The authors have declared that no competing interests exist.
Conceived and designed the experiments: modw dn js podw ftk. Performed the experiments: modw dn js podw gs. Analyzed the data: modw js dn podw rl ps bg ftk mr. Contributed reagents/materials/analysis tools: modw dn ps tn gs cjz. Wrote the paper: modw dn ftk.
HCC is diagnosed in approximately half a million people per year, worldwide. Staging is a more complex issue than in most other cancer entities and, mainly due to unique geographic characteristics of the disease, no universally accepted staging system exists to date. Focusing on survival rates we analyzed demographic, etiological, clinical, laboratory and tumor characteristics of HCC-patients in our institution and applied the common staging systems. Furthermore we aimed at identifying the most suitable of the current staging systems for predicting survival.
Overall, 405 patients with HCC were identified from an electronic medical record database. The following seven staging systems were applied and ranked according to their ability to predict survival by using the Akaike information criterion (AIC) and the concordance-index (c-index): BCLC, CLIP, GETCH, JIS, Okuda, TNM and Child-Pugh. Separately, every single variable of each staging system was tested for prognostic meaning in uni- and multivariate analysis. Alcoholic cirrhosis (44.4%) was the leading etiological factor followed by viral hepatitis C (18.8%). Median survival was 18.1 months (95%-CI: 15.2–22.2). Ascites, bilirubin, alkaline phosphatase, AFP, number of tumor nodes and the BCLC tumor extension remained independent prognostic factors in multivariate analysis. Overall, all of the tested staging systems showed a reasonable discriminatory ability. CLIP (closely followed by JIS) was the top-ranked score in terms of prognostic capability with the best values of the AIC and c-index (AIC 2286, c-index 0.71), surpassing other established staging systems like BCLC (AIC 2343, c-index 0.66). The unidimensional scores TNM (AIC 2342, c-index 0.64) and Child-Pugh (AIC 2369, c-index 0.63) performed in an inferior fashion.
Compared with six other staging systems, the CLIP-score was identified as the most suitable staging system for predicting prognosis in a large German cohort of predominantly non-surgical HCC-patients.
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide
After all, it remains unclear which of the established staging systems should be preferred for a patient diagnosed with HCC. A precise answer to this question would facilitate not only clinical management of the individual patient but risk stratification in clinical studies, as well. This is a critical issue since a rising number of clinical studies can be noted due to the advent of effective systemic treatment options
The aim of this study was to compare the ability of seven established staging systems to predict survival for patients in a large western HCC population. The validation of the staging systems was preceded by a precise retrospective characterization of the study population in order to ensure proper interpretation of the validation data. Additionally, this analysis was designed to identify the most relevant single prognostic variables incorporated in the staging systems.
In this retrospective study, we identified HCC- patients treated at the Department of Medicine II of Munich's University Hospital between January 1998 and March 2009. The research study was approved by the ethics committee of the University of Munich and the need for written informed consent was waived, because the data were analyzed retrospectively and anonymously. Histological or radiological (AASLD radiologic criteria
Patients were identified from a data base collection in our institution, by using the International Classification of Diseases (ICD) code 150.0 for primary liver cancer. Clinical, tumor related and laboratory data needed to stage patients in all seven staging systems were retrieved from our electronic medical records. Additionally, a wide range of other parameters was compiled in order to further characterize our HCC-collective. The following data were collected: Age, sex, date of initial diagnosis, date of initial therapy, survival status, date of death, end of observation, liver cirrhosis, etiology, mode of therapy, Eastern Cooperative Oncology Group status (ECOG), Karnofsky-index, histology, ascites, hepatic encephalopathy (HE), portal vein thrombosis, portal hypertension, tumor extension, tumor burden (>/<50% of liver), number of tumor nodes, macroscopic vascular invasion, distant metastasis, lymph node involvement, BCLC tumor features ([1]: singular <2 cm, [2]: 3 nodules ≤3 cm or 1 nodule 2- ≤5 cm, [3]: multilocular, [4]: Portal invasion, N1, M1). Furthermore, the following laboratory parameters were retrieved in order to be able to calculate all tested staging systems: AFP, bilirubin, alkaline phosphatase, Quick and albumin.
In those cases without histology, the diagnosis of liver cirrhosis was made dependent on typical clinical signs of portal hypertension or on unequivocal radiological signs. Portal hypertension was diagnosed, if an elevated hepatic vein pressure above 10 mm/Hg, esophageal varices, splenomegaly or a platelet count below 100.000/µl were noted. Classification of ascites was performed according to the Child-Pugh score. Ascites detected by imaging but not visible on physical examination was termed mild, while the ascites was classified as “massive”, if clinically visible. Whenever exact classification of HE was missing in medical records, clinical signs of HE like tiredness, confusion and coma were used to retrospectively classify the respective HE grades I–IV
Whenever medical records did not include exact documentation of Karnofsky performance (KPS)
All treatment decisions were based on an interdisciplinary tumor composed of hepatologists, (interventional-) radiologists, oncologists and surgeons. Although the advent of staging systems including treatment recommendations according to specific stages like BCLC has had an impact on these boards, treatment allocation to date remains an individual approach.
All baseline tumor parameters necessary to characterize the HCC-cohort and to calculate the staging systems were obtained by reviewing radiology and pathology reports, respectively. When in doubt concerning certain tumor measurements a radiologist (C.Z.) with 8 years experience in abdominal CT and MRI reevaluated the baseline images. Regional lymph node involvement was assumed when suspect lymph nodes (>1 cm in diameter) were detected on MRI and CT, respectively. Information on survival was retrieved from the clinical records, whenever possible. In all other cases the primary care physician was contacted via telephone or fax.
Out of 405, 365 patients showed sufficient data to perform stratification according to Child-Pugh-score, 395 patients according to TNM, 373 patients according to Okuda, 352 patients according to CLIP, 341 patients according to BCLC, 358 patients according to JIS, and 304 patients according to GETCH. 290 Patients could be classified by all staging systems. In order to keep the numbers of patients with incomplete data as small as possible this cohort was enlarged to 354 patients by substituting missing values for laboratory parameters by the median (Bilirubin 1, Quick 2, AFP 11, Albumin 16, and AP 42 values). Ranking of scores was done for both cohorts of 290 and 354 patients, respectively. There were no substantial differences found, thus only values for the 354 patients are reported.
For statistical analysis SAS-Software [SAS V9.2, SAS Institute Inc., Cary, NC] was used. p<0.05 indicated statistical significance, with a p<0.0001 the parameter was considered to be of high statistical significance.
For univariate analysis overall survival was estimated by using the Kaplan-Meier method from the date of primary diagnosis of HCC to the date of death or last follow-up. Survival curves were compared using the log-rank test. Additionally to the p-value medians of survival time and 95% confidence intervals for the different strata are given. Both, single parameters and the whole scores were analysed concerning their prognostic significance. For Kaplan-Meier-analysis of continuous variables, one or more cut-off values are necessary; therefore, laboratory values were divided into quartiles.
While the univariate analysis was performed for all the patients showing the individual parameter, multivariate analysis relates only to the cohort of n = 354 patients who could be classified in all staging systems as described above. This number reflects those patients who could be classified in all staging systems. In order to keep the numbers of patients with incomplete data as small as possible, for calculating the scores and for multivariate analysis missing values for laboratory parameters were substituted by the median. In those parameters showing significance in univariate analysis using Cox proportional hazards regression model was conducted in order to examine their independent prognostic relevance. To avoid arbitrary cut-off values in this model laboratory values were taken as base two logarithms and used as continuous variables.
Ranking of staging systems was achieved by the Akaike information criterion (AIC)
The etiological factors for HCC are reported in
Etiological Factor | n | % |
|
180 | 44.4 |
|
76 | 18.8 |
|
60 | 14.8 |
|
24 | 5.9 |
|
23 | 5.7 |
|
10 | |
|
3 | |
|
3 | |
|
2 | |
|
1 | |
|
1 | |
|
1 | |
|
1 | |
|
1 | |
|
21 | 5.2 |
|
7 | 1.7 |
|
4 | 1.0 |
|
4 | 1.0 |
|
3 | |
|
1 | |
|
3 | 0.7 |
|
1 | |
|
1 | |
|
1 | |
|
3 | 0.7 |
|
3 |
Diagnosis of HCC was based on histology in 52.1% of patients. The most relevant clinical and demographic data of the patient population are depicted in
n | % | Median survival [months] | 95%-CI | p-value | |
|
0.163 | ||||
<64 Years | 199 | 49.1 | 15.5 | 12.2–18.8 | |
>64 Years | 206 | 50.9 | 23.1 | 18.1–29.7 | |
|
0.3872 | ||||
Female | 70 | 17.3 | 19.6 | 14.4–32.7 | |
Male | 335 | 82.7 | 17.2 | 14.4–21.7 | |
|
<0.0001* | ||||
0 | 219 | 60.7 | 22.9 | 16.9–28.8 | 0 vs. 1: 0.002* |
1 | 115 | 31.9 | 13.7 | 9.8–20.3 | 1 vs. 2: 0.061 |
2 | 21 | 5.8 | 3.9 | 2.1–23.1 | 2 vs. 3: 0.108 |
3 | 6 | 1.7 | 1.6 | 0.5–8.4 | |
|
0.0417* | ||||
No | 66 | 16.3 | 28.4 | 18.9–38.2 | |
Yes | 338 | 83.7 | 16.1 | 14.1–21.3 | |
|
<0.0001* | ||||
No | 266 | 66.5 | 25.6 | 21.1–29.7 | No vs. mo:<0.0001* |
Moderate | 89 | 22.3 | 11,.1 | 7.3–15.2 | Mo. vs. ma: <0.0001* |
Massive | 45 | 11.3 | 3.3 | 2.3–4.5 | |
|
0.1605 | ||||
No | 291 | 77.4 | 20.1 | 15.6–24.1 | |
Yes | 85 | 22.6 | 11.7 | 7.6–21.4 | |
|
0.0310* | ||||
No | 141 | 36.3 | 25.6 | 15.5–30.8 | |
Yes | 247 | 63.7 | 16.1 | 14.1–20.6 | |
|
<0.0001* | ||||
No | 327 | 81.6 | 21.4 | 17.2–25.6 | No vs. part: <0.0001* |
Partial | 54 | 13.5 | 6.0 | 3.9–15.2 | Part. vs. comp: 0.182 |
Complete | 20 | 5.0 | 4.4 | 1.9–9.2 |
(* = statistically significant). Mo = moderate, ma = massive, part = partial, comp = complete.
The results of the evaluation of baseline laboratory parameters that are part of some of the tested staging systems are summarized in
n | Min. | Lower Quartile | Median | Upper Quartile | 95th P*. | Max. | |
|
388 | 0.8 | 6.65 | 40.5 | 423.0 | 19788.0 | 577000.0 |
|
404 | 0.25 | 0.9 | 1.3 | 2.2 | 5.9 | 32.7 |
|
402 | 35.0 | 65.0 | 75.0 | 85.0 | 100.0 | 125.0 |
|
341 | 31 | 95 | 142 | 209 | 421 | 1371 |
|
378 | 1.4 | 3.3 | 3.8 | 4.2 | 4.8 | 5.1 |
(P* = percentile).
n | Median survival [months] | 95%-CI | p-value | |
|
overall <0.0001* | |||
¼ | 97 | 29.7 | 19.6–38.8 | ¼ vs. ½: 0.777 |
½ | 97 | 28.4 | 21.3–38.2 | ½ vs. ¾: 0.001* |
¾ | 97 | 14.4 | 10.0–17.2 | ¾ vs. 1: 0.017* |
1 | 97 | 8.6 | 6.0–12.7 | |
|
overall<0.0001* | |||
¼ | 98 | 28.8 | 22.5–34.0 | ¼ vs. ½: 0.214 |
½ | 109 | 18.9 | 15.6–28.4 | ½ vs. ¾: 0.55 |
¾ | 98 | 17.2 | 13.9–22.9 | ¾ vs. 1: 0.004* |
1 | 99 | 9.1 | 5.7–11.6 | |
|
overall 0.0215* | |||
¼ | 117 | 14.0 | 9.8–23.1 | ¼ vs. ½: 0.195 |
½ | 91 | 14.1 | 9.8–16.9 | ½ vs. ¾: 0.021* |
¾ | 98 | 25.3 | 15.2–32.7 | ¾ vs. 1: 0.371 |
1 | 96 | 23.4 | 16.8–30.8 | |
|
overall <0.0001* | |||
¼ | 88 | 9.2 | 6.2–14.1 | ¼ vs. ½: 0.37 |
½ | 93 | 13.5 | 10.5–18.3 | ½ vs. ¾: 0.133 |
¾ | 106 | 22.2 | 14.4–28.6 | ¾ vs. 1: 0.025* |
1 | 91 | 31.4 | 21.1–38.2 | |
|
overall <0.0001* | |||
¼ | 85 | 32,7 | 26,8–38,8 | ¼ vs. ½:0,150 |
½ | 85 | 27,6 | 21,7–48,1 | ½ vs. ¾: 0,030* |
¾ | 86 | 18,1 | 13,5–25,2 | ¾ vs. 1: <0,0001* |
1 | 85 | 6,4 | 4,5–9,8 |
(* = Statistically significant).
Tumor related data are summarized in
n | % | Median survival [months] | 95%-CI | p-value | |
|
<0.0001* | ||||
[1] Singular ≤2 cm | 19 | 4.7 | 47.4 | 23.1- | [1] vs. [2]: 0.376 |
[2] 3 ≤3 cm, singular ≤5 cm | 84 | 20.8 | 48.8 | 23.1–79.8 | [2] vs. [3]: p<0.0001* |
[3] Multilocular/multifocal | 191 | 47.3 | 18.6 | 15.6–24.1 | [3] vs. [4]: p<0.0001* |
[4] Portal vein infiltration, N1, M1 | 110 | 27.2 | 6.3 | 4.5–10.1 | |
|
<0.0001* | ||||
1 | 156 | 38.5 | 33.1 | 23.1–48.8 | 1 vs. 2: 0.108 |
2 | 74 | 18.3 | 24.1 | 21.1–32.7 | 2 vs. 3: 0.137 |
3 | 38 | 9.4 | 18.3 | 10.5–25.6 | 3 vs. 4: 0.024* |
>3 | 137 | 33.8 | 9.8 | 7.1–13.7 | |
|
<0.0001* | ||||
<50% | 354 | 87.4 | 22.5 | 18.1–25.9 | |
>50% | 51 | 12.6 | 3.6 | 2.3–7.0 | |
|
<0.0001* | ||||
No | 314 | 79.9 | 22.5 | 18.1–26.8 | |
Yes | 79 | 20.1 | 6.0 | 4.4–10.5 | |
|
0.0436* | ||||
<1 cm | 290 | 71.8 | 20.1 | 15.5–25.5 | |
>1 cm | 114 | 28.2 | 15.8 | 11.8–20.3 | |
|
<0.0001* | ||||
No | 378 | 93.6 | 20.1 | 16.1–23.1 | |
Yes | 26 | 6.4 | 6.2 | 3.5–12.2 |
(CI = confidence interval; * = statistically significant).
Therapy | n | % |
TACE | 215 | 53.1 |
Local ablation | 53 | 13.1 |
BSC | 47 | 11.6 |
Resection | 42 | 10.4 |
Sorafenib | 26 | 6.4 |
Tamoxifen | 12 | 3.0 |
Chemotherapy | 5 | 1.2 |
SIRT | 3 | 0.7 |
OLT | 2 | 0.5 |
(Local ablation = 37 TACE/RFA, 14 RFA, 2 PEI).
Median duration of follow-up was 14 months (range 0.2–113.1). By the end of follow-up in September 2009, 273/405 (67.4%) of the patients had died. Overall median survival was 18.1 months (95% CI: 15.2–22.2). The 1-, 3-, and 5-year overall survival rates were 63%, 29% and 17%, respectively (
Median survival was 18.1 months (95%-CI: 15.2–22.2). The 1-, 3-, and 5-year overall survival rates were 63%, 29% and 17%, respectively.
The following 16 parameters were associated with a significant impact on overall survival in
In
Hazard ratio for death | 95% CI | P | |
|
1.098 | 1.062 to 1.135 | <0.0001* |
|
1.612 | 1.345 to 1.932 | <0.0001* |
|
1.494 | 1.256 to 1.777 | <0.0001* |
|
1.534 | 1.258 to 1.870 | <0.0001* |
|
1.201 | 1.070 to 1.347 | <0.0019* |
|
1.561 | 1.278 to 1.907 | <0.0001* |
(* = Statistically significant).
Patient stratification and estimated median survival time according to the 7 staging systems are depicted in
(No cirrhosis vs. Child A: p = 0.459; Child A vs. Child B: p = 0.009*; Child B vs. Child C: p = 0.016*).
(TNM I vs. TNM II: p<0.0001*; TNM II vs. TNM III: p = 0.012*; TNM III vs. TNM IV: p = 0.03*).
(Okuda I vs. Okuda II: p<0.0001*; Okuda II vs. Okuda III: p = 0.001*).
(CLIP 0 vs. CLIP 1: p = 0.262; CLIP 1 vs. CLIP 2: p = 0.001*; CLIP 2 vs. CLIP 3: p = 0.023*; CLIP 3 vs. CLIP≥4: p = 0.005*).
(BCLC A vs. BCLC B: p = 0.001*; BCLC B vs. BCLC C: p = 0.018*; BCLC C vs. BCLC D: p = 0.005*).
(JIS 0 vs. JIS 1: p = 0.233; JIS 1 vs. JIS 2: p = 0.391; JIS 2 vs. JIS 3: p<0.0001*; JIS 3 vs. JIS 4: p<0.0001*; JIS 4 vs. JIS 5: p<0.0001*).
(GETCH “low risk group” vs. “medium risk group”: p<0.0001*; GETCH “medium risk group” vs.“high risk group”: p<0.0001*).
Staging System | n | % | Median survival [months] | 95%-CI | p-value |
|
<0.0001* | ||||
No cirrhosis (nc) | 66 | 18.1 | 28.4 | 18.9–38.2 | nc vs. A: 0.469 |
A | 130 | 35.6 | 24.1 | 16.8–30.1 | A vs. B: 0.0009* |
B | 120 | 32.9 | 11.8 | 9.1–16.9 | B vs. C: 0.016* |
C | 49 | 13.4 | 5.5 | 3.0–7.6 | |
|
<0.0001* | ||||
I | 122 | 30.9 | 47.4 | 25.3–63.8 | I vs. II: <0.0001* |
II | 108 | 27.3 | 23.4 | 19.6–30.1 | II vs. III: 0.012* |
III | 114 | 28.9 | 12.2 | 9.1–15.2 | III vs. IV: 0.03* |
IV | 51 | 12.9 | 5.4 | 3.5–11.6 | |
|
<0.0001* | ||||
I | 202 | 54.2 | 28.6 | 24.1–34.0 | I vs. II: <0.0001* |
II | 145 | 38.9 | 10.0 | 6.9–13.0 | II vs. III: 0.001* |
III | 26 | 7.0 | 2.5 | 1.6–7.5 | |
|
<0.0001* | ||||
0 | 43 | 12.2 | 63.8 | 14.7–93.9 | 0 vs. 1: 0.262 |
1 | 131 | 37.2 | 28.6 | 23.1–38.2 | 1 vs. 2: 0.001* |
2 | 80 | 22.7 | 14.4 | 11.8–20.3 | 2 vs. 3: 0.023* |
3 | 52 | 14.8 | 9.2 | 5.7–13.7 | 3 vs. ≥4: 0.005* |
≥4 | 46 | 13.1 | 3.3 | 2.0–3.8 | |
|
<0.0001* | ||||
A | 50 | 14.7 | 76.2 | 31.4- | A vs. B: 0.001* |
B | 99 | 29.0 | 20.6 | 15.8–29.7 | B vs C: 0.018* |
C | 138 | 40.5 | 13.7 | 9.2–19.0 | C vs. D: 0.005* |
D | 54 | 15.8 | 5.4 | 2.6–7.6 | |
|
<0.0001* | ||||
0 | 6 | 1.7 | 14.6- | 0 vs. 1: 0.233 | |
1 | 63 | 17.6 | 33.1 | 21.3–63.8 | 1 vs. 2: 0.391 |
2 | 135 | 37.7 | 28.8 | 20.3–32.7 | 2 vs. 3: <0.0001* |
3 | 85 | 23.7 | 12.2 | 9.4–19.0 | 3 vs. 4: <0.0001* |
4 | 56 | 15.6 | 4.7 | 3.5–6.0 | 4 vs. 5: <0.0001* |
5 | 13 | 3.6 | 2.0 | 0.5–3.3 | |
|
<0.0001* | ||||
Low | 103 | 33.9 | 34.8 | 28.4–49.5 | L vs. I: <0.0001* |
Intermediate | 176 | 57.9 | 14.2 | 11.6–19.0 | I vs. H: <0.0001* |
High | 25 | 8.2 | 2.7 | 1.7–4.4 |
(CI = Confidence interval; * = statistically significant).
Further statistical analysis was performed in order to identify the staging system with the best predictive ability for survival. As shown in
Rank | Score | c-index | 95% CI |
|
CLIP | 0.71 | 0.68 to 0.75 |
|
JIS | 0.70 | 0.66 to 0.74 |
|
Okuda | 0.66 | 0.63 to 0.69 |
|
BCLC | 0.66 | 0.62 to 0.69 |
|
GETCH | 0.64 | 0.61 to 0.67 |
|
TNM | 0.64 | 0.60 to 0.68 |
|
Child | 0.63 | 0.60 to 0.67 |
A higher c-index indicates better prognostic ability.
Rank | Score | AIC-Score |
|
CLIP | 2286 |
|
JIS | 2293 |
|
Okuda | 2337 |
|
GETCH | 2342 |
|
TNM | 2342 |
|
BCLC | 2343 |
|
Child | 2369 |
A Lower AIC value indicates better prognostic ability.
The performance of HCC staging systems always needs to be interpreted within the specific context of the examined study population. Therefore, an extensive characterization of the HCC-collective, going beyond the parameters needed for the staging systems, preceded the validation process in our study. The majority of patients were male (82.3%), and the median age of all patients was 63.4 years (range 27.8–84.8). These findings, as well as the fact that HCC predominantly arose in a cirrhotic liver (83.7%) are in line with most European HCC studies. In these studies, alcohol and HCV respectively have repeatedly been identified as the two leading etiologic factors for HCC in Europe
Many recent validation studies applied the staging systems to more selected groups of patients
Overall median survival was 18.1 months and 5-year overall survival rate was 17%. Our survival data are comparable to another recent study from southern Germany, which showed an overall median survival of 19 months in a group that included more resectable HCC patients
Identification of prognostic factors within a given study population is the basis on which all staging systems have been developed. In the present study, a broad range of clinical, laboratory and tumor parameters showed statistical significance in
A clear recommendation which staging system to choose for HCC patients, is of great importance for clinical decisions as well as planning of interventional studies
There are some potential limitations of this study. First, the retrospective fashion of the data collection resulted in a lack of data in some cases. Especially parameters like ECOG and HE are subject to interpretation and are more easily obtained in a prospective study. We tried to control this problem by applying standardized methods of obtaining these data. Furthermore, the good quality of our clinical database helped to retrieve all the necessary data, even retrospectively. Because of the clinical significance of the parameters needed for calculation of the scores, these values were available for most of the patients at time of diagnosis despite the retrospective character of this study. Second, relatively few patients were in the very early and early stages, limiting the value of our data for surgical cohorts and probably underestimating the prognostic capability of the TNM system, which is traditionally strong in surgical HCC patients. Finally, due to major differences in epidemiology as well as clinical and tumor parameters, applicability of our results obtained in a western HCC cohort to other geographic regions (i.e. Asia) is limited.
In conclusion, our results indicate that in non-selected western HCC patients the Cancer of the Liver Italian Program-score (CLIP) (closely followed by JIS) is the best performing staging system among the seven currently used prognostic models.
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