Literature DB >> 28261338

Predictive factors in patients with hepatocellular carcinoma receiving sorafenib therapy using time-dependent receiver operating characteristic analysis.

Hiroki Nishikawa1, Norihiro Nishijima2, Hirayuki Enomoto1, Azusa Sakamoto2, Akihiro Nasu2, Hideyuki Komekado2, Takashi Nishimura1, Ryuichi Kita2, Toru Kimura2, Hiroko Iijima1, Shuhei Nishiguchi1, Yukio Osaki2.   

Abstract

AIMS: To investigate variables before sorafenib therapy on the clinical outcomes in hepatocellular carcinoma (HCC) patients receiving sorafenib and to further assess and compare the predictive performance of continuous parameters using time-dependent receiver operating characteristics (ROC) analysis. PATIENTS AND METHODS: A total of 225 HCC patients were analyzed. We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of continuous parameters which were significant in the multivariate analysis in terms of OS and PFS. Total sum of area under the ROC in all time points (defined as TAAT score) in each case was calculated.
RESULTS: Our cohort included 175 male and 50 female patients (median age, 72 years) and included 158 Child-Pugh A and 67 Child-Pugh B patients. The median OS time was 0.68 years, while the median PFS time was 0.24 years. On multivariate analysis, gender, body mass index (BMI), Child-Pugh classification, extrahepatic metastases, tumor burden, aspartate aminotransferase (AST) and alpha-fetoprotein (AFP) were identified as significant predictors of OS and ECOG-performance status, Child-Pugh classification and extrahepatic metastases were identified as significant predictors of PFS. Among three continuous variables (i.e., BMI, AST and AFP), AFP had the highest TAAT score for the entire cohort. In subgroup analyses, AFP had the highest TAAT score except for Child-Pugh B and female among three continuous variables.
CONCLUSION: In continuous variables, AFP could have higher predictive accuracy for survival in HCC patients undergoing sorafenib therapy.

Entities:  

Keywords:  Clinical outcomes; Hepatocellular carcinoma; Predictive factor; Sorafenib; Time-dependent ROC analysis.

Year:  2017        PMID: 28261338      PMCID: PMC5332888          DOI: 10.7150/jca.16786

Source DB:  PubMed          Journal:  J Cancer        ISSN: 1837-9664            Impact factor:   4.207


Introduction

Hepatocellular carcinoma (HCC) is globally one of the leading causes of cancer-related deaths, which accounts for 5-6% of all new cancers. 1-6 Significant advances in HCC therapy during the last few decades have been achieved. 1, 2, 4, 5 However, unfortunately, a curative treatment for HCC can be applied to a limited number of HCC subjects. 5, 7 Sorafenib is a multi-kinase inhibitory anti-cancer agent that can effectively suppresses tumor growth and cancer cell proliferation. 8, 9 Two pivotal randomized phase III studies presented that subjects with unresectable HCC receiving sorafenib therapy were able to obtain survival benefits as compared with the placebo group with statistical significance. 8, 9 More than half decade have passed after the introduction of sorafenib for unresectable HCC therapy in the clinical settings. However, sorafenib is as yet considered as first-line systemic chemotherapeutic agent for unresectable HCC. 10, 11 Prognostic factors at baseline associated with survival in HCC patients undergoing sorafenib therapy have also been investigated and they include age, gender, liver function, the Eastern Cooperative Oncology Group (ECOG)-performance status (PS), tumor marker and tumor status. 12-21 Receiver operating characteristics (ROC) analysis is a well-established statistical method and is frequently used to assess the discriminatory ability of continuous parameters for a binary disease outcome such as being alive or dead. However, it should be noted that disease outcomes are usually time-dependent. 22 Time-dependent ROC curves have thus been brought into use to fully evaluate the prediction ability of clinical parameters for time-dependent disease outcomes. 22 However, ROC analysis to evaluate the predictive power of clinical factors for survival that takes time dependence into consideration has not been fully examined in HCC patients undergoing sorafenib therapy. Again, because disease outcomes are often time-dependent, time-dependent ROC analysis seems to be an essential statistical method for the precise evaluation of continuous variables on outcomes. The aim of the present study was to investigate variables before sorafenib therapy on the clinical outcomes in HCC patients receiving sorafenib. Additionally, in order to further assess and compare the predictive performance of continuous parameters, we created time-dependent ROC curves for censored data and adopted the area under the ROC curve (AUROC) as the criterion. 22

Patients and methods

Patients and indications for sorafenib treatment

Between June 2009 and August 2015, 234 HCC patients treated with sorafenib were admitted to the Division of Hepatobiliary and Pancreatic Disease, Department of Internal Medicine, Hyogo College of Medicine, Hyogo, Japan and at the Department of Gastroenterology and Hepatology, Osaka Red Cross Hospital, Osaka, Japan. We included the following variables into analysis: age, gender, body mass index (BMI), cause of liver disease, initial dose of sorafenib, Child-Pugh classification, ECOG-PS, HCC stage as defined by Japanese guidelines, laboratory parameters including platelet count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma glutamyl transpeptidase (GGT), alpha-fetoprotein (AFP) and des-γ-carboxy prothrombin (DCP). A total of 225 HCC patients with all these data available were analyzed in this study. HCC was diagnosed as described elsewhere. 23-25 Sorafenib therapy was recommended in patients with unresectable HCCs and with the following clinical features as determined by radiologic findings using dynamic computed tomography (CT): (1) the presence of metastatic lesions outside the liver; (2) poor response to previous transcatheter arterial therapies for HCC (transcatheter arterial chemoembolization [TACE] or transcatheter arterial infusion [TAI] chemotherapy); (3) unsuitability for TACE or TAI due to anatomical reasons; and (4) vascular invasion such as tumor thrombus into the portal vein. 23, 24, 26 Subjects who had poor PS (ECOG-PS ≥3) were not recommended for sorafenib therapy. 23, 24 We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of parameters which were significant in the multivariate analysis in terms of OS and PFS. Since this study was a retrospective analysis of patients' clinical data, all treatments were performed in an open-label manner. Our study was performed in accordance with the Declaration of Helsinki and with approvals from the ethics committees of each hospital (Hyogo College of Medicine and Osaka Red Cross Hospital).

Sorafenib therapy

For subjects with no obvious risk factors, the recommended initial sorafenib dose of 800 mg/day (400 mg twice a day) was administered. 8, 9 In some subjects, the starting dose was reduced considering clinical characteristics such as body weight, age, ECOG-PS, and liver function. The daily sorafenib dose according to the degree of adverse events under sorafenib therapy was adjusted by each attending physician. For subjects who received an initial reduced sorafenib dose with well tolerability, dose escalation was permitted. In cases with adverse events, sorafenib therapy was stopped until the clinical symptoms resolved to grade 2 or less. In principle, the treatment efficacy of sorafenib was assessed every 4-8 weeks after the initiation of therapy according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST) and/or the values of tumor markers. 23, 24, 27, 28 Sorafenib therapy was continued until the development of the following conditions: HCC disease progression, unacceptable sorafenib-related drug toxicities, or the patient's wish for stopping treatment. After cessation of sorafenib therapy for any reason, physicians sufficiently evaluated the clinical conditions (tumor status or the general status) of each subject, and evaluated the suitability of other treatments (transcatheter arterial therapies or systemic chemotherapy besides sorafenib) with the purpose of ameliorating clinical outcome. 23-26

Evaluation of treatment efficacy

The best treatment efficacy achieved during sorafenib therapy was determined according to the mRECIST criteria and/or tumor marker levels as previously indicated. 23, 24, 27 As reported elsewhere, the treatment efficacy was classified into the following four categories: (i) complete response (CR), (ii) partial response (PR), (iii) stable disease (SD), and (iv) progressive disease (PD). 24, 27 We defined the objective response rate (ORR) as the proportion of subjects with the best tumor treatment response rates considering CR and PR. We defined the disease control rate (DCR) as the proportion of subjects with the best tumor treatment response rates considering CR, PR, and SD.

Statistical analyses

In continuous parameters, we performed ROC curve analysis of survival (OS and PFS) for selection of the optimal cutoff value that is associated with maximal total value of specificity and sensitivity and we classified them into two groups using these cutoff points and treated them as categorical covariates. Kaplan-Meier curves were created and compared by using the log-rank test. Parameters with P value less than 0.05 in the univariate analysis were entered into the multivariate analyses (Cox proportional hazard model). Furthermore, we analyzed time-dependent ROC curves of significant predictors for survival (continuous variables) in the multivariate analysis and compared between AUROCs for these parameters in each time point. 22 We also calculated the Total sum of AUROCs in All Time-points (defined as TAAT score) in each continuous parameter. TAAT scores in significant continuous parameters in the multivariate analysis were also compared. In this analysis, we regarded a covariate with higher TAAT score as a covariate with higher predictive power. OS was defined as the period from the start of sorafenib therapy until death (due to any cause) or the last follow-up visit. PFS was defined as the period from the start of sorafenib therapy until the date of the confirmation of progression-free disease or death (due to any cause). 23, 24 Data were presented as number or median values (range). A P value <0.05 was considered statistically significant. All statistical analyses were performed using the JMP 11 software (SAS Institute Inc., Cary, NC).

Results

Baseline characteristics

The baseline characteristics of analyzed patients (n=225) are presented in Table 1. They included 175 male and 50 female patients with a median age of 72 years (range, 40-91 years). In terms of cause of liver disease, hepatitis C virus (HCV) was in the majority. They included 158 patients with Child-Pugh class A and 67 patients with Child-Pugh class B. In 64 (28.4%) patients, the standard dose of sorafenib (800 mg/day) was administered at the start of the therapy and 191 patients (84.9%) had ECOG-PS 0. The most common previous therapies for HCC included the transcatheter arterial therapies such as TACE or TAI, followed by percutaneous ablative therapies, and surgical resection (SR). As for HCC stage, they included stage I in 1, stage II in 17, stage III in 78, stage IVA in 44 and stage IVB in 85, respectively.
Table 1

Baseline characteristics (n=225).

VariablesNumber ormedian value (range)
Age (years)72 (40-91)
Gender, male / female175 / 50
Body mass index (kg/m2)21.615 (14.539-42.192)
Causes of liver disease
B / C / non-B and non-C / B and C32 / 141 / 48 / 4
Initial dose of sorafenib (mg/day),800 / 600 / 400 / 20064 / 1 / 157 / 3
Child-Pugh classification, A / B158 / 67
ECOG-performance status
0 / 1 / 2191 / 29 / 5
HCC stage, I / II / III / IVA / IVB1 / 17 / 78 / 44 / 85
Previous therapies for HCC
Transcatheter arterial therapies, yes / no204 / 21
Percutaneous ablative therapies, yes / no127 / 98
Surgical resection, yes / no73 / 152
Tumor burden ≥50%, yes / no22 / 203
Total bilirubin (mg/dL)0.8 (0.2-5.1)
Serum albumin (g/dL)3.4 (1.7-4.8)
Prothrombin time (%)79.05 (48-116)
Platelet count (×104/mm3)11.6 (3.4-56.7)
AST (IU/L)51 (15-791)
ALT (IU/L)34 (6-380)
ALP (IU/L)403 (124-4535)
GGT (IU/L)72 (14-2172)
AFP (ng/mL)141.4 (1.7-688400)
DCP (mAU/mL)748 (10-421210)

Data are expressed as number or median (range). ECOG; the Eastern Cooperative Oncology Group, HCC; hepatocellular carcinoma, AST; aspartate aminotransferase, ALT; alanine aminotransferase, ALP; alkaline phosphatase, GGT; gamma glutamyl transpeptidase, AFP; alpha-fetoprotein, DCP; des-γ-carboxy prothrombin.

OS and PFS in the entire cohort

The median follow-up period in this study was 0.62 years (0.03-5.58 years). The median OS time was 0.68 years, while the median PFS time was 0.24 years. (Fig. 1A and 1B).
Figure 1

(A) Cumulative overall survival rate for the entire cohort. The median OS time was 0.68 years. (B) Cumulative progression free survival rate for the entire cohort. The median PFS time was 0.24 years. (C) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for all cases (n=225).

Treatment duration, best treatment response, serious adverse events and causes of death

The median (range) treatment duration was 0.20 years (0.01-2.94 years). In the analysis of the best tumor response, CR was achieved in 4, PR in 13, SD in 64, and PD in 88, while 56 were not evaluated (NE); the ORR and DCR were thus calculated to be 7.6% (17/225) and 36.0% (81/225), respectively. Serious adverse events of grade 3 or more as defined by Common Terminology Criteria for Adverse Events (CTCAE) ver. 3.0 were observed in 87 cases (38.7%). During the follow-up period, 193 (85.8%) patients died: 165 due to HCC progression, 7 due to liver failure, and 21 due to other causes.

Univariate and multivariate analyses of parameters contributing to OS

The univariate analysis identified that the following variables significantly contributed to OS for all cases (n=225): gender (P=0.0121); BMI ≥21.94 kg/m2 (P=0.0053); initial dose of sorafenib (P=0.0253); ECOG-PS (P=0.0048); Child-Pugh classification (P<0.0001); extrahepatic metastases (P=0.0050); portal vein invasion (P=0.0417); tumor burden ≥50% (P=0.0002); AST ≥24 IU/l (P=0.0141); ALP ≥299 IU/l (P=0.0368); GGT ≥197 IU/l (P=0.0305); AFP ≥456.5 ng/ml (P=0.0002); and DCP ≥170 mAU/ml (P=0.0004) (Table 2). The odds ratios (ORs) and 95% confidence intervals (CIs) as determined by multivariate analysis for the 13 variables (selected based on a P value <0.05 in univariate analysis) are listed in table 2. On multivariate analysis, gender (P=0.0024), BMI ≥21.94 kg/m2 (P=0.0035), Child-Pugh classification (P=0.0020), extrahepatic metastases (P=0.0007), tumor burden ≥50% (P=0.0003), AST ≥29 IU/l (P=0.0134) and AFP ≥456.5 ng/ml (P=0.0008) were identified as significant predictors of OS.
Table 2

Univariate and multivariate analyses of factors contributing to overall survival.

VariablesnUnivariateanalysisMultivariate analysis
Odds ratio (95% CI)P valuea
Gender, male vs. female175 / 500.01211.885 (1.245-2.919)0.0024
Age (years), ≥67 vs. <67165 / 600.1671
BMI (kg/m2), <21.94 vs. ≥21.94120 /1050.00531.563 (1.157-2.105)0.0035
Initial dose of sorafenib, 800 mg/day / reduced dose of sorafenib64 / 1610.02531.257 (0.904-1.770)0.1766
ECOG-PS 0, yes / no191 / 340.00480.784 (0.528-1.197)0.2517
Child-Pugh classification, A / B158 / 67<0.00010.581 (0.417-0.817)0.0020
Extrahepatic metastases, yes / no85 / 1400.00501.742 (1.267-2.387)0.0007
Portal vein invasion, yes / no50 / 1750.04171.313 (0.905-1.873)0.1480
Tumor burden ≥50%, yes / no22 / 2030.00022.841 (1.647-4.698)0.0003
AST (IU/l), ≥29 vs. <29191 / 340.01411.778 (1.122-2.947)0.0134
ALT (IU/l), ≥54 vs. <5451 / 1740.6531
ALP (IU/l), ≥299 vs. <299174 / 510.03681.015 (0.698-1.507)0.9409
GGT (IU/l), ≥197 vs. <19740 / 1850.03051.203 (0.696-1.534)0.9110
Platelet count (×104 / mm3), ≥16.7 vs. <16.759 / 1660.1057
Serum AFP (ng/ml), ≥456.5 vs. <456.588 / 1370.00021.758 (1.269-2.424)0.0008
DCP (mAU/ml), ≥170 vs. <170158 / 670.00041.098 (0.769-1.587)0.6109

CI; confidence interval, BMI; body mass index, ECOG-PS; the Eastern Cooperative Oncology Group performance status, AST; aspartate aminotransferase, ALT; alanine aminotransferase, ALP; alkaline phosphatase, GGT; gamma glutamyl transpeptidase, AFP, alpha-fetoprotein; DCP, des-γ-carboxy prothrombin, a; Cox proportional hazard model.

Univariate and multivariate analyses of factors contributing to PFS

The univariate analysis identified that the following variables significantly contributed to PFS for all cases (n=225): ECOG-PS (P=0.0023); Child-Pugh classification (P=0.0297); extrahepatic metastases (P=0.0027); portal vein invasion (P=0.0313); and tumor burden ≥50% (P=0.0380). The ORs and 95% CIs determined by multivariate analysis for the 5 variables (selected based on a P value <0.05 in univariate analysis) are detailed in table 3. On multivariate analysis, ECOG-PS (P=0.0188), Child-Pugh classification (P=0.0429) and extrahepatic metastases (P=0.0014) were identified as significant predictors of PFS. There were no significant continuous variables linked to PFS in this multivariate analysis. Thus, we did not perform time-dependent ROC analysis of PFS.
Table 3

Univariate and multivariate analyses of factors contributing to progression free survival.

VariablesnUnivariateanalysisMultivariate analysis
Odds ratio (95% CI)P valuea
Gender, male vs. female175 / 500.3035
Age (years), ≥60 vs. <60196 / 290.0878
BMI (kg/m2), ≥22.05 vs. <22.05101 /1240.9923
Initial dose of sorafenib, 800 mg/day / reduced dose of sorafenib64 / 1610.1030
ECOG-PS 0, yes / no191 / 340.00230.614 (0.424-0.919)0.0188
Child-Pugh classification, A / B158 / 670.02970.725 (0.536-0.990)0.0429
Extrahepatic metastases, yes / no85 / 1400.00271.611 (1.206-2.141)0.0014
Portal vein invasion, yes / no50 / 1750.03131.330 (0.939-1.854)0.1067
Tumor burden ≥50%, yes / no22 / 2030.03801.493 (0.921-2.303)0.1004
AST (IU/l), ≥28 vs. <28198 / 270.4771
ALT (IU/l), ≥19 vs. <19194 / 310.5663
ALP (IU/l), ≥1045 vs. <104515 / 2100.2215
GGT (IU/l), ≥310 vs. <31023 / 2020.7722
Platelet count (×104 / mm3), ≥14.4 vs. <14.482 / 1430.0756
Serum AFP (ng/ml), ≥17.5 vs. <17.5164 / 610.3883
DCP (mAU/ml), ≥3360 vs. <336074 / 1510.1945

CI; confidence interval, BMI; body mass index, ECOG-PS; the Eastern Cooperative Oncology Group performance status, AST; aspartate aminotransferase, ALT; alanine aminotransferase, ALP; alkaline phosphatase, GGT; gamma glutamyl transpeptidase, AFP, alpha-fetoprotein; DCP, des-γ-carboxy prothrombin, a; Cox proportional hazard model.

Time-dependent ROC analysis of BMI, AFP and AST values for OS in the entire cohort

Plots of AUROCs (at 6-month, 1-year and 2-year) of BMI, AFP and AST for OS in the entire cohort are shown in table 4 and fig. 1C. BMI, AFP and AST are significant continuous parameters in our multivariate analysis for OS. The AUROCs at 6-month, 1- and 2-year were 0.55693, 0.53517 and 0.63980, respectively, in BMI, 0.63766, 0.64577 and 0.67266, respectively, in AFP and 0.62600, 0.58252 and 0.50846, respectively, in AST. The TAAT score in AFP was the highest among three continuous parameters (TAAT score=1.95609).
Table 4

Time-dependent ROC analysis among three continuous parameters that were significant in the multivariate analysis.

All cases (n=225)6-month1-year2-yearTAAT score
BMI0.556930.535170.639801.73190
AFP0.637660.645770.672661.95609
AST0.626000.582520.508461.71698
Child-Pugh A (n=158)6-month1-year2-yearTAAT score
BMI0.577970.553420.624101.75549
AFP0.599430.632830.670801.90306
AST0.573230.587000.536821.69705
Child-Pugh B (n=67)6-month1-year2-yearTAAT score
BMI0.450090.536760.766081.75293
AFP0.656080.599670.532161.78791
AST0.685120.485290.818711.98912
ECOG-PS 0 (n=191)6-month1-year2-yearTAAT score
BMI0.530840.491660.613761.63626
AFP0.579880.635350.652921.86815
AST0.633760.574690.506391.71484
ECOG-PS 1 or 2 (n=34)6-month1-year2-yearTAAT score
BMI0.609020.653850.793102.05597
AFP0.853380.648350.758622.26035
AST0.685120.485290.818711.98912
Tumor burden <50% (n=203)6-month1-year2-yearTAAT score
BMI0.551160.542750.645801.73971
AFP0.633870.643250.680371.95749
AST0.564430.552670.530421.64752
Extrahepatic metastasis, yes (n=85)6-month1-year2-yearTAAT score
BMI0.563160.491530.474181.52887
AFP0.676850.649720.704232.03080
AST0.376620.420900.544601.34212
Extrahepatic metastasis, no (n=140)6-month1-year2-yearTAAT score
BMI0.556290.548640.680671.78560
AFP0.607690.639060.655231.90198
AST0.644320.600340.537821.78248
Portal vein invasion, yes (n=50)6-month1-year2-yearTAAT score
BMI0.613760.688910.812202.11487
AFP0.691360.676470.829272.19710
AST0.625220.530540.551221.70698
Portal vein invasion, no (n=175)6-month1-year2-yearTAAT score
BMI0.487930.507150.588501.58358
AFP0.642550.633560.624311.90042
AST0.620060.597240.502071.71937
Male (n=175)6-month1-year2-yearTAAT score
BMI0.591700.543340.599031.73407
AFP0.656390.676300.813802.14649
AST0.625530.570370.519681.71558
Female (n=50)6-month1-year2-yearTAAT score
BMI0.582250.500000.717651.79990
AFP0.597400.548080.525091.67057
AST0.575760.627140.458821.66172

ECOG-PS; the Eastern Cooperative Oncology Group performance status, BMI; body mass index, AFP; alpha-fetoprotein, AST; aspartate aminotransferase. TAAT score indicates Total sum of AUROCs in All Time-points.

Time-dependent ROC analysis of BMI, AFP and AST values for OS according to Child-Pugh classification

In patients with Child-Pugh A (n=158), the TAAT score in AFP (1.90306) was the highest, followed by that in BMI (1.75549). (Fig. 2A) In patients with Child-Pugh B (n=67), the TAAT score in AST (1.98912) was the highest, followed by that in AFP (1.78791). (Fig. 2B)
Figure 2

(A and B) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for patients with Child-Pugh A (2A, n=158) and Child-Pugh B (2B, n=67). (C and D) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for patients with ECOG-PS 0 (2C, n=191) and ECOG-PS 1 or 2 (2D, n=34).

Time-dependent ROC analysis of BMI, AFP and AST values for OS according to ECOG-PS

In patients with ECOG-PS 0 (n=191), the TAAT score in AFP (1.86815) was the highest, followed by that in AST (1.71484). (Fig. 2C) In patients with ECOG-PS 1 or 2 (n=34), the TAAT score in AFP (2.26035) was the highest, followed by that in BMI (2.05597). (Fig. 2D)

Time-dependent ROC analysis of BMI, AFP and AST values for OS according to the tumor status (extrahepatic metastasis, tumor burden or portal vein invasion)

In patients with extrahepatic metastasis (n=85), the TAAT score in AFP (2.03080) was the highest, followed by that in BMI (1.52887). (Fig. 3A) In patients without extrahepatic metastasis (n=140), the TAAT score in AFP (1.90198) was the highest, followed by that in BMI (1.78560). (Fig. 3B). In patients with tumor burden <50% (n=203), the TAAT score in AFP (1.95749) was the highest, followed by that in BMI (1.73971). (Fig. 3C) Due to the small number of cases in patients with tumor burden ≥50% (n=22), we did not perform time-dependent ROC analysis in this cohort. In patients with portal vein invasion (n=50), the TAAT score in AFP (2.19710) was the highest, followed by that in BMI (1.52887). (Fig. 4A) In patients without portal vein invasion (n=175), the TAAT score in AFP (1.90042) was the highest, followed by that in AST (1.71937). (Fig. 4B).
Figure 3

(A and B) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for patients with extrahepatic metastases (3A, n=85) and without extrahepatic metastases (3B, n=140). (C) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for patients with tumor burden <50% (3C, n=203).

Figure 4

(A and B) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for patients with portal vein invasion (4A, n=50) and without portal vein invasion (4B, n=175). (C and D) Plots of AUROCs at 6-month, 1-year and 2-year in BMI, AFP and AST values for male patients (4C, n=175) and female patients (4D, n=50).

Time-dependent ROC analysis of BMI, AFP and AST values for OS according to gender

In male patients (n=175), the TAAT score in AFP (2.14649) was the highest, followed by that in BMI (1.73407). (Fig. 4C) In female patients (n=50), the TAAT score in BMI (1.79990) was the highest, followed by that in AFP (1.67057). (Fig. 4D)

Discussion

To the best of our knowledge, there have been no reports with regard to prognostic investigation for HCC patients receiving sorafenib therapy using time-dependent ROC analysis. As mentioned earlier, it should be highlighted that most clinical continuous parameters are time-dependent. Investigation using time-dependent ROC analysis is clinically beneficial. We therefore conducted this current analysis. The major advantage of this study is the large number of enrolled subjects. Our proposed TAAT scoring system is the novel scoring system. As demonstrated in our figures, lines with plots of AUROCs in continuous parameters tended to be crossed. We therefore adopted this scoring system for assessing the predictive ability of outcomes. The shorter median OS time in this study (0.68 years) compared with the previous report can be explained by the higher proportion of Child-Pugh B patients in our data (29.8% [67/225]). 8 In our time-dependent ROC analyses, AFP had the highest TAAT score among three continuous parameters and in many of sub-group analyses, similar trends were confirmed. These results indicate that in continuous variables, AFP had the highest predictive ability for survival in HCC patients undergoing sorafenib therapy. Because AFP is a well verified predictive factor in HCC patients receiving sorafenib therapy, it is not so surprising to obtain current results. 12-21 However, these have not been confirmed using time-dependent analysis. In this regard, we believe that our current results are worth reporting. On the other hand, in terms of ORs in BMI, AST and AFP, AST had the highest OR (1.778) for OS. However, the TAAT score of AFP was the highest for the entire cohort. The effect of continuous variables on clinical outcome should not be determined based on OR alone. It is also of note that the TAAT score of AFP was the highest among three significant continuous parameters irrespective of tumor status (extrahepatic metastasis or portal vein invasion). These results may shed some lights on the sorafenib therapy in HCC. Lower BMI was an adverse predictor in our results. Previous studies demonstrated that higher BMI was an adverse predictor in HCC patients undergoing TACE, while it was a favorable predictor in HCC patients undergoing SR. 29, 30 On the other hand, in our previous studies, BMI itself did not affect prognosis in HCV-related or non-B and non-C HCC patients undergoing SR. 31, 32 Thus, whether BMI can affect prognosis in HCC patients remains unclear. However, higher prevalence of poorer ECOG-PS (PS ≥1) in patients with BMI <21.94 kg/m2 (19.17%, [23/120]) as compared with that in patients with BMI ≥21.94 kg/m2 (10.48%, [11/105]) may explain our current results. In our data, female patients had significantly longer OS time than male patients and it revealed to be significant in the multivariate analysis in terms of OS. Our previous study demonstrated that female gender was an independent predictor of good response to sorafenib. 23 This may be associated with our current results. We acknowledge several limitations of the present study. Firstly, this is a retrospective observational study. Secondly, the initial dose of sorafenib differed between the patients and the duration of sorafenib administration in this study is relatively short, creating bias. Thirdly, various anticancer therapies were employed after the cessation of sorafenib therapy, and these therapies could have potentially caused bias in the clinical outcomes of the analyzed subjects. Fourthly, our study population only included Japanese patients with relatively low body weights compared to patients in Western countries: whether our results can be applied to HCC patients with different patient backgrounds remains unknown. Fifthly, the data of period from initial HCC diagnosis until death are missing, also creating bias. Finally, our proposed TAAT scoring system is not a well-established statistical method and it should be fully verified in the future. However, in this study, AFP value was confirmed to be a highly useful predictor in HCC patients receiving sorafenib therapy using time-dependent ROC analysis. In conclusion, we examined prognostic parameters in HCC patients treated with sorafenib using time-dependent ROC analysis. Among continuous variables, AFP could have the highest predictive ability for survival.
  32 in total

1.  Efficacy and safety of sorafenib in patients with advanced hepatocellular carcinoma: subanalyses of a phase III trial.

Authors:  Jordi Bruix; Jean-Luc Raoul; Morris Sherman; Vincenzo Mazzaferro; Luigi Bolondi; Antonio Craxi; Peter R Galle; Armando Santoro; Michel Beaugrand; Angelo Sangiovanni; Camillo Porta; Guido Gerken; Jorge A Marrero; Andrea Nadel; Michael Shan; Marius Moscovici; Dimitris Voliotis; Josep M Llovet
Journal:  J Hepatol       Date:  2012-06-19       Impact factor: 25.083

Review 2.  Transarterial chemoembolization failure/refractoriness: JSH-LCSGJ criteria 2014 update.

Authors:  Masatoshi Kudo; Osamu Matsui; Namiki Izumi; Masumi Kadoya; Takuji Okusaka; Shiro Miyayama; Koichiro Yamakado; Kaoru Tsuchiya; Kazuomi Ueshima; Atsushi Hiraoka; Masafumi Ikeda; Sadahisa Ogasawara; Tatsuya Yamashita; Tetsuya Minami
Journal:  Oncology       Date:  2014-11-22       Impact factor: 2.935

3.  Liver function assessment according to the Albumin-Bilirubin (ALBI) grade in sorafenib-treated patients with advanced hepatocellular carcinoma.

Authors:  Sadahisa Ogasawara; Tetsuhiro Chiba; Yoshihiko Ooka; Eiichiro Suzuki; Naoya Kanogawa; Tomoko Saito; Tenyu Motoyama; Akinobu Tawada; Fumihiko Kanai; Osamu Yokosuka
Journal:  Invest New Drugs       Date:  2015-10-14       Impact factor: 3.850

4.  Effect of body mass index on survival after curative therapy for non-B non-C hepatocellular carcinoma.

Authors:  Hiroki Nishikawa; Yukio Osaki; Haruhiko Takeda; Azusa Sakamoto; Sumio Saito; Norihiro Nishijima; Akihiro Nasu; Akira Arimoto; Ryuichi Kita; Toru Kimura
Journal:  J Gastrointestin Liver Dis       Date:  2013-06       Impact factor: 2.008

Review 5.  Modified RECIST (mRECIST) assessment for hepatocellular carcinoma.

Authors:  Riccardo Lencioni; Josep M Llovet
Journal:  Semin Liver Dis       Date:  2010-02-19       Impact factor: 6.115

Review 6.  Evidence-Based Diagnosis, Staging, and Treatment of Patients With Hepatocellular Carcinoma.

Authors:  Jordi Bruix; Maria Reig; Morris Sherman
Journal:  Gastroenterology       Date:  2016-01-12       Impact factor: 22.682

7.  Clinical features associated with radiological response to sorafenib in unresectable hepatocellular carcinoma: a large multicenter study in Japan.

Authors:  Haruhiko Takeda; Hiroki Nishikawa; Yukio Osaki; Kaoru Tsuchiya; Kouji Joko; Chikara Ogawa; Hiroyoshi Taniguchi; Etsuro Orito; Yasushi Uchida; Namiki Izumi
Journal:  Liver Int       Date:  2014-06-10       Impact factor: 5.828

8.  Sorafenib treatment in Child-Pugh A and B patients with advanced hepatocellular carcinoma: safety, efficacy and prognostic factors.

Authors:  Sadahisa Ogasawara; Tetsuhiro Chiba; Yoshihiko Ooka; Naoya Kanogawa; Tomoko Saito; Tenyu Motoyama; Eiichiro Suzuki; Akinobu Tawada; Fumihiko Kanai; Osamu Yokosuka
Journal:  Invest New Drugs       Date:  2015-04-12       Impact factor: 3.651

9.  Treatment for hepatocellular carcinoma in Japan over the last three decades: Our experience and published work review.

Authors:  Yukio Osaki; Hiroki Nishikawa
Journal:  Hepatol Res       Date:  2014-07-18       Impact factor: 4.288

10.  Safety and effectiveness of sorafenib in Japanese patients with hepatocellular carcinoma in daily medical practice: interim analysis of a prospective postmarketing all-patient surveillance study.

Authors:  Shuichi Kaneko; Kenji Ikeda; Yasushi Matsuzaki; Junji Furuse; Hironobu Minami; Yutaka Okayama; Toshiyuki Sunaya; Yuichiro Ito; Lyo Inuyama; Kiwamu Okita
Journal:  J Gastroenterol       Date:  2016-03-01       Impact factor: 7.527

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  1 in total

1.  Impact of baseline characteristics on outcomes of advanced HCC patients treated with sorafenib: a secondary analysis of a phase III study.

Authors:  Omar Abdel-Rahman
Journal:  J Cancer Res Clin Oncol       Date:  2018-02-17       Impact factor: 4.322

  1 in total

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