Scoring System Based on Tumor Markers and Child-Pugh Classification for HCC Patients who Underwent Liver Resection

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1 Scoring System Based on Tumor Markers and Child-Pugh Classification for HCC Patients who Underwent Liver Resection SHIGEKI NAKAGAWA 1, HIROMITSU HAYASHI 1, HIDETOSHI NITTA 1, HIROHISA OKABE 1, KEITA SAKAMOTO 1, TAKAAKI HIGASHI 1, HIDEYUKI KUROKI 1, KATSUNORI IMAI 1, DAISUKE HASHIMOTO 1, YASUO SAKAMOTO 1,2, AKIRA CHIKAMOTO 1, TORU BEPPU 1,2 and HIDEO BABA 1 1 Department of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Kumamoto, Japan; 2 Department of Multidisciplinary Treatment for Gastroenterological Cancer, Kumamoto University Hospital, Kumamoto, Japan Abstract. Background: The long-term prognosis of hepatocellular carcinoma (HCC) patients after hepatic resection (HR) remains poor because of limited liver function and frequent recurrences. We created a prognostic system of HCC based on tumor markers and Child-Pugh classification. Patients and Methods: This study investigated 427 HCC patients and three tumor markers (alphafetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3), des-γ -carboxyprothrombin (DCP)) in relation to Child-Pugh classification by the stepwise Cox regression model for establishing a tumor marker staging (TMS). Results: The TMS shows four levels (0/1/2/3) with 5-year recurrence rate of each stage of 76.7, 72.3, 80.9 and 100%, respectively, and 5-year overall survival of 77.0, 68.7, 52.1 and 28.9%, respectively. This TMS appears to be a better model to predict the recurrence and survival of HCC patients after hepatectomy than only the number of positive tumor markers. Conclusion: TMS is a useful staging system to evaluate biological status and background liver function. Hepatocellular carcinoma (HCC) is a common malignancy worldwide, especially in Asian countries with an increasing incidence in Western countries (1, 2). Development of devices for diagnosis, such as computed tomography (CT), Correspondence to: Professor Hideo Baba, MD, Ph.D., Department of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Honjo, Kumamoto , Japan. Tel: , Fax: , hdobaba@ kumamoto-u.ac.jp Key Words: Hepatocellular carcinoma (HCC), alpha-fetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3), des-γ-carboxyprothrombin (DCP), tumor marker. angiography, vascular imaging, ultrasonography and magnetic resonance imaging (MRI) enables for detection of early stages of HCC. The development of therapeutic modalities, including liver transplantation, hepatic resection, trans-arterial chemoembolization and localized ablation therapy has improved the prognosis of HCC patients (3-5). Nevertheless, short- and long-term prognoses remain a difficult task to accomplish. For the diagnosis of HCC, three tumor markers, alphafetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) and des-γ-carboxyprothrombin (DCP), are usually being examined in addition to the diagnostic imaging. These tumor markers are useful tools not only for the diagnosis but also for the evaluation of the the malignant potential of HCC and prediction of prognosis (6-10). Recently, the examination of all three tumor markers was proven useful in predicting the prognosis of curativelyresected HCC (11-13). To predict the prognosis of HCC patients, the tumor-nodemetastasis (TMN) staging, which proposed by the International Union against Cancer (UICC) (14) or the Liver Cancer Study Group of Japan are being followed. However, new staging systems that combined tumor malignancy and liver function, such as the Cancer of the Liver Italian Program (CLIP) (15, 16) and Japan Integrated Staging (JIS) (17) system, have been created and clarified the usefulness to predict the prognosis of HCC patients. Not only tumor factors, such as TNM staging and tumor markers, but also liver function is also important to define the prognosis (18) in HCC patients as HCC may occur from cirrhotic liver or liver with inflammation. Thus, in the present study, we attempted to predict HCC prognosis by combining both liver function and expression of tumor markers. This approach involved the combination of the Child-Pugh score as liver function and the number of tumor markers expressed in HCC as tumor malignancy /2015 $

2 Table I. Patients background and clinicopathological findings of the study. Variable n=427 Sex (Male/Female) 350/77 Age 67 (30-83) Etiology (HBV/HCV/NBNC/HBV+HCV) 109/195/113/10 Child-Pugh Classification (A/B) 353/74 Albumin 3.9 ( ) Total bilirubin 0.8 ( ) Prothrombin activity 91 ( ) PLT( 10 4 /mm 3 ) 14.0 ( ) ICG R15 (%) 12.7 ( ) Number of tumors; median (range) 1 (1-9) Single/Multiple 274/153 Tumor size (cm) 3.5 (1.0-20) Macroscopic vascular invasion (-/+) 372/55 Microscopic vascular invasion (-/+) 206/221 Differentiation (well-mod/include poor) 327/100 Growth pattern (expansive/infiltrative) 286/41 AFP (ng/ml); median (range) 16.4 ( ) 20 ng/ml/<20 ng/ml 206/221 AFP-L3 (%); median (range) 0.5 ( ) 10 %/<10 % 117/310 DCP (mau/ml); median (range) 80 ( ) 40 mau/ml/<40 mau/ml 268/159 Liver resection (Anatomical/Non-anatomical) 279/148 Treatment for HCC (initial/non-initial) 119/308 HBV, Hepatitis B virus; HCV, hepatitis C virus; NBNC, non-b non-c; PLT, platelet count; ICG R15, Indocyanine Green Retention rate at 15 min; AFP; alpha-fetoprotein; AFP-L3, Lens culinaris agglutinin-reactive fraction of AFP; DCP, des-γ -carboxyprothrombin. Patients and Methods Patients and diagnosis. The study population consisted of 427 HCC patients who underwent curative hepatic resection at the Department of Gastroenterological Surgery, Kumamoto University Hospital, between January 2001 and May The patients underwent imaging studies, such as ultrasonography, dynamic CT and enhanced MRI, as well as CT angiography for diagnosis and staging of HCC before surgery. The final diagnosis was confirmed pathologically in the resected specimens. The severity of liver disease (liver fibrosis staging and hepatitis activity grading) was also evaluated according to the criteria proposed by the Inuyama classification (19). This was a retrospective, non-interventional, observational study, approved by the institutional ethics committee of Kumamoto University Hospital and performed in accordance with the Helsinki Declaration of Written informed consent was obtained from all patients. Measurement of hepatocellular carcinoma tumor markers. AFP, AFP-L3 and DCP were measured immediately before hepatic resection. The serum AFP level was determined by a chemiluminescent enzyme immunoassay (Siemens Immulite AFP IV; Mitsubishi Chemical Medience, Tokyo, Japan) and the serum AFP-L3 level was expressed as a percentage of the total AFP (AFP- L3/ total AFP 100) by lectin affinity electrophoresis coupled with antibody-affinity blotting (AFP-L3 Test Wako; Wako Pure Chemical Industries Ltd., Osaka, Japan). Serum DCP was determined by a chemiluminescent enzyme immuno assay (Lumipulse PIVKA-II Eisai; Eisai, Tokyo, Japan). The upper limits of the normal range of AFP, AFPL3 and DCP in our institution were 20 ng/ml, 10 % and 40 mau/ml, respectively. Tumor markers higher than the upper limit of the normal range were defined as positive. Treatment and surveillance. The surgical procedure was selected based on the tumor location, extent of the tumor, parenchymal liver function and the patients' general condition. Hepatic resection (HR) was considered as the first choice treatment for patients with good liver functional reserve (20). If the liver function allowed, anatomical resection was employed. The reasons for undergoing radiofrequency risk associated with general condition and refusal of HR. The follow-up program included AFP, AFP-L3 and DCP assays every 1-2 months, as well as ultrasonography, dynamic CT or dynamic MRI every 3-4 months after surgery. When a recurrence of HCC was detected, patients received further treatment for HCC, such as repeated hepatectomy, ablation therapy or trans-arterial chemoembolization (TACE). After treatment for recurrent lesions, the same surveillance was continued. Table II. The weight of number of positive tumor markers and Child-Pugh score for predicting overall survival. Univariate analysis Multivariate analysis RR 95%CI p-value RR 95%CI p-value β-value Number of positive tumor markers ** ** < *** < *** Child-Pugh classification A 1 1 B RR, Relative risk; CI, confidence interval. * p<0.05, ** p<0.01, *** p<

3 Nakagawa et al: Staging Based on Tumor Marker and Child-Pugh Table III. Tumor marker staging classification. Parameter/score Number of positive tumor markers 0 1 or 2 3 Child-Pugh stage A B Statistical analysis. Dichotomous variables were compared using the χ 2 test, where as continuous variables were compared using t-tests. The univariate and multivariate analysis based on the Cox regression model was used to estimate risk factors related to recurrence-free survival (RFS) and overall survival (OS), continuous variables were converted into binary. All p values of <0.05 were considered to be significant. The stepwise Cox regression model was used to provide the coefficient for Child-Pugh classification and the number of tumor markers. All analyses were performed using the JMP program (SAS Institute, Cary, NC, USA). Results Patients characteristics. Table I shows the patients background and clinicopathological characteristics of this study. Among the 427 patients, there were 350 men and 77 women ranging in age from years. More than three quarters (82.7%) of the patients belonged to Child-Pugh class A and 17.3% belonged to class B. The median values of serum AFP, AFP-L3 and DCP levels were 16.4 ng/ml, less than 0.5% and 80.0 mau/ml, respectively. Serum AFP, AFP-L3 and DCP levels over the upper limits of normal range were observed in 48.2% of the patients, 27.4% and 62.8%, respectively. Univariate analysis of the perioperative risk factors associated with recurrence rate and overall survival. The recurrence rates of all patients at 1, 3 and 5 years were 32.1, 60.3 and 77.0%, while the OS rates at 1, 3 and 5 years were 90.6, 72.0 and 64.8%. Multivariate analysis revealed that low serum albumin level (relative risk (RR)=1.49, p=0.0084), decreased platelet (PLT) count (RR=1.51, p=0.0086), multiple tumor (RR=1.93, p<0.0001) and tumor size >3.5cm (RR=1.55, p=0.0034) were the independent risk factors to predict high recurrence rate. Low serum albumin (RR=1.72, p=0.0163), multiple tumor (RR=1.62, p=0.0232) and tumor size >3.5cm (RR=2.28, p=0.0002) were the independent risk factors for poor OS by multivariate analysis. Coefficient weighting of tumor markers and Child-Pugh classification for predicting overall survival and newlyproposed prognostic scoring system; Tumor Marker Score (TMS) Stage. Table II shows the univariate and multivariate analysis of the number of tumor markers and Child-Pugh classification for OS and coefficient score (β value). The number of tumor markers and Child Pugh classification showed various scores that ranged from 0-2 of the Cox regression model, which is a rounded value based on 10 coefficients (Table III). Then, we added each score and classified HCC patients into four levels, thus establishing TMS stages 0 to 3. In each stage, recurrence rates at 1, 3 and 5 years were as follows: 14.9, 47.9 and 76.7% in TMS stage 0; 34.1, 58.7 and 72.3% in TMS stage 1; 39.9, 64.5 and 80.9% in TMS stage 2; and 63.9, 82.0 and 100% in TMS stage 3. OS in each stage was as follows: 99.7, 83.0 and 77.0% in TMS stage 0; 95.1, 76.5 and 68.7% in TMS stage 1; 79.6, 59.6 and 51.2% in TMS stage 2; and 53.9, 28.9 and 28.9% in TMS stage 3. The Kaplan-Meyer curves are shown in Figure 1. Comparison of scoring systems. The Kaplan-Meier survival curves for recurrence and OS by the TMS staging, number of tumor markers and CLIP scoring system are shown in Figures 1-3, respectively. The RRs for recurrence of TMS stage 0, 1, 2 and 3 are 1, 1.30, 1.92 and As shown in Table IVa, the RRs of only the number of tumor markers 0, 1, 2 and 3 are 1, 1.26, 2.53 and The RRs of CLIP 0 1, 2 and 3-5 are 1, 1.47, 2.51 and Of note about OS, as shown in Tabke IVb, the RR of CLIP 0. 1, 2, and 3-5 are 1, 2.53, 3.00 and The RR of only the number of tumor markers 0, 1, 2 and 3 are 1, 1.33, 2.27 and The RR for OS of TMS staging are 1, 1.41, 2.66 and Discussion AFP is the most widely used tumor marker for HCC and its high serum levels correlate with poor prognosis (21-28) and, as we have previously reported, the doubling time of preoperative AFP is a significant predictor for both DFS and OD (10). AFP-L3-positive status has been demonstra - ted to correlate with a large number of HCC tumors or those with a high malignant potential (7). A high level of serum DCP was reported to correlate with portal vein invasion and indicates a poor prognosis in HCC patients (25, 29). An elevated preoperative DCP has been demonstrated to be associated with a high recurrence rate after liver transplantation (30-32). However, the efficacies of preoperative levels of each tumor marker were not clear in the present study. Recently, the utility of the combined measurement of these three tumor markers (AFP, AFP-L3 and DCP) was demonstrated in predicting the outcome and recurrence for HCC patients treated with HR (11, 12). As we previously discussed (13), tumor markers evaluated before and after HR are used in these studies and examining their levels and postoperative levels seems imperative. However, predicting the patients prognosis before surgery is very important because we can choose the appropriate treatment modality based on the patient s own prognostic profile. Therefore, in this study, we attempted to predict prognosis by using only preoperative parameters. 2159

4 Table IVa. Comparison of the relative risk for recurrence of each classification. CLIP Number of tumor markers TMS Score RR p-value Number RR p-value Stage RR p-value * < *** * ** < *** ** * CLIP, Cancer of the liver Italian program; TMS, tumor marker staging; RR, relative risk. * p<0.05, ** p<0.01, *** p< Table IVb. Comparison of the relative risk for OS of each classification. CLIP Number of tumor markers TMS Score RR p-value Number RR p-value Stage RR p-value * *** ** *** < *** < *** < *** OS, Overall survival; CLIP, Cancer of the Liver Italian Program; TMS, tumor marker staging; RR, relative risk. * p<0.05, ** p<0.01, *** p< Figure 1. Recurrence rate and overall survival curves according to the TMS staging are shown. p-values and relative risk are shown in table IVa and b. Bruinx et al. reviewed that four main factors affect the prognosis of patients with HCC: (i) tumor characteristics, such as stage, aggressiveness and growth rate of the tumor; (ii) general health; (iii) liver function; and (iv) specific intervention. We considered the number of positive tumor markers as tumor characteristics and the Child-Pugh score as a liver function status. The staging system to estimate the patients prognosis is simple and based on factors that are easy to collect and should be constant between each participating institution. The herein presented TMS system can be calculated only from laboratory data and patient interview without any means of diagnostic imaging. The TMS system is also based on the cutoff line as a standard value and, therefore, it is universally useful if the measuring procedure is different between each institute even if cut-off values were different between several hospitals. 2160

5 Nakagawa et al: Staging Based on Tumor Marker and Child-Pugh Figure 2. Recurrence rate and overall survival curves according to the number of positive tumor markers are shown. p-values and relative risk are shown in table IVa and b. Figure 3. Recurrence rate and overall survival curves according to the CLIP score are shown. p-values and relative risk are shown in table IVa and b. In the present study, we created a new tumor marker staging (TMS) system that combines the number of positive tumor markers, as well as the Child-Pugh classification and is compared with the number of positive tumor markers and CLIP scoring system. The CLIP score was organized by variables that are examined for the HCC diagnosis routinely and based on laboratory data, Child-Pugh classification and imaging studies. The TMS system shows a similar or better analysis power compared with the CILP score for predicting RFS and OS of HCC patients after HR, even though TMS does not contain any imaging evaluation. Compared with the number of tumor markers only, TMS also exhibited better analysis power. However, it is clinically necessary to evaluate imaging findings for an in-depth look at diagnosis for decision-making on treatment for HCC patients, especially in the planning of surgical resection. Useful ways for further classification, in addition to imaging findings, include TMN, Okuda, BCLC and JIS staging (17, 33, 34). These staging systems favor prediction of prognosis of HCC patients with or without surgery and, in fact, many reports have shown their usefulness and the availability of other systems as well (17, 33-37). However, there exist some points to be improved as these systems do not include the measurement of biological factors, such as tumor markers. Sometimes, however, imaging findings do not reflect the gravity of the malignancy. It has been reported that it is difficult to 2161

6 diagnose small intrahepatic metastasis or microscopic portal vein invasion correctly by imaging features alone, especially when the tumors are small (29, 38). A few papers have confirmed that tumor markers are useful to predict the pathological malignancy of the HCC tumor, such as micro - vascular invasion or poor differentiation (11, 13). In order to evaluate tumor malignancy, including intrahepatic metastasis or microvascular invasion, it appears better to evaluate the positivity of tumor markers in addition to the staging systems based on imaging findings. In the present study, we showed that the TMS system was useful to predict the RFS and OS of HCC patients who underwent curative surgery. Its effectiveness should be validated in relation with the other staging systems currently employed and based on diagnostic imaging findings. References 1 Shaw JJ and Shah SA: Rising incidence and demographics of hepatocellular carcinoma in the USA: what does it mean? 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