavorable prognosis of HCC patients.[48, 49]

There some limitations of this study needed to be figured out. Firstly, as the high prevalence of HBV in China, we only enrolled patients with a history of HBV infection, and positive HBeAg was one of the elements in present nomograms. Therefore, the usage of these prediction models in other etiologies-related HCC is limited. Secondly, this study is a retrospective study, further prospective and external validations were necessary. Thirdly, the superiority between these nomograms and conventional staging systems need to be cautiously interpreted. These nomograms integrated multiple postoperative variables and were helpful for postoperative decision making, while the conventional staging systems were meaningful in guiding the treatment for all patients with HCC based on preoperative parameters.

In conclusion, using a large cohort of patients with HCC, we found that there many clinicopathologic difference between cirrhotic and non-cirrhotic patients with HCC with background disease of HBV infection. Univariate and multivariate analyses revealed that five clinical variables were significantly associated with RFS and seven variables were significantly associated with OS. Using these variables, nomograms for predicting RFS and OS of cirrhotic patients with HCC were generated. These nomograms showed good accuracy and optimal performance when compared with conventional staging systems.

HCC: Hepatocellular carcinoma; HBV: Hepatitis B virus; HBV-DNA: Hepatitis B virus deoxyribonucleic acid; HBeAg: Hepatitis B e antigen; AFP: Alpha-fetoprotein

GGT: Gamma-glutamyl transpeptidase; MVI: Microvascular invasion; BCLC: Barcelona Clinic Liver Cancer; RFS: Recurrence-free survival; OS: Overall survival.

Acknowledgments

None

Authors’ contributions

ZM and XMQ conceived and designed the study; XLL and DFZ performed all experiments; WP and LL responsible for the analysis and interpretation of data. XLL wrote the paper. All authors read and approved the final manuscript.

Funding

This study was supported by the Key Technology Research and Development Program of the Sichuan Province (Nos. 2021YFSY0009 and 2021YFS0106); the Post-Doctor Research Project, West China Hospital, Sichuan University (Nos. 2020HXBH076).

Availability of data and materials

The datasets generated and analysed during the current study are not publicly available due to patient privacy but are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

This study was approved by The Clinical Medical Research Ethics Committee of the West China Hospital of the Sichuan University (IRB number: FWA00009482IRBIORG0004190) and was performed in accordance with the Declaration of Helsinki. All patients signed a preoperative informed consent form and agreed to participate in the accompanying scientific research.

Consent for publication

The manuscript is approved for publication by all the authors. Written informed consent was obtained from the patients and/or their legal guardians for publication, and any accompanying images, sex, age of these patients.

Competing interests

The authors declare no competing interests.

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Table 1. Clinical differences between cirrhotic Table 1. Clinical differences between cirrhotic

and non-cirrhotic patients with HCC and non-cirrhotic patients with HCC

Clinical parameters	Non-cirrohsis (n=328, %)	Cirrohsis (n=675, %)	P-value	Clinical parameters	Non-cirrohsis (n=328, %)	Cirrohsis (n=675, %)	P-value
Gender			0.778	TBIL (μmol/L)			0.02
Male	275 (83.8)	570 (84.5)		≥ 28	8 (2.3)	36 (5.4)
Female	53 (16.2)	105 (15.5)		< 28	320 (97.7)	639 (94.6)
Age (years)			0.014	ALT (IU/L)			0.659
≥ 60	101 (30.9)	152 (22.5)		≥ 50	112 (34.1)	240 (35.5)
< 60	227 (69.1)	523 (77.5)		< 50	216 (65.9)	435 (64.5)
HBV-DNA (copies/mL)			0.002	AST (IU/L)			0.385
≥ 103	169 (51.4)	397 (58.8)		≥ 40	153 (46.6)	334 (49.5)
< 103	159 (48.6)	278 (41.2)		<40	175 (53.4)	341 (50.5)
HBeAg			0.002	ALB (g/L)			0.054
Positive	43 (13.1)	149 (22.1)		≥ 40	224 (68.2)	419 (62.1)
Negative	285 (86.9)	526 (77.9)		<40	104 (31.8)	256 (37.9)
AFP (ng/mL)			0.032	GGT (IU/L)			0.363
≤ 20	116 (35.3)	227 (33.6)		≥ 60	170 (51.7)	329 (48.7)
20-400	65 (19.7)	182 (27.0)		< 60	158 (48.3)	346 (51.3)
≥ 400	147 (45.0)	266 (39.4)		Child-pugh			0.961
WBC (×10⁹/L)			< 0.001	A	323 (98.6)	666 (98.6)
≥ 4	297 (90.6)	502 (74.3)		B	5 (1.4)	9 (1.4)
< 4	31 (9.4)	173 (25.7)		Tumor diameter, mean (SD), cm	7.44 (3.91)	5.53 (3.25)	< 0.001
NEU (×10⁹/L)			< 0.001	Tumor number			0.015
≥ 3.56	184 (56.0)	239 (35.4)		multi	36 (11.1)	113 (16.8)
< 3.56	144 (44.0)	436 (64.6)		single	292 (88.9)	562 (83.2)
LYM (×10⁹/L)			0.089	Differentiation			0.628
≥ 1.1	261 (79.5)	505 (74.8)		I+II	193 (58.8)	383 (56.8)
< 1.1	67 (20.5)	238 (35.2)		III+IV	135 (41.2)	292 (43.2)
PLT (×10⁹/L)			< 0.001	MVI			0.24
≥ 100	275 (83.8)	409 (60.6)		Present	128 (38.9)	238 (35.2)
< 100	53 (16.2)	266 (39.4)		Absent	200 (61.1)	437 (64.8)
NLR			< 0.001	Satellite lesion			0.328
≥ 3	114 (34.9)	152 (22.5)		Present	48 (14.5)	83 (12.3)
< 3	214 (65.1)	523 (77.5)		Absent	280 (85.5)	592 (87.7)
PLR			< 0.001	Resection			< 0.001
≥ 111	140 (42.6)	167 (24.8)		Anatomic	187 (56.9)	287 (42.5)
< 111	188 (57.4)	508 (75.2)		Non-anatomic	141 (43.1)	388 (57.5)
PT (s)			< 0.001	Blood loss (mL)			0.872
≥ 12.8	48 (14.5)	186 (27.5)		≥ 400	272 (82.9)	567 (84.0)
< 12.8	280 (85.5)	489 (72.5)		< 400	56 (17.1)	108 (16.0)
INR			< 0.001	Transfusion			0.734
≥ 1.15	47 (14.2)	172 (25.5)		Yes	51 (15.6)	109 (16.1)
< 1.15	281 (85.8)	503 (74.5)		No	277 (84.4)	566 (83.9)
Fib (g/L)			< 0.001
≥ 2	297 (90.6)	538 (79.7)
< 2	31 (9.4)	137 (20.3)

Bold numbers indicate statistical significance.

HBV-DNA, hepatitis B virus deoxyribonucleic acid; HBeAg, hepatitis B e antigen; AFP, alpha-fetoprotein; WBC, white blood cell; NEU, neutrophil; LYM, lymphocyte; PLT, platelet; NLR, neutrophil-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; PT, prothrombin time; s, second; INR, international normalized ratio; Fib, fibrinogen; TBIL, total bilirubin; ALT, alanine transaminase; AST, aspartate aminotransferase; ALB, albumin; GGT, gamma-glutamyl transpeptidase; SD, standard deviation; MVI, microvascular invasion.

Table 2. The baseline characteristics of cirrhotic patients with HCC in training and validation cohort.

Clinical parameters	Traning cohort (n=450, %)	Validation cohort (n=225, %)	P-value
Gender, male	374 (86.2)	176 (81.1)	0.092
Age, ≥ 60 y	96 (22.2)	50 (23.0)	0.214
HBV-DNA, ≥ 103 copies/ml	246 (56.8)	137 (63.0)	0.367
HBeAg, positive	95 (21.9)	49 (22.6)	0.366
AFP, ≤ 20 ng/mL	173 (40.0)	83 (38.4)	0.866
AFP, 20-400 ng/mL	146 (33.7)	72 (33.3)
AFP, ≥ 400 ng/mL	114 (26.3)	61 (28.2)
WBC, ≥ 4 × 10⁹/L	174 (40.0)	84 (38.5)	0.498
NEU, ≥ 3.56 × 10⁹/L	156 (36.0)	74 (34.3)	0.657
LYM, ≥ 1.1 × 10⁹/L	327 (75.3)	160 (73.6)	0.632
PLT, ≥ 100 × 10⁹/L	266 (61.3)	132 (60.8)	0.909
NLR, ≥ 3	110 (25.4)	36 (16.7)	0.012
PLR, ≥ 111	121 (27.9)	40 (18.5)	0.009
PT, ≥ 12.8 s	125 (28.7)	55 (25.1)	0.388
INR, ≥ 1.15	115 (26.5)	51 (23.5)	0.408
Fib, ≥ 2 g/L	346 (79.6)	173 (79.9)	0.942
TB, ≥ 28 μmol/L	28 (6.5)	7 (3.2)	0.084
ALT, ≥ 50 IU/L	168 (38.7)	63 (29.0)	0.015
AST, ≥ 40 IU/L	229 (52.8)	93 (42.9)	0.017
ALB, ≥ 40 g/L	274 (63.1)	130 (59.9)	0.424
GGT, ≥ 60 IU/L	216 (49.8)	101 (46.5)	0.438
Child-pugh, Stage B	8 (1.8)	1 (0.5)	0.285
Tumor diameter, mean (SD), cm	5.65 (3.35)	5.28 (3.03)	0.178
Tumor number, multiple	73 (16.9)	36 (16.6)	0.931
Differentiation, III+IV	188 (43.4)	93 (42.9)	0.771
MVI, present	166 (38.2)	63 (29.0)	0.02
Satellite, present	56 (12.9)	24 (11.1)	0.493
Type of hepatectomy,anatomic	185 (42.7)	92 (42.3)	0.916
Blood loss, ≥ 400 mL	337 (86.8)	163 (75.0)	0.329
Transfusion, yes	67 (15.4)	38 (17.5)	0.523

Bold numbers indicate statistical significance.

HBV-DNA, hepatitis B virus deoxyribonucleic acid; HBeAg, hepatitis B e antigen; AFP, alpha-fetoprotein; WBC, white blood cell; NEU, neutrophil; LYM, lymphocyte; PLT, platelet; NLR, neutrophil-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; PT, prothrombin time; s, second; INR, international normalized ratio; Fib, fibrinogen; TBIL, total bilirubin; ALT, alanine transaminase; AST, aspartate aminotransferase; ALB, albumin; GGT, gamma-glutamyl transpeptidase; SD, standard deviation; MVI, microvascular invasion.

Table 3. Independent risk factors for RFS and OS verified by univariate and multivariate analyses.

Clinical parameters	RFS		OS
Clinical parameters	HR (95% CI)	P-value	HR (95% CI)	P-value
*Univariate analysis*
SEX (male/female)	0.894 (0.596-1.210)	0.365	0.816（0.537-1.238）	0.338
Age (≥60/<60 years)	0.797 (0.600-1.06)	0.118	0.844（0.608-1.170）	0.308
HBV-DNA (≥103/<103 copies/mL)	1.433(1.112-1.845)	0.005	1.566（1.159-2.117）	0.004
HBeAg (positive/negative)	1.397(1.067-1.830)	0.015	1.487（1.094-2.021）	0.011
AFP(≤ 20/20-400/≥ 400 ng/mL)	1.801(1.427-2.273)	<0.001	1.912(1.463-2.497)	<0.001
WBC (≥4/<4 × 109/L)	1.353(0.957-1.913)	0.087	1.340(0.900-1.995)	0.149
NEU (≥3.56/<3.56 × 109/L)	1.310(1.033-1.662)	0.026	1.529(1.165-2.007)	0.002
LYM (≥1.1/<1.1 × 109/L)	1.331（1.005-1.763）	0.046	1.430(1.027-1.992)	0.034
PLT (≥100/<100 × 109/L)	1.205（0.949-1.530)	0.126	1.424(1.075-1.886)	0.014
NLR (≥3/<3)	1.366(1.057-1.765)	0.017	1.293(0.961-1.739)	0.09
PLR (≥111/<111)	1.294(1.005-1.665)	0.045	1.364(1.022-1.820)	0.035
PT (≥12.8/<12.8 s)	0.953(0.720-1.260)	0.735	0.929(0.673-1.283)	0.656
INR (≥1.15/<1.15)	0.897(0.688-1.169)	0.421	0.923(0.678-1.257)	0.611
Fib (≥2/<2 g/L)	1.279(0.930-1.761)	0.131	1.336(0.904-1.997)	0.147
TB (≥28/<28 μmol/L)	0.740(0.447-1.226)	0.243	0.690(0.376-1.265)	0.23
ALT (≥50/<50 IU/L)	1.154(0.912-1.458)	0.233	1.106(0.843-1.452)	0.467
AST (≥40/<40 IU/L)	1.255(0.995-1.583)	0.055	1.391(1.061-1.823)	0.017
ALB (≥40/<40 g/L)	0.899(0.708-1.141)	0.382	0.781(0.594-1.026)	0.075
GGT (≥60/<60 IU/L)	1.540(1.220-1.943)	<0.001	2.027(1.539-2.669)	<0.001
Child-pugh (A/B)	1.489(0.663-3.344)	0.335	0.978(0.367-2.655)	0.979
Tumor diameter	1.734(1.370-2.195)	<0.001	1.960(1.487-2.583)	<0.001
Tumor nuber (multiple/solitary)	1.543(1.157-2.057)	0.003	1.217(0.863-1.716)	0.263
Differentiation (III+IV/I+II)	1.300(1.035-1.634)	0.024	1.653(1.269-2.152)	<0.001
MVI (present/negative)	2.130(1.689-2.687)	<0.001	2.529(1.934-3.307)	<0.001
satellite (present/negative)	1.906(1.396-2.603)	<0.001	1.743(1.217-2.496)	0.002
Anatomic hepatectomy (yes/no)	1.214(0.961-1.534)	0.103	1.432(1.095-1.873)	0.009
Blood loss (≥400/<400 mL)	2.846(0.860-9.415)	0.087	3.861(0.902-16.529)	0.069
Transfusion (yes/no)	1.655(0.819-3.346)	0.16	1.351(0.600-3.043)	0.468
*Multivariate analysis*
HBeAg	1.426(1.085-1.874)	0.011	1.517(1.105-2.081)	0.01
AFP	1.576(1.237-2.008)	<0.001	1.477(1.113-1.960)	0.007
Tumor diameter	1.358(1.060-1.739)	0.015	1.383(1.024-1.868)	0.035
MVI	1.943(1.527-2.471)	<0.001	2.113(1.594-2.802)	<0.001
Satellite lesion	1.794(1.305-2.467)	<0.001	1.509(1.05-2.167)	0.026
GGT	ND	ND	1.416(1.051-1.907)	0.022
Differentiation	ND	ND	1.411(1.078-1.847)	0.012

Bold numbers indicate statistical significance.

RFS, recurrence-free survival; OS, overall survival; HR, hazard ratio; CI, confidence interval; HBV-DNA, hepatitis B virus deoxyribonucleic acid; HBeAg, hepatitis B e antigen; AFP, alpha-fetoprotein; WBC, white blood cell; NEU, neutrophil; LYM, lymphocyte; PLT, platelet; NLR, neutrophil-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; PT, prothrombin time; s, second; INR, international normalized ratio; Fib, fibrinogen; TBIL, total bilirubin; ALT, alanine transaminase; AST, aspartate aminotransferase; ALB, albumin; GGT, gamma-glutamyl transpeptidase; SD, standard deviation; MVI, microvascular invasion; ND, no data.

Table 4. Comparison of accuracy between present nomograms and four conventional staging systems via C-index.

Prognostic system	RFS				OS
Prognostic system	C-index	95% CI	P1^*	P2^#	C-index	95% CI	P1^*	P2^#
*Training cohort*
Present nomogram	0.739	0.709-0.769	<0.001	1.0(Ref.)	0.789	0.759-0.819	<0.001	1.0(Ref.)
BCLC	0.615	0.587-0.643	<0.001	<0.001	0.633	0.601-0.665	<0.001	<0.001
AJCC^8th	0.547	0.522-0.572	<0.001	<0.001	0.541	0.513-0.569	0.006	<0.001
JIS score	0.541	0.517-0.566	0.001	<0.001	0.524	0.497-0.551	0.09	<0.001
HKLC	0.595	0.566-0.624	<0.001	<0.001	0.612	0.578-0.646	<0.001	<0.001
*Validation cohort*
Present nomogram	0.752	0.712-0.792	<0.001	1.0(Ref.)	0.813	0.775-0.851	<0.001	1.0(Ref.)
BCLC	0.615	0.583-0.647	<0.001	<0.001	0.636	0.589-0.683	<0.001	<0.001
AJCC^8th	0.562	0.527-0.597	<0.001	<0.001	0.576	0.535-0.617	<0.001	<0.001
JIS score	0.554	0.521-0.587	0.002	<0.001	0.565	0.524-0.606	0.002	<0.001
HKLC	0.601	0.559-0.643	<0.001	<0.001	0.616	0.567-0.665	<0.001	<0.001

^*represent significance of staging systems;

^#represent significance between present nomograms and conventional staging systems;

Ref. reference; RFS, recurrence-free survival; OS, overall survival; CI, confidence interval; BCLC, Barcelona Clinic Liver Cancer staging system; AJCC^8th, the eighth version of American Joint Committee on Cancer; JIS score, the Japan Integrated Staging Score; HKLC, the Hong Kong Liver Cancer prognostic classification scheme.

No competing interests reported.

Novel postoperative nomograms for predicting individual prognosis of hepatitis B-related hepatocellular carcinoma with cirrhosis

Status:

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Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1