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A Novel Prognostic Nomogram Is More Accurate than Conventional Staging Systems for Predicting Survival after Resection of Hepatocellular Carcinoma
A Novel Prognostic Nomogram Is More Accurate than Conventional Staging Systems for Predicting Survival after Resection of Hepatocellular Carcinoma Clifford S Cho, MD, Mithat Gonen, PhD, Jinru Shia, MD, Michael W Kattan, PhD, David S Klimstra, MD, William R Jarnagin, MD, FACS, Michael I D’Angelica, MD, Leslie H Blumgart, MD, FACS, Ronald P DeMatteo, MD, FACS Prediction of survival after resection of hepatocellular carcinoma (HCC) remains difficult. Numerous staging systems have been devised for purposes of risk classification; we sought to identify the optimal staging system to predict postoperative survival. STUDY DESIGN: One hundred eighty-four patients who underwent primary complete resection of HCC at our institution between 1989 and 2002 were classified according to 8 contemporary staging systems. The ability of these systems to predict relative survival for randomly selected pairs of patients was quantified using the Harrel’s concordance index. A novel prognostic nomogram was constructed using prognostically relevant variables. RESULTS: After a median followup of 46 months for surviving patients, the median overall survival was 38 months. The concordance indices for the existing staging systems ranged from 0.54 to 0.59. Only the 2002 American Joint Commission on Cancer system demonstrated a concordance index with a 95% confidence interval exceeding 0.5, indicating that the ability of conventional systems to predict relative survival of randomly selected pairs of patients was generally no better than chance. We developed a novel nomogram based on patient age, serum ␣-fetoprotein level, operative blood loss, resection margin status, tumor size, satellite lesions, and vascular invasion. The nomogram demonstrated a markedly superior concordance index of 0.74 (95% CI, 0.68 to 0.80). A separate nomogram for prediction of recurrence-free survival was also generated. CONCLUSIONS: Contemporary staging systems for HCC do not accurately predict postoperative outcomes. Our prognostic nomogram provides a mechanism for accurate prediction of survival and risk stratification and will require validation at other hepatobiliary centers. (J Am Coll Surg 2008;206: 281–291. © 2008 by the American College of Surgeons) BACKGROUND:
Hepatocellular carcinoma (HCC) remains a substantial world health problem; it is estimated that the incidence of HCC in the US will continue to increase in a dramatic fashion during the next several decades.1 This has motivated a great deal of interest in optimizing the management of this difficult disease. Unfortunately, development of a
rational treatment strategy for HCC is complicated by its geographic and biologic heterogeneity and the multitude of treatment options that are currently available. HCC often develops in a setting of chronic liver dysfunction, which can limit the applicability of invasive therapeutic modalities and increase the likelihood of tumor recurrence. Surgical resection in the form of partial hepatectomy has emerged as a mainstay of potentially curative therapy, but orthotopic liver transplantation, tumor ablation, and hepatic intraarterial therapies provide alternative options. In an attempt to stratify expected survival outcomes for HCC patients treated by partial hepatectomy, a number of staging systems have been developed. Unfortunately, their criteria vary greatly, and no single system has consistently emerged as the optimal predictor of postoperative survival. The objective of the present analysis was to validate and
Competing Interests Declared: None. Received June 13, 2007; Revised July 23, 2007; Accepted July 25, 2007. From the Hepatobiliary Service (Cho, Jarnagin, D’Angelica, Blumgart, De Matteo), Department of Epidemiology and Biostatistics (Gonen), and Department of Pathology (Shia, Klimstra), Memorial Sloan-Kettering Cancer Center, New York, NY; and Department of Quantitative Health Sciences, The Cleveland Clinic Foundation, Cleveland, OH (Kattan). Correspondence address: Clifford S Cho, MD, Department of Surgery, University of Wisconsin School of Medicine and Public Health, H4/724, 600 Highland Ave Madison, WI 53792-7375.
© 2008 by the American College of Surgeons Published by Elsevier Inc.
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Abbreviations and Acronyms
AFP AJCC CLIP HCC IHPBS
⫽ ⫽ ⫽ ⫽ ⫽
␣-fetoprotein American Joint Commission on Cancer Cancer of the Liver Italian Program hepatocellular carcinoma International Hepato-Pancreato-Biliary Association
compare some of the major HCC staging systems in use today. We drew on our experience with patients undergoing complete resection of HCC at our tertiary hepatobiliary referral center to compare the ability of these staging systems to predict survival after resection; in addition, we generated a novel predictive model for more accurate estimation of outcomes.
METHODS Relevant patient, operative, pathologic, and outcomes data were collected using a prospective, single-institution database of patients undergoing partial hepatectomy for HCC at Memorial Sloan-Kettering Cancer Center. We limited the data set to those patients undergoing resection between 1989 and 2002 to identify a contemporary cohort of patients with sufficient duration of postoperative followup. Patients undergoing repeat or noncurative resections were excluded from analysis. Repeat pathologic analysis was performed to confirm the histologic diagnosis of HCC; because of oncologic and staging discrepancies that have been described between fibrolamellar and nonfibrolamellar variants of HCC,2,3 patients with fibrolamellar HCC were excluded. Operative mortalities were not excluded from analysis. Medical records were reviewed to obtain followup information about survival and recurrence status. Postoperative complications were graded on a 5-point system previously defined as follows: grade 1, complication requiring oral medical therapy or bedside care; grade 2, complication requiring intravenous medical therapy; grade 3, complication requiring operative or radiologic intervention; grade 4, complication resulting in unintended organ resection or chronic disability; grade 5, complication resulting in death.4 Clinicopathologic variables were used to stage patients according to eight major contemporary HCC staging systems. Survival outcomes were calculated using KaplanMeier methodology. The ability of a staging system to stratify postresection survival was quantified using Harrell’s concordance index.5 This construct represents the probability that, for each randomly generated pair of patients from a data set, the patient who lived longer was predicted to have had the favorable outcomes based on the staging system used. A staging system with a concordance index of
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1 would have predicted the correct outcomes in all patients; a concordance index of 0 would mean that the incorrect outcomes were predicted in all patients; a concordance index of 0.5 would imply that the system correctly predicted the outcomes 50% of the time (in essence having no predictive ability). Noninformative pairs (eg, pairs for whom survival was equal or in whom the survivor had a shorter followup interval) were not included in the calculation of the concordance index. Each of the clinicopathologic variables collected were subjected to univariate analysis using the log-rank test for categorical variables and Cox regression analysis for continuous variables. Methodology of nomogram construction using logistic regression and internal validation was identical to that used and published previously.6 A calibration curve was generated to depict the agreement between nomogram-predicted probability of survival at 3 years and observed probability of survival at 3 years based on KaplanMeier methodology. Comparison between the nomogram and conventional staging systems was performed by generating 2,000 bootstrap samples and computing concordance indices for each system. This generates an approximation of the sampling distribution of all pairwise differences between concordance indices. A p value for the significance of difference was determined by using the asymptotic significance level described previously.7 Nomograms for prediction of overall survival and recurrence-free survival were generated independently.
RESULTS Patient characteristics
After excluding those patients who did not meet inclusion criteria, we identified 184 patients who underwent complete primary resection of HCC from the prospective database. Mean age of the patients was 63 years (range 26 to 87 years), and 67% were men. Race distribution demonstrated that 61% were Caucasian, 28% were Asian, and 11% were of other backgrounds. Fifty-nine percent of patients presented with symptoms referable to their tumor burden. Although 35% of patients had histologic evidence of cirrhosis in the explanted specimens, the majority of patients presented with well-preserved hepatic function; 96% of patients had biochemical profiles consistent with Child-Turcotte-Pugh8 class A status, 4% had evidence of class B cirrhosis, and no patients had evidence of class C cirrhosis. The median Model for End-Stage Liver Disease score9 was 17 (range 6 to 82). For patients in whom an ␣-fetoprotein (AFP) level was documented preoperatively, median AFP was 43.8 ng/mL (range 1.2 to 422,000 ng/ mL) with 23% demonstrating AFP levels ⬎ 2,000 ng/mL.
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Treatment characteristics
Seven percent of patients underwent some form of preoperative neoadjuvant chemotherapy, and 3% underwent postoperative adjuvant chemotherapy. A majority (59%) required at least a hemihepatectomy. Median operative blood loss was 700 mL (range 50 to 8,500 mL). Forty-three percent of patients experienced at least 1 documented complication in the first 30 postoperative days. Ten percent of all patients had grade 1 complications, 20% had grade 2 complications, 9% had grade 3 complications, 1% had grade 4 complications, and 5% had grade 5 complications. The overall 60-day operative mortality rate was 5%. Pathologic characteristics
The median number of tumors identified on pathologic analysis was 1 (range 1 to 5), and the median size of the largest tumor was 9.5 cm (range 1.7 to 26 cm). Twenty-one percent of patients had a maximal tumor size ⱕ 5 cm; 49% were ⱖ 10 cm in maximal size. Only 38 patients (21%) had tumor characteristics that met the Milan HCC criteria for liver transplantation.10 Forty percent presented with bilobar disease (defined as single tumors involving both the right and left hemilivers or multiple tumors distributed in both hemilivers) and 29% had pathologic evidence of satellitosis. Sixty-one percent had evidence of microvascular invasion, and 3% had demonstrable nodal metastases (portal lymphadenectomy was not routinely performed in all patients). Histologic grade was defined as well differentiated in 20%, moderately differentiated in 56%, and poorly differentiated in 24%. The median margin of resection was 0.8 cm (range 0 to 5.5 cm) with an 8% rate of positive microscopic margins. Survival outcomes
After a median followup of 46 months for surviving patients, median overall survival was 38 months, and likelihood of 5-year overall survival was 38% (Fig. 1A). Median disease-specific survival was 54 months and likelihood of 5-year disease-specific survival was 47% (Fig. 1B). Median recurrence-free survival was 36 months with a likelihood of 5-year recurrence-free survival of 28% (Fig. 1C). American Joint Commission on Cancer 1997
Criteria for staging by the American Joint Commission on Cancer (AJCC) 1997 edition11 are shown in Figure 2A. When applied to our cohort of patients, we observed that 44.7% of patients were classified as stage IVA, because patients with multiple, bilobar tumors are defined as having stage IV disease. Because T1 tumors were defined as single tumors ⬍ 2 cm, with no evidence of microvascular invasion, only 1.8% of patients were categorized as having stage I disease. Kaplan-Meier analysis of overall survival
Figure 1. Kaplan-Meier estimates of survival. (A) Overall survival (OS); (B) disease-specific survival (DSS); (C) recurrence-free survival (RFS).
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Figure 2. Hepatocellular carcinoma staging systems. AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic Liver Cancer; CLIP, Cancer of the Liver Italian Program; IHPBA, International Hepato-Pancreato-Biliary Association; JIS, Japanese Integrated Staging.
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determined a statistically significant differentiation of survival curves by stage (p ⫽ 0.015); the concordance index was 0.57 (95% CI, 0.49 to 0.64). International Hepato-Pancreato-Biliary Association
When staged according to the simplified International Hepato-Pancreato-Biliary Association (IHPBA) staging system criteria12 (Figs. 2B, 3B), a preponderance of patients were classified as having stage II and III disease (36.4% and 50%, respectively). Because stage I disease was defined as single tumors ⬍ 2 cm in size with no vascular invasion, very few patients (1.6%) were classified as having stage I disease; the definition of stage IV disease as the presence of nodal or distant metastases resulted in a small number (9.2%) of stage IV patients. Kaplan-Meier analysis confirmed a statistically significant discrimination of survival curves (p ⫽ 0.018); the concordance index was 0.55 (95% CI, 0.48 to 0.62). AJCC 2002
Redefinition of T status converted more of our patients into stage I and II classification using the updated AJCC/ Union Internationale Contre le Cancer joint 2002 staging system13 (31.5% and 30.4%, respectively) as compared with the earlier 1997 iteration (Figs. 2C, 3C). Redefinition of stage IV as the presence of distant metastatic disease resulted in a substantial decrease in the number of stage IV patients (3.0%). Kaplan-Meier analysis showed significant discriminatory ability (p ⫽ 0.007); the concordance index was 0.59 (95% CI, 0.52 to 0.66). Vauthey
Application of the Vauthey (Figs. 2D, 3D) HCC staging system14 yielded an even distribution of patients in stages I, II, and IIIA (32.9%, 38.3%, and 24.6%, respectively). Fibrosis scores were not available for all patients and were not incorporated. Because of the small number of patients in our series with demonstrable nodal metastases, very few patients were categorized into stage IIIB (1.2%). Three percent were classified as having stage IV disease, defined by the presence of distant metastases. Discrimination between stages was statistically significant (p ⫽ 0.031); the concordance index was 0.57 (95% CI, 0.49 to 0.64). Okuda
The Okuda staging system15 (Figs. 2E, 3E) categorizes HCC patients based mostly on measures of functional hepatic reserve, with only 1 broad oncologic variable (tumor extension involving ⬎ 50% of the liver). Given the preponderance of patients in our series with preserved liver function, a majority of patients (77.2%) were in Okuda class I, with only 1 patient having class III disease. Nevertheless, differentiation of survival curves was significant (p ⫽
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0.0001); the concordance index was calculated as 0.56 (95% CI, 0.49 to 0.63). Barcelona Clinic Liver Cancer
The Barcelona Clinic Liver Cancer staging system16 (Figs. 2F, 3F) has been used to triage HCC patients into appropriate treatment modalities and incorporates functional status, extent of liver dysfunction, and oncologic variables. Because of the large number of patients with symptomatic tumors or vascular invasion, the majority of patients in our series (77.7%) were categorized into class C. Kaplan-Meier analysis demonstrated statistically significant differentiation of survival curves (p ⫽ 0.012); the concordance index was 0.55 (95% CI, 0.49 to 0.61). Cancer of the Liver Italian Program
The Cancer of the Liver Italian Program (CLIP) (Figs. 2G, 3G) staging system17 incorporates measures of hepatic function, tumor morphologic characteristics, AFP level, and presence of portal vein thrombosis into a scoring system. There was a preponderance of patients in our series with lower CLIP scores. Kaplan-Meier curves were statistically distinct (p ⫽ 0.0004); the concordance index was 0.54 (95% CI, 0.46 to 0.62). Japanese Integrated Staging
The Japanese Integrated Staging scoring system18 (Figs. 2H, 3H) combines the IHPBA system with Child-Pugh class to incorporate a measure of hepatic functional status. Because of the small number of patients with advanced cirrhosis in our series, the distribution of patients by the Japanese Integrated Staging scoring system was not dissimilar from that observed with the IHPBA system alone. Kaplan-Meier analysis confirmed significant differentiation of survival curves (p ⫽ 0.031) with a concordance index of 0.56 (95% CI, 0.48 to 0.63). Analysis of prognostic factors
Results of univariate analysis of patient, treatment, and pathologic factors identified the presence of tumor-related symptoms, size ⬎ 5 cm, bilobar involvement, vascular invasion, satellitosis, portal vein thrombosis, extrahepatic invasion of adjacent anatomic structures, and ⬎ 50% hepatic parenchymal involvement as categorical variables and age, tumor size, albumin, and estimated blood loss as continuous variables associated with worse overall survival (Table 1). Survival nomogram
Incorporation of informative prognostic variables for overall survival into a predictive modeling system yielded the HCC survival nomogram (Fig. 4). The variables of patient age, estimated blood loss, margin positivity, presence of satellite lesions, vascular invasion, tumor size ⬎ 5 cm, and AFP were found to be most informative in the optimal
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Figure 3. Kaplan-Meier estimates of overall survival. (A) American Joint Committee on Cancer (AJCC) 1997 staging system; (B) International Hepato-Pancreato-Biliary Association (IHPBA) staging system; (C) AJCC 2002 staging system; (D) Vauthey staging system; (E) Okuda staging system; (F) Barcelona Clinic Liver Cancer (BCLC) staging system; (G) Cancer of the Liver Italian Program (CLIP) staging system; (H) Japanese Integrated Staging (JIS) scoring system. c-index, concordance index.
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Table 1. Analysis of Variables Associated with Overall Survival Variable
Age (y) Gender Male Female Preoperative symptoms No Yes Maximal tumor size ⱖ 5 cm No Yes Tumor size (cm) Tumor number Differentiation Well Moderate Poor Bilobar involvement No Yes ⬎ 50% parenchymal involvement No Yes Tumor encapsulation No Partial Complete Extrahepatic invasion No Yes Rupture No Yes Pedunculated morphology No Yes Vascular invasion No Yes Portal vein thrombosis No Yes Satellitosis No Yes Margin status No Yes Margin length (mm)
n
Median p Value survival (mo) (univariate)
0.016 0.10 61 123
57 37
54 78
72 32
34 149
117 36
0.0009
32 92 40
51 38 49
105 69
70 30
136 32
55 21
46 39 18
39 42 67
141 31
51 20
159 12
42 20
156 27
38 65
64 101
68 28
36 25
70 22
0.0002 0.015 0.29 0.74
0.0032
0.0002
0.47
0.011
0.38
0.12
0.0008
0.0016
55 28
166 14
49 30
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Table 1. Continued Variable
Nodal metastases No Yes Perineural invasion No Yes Distant metastases No Yes Cirrhosis No Yes Steatosis No Yes Albumin (g/dL) ␣-fetoprotein (ng/mL) Estimated blood loss (mL)
n
Median p Value survival (mo) (univariate)
0.72 76 2
33 2
95 4
51 19
170 5
48 31
118 63
39 54
136 43
39 51
0.17
0.23
0.69
0.57
0.001 0.43 ⬍ 0.0001
prediction of individual survival. This nomogram predicts the probability of overall survival at 3 and 5 years after complete resection. The concordance index for the nomogram was 0.74. Nomogram validation using leave-one-out methodology yielded a 95% confidence interval of 0.68 to 0.80. When 30-day perioperative mortalities were excluded, the concordance index was 0.67, with a 95% confidence interval of 0.61 to 0.73. A calibration curve plotting expected nomogram-predicted overall survival at 3 years and observed overall survival at 3 years based on Kaplan-Meier methodology is shown in Figure 5. Although there is some evidence of underprediction, the confidence intervals span the 45-degree line except at the low end of the spectrum, indicating acceptable calibration. Comparison of concordance indices between the staging systems and nomogram is shown in Figure 6. The concordance index of the nomogram was found to be significantly better than the concordance index of all staging systems analyzed (p ⬍ 0.01 for all comparisons). Recurrence nomogram
0.0016 125 52
Hepatocellular Carcinoma Nomogram
0.15
0.75
Informative prognostic variables were also incorporated into a predictive nomogram for HCC recurrence (Fig. 7). The same variables found to be informative in the prediction of survival were found to be informative in the optimal prediction of recurrence. When used to predict the probability of disease-free survival at 3 and 5 years after complete resection, the nomogram concordance index was 0.67; validation generated a 95% confidence interval of 0.61 to 0.73.
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Figure 4. Hepatocellular carcinoma survival nomogram. (To use the nomogram, an individual patient’s values are located on each variable axis, and a line is drawn upward to determine the number of points received for each variable value. The sum of these numbers is located on the Total Points axis, and a line is drawn downward to the survival axes to determine the likelihood of 3- or 5-year survival.) AFP, ␣-fetoprotein; EBL, estimated blood loss.
DISCUSSION Development of a rational treatment algorithm for patients presenting with HCC is made challenging by the broad heterogeneity of patients and treatment options. Controversy persists in defining the role of partial hepatectomy vis-à-vis other treatment modalities, including orthotopic
Figure 6. Concordance indices. The dotted line denotes the upper limit of the 95% confidence interval of the conventional staging system with the highest concordance index (the AJCC 2002 staging system). (p ⬍ 0.01 for comparisons between nomogram and all conventional staging systems.) AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic Liver Cancer; CLIP, Cancer of the Liver Italian Program; IHPBA, International Hepato-Pancreato-Biliary Association; JIS, Japanese Integrated Staging; MSKCC, Memorial Sloan-Kettering Cancer Center.
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Figure 5. Hepatocellular carcinoma survival nomogram calibration curve. Nomogram-predicted overall survival at 3 years is plotted on the x axis; actual overall survival at 3 years is plotted on the y axis.
liver transplantation, tumor ablation, and hepatic arterial (chemo/radio)embolization. To quantify expected outcomes for HCC patients treated by resection, a number of centers and organizations have proposed staging and scoring systems that stratify patients into defined risk classifications with distinct expected survival outcomes.19-26 In the present analysis, we attempted to comparatively validate eight modern staging and scoring systems using our institutional experience with patients undergoing complete resection for HCC. It must be acknowledged that not all of these staging systems were originally developed for the pur-
Figure 7. Hepatocellular carcinoma recurrence nomogram. AFP, ␣-fetoprotein; EBL, estimated blood loss.
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pose of postoperative prognostication; whereas the AJCC, IHPBA, and Vauthey systems are based on pathologic variables that can only be ascertained after surgical resection, systems like the Okuda, Barcelona Clinic Liver Cancer, CLIP, and Japanese Integrated Staging are based on clinical variables that permit stratification of all HCC patients into appropriate modalities of therapy. Regardless, we observed that each system was able to differentiate patients treated with partial hepatectomy into distinct risk categories as tested by Kaplan-Meier methodology. The ability of these systems to predict individual survival after resection was suboptimal. Using the Harrell’s concordance index5 as a quantitative measure of predictive ability, only the 2002 updated joint AJCC/Union Internationale Contre le Cancer staging system13 demonstrated a predictive ability that was statistically distinguishable from that which would be predicted by random chance alone, ie, it had a concordance index whose 95% confidence interval was ⬎ 0.5. Even this distinction was marginal (95% CI, 0.52 to 0.66). Our findings highlight the shortcomings of standard risk classification schemes used in contemporary cancer staging.27 Although most staging and scoring systems permit differentiation of statistically distinct risk categories, there remains a great deal of heterogeneity within each risk category that hinders predictive modeling of survival outcomes on an individual, patient-by-patient basis. This inherent shortcoming has been demonstrated for prostate cancer,6 sarcoma,28 gastric cancer,29 and pancreas cancer.30 The relative inability of contemporary staging systems to predict individual outcomes for patients undergoing surgical resection of HCC prompted us to develop a novel predictive modeling system using nomogram methodology. The resulting model permits far more accurate prediction of outcomes, with a calculated concordance index significantly higher than those observed with standard staging methods. The measured concordance index of 0.74 is comparable with those generated by other recent prognostic nomograms for pancreas adenocarcinoma (0.64),30 extremity sarcoma (0.77),28 and gastric adenocarcinoma (0.80).29 Clinicopathologic variables found to be associated with survival were initially tested for nomogram construction, and those variables improving the predictive ability of the nomogram construct were retained. The nomogram was also refined by testing all other variables and incorporating those that optimized overall predictive ability. As a result, the variables found to be sufficiently informative and predictive to warrant inclusion into the nomogram for overall survival were patient age, margin, presence of satellite lesions, presence of vascular invasion, maximal tumor size ⬎ 5 cm, AFP level, and estimated operative blood loss. Interestingly, the same variables were found to be informa-
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tive in the generation of the nomogram for recurrence-free survival, albeit with different relative weights. Most of these variables have been associated with survival in previous analyses.31-41 Even in the present study, not all of these variables were statistically associated with survival on univariate analysis. It is important to recognize that the nomogram is a predictive, and not an associative, model; the criterion for inclusion of a variable is its ability to demonstrably improve the probability that the model will correctly predict survival outcomes (as quantified by the concordance index). Indeed, not all of the variables associated with adverse survival contributed to the predictive ability of the nomogram. Much of the predictive advantage posed by the nomogram over standard staging methods rests in its ability to incorporate each clinicopathologic variable according to both its own relative predictive impact and its complex interaction with the other variables. Estimated blood loss was found to be highly informative in the prediction of survival and, to a lesser extent, recurrence. The importance of estimated blood loss did not appear to be strictly in the prediction of early perioperative survival; indeed, when 30-day perioperative mortalities were excluded, the predictive ability of the nomogram continued to outperform that of conventional staging systems. Because of the wide range of AFP levels measured in our series of patients, a logarithmic transformation of AFP level was incorporated into the nomogram. Care was taken to use only those clinicopathologic variables that were reproducibly and commonly measured into the nomogram. Not all patients undergoing resection of HCC will have preoperative serum AFP levels measured; indeed, 28 patients in our series did not have AFP levels recorded. Nevertheless, AFP was included, as it optimized the predictive ability of the nomogram. Exclusion of AFP as a variable yielded a slightly less accurate nomogram for overall survival, with a concordance index of 0.71 (95% CI, 0.65 to 0.77). Similarly, exclusion of AFP from the nomogram for recurrencefree survival resulted in a lower concordance index of 0.62 (95% CI, 0.56 to 0.67). The largest shortcoming of this analysis is its reliance on a single institutional data set of HCC patients. Marked clinicopathologic heterogeneity among HCC patients around the world has been well documented, and the referral patterns and clinical practices of our particular Western institution introduce substantial selection biases. For example, as has been the case in previous reports from our service, the majority of patients treated at our center have had well-preserved hepatic functional status, with a minority of patients demonstrating clinical and pathologic evidence of cirrhosis. The presence of cirrhosis has been found to be a substantial prognostic factor in analyses from other
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centers.42-45 The absence of a statistically significant association between cirrhosis and outcomes in our study is likely to derive from the relative paucity of patients with clinically significant cirrhosis in our series. Because of the geographic and institutional heterogeneity that exists among patients afflicted with HCC, it will certainly be necessary to validate this predictive nomogram at other centers treating large numbers of HCC patients with surgical resection. If validated, this nomogram (or a variation thereof ) could serve as a useful instrument in the design of future clinical trial stratification or in the comparative assessment of novel treatment modalities.
Author Contributions Study conception and design: Cho, DeMatteo Acquisition of data: Cho, Shia, Klimstra, Jarnagin, D’Angelica, Blumgart, DeMatteo Analysis and interpretation of data: Cho, Gonen, Kattan, DeMatteo Drafting of manuscript: Cho, DeMatteo Critical revision: Cho, Gonen, Shia, Klimstra, Jarnagin, D’Angelica, Blumgart, DeMatteo
REFERENCES 1. Everson GT. Increasing incidence and pretransplantation screening of hepatocellular carcinoma. Liver Transpl 2000;6[Suppl 2]:S2– S10. 2. Stipa F, Yoon SS, Liau KH, et al. Outcome of patients with fibrolamellar hepatocellular carcinoma. Cancer 2006;106:1331–1338. 3. Hemming AW, Langer B, Sheiner P, et al. Aggressive surgical management of fibrolamellar hepatocellular carcinoma. J Gastrointest Surg 1997;1:342–346. 4. Martin RC, Jaques DP, Brennan MF, Karpeh M. Achieving R0 resection for locally advanced gastric cancer: is it worth the risk of multiorgan resection? J Am Coll Surg 2002;194:568–577. 5. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluation assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15: 361–387. 6. Kattan MW, Eastham JA, Stapleton AMF, et al. A preoperative nomogram for disease recurrence following radical prostatectomy for prostate cancer. J Natl Cancer Inst 1998;90:766–771. 7. Efron B, Tibshirani RJ. An introduction to the bootstrap. Boca Raton, FL: Chapman and Hall; 1993. 8. Pugh RN, Murray-Lyon IM, Dawson JL, et al. Transection of the esophagus for bleeding esophageal varices. Br J Surg 1973; 67:773–775. 9. Malinchoc M, Kamath PS, Gordon FD, et al. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864–871. 10. Mazzaferro V, Regalia E, Doci R, et al. Liver transplantation for the treatment of small hepatocellular carcinomas in patients with cirrhosis. N Engl J Med 1996;334:693–699.
J Am Coll Surg
11. Liver (including intrahepatic bile ducts). In: American Joint Committee on Cancer: AJCC cancer staging manual. 5th ed. Philadelphia: Lippincott-Raven; 1998:98⫺126. 12. Makuuchi M, Belghiti J, Belli G, et al. Working Group of the International Scientific Committee of the International Hepato-Pancreato-Biliary Association. IHPBA concordant classification of primary liver cancer: working group report. J Hepatobiliary Pancreat Surg 2003;10:26–30. 13. Liver (including intrahepatic bile ducts). In: American Joint Committee on Cancer: AJCC Cancer staging manual. 6th ed. New York: Springer; 2002:131⫺138. 14. Vauthey JN, Lauwers GY, Esnaola NF, et al. Simplified staging for hepatocellular carcinoma. J Clin Oncol 2002;20:1527– 1536. 15. Okuda K, Ohtsuki T, Obata H. Natural history of hepatocellular carcinoma and prognosis in relation to treatment: study of 850 patients. Cancer 1985;56:918–928. 16. Llovet JM, Bru C, Cruix J. Prognosis of hepatocellular carcinoma: the BCLC staging classification. Semin Liver Dis 1999; 19:329–338. 17. The Cancer of the Liver Italian Program (CLIP) Investigators. Prospective validation of the CLIP score: a new prognostic system for patients with cirrhosis and hepatocellular carcinoma. Hepatology 2000;31:840–845. 18. Kudo M, Chung H, Osaki Y. Prognostic staging system for hepatocellular carcinoma (CLIP score): its value and limitations, and a proposal for a new staging system, the Japan Integrated Staging Score (JIS score). J Gastroenterol 2003;38:207–215. 19. Farinati F, Rinaldi M, Gianni S, Naccarato R. How should patients with hepatocellular carcinoma be staged? Validation of a new prognostic system. Cancer 2000;89:2266–2273. 20. Zhao WH, Ma ZM, Zhou XR, et al. Prediction of recurrence and prognosis in patients with hepatocellular carcinoma after resection by use of CLIP score. World J Gastroenterol 2002;8: 237–242. 21. Bruix J, Llovet JM. Prognostic assessment and evaluation of the benefits of treatment. J Clin Gastroenterol 2002;35[Suppl 2]:S138–S142. 22. Levy I, Sherman M. Staging of hepatocellular carcinoma: assessment of the CLIP, Okuda, and Child-Pugh staging systems in a cohort of 257 patients in Toronto. Gut 2002;50:881–885. 23. Rabe C, Lenz M, Schmitz V, et al. An independent evaluation of modern prognostic scores in a central European cohort of 120 patients with hepatocellular carcinoma. Eur J Gastroenterol Hepatol 2003;15:1305–1315. 24. Ramacciato G, Mercantini P, Cautero N, et al. Prognostic evaluation of the new American Joint Committee on Cancer/ International Union Against Cancer staging system for hepatocellular carcinoma: analysis of 112 cirrhotic patients resected for hepatocellular carcinoma. Ann Surg Oncol 2005;12:289–297. 25. Marrero JA, Fontana RJ, Barrat A, et al. Prognosis of hepatocellular carcinoma: comparison of 7 staging systems in an American cohort. Hepatology 2005;42:707–716. 26. Grieco A, Pompili M, Caminiti G, et al. Prognostic factors for survival in patients with early-intermediate hepatocellular carcinoma undergoing non-surgical therapy: comparison of Okuda, CLIP and BCLC staging systems in a single Italian center. Gut 2005;54:411–418. 27. Kattan MW. Nomograms are superior to staging and risk grouping systems for identifying high-risk patients: preoperative application in prostate cancer. Curr Opin Urol 2003;13:111–116.
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28. Kattan MW, Leung DH, Brennan MF. Postoperative nomogram for 12-year sarcoma-specific death. J Clin Oncol 2002;20: 791–796. 29. Kattan MW, Karpeh MS, Mazumdar M, Brennan MF. Postoperative nomogram for disease-specific survival after an R0 resection for gastric carcinoma. J Clin Oncol 2003;21:3647– 3650. 30. Brennan MF, Kattan MW, Klimstra D, Conlon K. Prognostic nomogram for patients undergoing resection for adenocarcinoma of the pancreas. Ann Surg 2004;240:293–298. 31. Vauthey JN, Klimstra D, Francheschi D, et al. Factors affecting long-term outcome after hepatic resection for hepatocellular carcinoma. Am J Surg 1995;169:28–35. 32. Fong Y, Sun RL, Jarnagin W, Blumgart LH. An analysis of 412 cases of hepatocellular carcinoma at a Western center. Ann Surg 1999;229:790–800. 33. Cho CS, Knechtle SJ, Heisey DM, et al. Analysis of tumor characteristics and survival in liver transplant recipients with incidentally diagnosed hepatocellular carcinoma. J Gastrointest Surg 2001;5:594–602. 34. Nagasue N, Ono T, Yamanoi A, et al. Prognostic factors and survival after hepatic resection for hepatocellular carcinoma without cirrhosis. Br J Surg 2001;88:515–522. 35. Poon RTP, Fan ST, Lo CM, et al. Improving survival results after resection of hepatocellular carcinoma: a prospective study of 377 patients over 10 years. Ann Surg 2001;234:63–70. 36. Poon RTP, Fan ST, Lo CM, et al. Long-term survival and pattern of recurrence after resection of small hepatocellular carcinoma in patients with preserved liver function: implications for a strategy of salvage transplantation. Ann Surg 2002; 235:373–382.
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37. Ercolani G, Grazi GL, Ravaioli M, et al. Liver resection for hepatocellular carcinoma on cirrhosis: univariate and multivariate analysis of risk factors for intrahepatic recurrence. Ann Surg 2003;237:536–543. 38. Cha C, Fong Y, Jarnagin WR, et al. Predictors and patterns of recurrence after resection of hepatocellular carcinoma. J Am Coll Surg 2003;197:753–758. 39. Cha CH, Ruo L, Fong Y, et al. Resection of hepatocellular carcinoma in patients otherwise eligible for transplantation. Ann Surg 2003;238:315–323. 40. Liau KH, Ruo L, Shia J, et al. Outcome of partial hepatectomy for large (⬎10 cm) hepatocellular carcinoma. Cancer 2005;104: 1948–1955. 41. Shah SA, Greig PD, Gallinger S, et al. Factors associated with early recurrence after resection for hepatocellular carcinoma and outcomes. J Am Coll Surg 2006;202:275–283. 42. Poon RT, Fan ST, Ng IO, et al. Different risk factors and prognosis for early and late intrahepatic recurrence after resection of hepatocellular carcinoma. Cancer 2000;89:500–507. 43. Laurent C, Blanc JF, Nobili S, et al. Prognostic factors and longterm survival after hepatic resection for hepatocellular carcinoma originating from noncirrhotic liver. J Am Coll Surg 2005;201:656–662. 44. Ng KK, Vauthey JN, Pawlik TM, et al. International Cooperative Study Group on Hepatocellular Carcinoma. Is hepatic resection for large or multinodular hepatocellular carcinoma justified? Results from a multi-institutional database. Ann Surg Oncol 2005;12:364–373. 45. Portolani N, Coniglio A, Ghidoni S, et al. Early and late recurrence after liver resection for hepatocellular carcinoma: prognostic and therapeutic implications. Ann Surg 2006;243:229–235.
Hepatocellular carcinoma (HCC) remains a substantial world health problem; it is estimated that the incidence of HCC in the US will continue to increase in a dramatic fashion during the next several decades.1 This has motivated a great deal of interest in optimizing the management of this difficult disease. Unfortunately, development of a
rational treatment strategy for HCC is complicated by its geographic and biologic heterogeneity and the multitude of treatment options that are currently available. HCC often develops in a setting of chronic liver dysfunction, which can limit the applicability of invasive therapeutic modalities and increase the likelihood of tumor recurrence. Surgical resection in the form of partial hepatectomy has emerged as a mainstay of potentially curative therapy, but orthotopic liver transplantation, tumor ablation, and hepatic intraarterial therapies provide alternative options. In an attempt to stratify expected survival outcomes for HCC patients treated by partial hepatectomy, a number of staging systems have been developed. Unfortunately, their criteria vary greatly, and no single system has consistently emerged as the optimal predictor of postoperative survival. The objective of the present analysis was to validate and
Competing Interests Declared: None. Received June 13, 2007; Revised July 23, 2007; Accepted July 25, 2007. From the Hepatobiliary Service (Cho, Jarnagin, D’Angelica, Blumgart, De Matteo), Department of Epidemiology and Biostatistics (Gonen), and Department of Pathology (Shia, Klimstra), Memorial Sloan-Kettering Cancer Center, New York, NY; and Department of Quantitative Health Sciences, The Cleveland Clinic Foundation, Cleveland, OH (Kattan). Correspondence address: Clifford S Cho, MD, Department of Surgery, University of Wisconsin School of Medicine and Public Health, H4/724, 600 Highland Ave Madison, WI 53792-7375.
© 2008 by the American College of Surgeons Published by Elsevier Inc.
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Abbreviations and Acronyms
AFP AJCC CLIP HCC IHPBS
⫽ ⫽ ⫽ ⫽ ⫽
␣-fetoprotein American Joint Commission on Cancer Cancer of the Liver Italian Program hepatocellular carcinoma International Hepato-Pancreato-Biliary Association
compare some of the major HCC staging systems in use today. We drew on our experience with patients undergoing complete resection of HCC at our tertiary hepatobiliary referral center to compare the ability of these staging systems to predict survival after resection; in addition, we generated a novel predictive model for more accurate estimation of outcomes.
METHODS Relevant patient, operative, pathologic, and outcomes data were collected using a prospective, single-institution database of patients undergoing partial hepatectomy for HCC at Memorial Sloan-Kettering Cancer Center. We limited the data set to those patients undergoing resection between 1989 and 2002 to identify a contemporary cohort of patients with sufficient duration of postoperative followup. Patients undergoing repeat or noncurative resections were excluded from analysis. Repeat pathologic analysis was performed to confirm the histologic diagnosis of HCC; because of oncologic and staging discrepancies that have been described between fibrolamellar and nonfibrolamellar variants of HCC,2,3 patients with fibrolamellar HCC were excluded. Operative mortalities were not excluded from analysis. Medical records were reviewed to obtain followup information about survival and recurrence status. Postoperative complications were graded on a 5-point system previously defined as follows: grade 1, complication requiring oral medical therapy or bedside care; grade 2, complication requiring intravenous medical therapy; grade 3, complication requiring operative or radiologic intervention; grade 4, complication resulting in unintended organ resection or chronic disability; grade 5, complication resulting in death.4 Clinicopathologic variables were used to stage patients according to eight major contemporary HCC staging systems. Survival outcomes were calculated using KaplanMeier methodology. The ability of a staging system to stratify postresection survival was quantified using Harrell’s concordance index.5 This construct represents the probability that, for each randomly generated pair of patients from a data set, the patient who lived longer was predicted to have had the favorable outcomes based on the staging system used. A staging system with a concordance index of
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1 would have predicted the correct outcomes in all patients; a concordance index of 0 would mean that the incorrect outcomes were predicted in all patients; a concordance index of 0.5 would imply that the system correctly predicted the outcomes 50% of the time (in essence having no predictive ability). Noninformative pairs (eg, pairs for whom survival was equal or in whom the survivor had a shorter followup interval) were not included in the calculation of the concordance index. Each of the clinicopathologic variables collected were subjected to univariate analysis using the log-rank test for categorical variables and Cox regression analysis for continuous variables. Methodology of nomogram construction using logistic regression and internal validation was identical to that used and published previously.6 A calibration curve was generated to depict the agreement between nomogram-predicted probability of survival at 3 years and observed probability of survival at 3 years based on KaplanMeier methodology. Comparison between the nomogram and conventional staging systems was performed by generating 2,000 bootstrap samples and computing concordance indices for each system. This generates an approximation of the sampling distribution of all pairwise differences between concordance indices. A p value for the significance of difference was determined by using the asymptotic significance level described previously.7 Nomograms for prediction of overall survival and recurrence-free survival were generated independently.
RESULTS Patient characteristics
After excluding those patients who did not meet inclusion criteria, we identified 184 patients who underwent complete primary resection of HCC from the prospective database. Mean age of the patients was 63 years (range 26 to 87 years), and 67% were men. Race distribution demonstrated that 61% were Caucasian, 28% were Asian, and 11% were of other backgrounds. Fifty-nine percent of patients presented with symptoms referable to their tumor burden. Although 35% of patients had histologic evidence of cirrhosis in the explanted specimens, the majority of patients presented with well-preserved hepatic function; 96% of patients had biochemical profiles consistent with Child-Turcotte-Pugh8 class A status, 4% had evidence of class B cirrhosis, and no patients had evidence of class C cirrhosis. The median Model for End-Stage Liver Disease score9 was 17 (range 6 to 82). For patients in whom an ␣-fetoprotein (AFP) level was documented preoperatively, median AFP was 43.8 ng/mL (range 1.2 to 422,000 ng/ mL) with 23% demonstrating AFP levels ⬎ 2,000 ng/mL.
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Treatment characteristics
Seven percent of patients underwent some form of preoperative neoadjuvant chemotherapy, and 3% underwent postoperative adjuvant chemotherapy. A majority (59%) required at least a hemihepatectomy. Median operative blood loss was 700 mL (range 50 to 8,500 mL). Forty-three percent of patients experienced at least 1 documented complication in the first 30 postoperative days. Ten percent of all patients had grade 1 complications, 20% had grade 2 complications, 9% had grade 3 complications, 1% had grade 4 complications, and 5% had grade 5 complications. The overall 60-day operative mortality rate was 5%. Pathologic characteristics
The median number of tumors identified on pathologic analysis was 1 (range 1 to 5), and the median size of the largest tumor was 9.5 cm (range 1.7 to 26 cm). Twenty-one percent of patients had a maximal tumor size ⱕ 5 cm; 49% were ⱖ 10 cm in maximal size. Only 38 patients (21%) had tumor characteristics that met the Milan HCC criteria for liver transplantation.10 Forty percent presented with bilobar disease (defined as single tumors involving both the right and left hemilivers or multiple tumors distributed in both hemilivers) and 29% had pathologic evidence of satellitosis. Sixty-one percent had evidence of microvascular invasion, and 3% had demonstrable nodal metastases (portal lymphadenectomy was not routinely performed in all patients). Histologic grade was defined as well differentiated in 20%, moderately differentiated in 56%, and poorly differentiated in 24%. The median margin of resection was 0.8 cm (range 0 to 5.5 cm) with an 8% rate of positive microscopic margins. Survival outcomes
After a median followup of 46 months for surviving patients, median overall survival was 38 months, and likelihood of 5-year overall survival was 38% (Fig. 1A). Median disease-specific survival was 54 months and likelihood of 5-year disease-specific survival was 47% (Fig. 1B). Median recurrence-free survival was 36 months with a likelihood of 5-year recurrence-free survival of 28% (Fig. 1C). American Joint Commission on Cancer 1997
Criteria for staging by the American Joint Commission on Cancer (AJCC) 1997 edition11 are shown in Figure 2A. When applied to our cohort of patients, we observed that 44.7% of patients were classified as stage IVA, because patients with multiple, bilobar tumors are defined as having stage IV disease. Because T1 tumors were defined as single tumors ⬍ 2 cm, with no evidence of microvascular invasion, only 1.8% of patients were categorized as having stage I disease. Kaplan-Meier analysis of overall survival
Figure 1. Kaplan-Meier estimates of survival. (A) Overall survival (OS); (B) disease-specific survival (DSS); (C) recurrence-free survival (RFS).
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Figure 2. Hepatocellular carcinoma staging systems. AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic Liver Cancer; CLIP, Cancer of the Liver Italian Program; IHPBA, International Hepato-Pancreato-Biliary Association; JIS, Japanese Integrated Staging.
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determined a statistically significant differentiation of survival curves by stage (p ⫽ 0.015); the concordance index was 0.57 (95% CI, 0.49 to 0.64). International Hepato-Pancreato-Biliary Association
When staged according to the simplified International Hepato-Pancreato-Biliary Association (IHPBA) staging system criteria12 (Figs. 2B, 3B), a preponderance of patients were classified as having stage II and III disease (36.4% and 50%, respectively). Because stage I disease was defined as single tumors ⬍ 2 cm in size with no vascular invasion, very few patients (1.6%) were classified as having stage I disease; the definition of stage IV disease as the presence of nodal or distant metastases resulted in a small number (9.2%) of stage IV patients. Kaplan-Meier analysis confirmed a statistically significant discrimination of survival curves (p ⫽ 0.018); the concordance index was 0.55 (95% CI, 0.48 to 0.62). AJCC 2002
Redefinition of T status converted more of our patients into stage I and II classification using the updated AJCC/ Union Internationale Contre le Cancer joint 2002 staging system13 (31.5% and 30.4%, respectively) as compared with the earlier 1997 iteration (Figs. 2C, 3C). Redefinition of stage IV as the presence of distant metastatic disease resulted in a substantial decrease in the number of stage IV patients (3.0%). Kaplan-Meier analysis showed significant discriminatory ability (p ⫽ 0.007); the concordance index was 0.59 (95% CI, 0.52 to 0.66). Vauthey
Application of the Vauthey (Figs. 2D, 3D) HCC staging system14 yielded an even distribution of patients in stages I, II, and IIIA (32.9%, 38.3%, and 24.6%, respectively). Fibrosis scores were not available for all patients and were not incorporated. Because of the small number of patients in our series with demonstrable nodal metastases, very few patients were categorized into stage IIIB (1.2%). Three percent were classified as having stage IV disease, defined by the presence of distant metastases. Discrimination between stages was statistically significant (p ⫽ 0.031); the concordance index was 0.57 (95% CI, 0.49 to 0.64). Okuda
The Okuda staging system15 (Figs. 2E, 3E) categorizes HCC patients based mostly on measures of functional hepatic reserve, with only 1 broad oncologic variable (tumor extension involving ⬎ 50% of the liver). Given the preponderance of patients in our series with preserved liver function, a majority of patients (77.2%) were in Okuda class I, with only 1 patient having class III disease. Nevertheless, differentiation of survival curves was significant (p ⫽
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0.0001); the concordance index was calculated as 0.56 (95% CI, 0.49 to 0.63). Barcelona Clinic Liver Cancer
The Barcelona Clinic Liver Cancer staging system16 (Figs. 2F, 3F) has been used to triage HCC patients into appropriate treatment modalities and incorporates functional status, extent of liver dysfunction, and oncologic variables. Because of the large number of patients with symptomatic tumors or vascular invasion, the majority of patients in our series (77.7%) were categorized into class C. Kaplan-Meier analysis demonstrated statistically significant differentiation of survival curves (p ⫽ 0.012); the concordance index was 0.55 (95% CI, 0.49 to 0.61). Cancer of the Liver Italian Program
The Cancer of the Liver Italian Program (CLIP) (Figs. 2G, 3G) staging system17 incorporates measures of hepatic function, tumor morphologic characteristics, AFP level, and presence of portal vein thrombosis into a scoring system. There was a preponderance of patients in our series with lower CLIP scores. Kaplan-Meier curves were statistically distinct (p ⫽ 0.0004); the concordance index was 0.54 (95% CI, 0.46 to 0.62). Japanese Integrated Staging
The Japanese Integrated Staging scoring system18 (Figs. 2H, 3H) combines the IHPBA system with Child-Pugh class to incorporate a measure of hepatic functional status. Because of the small number of patients with advanced cirrhosis in our series, the distribution of patients by the Japanese Integrated Staging scoring system was not dissimilar from that observed with the IHPBA system alone. Kaplan-Meier analysis confirmed significant differentiation of survival curves (p ⫽ 0.031) with a concordance index of 0.56 (95% CI, 0.48 to 0.63). Analysis of prognostic factors
Results of univariate analysis of patient, treatment, and pathologic factors identified the presence of tumor-related symptoms, size ⬎ 5 cm, bilobar involvement, vascular invasion, satellitosis, portal vein thrombosis, extrahepatic invasion of adjacent anatomic structures, and ⬎ 50% hepatic parenchymal involvement as categorical variables and age, tumor size, albumin, and estimated blood loss as continuous variables associated with worse overall survival (Table 1). Survival nomogram
Incorporation of informative prognostic variables for overall survival into a predictive modeling system yielded the HCC survival nomogram (Fig. 4). The variables of patient age, estimated blood loss, margin positivity, presence of satellite lesions, vascular invasion, tumor size ⬎ 5 cm, and AFP were found to be most informative in the optimal
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Figure 3. Kaplan-Meier estimates of overall survival. (A) American Joint Committee on Cancer (AJCC) 1997 staging system; (B) International Hepato-Pancreato-Biliary Association (IHPBA) staging system; (C) AJCC 2002 staging system; (D) Vauthey staging system; (E) Okuda staging system; (F) Barcelona Clinic Liver Cancer (BCLC) staging system; (G) Cancer of the Liver Italian Program (CLIP) staging system; (H) Japanese Integrated Staging (JIS) scoring system. c-index, concordance index.
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Table 1. Analysis of Variables Associated with Overall Survival Variable
Age (y) Gender Male Female Preoperative symptoms No Yes Maximal tumor size ⱖ 5 cm No Yes Tumor size (cm) Tumor number Differentiation Well Moderate Poor Bilobar involvement No Yes ⬎ 50% parenchymal involvement No Yes Tumor encapsulation No Partial Complete Extrahepatic invasion No Yes Rupture No Yes Pedunculated morphology No Yes Vascular invasion No Yes Portal vein thrombosis No Yes Satellitosis No Yes Margin status No Yes Margin length (mm)
n
Median p Value survival (mo) (univariate)
0.016 0.10 61 123
57 37
54 78
72 32
34 149
117 36
0.0009
32 92 40
51 38 49
105 69
70 30
136 32
55 21
46 39 18
39 42 67
141 31
51 20
159 12
42 20
156 27
38 65
64 101
68 28
36 25
70 22
0.0002 0.015 0.29 0.74
0.0032
0.0002
0.47
0.011
0.38
0.12
0.0008
0.0016
55 28
166 14
49 30
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Table 1. Continued Variable
Nodal metastases No Yes Perineural invasion No Yes Distant metastases No Yes Cirrhosis No Yes Steatosis No Yes Albumin (g/dL) ␣-fetoprotein (ng/mL) Estimated blood loss (mL)
n
Median p Value survival (mo) (univariate)
0.72 76 2
33 2
95 4
51 19
170 5
48 31
118 63
39 54
136 43
39 51
0.17
0.23
0.69
0.57
0.001 0.43 ⬍ 0.0001
prediction of individual survival. This nomogram predicts the probability of overall survival at 3 and 5 years after complete resection. The concordance index for the nomogram was 0.74. Nomogram validation using leave-one-out methodology yielded a 95% confidence interval of 0.68 to 0.80. When 30-day perioperative mortalities were excluded, the concordance index was 0.67, with a 95% confidence interval of 0.61 to 0.73. A calibration curve plotting expected nomogram-predicted overall survival at 3 years and observed overall survival at 3 years based on Kaplan-Meier methodology is shown in Figure 5. Although there is some evidence of underprediction, the confidence intervals span the 45-degree line except at the low end of the spectrum, indicating acceptable calibration. Comparison of concordance indices between the staging systems and nomogram is shown in Figure 6. The concordance index of the nomogram was found to be significantly better than the concordance index of all staging systems analyzed (p ⬍ 0.01 for all comparisons). Recurrence nomogram
0.0016 125 52
Hepatocellular Carcinoma Nomogram
0.15
0.75
Informative prognostic variables were also incorporated into a predictive nomogram for HCC recurrence (Fig. 7). The same variables found to be informative in the prediction of survival were found to be informative in the optimal prediction of recurrence. When used to predict the probability of disease-free survival at 3 and 5 years after complete resection, the nomogram concordance index was 0.67; validation generated a 95% confidence interval of 0.61 to 0.73.
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Figure 4. Hepatocellular carcinoma survival nomogram. (To use the nomogram, an individual patient’s values are located on each variable axis, and a line is drawn upward to determine the number of points received for each variable value. The sum of these numbers is located on the Total Points axis, and a line is drawn downward to the survival axes to determine the likelihood of 3- or 5-year survival.) AFP, ␣-fetoprotein; EBL, estimated blood loss.
DISCUSSION Development of a rational treatment algorithm for patients presenting with HCC is made challenging by the broad heterogeneity of patients and treatment options. Controversy persists in defining the role of partial hepatectomy vis-à-vis other treatment modalities, including orthotopic
Figure 6. Concordance indices. The dotted line denotes the upper limit of the 95% confidence interval of the conventional staging system with the highest concordance index (the AJCC 2002 staging system). (p ⬍ 0.01 for comparisons between nomogram and all conventional staging systems.) AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic Liver Cancer; CLIP, Cancer of the Liver Italian Program; IHPBA, International Hepato-Pancreato-Biliary Association; JIS, Japanese Integrated Staging; MSKCC, Memorial Sloan-Kettering Cancer Center.
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Figure 5. Hepatocellular carcinoma survival nomogram calibration curve. Nomogram-predicted overall survival at 3 years is plotted on the x axis; actual overall survival at 3 years is plotted on the y axis.
liver transplantation, tumor ablation, and hepatic arterial (chemo/radio)embolization. To quantify expected outcomes for HCC patients treated by resection, a number of centers and organizations have proposed staging and scoring systems that stratify patients into defined risk classifications with distinct expected survival outcomes.19-26 In the present analysis, we attempted to comparatively validate eight modern staging and scoring systems using our institutional experience with patients undergoing complete resection for HCC. It must be acknowledged that not all of these staging systems were originally developed for the pur-
Figure 7. Hepatocellular carcinoma recurrence nomogram. AFP, ␣-fetoprotein; EBL, estimated blood loss.
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pose of postoperative prognostication; whereas the AJCC, IHPBA, and Vauthey systems are based on pathologic variables that can only be ascertained after surgical resection, systems like the Okuda, Barcelona Clinic Liver Cancer, CLIP, and Japanese Integrated Staging are based on clinical variables that permit stratification of all HCC patients into appropriate modalities of therapy. Regardless, we observed that each system was able to differentiate patients treated with partial hepatectomy into distinct risk categories as tested by Kaplan-Meier methodology. The ability of these systems to predict individual survival after resection was suboptimal. Using the Harrell’s concordance index5 as a quantitative measure of predictive ability, only the 2002 updated joint AJCC/Union Internationale Contre le Cancer staging system13 demonstrated a predictive ability that was statistically distinguishable from that which would be predicted by random chance alone, ie, it had a concordance index whose 95% confidence interval was ⬎ 0.5. Even this distinction was marginal (95% CI, 0.52 to 0.66). Our findings highlight the shortcomings of standard risk classification schemes used in contemporary cancer staging.27 Although most staging and scoring systems permit differentiation of statistically distinct risk categories, there remains a great deal of heterogeneity within each risk category that hinders predictive modeling of survival outcomes on an individual, patient-by-patient basis. This inherent shortcoming has been demonstrated for prostate cancer,6 sarcoma,28 gastric cancer,29 and pancreas cancer.30 The relative inability of contemporary staging systems to predict individual outcomes for patients undergoing surgical resection of HCC prompted us to develop a novel predictive modeling system using nomogram methodology. The resulting model permits far more accurate prediction of outcomes, with a calculated concordance index significantly higher than those observed with standard staging methods. The measured concordance index of 0.74 is comparable with those generated by other recent prognostic nomograms for pancreas adenocarcinoma (0.64),30 extremity sarcoma (0.77),28 and gastric adenocarcinoma (0.80).29 Clinicopathologic variables found to be associated with survival were initially tested for nomogram construction, and those variables improving the predictive ability of the nomogram construct were retained. The nomogram was also refined by testing all other variables and incorporating those that optimized overall predictive ability. As a result, the variables found to be sufficiently informative and predictive to warrant inclusion into the nomogram for overall survival were patient age, margin, presence of satellite lesions, presence of vascular invasion, maximal tumor size ⬎ 5 cm, AFP level, and estimated operative blood loss. Interestingly, the same variables were found to be informa-
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tive in the generation of the nomogram for recurrence-free survival, albeit with different relative weights. Most of these variables have been associated with survival in previous analyses.31-41 Even in the present study, not all of these variables were statistically associated with survival on univariate analysis. It is important to recognize that the nomogram is a predictive, and not an associative, model; the criterion for inclusion of a variable is its ability to demonstrably improve the probability that the model will correctly predict survival outcomes (as quantified by the concordance index). Indeed, not all of the variables associated with adverse survival contributed to the predictive ability of the nomogram. Much of the predictive advantage posed by the nomogram over standard staging methods rests in its ability to incorporate each clinicopathologic variable according to both its own relative predictive impact and its complex interaction with the other variables. Estimated blood loss was found to be highly informative in the prediction of survival and, to a lesser extent, recurrence. The importance of estimated blood loss did not appear to be strictly in the prediction of early perioperative survival; indeed, when 30-day perioperative mortalities were excluded, the predictive ability of the nomogram continued to outperform that of conventional staging systems. Because of the wide range of AFP levels measured in our series of patients, a logarithmic transformation of AFP level was incorporated into the nomogram. Care was taken to use only those clinicopathologic variables that were reproducibly and commonly measured into the nomogram. Not all patients undergoing resection of HCC will have preoperative serum AFP levels measured; indeed, 28 patients in our series did not have AFP levels recorded. Nevertheless, AFP was included, as it optimized the predictive ability of the nomogram. Exclusion of AFP as a variable yielded a slightly less accurate nomogram for overall survival, with a concordance index of 0.71 (95% CI, 0.65 to 0.77). Similarly, exclusion of AFP from the nomogram for recurrencefree survival resulted in a lower concordance index of 0.62 (95% CI, 0.56 to 0.67). The largest shortcoming of this analysis is its reliance on a single institutional data set of HCC patients. Marked clinicopathologic heterogeneity among HCC patients around the world has been well documented, and the referral patterns and clinical practices of our particular Western institution introduce substantial selection biases. For example, as has been the case in previous reports from our service, the majority of patients treated at our center have had well-preserved hepatic functional status, with a minority of patients demonstrating clinical and pathologic evidence of cirrhosis. The presence of cirrhosis has been found to be a substantial prognostic factor in analyses from other
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centers.42-45 The absence of a statistically significant association between cirrhosis and outcomes in our study is likely to derive from the relative paucity of patients with clinically significant cirrhosis in our series. Because of the geographic and institutional heterogeneity that exists among patients afflicted with HCC, it will certainly be necessary to validate this predictive nomogram at other centers treating large numbers of HCC patients with surgical resection. If validated, this nomogram (or a variation thereof ) could serve as a useful instrument in the design of future clinical trial stratification or in the comparative assessment of novel treatment modalities.
Author Contributions Study conception and design: Cho, DeMatteo Acquisition of data: Cho, Shia, Klimstra, Jarnagin, D’Angelica, Blumgart, DeMatteo Analysis and interpretation of data: Cho, Gonen, Kattan, DeMatteo Drafting of manuscript: Cho, DeMatteo Critical revision: Cho, Gonen, Shia, Klimstra, Jarnagin, D’Angelica, Blumgart, DeMatteo
REFERENCES 1. Everson GT. Increasing incidence and pretransplantation screening of hepatocellular carcinoma. Liver Transpl 2000;6[Suppl 2]:S2– S10. 2. Stipa F, Yoon SS, Liau KH, et al. Outcome of patients with fibrolamellar hepatocellular carcinoma. Cancer 2006;106:1331–1338. 3. Hemming AW, Langer B, Sheiner P, et al. Aggressive surgical management of fibrolamellar hepatocellular carcinoma. J Gastrointest Surg 1997;1:342–346. 4. Martin RC, Jaques DP, Brennan MF, Karpeh M. Achieving R0 resection for locally advanced gastric cancer: is it worth the risk of multiorgan resection? J Am Coll Surg 2002;194:568–577. 5. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluation assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15: 361–387. 6. Kattan MW, Eastham JA, Stapleton AMF, et al. A preoperative nomogram for disease recurrence following radical prostatectomy for prostate cancer. J Natl Cancer Inst 1998;90:766–771. 7. Efron B, Tibshirani RJ. An introduction to the bootstrap. Boca Raton, FL: Chapman and Hall; 1993. 8. Pugh RN, Murray-Lyon IM, Dawson JL, et al. Transection of the esophagus for bleeding esophageal varices. Br J Surg 1973; 67:773–775. 9. Malinchoc M, Kamath PS, Gordon FD, et al. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864–871. 10. Mazzaferro V, Regalia E, Doci R, et al. Liver transplantation for the treatment of small hepatocellular carcinomas in patients with cirrhosis. N Engl J Med 1996;334:693–699.
J Am Coll Surg
11. Liver (including intrahepatic bile ducts). In: American Joint Committee on Cancer: AJCC cancer staging manual. 5th ed. Philadelphia: Lippincott-Raven; 1998:98⫺126. 12. Makuuchi M, Belghiti J, Belli G, et al. Working Group of the International Scientific Committee of the International Hepato-Pancreato-Biliary Association. IHPBA concordant classification of primary liver cancer: working group report. J Hepatobiliary Pancreat Surg 2003;10:26–30. 13. Liver (including intrahepatic bile ducts). In: American Joint Committee on Cancer: AJCC Cancer staging manual. 6th ed. New York: Springer; 2002:131⫺138. 14. Vauthey JN, Lauwers GY, Esnaola NF, et al. Simplified staging for hepatocellular carcinoma. J Clin Oncol 2002;20:1527– 1536. 15. Okuda K, Ohtsuki T, Obata H. Natural history of hepatocellular carcinoma and prognosis in relation to treatment: study of 850 patients. Cancer 1985;56:918–928. 16. Llovet JM, Bru C, Cruix J. Prognosis of hepatocellular carcinoma: the BCLC staging classification. Semin Liver Dis 1999; 19:329–338. 17. The Cancer of the Liver Italian Program (CLIP) Investigators. Prospective validation of the CLIP score: a new prognostic system for patients with cirrhosis and hepatocellular carcinoma. Hepatology 2000;31:840–845. 18. Kudo M, Chung H, Osaki Y. Prognostic staging system for hepatocellular carcinoma (CLIP score): its value and limitations, and a proposal for a new staging system, the Japan Integrated Staging Score (JIS score). J Gastroenterol 2003;38:207–215. 19. Farinati F, Rinaldi M, Gianni S, Naccarato R. How should patients with hepatocellular carcinoma be staged? Validation of a new prognostic system. Cancer 2000;89:2266–2273. 20. Zhao WH, Ma ZM, Zhou XR, et al. Prediction of recurrence and prognosis in patients with hepatocellular carcinoma after resection by use of CLIP score. World J Gastroenterol 2002;8: 237–242. 21. Bruix J, Llovet JM. Prognostic assessment and evaluation of the benefits of treatment. J Clin Gastroenterol 2002;35[Suppl 2]:S138–S142. 22. Levy I, Sherman M. Staging of hepatocellular carcinoma: assessment of the CLIP, Okuda, and Child-Pugh staging systems in a cohort of 257 patients in Toronto. Gut 2002;50:881–885. 23. Rabe C, Lenz M, Schmitz V, et al. An independent evaluation of modern prognostic scores in a central European cohort of 120 patients with hepatocellular carcinoma. Eur J Gastroenterol Hepatol 2003;15:1305–1315. 24. Ramacciato G, Mercantini P, Cautero N, et al. Prognostic evaluation of the new American Joint Committee on Cancer/ International Union Against Cancer staging system for hepatocellular carcinoma: analysis of 112 cirrhotic patients resected for hepatocellular carcinoma. Ann Surg Oncol 2005;12:289–297. 25. Marrero JA, Fontana RJ, Barrat A, et al. Prognosis of hepatocellular carcinoma: comparison of 7 staging systems in an American cohort. Hepatology 2005;42:707–716. 26. Grieco A, Pompili M, Caminiti G, et al. Prognostic factors for survival in patients with early-intermediate hepatocellular carcinoma undergoing non-surgical therapy: comparison of Okuda, CLIP and BCLC staging systems in a single Italian center. Gut 2005;54:411–418. 27. Kattan MW. Nomograms are superior to staging and risk grouping systems for identifying high-risk patients: preoperative application in prostate cancer. Curr Opin Urol 2003;13:111–116.
Vol. 206, No. 2, February 2008
28. Kattan MW, Leung DH, Brennan MF. Postoperative nomogram for 12-year sarcoma-specific death. J Clin Oncol 2002;20: 791–796. 29. Kattan MW, Karpeh MS, Mazumdar M, Brennan MF. Postoperative nomogram for disease-specific survival after an R0 resection for gastric carcinoma. J Clin Oncol 2003;21:3647– 3650. 30. Brennan MF, Kattan MW, Klimstra D, Conlon K. Prognostic nomogram for patients undergoing resection for adenocarcinoma of the pancreas. Ann Surg 2004;240:293–298. 31. Vauthey JN, Klimstra D, Francheschi D, et al. Factors affecting long-term outcome after hepatic resection for hepatocellular carcinoma. Am J Surg 1995;169:28–35. 32. Fong Y, Sun RL, Jarnagin W, Blumgart LH. An analysis of 412 cases of hepatocellular carcinoma at a Western center. Ann Surg 1999;229:790–800. 33. Cho CS, Knechtle SJ, Heisey DM, et al. Analysis of tumor characteristics and survival in liver transplant recipients with incidentally diagnosed hepatocellular carcinoma. J Gastrointest Surg 2001;5:594–602. 34. Nagasue N, Ono T, Yamanoi A, et al. Prognostic factors and survival after hepatic resection for hepatocellular carcinoma without cirrhosis. Br J Surg 2001;88:515–522. 35. Poon RTP, Fan ST, Lo CM, et al. Improving survival results after resection of hepatocellular carcinoma: a prospective study of 377 patients over 10 years. Ann Surg 2001;234:63–70. 36. Poon RTP, Fan ST, Lo CM, et al. Long-term survival and pattern of recurrence after resection of small hepatocellular carcinoma in patients with preserved liver function: implications for a strategy of salvage transplantation. Ann Surg 2002; 235:373–382.
Cho et al
Hepatocellular Carcinoma Nomogram
291
37. Ercolani G, Grazi GL, Ravaioli M, et al. Liver resection for hepatocellular carcinoma on cirrhosis: univariate and multivariate analysis of risk factors for intrahepatic recurrence. Ann Surg 2003;237:536–543. 38. Cha C, Fong Y, Jarnagin WR, et al. Predictors and patterns of recurrence after resection of hepatocellular carcinoma. J Am Coll Surg 2003;197:753–758. 39. Cha CH, Ruo L, Fong Y, et al. Resection of hepatocellular carcinoma in patients otherwise eligible for transplantation. Ann Surg 2003;238:315–323. 40. Liau KH, Ruo L, Shia J, et al. Outcome of partial hepatectomy for large (⬎10 cm) hepatocellular carcinoma. Cancer 2005;104: 1948–1955. 41. Shah SA, Greig PD, Gallinger S, et al. Factors associated with early recurrence after resection for hepatocellular carcinoma and outcomes. J Am Coll Surg 2006;202:275–283. 42. Poon RT, Fan ST, Ng IO, et al. Different risk factors and prognosis for early and late intrahepatic recurrence after resection of hepatocellular carcinoma. Cancer 2000;89:500–507. 43. Laurent C, Blanc JF, Nobili S, et al. Prognostic factors and longterm survival after hepatic resection for hepatocellular carcinoma originating from noncirrhotic liver. J Am Coll Surg 2005;201:656–662. 44. Ng KK, Vauthey JN, Pawlik TM, et al. International Cooperative Study Group on Hepatocellular Carcinoma. Is hepatic resection for large or multinodular hepatocellular carcinoma justified? Results from a multi-institutional database. Ann Surg Oncol 2005;12:364–373. 45. Portolani N, Coniglio A, Ghidoni S, et al. Early and late recurrence after liver resection for hepatocellular carcinoma: prognostic and therapeutic implications. Ann Surg 2006;243:229–235.