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Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

Sorafenib improves overall survival (OS) of patients with hepatocellular carcinoma (HCC) in the absence of objective response. Thus, time to tumor progression (TTP) is used to capture benefits of novel molecular agents, but proof of its surrogacy with survival is lacking. Furthermore, survival predictors upon progression are not established and there is a need to characterize postprogression survival (PPS) and assess with time-dependent covariates analysis if it is influenced by progression pattern, and not solely by simultaneous impairment of liver function and performance status. We prospectively followed HCC patients treated with sorafenib. Clinical and biochemical evaluation were done every 4 weeks. Radiologic assessment of progression was done at week 4 and then every 8 weeks using RECIST 1.1. The progression pattern was divided into: intrahepatic/extrahepatic increase in tumor size, new intrahepatic lesion, and new extrahepatic lesion (NEH). We included 147 patients (hepatitis C virus [HCV] 57.1%, performance status [PS] 0 83.6%, Child-Pugh A 82.3%, and BCLC-C 47.3%). The median OS was 12.7 months and its independent predictors (hazard ratio [HR], 95% confidence interval [CI]) were: baseline BCLC 2.49 [1.66-3.73], PS 1.86 [1.12-3.10], registration during follow-up of Child-Pugh B or Child-Pugh C scores (2.36 [1.51-3.69] and 2.89 [1.62-5.15], respectively), definitive sorafenib interruption 2.48 [1.54-4.01], and TTP 3.39 [1.89-6.1]. The presence of NEH 2.42 [1.32-4.44] is also an independent predictor of OS and PPS in patients with radiologic progression. Conclusion: Tumor progression is a surrogate of survival but its impact varies according to progression pattern. Thus, PPS is influenced by progression pattern and this is key in prognostic prediction and second-line trial design and analysis. (Hepatology 2013; 58:2023–2031)

Abbreviations
BCLC

Barcelona Clinic Liver Cancer

EHG

extrahepatic growth

HCC

hepatocellular carcinoma

HCV

hepatitis C virus

IHG

intrahepatic growth

NEH

new extrahepatic lesion

OS

overall survival

PFS

progression-free survival

PPS

postprogression survival

PS

performance status

TTP

time to tumor progression

Sorafenib improves the overall survival (OS) of hepatocellular carcinoma (HCC) patients in the absence of objective response.[1] This has brought about the emergence of time to tumor progression (TTP) or progression-free survival (PFS) as better endpoints for detecting and capturing the benefits of novel molecular agents. However, the correlation between TTP and OS or PFS and OS has not been established in HCC.[2-4] Indeed, a phase 3 trial comparing sorafenib versus sunitinib showed a similar PFS but OS was significantly better in sorafenib-treated patients.[4] As in other cancer types, it is necessary to study postprogression survival (PPS) and define if progression pattern and treatment upon progression emerge as major confounders in understanding the OS data.[5-8]

This study of HCC patients treated with sorafenib investigates the correlation between tumor progression at imaging and survival using time-dependent covariate analysis.[9] In addition, we ascertain whether the patterns of tumor progression (growth versus new lesion, intrahepatic versus extrahepatic) have a different impact on OS and PPS. If OS was to vary according to pattern of progression, this would have to be taken into account when informing patients in clinical practice about life expectancy during disease evolution. At the same time, it would provide the background for changing the current design of clinical trials.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

This prospective study considered all patients referred between March 2008 and July 2011 for sorafenib treatment according to the Barcelona Clinic Liver Cancer (BCLC) strategy.[2, 10]

Inclusion criteria were: (1) HCC diagnosed according to American Association for the Study of Liver Diseases (AASLD) guidelines[2, 11]; (2) the presence of a naïve target lesion; (3) adequate liver function (albumin >2.8 g/dL; total bilirubin <3 mg/dL, and alanine and aspartate aminotransferases <5 times the upper limit of the normal range), and Child-Pugh score ≤7 points; (4) performance status (PS) 0-1; (5) controlled arterial hypertension and/or stable peripheral vascular disease; (6) adequate hematologic profile (platelet count >60 × 109/L, hemoglobin >8.5 g/dL, and prothrombin time >50%); and (7) adequate renal function (serum creatinine <1.5 times the upper limit of the normal range).

Exclusion criteria were: (1) myocardial infarction in the past year or active ischemic heart disease; (2) acute variceal bleeding in the past month; 3) severe peripheral arterial disease; (4) cardiac arrhythmia under treatment with drugs other than beta-blockers or digoxin; (5) uncontrolled ascites; (6) encephalopathy; or (7) inability to fulfill the follow-up schedule.

All patients provided written informed consent before enrolment. The study was approved by the Institutional Review Board and complied with the provisions of the Good Clinical Practice guidelines and the Declaration of Helsinki.

Outcomes and Assessments

TTP was defined as the time from the date of starting sorafenib to disease progression. Radiologic evaluation of response during follow-up was done by computed tomography (CT) scan according to the response evaluation criteria in solid tumors (RECIST) v.1.1[12] with the amendments were implemented in the pivotal SHARP trial that ultimately were reflected in the mRECIST proposal.[3, 13] We registered the cause of progression (patterns of progression): ≥20% increase in tumor size against a known baseline lesion (intrahepatic growth [IHG] or extrahepatic growth [EHG]), new intrahepatic lesion (NIH), or new extrahepatic lesion and/or vascular invasion (NEH).

Radiology assessment was blinded to the evolution and outcome of the patients. Those patients who died before the first imaging assessment were classified as progressors. OS was measured from the date of starting sorafenib until the date of death. PPS was measured from the date of detecting progression at radiology until the date of death or last follow-up.

The relationship of OS with TTP and with OS predictors was determined in the whole cohort. We also assessed the impact of progression pattern on OS and PPS in patients with radiologic progression. Moreover, we did a subanalysis of patients who, because of adequate liver function and preserved PS, were still fit for second-line treatment in research trials. This subgroup of patients represents the population where a competing risk due to liver function impairment is excluded, as occurred in the pivotal sorafenib trials[1, 14] (Fig. 1).

image

Figure 1. Enrollment and outcomes. Radiologic tumor progression: patients with tumor progression at radiology. Candidates for second-line trials: patients who would fulfill the inclusion criteria for second-line trials (patients with tumor progression but with preserved PS and liver function). SD: stable disease; PR: partial response; CR: complete response.

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Treatment

Sorafenib was initiated at full dose (800 mg/day), which was modified upon development of adverse events according to the manufacturer's recommendations. Treatment was continued until symptomatic progression, unacceptable adverse events, or death.

Follow-up

Clinical and laboratory assessment were done monthly and radiology tumor evaluation at week 4 and afterwards every 8 weeks. Adverse events were graded according to v. 3.0 of the CTCAE of the National Cancer Institute, during treatment and 30 days after the last dose.

Statistical Analysis

Categorical variables are described as frequencies and percentages and continuous variables as median and percentiles 25 and 75 (P25-P75). Times to event data were estimated by Kaplan-Meier with plots and median (95% confidence interval [95% CI]). Fisher's exact test was used to compare categorical variables and the Cochran-Armitage test to assess trends. The Mann-Whitney method was used to compare ordinal and continuous variables.

To define the predictors of OS we took into account the following baseline parameters: PS (0/1), Child-Pugh score (A/B 7 points), BCLC (B/C), extrahepatic spread (yes/no), total bilirubin, albumin, alpha-fetoprotein (AFP) (continued and categorized using median, tertiles, and three predefined different cutoffs [20, 200, 400]) and prior treatment (PEI/RFA/surgery). Moreover, we also assessed the impact of registering the transition from Child-Pugh A (used as reference) into Child-Pugh B or C. Using this approach, the analysis introduces registration of Child-Pugh B or Child-Pugh C at a timepoint as one of the different time-dependent events that have been tested. These also include a change in PS (using PS 0 as reference), sorafenib dose modification (full dose as reference), presentation of encephalopathy and/or untreatable ascites, decrease in prothrombin time below 50%, albumin below 2.8 mg/dL, and AFP. Analysis of AFP was done using the same cutoffs (median, tertiles, 20, 200, 400) as for the baseline. All statistics involving evolutionary events were done by means of time-dependent covariate analyses.[9] The inferential analysis for time to event data was conducted using the Cox univariate and multivariate regression model with time-dependent covariates to estimate hazard ratios (HR) and 95% CI.[9] Statistically significant variables from the univariate Cox analysis, progression pattern, and relevant variables from a clinical point of view were consistently included in the multivariate models, while also ensuring that the multivariate HR estimators did not change significantly when excluding those variables with P > 0.1.

When specified, adjusted survival functions from that Cox model were used to draw survival plots. The analysis was performed using SAS v. 9.2 software (SAS Institute, Cary, NC), SPSS v. 18 (SPSS, Chicago, IL), and significance was established at the 0.05 level (two-sided).

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

Between March 2008 and July 2011, 229 patients were assessed for sorafenib treatment. In all, 147 patients were enrolled and 82 patients were excluded as per inclusion and exclusion criteria (Fig. 1).

At the time of database lock (May 2012), the median follow-up was 11.6 months (range: 0.4-51.8): 111 died, 28 out of 147 patients were still alive (with seven continuing sorafenib), and eight were lost to follow-up.

Baseline Characteristics

Clinical and laboratory baseline characteristics are summarized in Table 1. All but four patients were cirrhotic. The most frequent etiology of cirrhosis was hepatitis C virus (HCV; 57.1%), followed by alcohol abuse (25.2%) and hepatitis B virus (HBV;11.6%). The majority of the patients were asymptomatic (PS-0 83.6%) and 77 (52.3%) were BCLC-B who failed or presented contraindication to surgery or locoregional treatment. Fifty-one patients (34.7%) presented vascular invasion, 121 patients (82.3%) were Child-Pugh A class. Sixty-five patients had not received previous therapies. None of the patients had received systemic therapy.

Table 1. Demographic and Baseline Characteristics of the Patients (Intention-to-Treat Population)
 Total cohort (n = 147)
  1. IQR: interquartile range [percentile 25 – percentile 75]; HCV: hepatitis virus C; HVB: hepatitis virus B; PS: prformance status; BCLC: Barcelona Clinic Liver Cancer classification; PT: prothrombin time; HB: hemoglobin; ASAT: aspartate aminotransferase; ALAT: alanine aminotransferase; AP: alkaline phosphatase; GGT: gamma-glutamyltranspeptidase.

  2. a

    Four patients with noncirrhotic liver.

Age, median [IQR] (years)64.1 [55.8-71.9]
Male/Female, n124/23
HCV/Ethanol/HVB/others, n84/37/17/9
*Child-Pugh A/B121/22/4
Vascular invasion yes/no, n51/96
Extrahepatic spread, yes/no, n27/120
BCLC stage, B/C, n77/70
Performance status, 0 /1, n123/24
AFP, median [IQR] (ng/dL)32 [7- 596]
PT,median [IQR] (%)83 [70-93]
Bilirubin, median [IQR] (mg/dL)1 [0.7-1.6]
Albumin, median [IQR] (g/dL)39 [36-43]
HB, median [IQR] (mg/dL)13.5 [12.0-14.8]
ASAT, median [IQR] (UI/L)68 [44-101]
ALAT, median [IQR] (UI/L)62 [39-103]
AP, median [IQR] (UI/L)292 [208-423]
GGT, median [IQR] (109/L)149 [78-256]
Platelets, median [IQR] (109/L)131 [84-193]
Systolic arterial pressure, median [IQR], mmHg130 [119-140]
Diastolic arterial pressure, median [IQR], mmHg76 [69-81]
Treatment, Adverse Events, and Dose Modification

The median duration of treatment was 6.7 months (range: 0.26-35). All but one patient presented at least one adverse event and all but four needed at least one dose modification. Table 1B in the Supporting Material shows the main reasons for definitive interruption. Seventy-four patients presented definitive interruption due to PS deterioration. Sixty-one of these 74 patients presented radiologic progression at the same time. Moreover, simultaneous radiologic progression was also observed in 11/14 patients who developed ascites and in 7/8 who presented encephalopathy. There were no deaths related to treatment.

Overall Survival and Radiologic Evaluation

The median OS was 12.7 months (95% CI; 10.3-15.2; P33: 8.2, P66: 16.1 months) (Fig. 2A). The response rate was: stable disease (SD) in 36 patients (24.5%), partial response in two patients, and complete response in one patient. Tumor progression occurred in 108 patients (73.5%). Median TTP was 5.1 months (95% CI; 3.7-6.4) (Fig. 2B). OS was significantly different when dividing patients according to median TTP (9.9 months versus 20.1 months; P < 0.001).

image

Figure 2. (A) Kaplan-Meier OS estimation for the whole cohort. Among 147 patients, the median OS was 12.7 months (95% CI 10.3-15.2). (B) Kaplan-Meier estimation of TTP for the whole cohort. Among 147 patients, the median TTP was 5.1 months (95% CI 3.7-6.4).

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Relationship Between Pattern of Progression and Overall Survival

The median OS in patients with radiologic tumor progression due to ≥20% increase in tumor size (IHG, n = 41; EHG, n = 9), NIH (n = 20), or NEH (n = 15) was 16.8, 10.7, 15.6, and 12.2 months, respectively. By the end of follow-up the patients still continuing with SD and partial/complete response (PR/CR) had an OS of 17.2 and 29.7 months.

Predictors of OS

The univariate analysis of the whole cohort identified four baseline predictors of OS (HR; 95% CI) (Table 2B of Supporting Material). As shown, baseline AFP and its evolution during treatment, as well as therapeutic interventions prior to sorafenib, were not statistically significant. The multivariate Cox analysis restricted them to: baseline BCLC, 2.49 (1.66-3.73) and baseline PS 1.86 (1.12-3.10) (Table 2).

Table 2. Multivariate Cox Analysis of Overall Survival
Multivariate Analysis
 Whole Cohort n = 147Radiologic Tumor Progression n = 85Candidates for 2nd Line Trials n = 43
HR [95% CI]P valueHR [95% CI]P valueHR [95% CI]P value
  1. NA: not applicable; PS: performance status; BCLC: Barcelona Clínic Liver Cancer classification; Transitory inter: transitory interruption; Intrahepatic growth: intrahepatic increase ≥20% of the tumor size in lesion previously documented; Extrahepatic growth: extrahepatic increase ≥20% of the tumor size in lesion previously documented.

  2. All shown variables were included in the multivariate Cox model for each population. In this case, estimates were obtained with the pattern of progression and not with the binary progression variable; however the results substituting pattern of progression with the binary progression variable were consistently similar (data not shown).

Baseline
PS (reference 0)1.86 [1.12 - 3.1]0.0172.77 [1.23 - 6.26]0.0142.81 [0.44 - 17.91]0.275
BCLC (reference B)2.49 [1.66 - 3.73]<0.0011.84 [1.09 - 3.13]0.0241.98 [0.81 - 4.82]0.134
Evolutionary event
Child Pugh score modification (reference A)1<0.00110.00810.043
Child-Pugh B (7-9 points)2.36 [1.51 - 3.69] 2.23 [1.25 - 3.97] 2.38 [1.07 - 5.33] 
Child-Pugh C (> 9 points)2.89 [1.62 - 5.15] 2.86 [1.31 - 6.22] 4.66 [0.98 - 22.07] 
Sorafenib dose (reference full dose)1<0.0011<0.00110.003
Reduction/transitory interruption0.54 [0.27 - 1.07] 0.54 [0.23 - 1.27] 0.28 [0.08 - 0.97] 
Definitive interruption2.48 [1.54 - 4.01] 2.42 [1.33 - 4.39] 2 [0.82 - 4.87] 
Tumor response (RECIST v1.1)
Progression3.39 [1.89 - 6.1]<0.001NA (whole progressors)
Type of progression
Intrahepatic growth  1.7 [0.96 - 3.02]0.0691.51 [0.65 - 3.47]0.336
Extrahepatic growth  2.39 [1.15 - 4.96]0.0192.60 [0.91 - 7.44]0.074
New intrahepatic lesion  1.15 [0.59 - 2.22]0.6811.62 [0.62 - 4.21]0.324
New extrahepatic lesion  2.42 [1.32 - 4.44]0.0042.81 [1.09 - 7.27]0.033

Afterwards, we analyzed if each of the evolutionary covariate changes during the treatment had any impact on OS, with statistical methodology that properly takes into account both baseline and evolutionary parameters.[9] We identified eight additional predictors of OS in the univariate analysis. However, the multivariate Cox analysis restricted them to: registration during follow-up of Child-Pugh B or Child-Pugh C scores (2.36, 1.51-3.69; and 2.89, 1.62-5.15, respectively), definitive sorafenib interruption: 2.48 (1.54-4.01), and radiologic tumor progression 3.39 (1.89-6.1) (Table 2). The baseline and the evolutionary predictors were maintained when we excluded the 23 patients without radiologic tumor progression. In addition, progression due to NEH (2.42, 1.32-4.44; or EHG 2.39, 1.15-4.96) was added as independent OS predictors in patients with radiologic tumor progression (Table 2).

Postprogression Survival

We excluded 23/147 patients from the analysis of PPS because they did not have at least one image evaluation and those 39 who had not presented radiologic progression at the time of database lock. Median PPS in the 85 patients with radiologic progression was 9.85 months (95% CI: 7.3-12.5). BCLC stage, PS, and Child-Pugh status, which were evaluated at the time of progression, together with progression due to NEH were the independent predictors of PPS (Table 3).

Table 3. Multivariate Cox Analysis of Postprogression Survival in Patients With Radiologic Tumor Progression Under Sorafenib Treatment
 Radiologic Tumor Progression n = 85Candidates for 2nd Line Trials n = 43
HR [95% CI]P valueHR [95% CI]P value
  1. BCLCp-B: Patients with radiologic progression but still within BCLC-B stage, being Child-Pugh ≤7 without ascites or encephalopathy; BCLCp-C: Patients with radiologic progression corresponding to BCLC-C including those who were already BCLC-C already at baseline, and being Child-Pugh ≤7 without ascites or encephalopathy.

  2. NA: not applicable.

Clinical and tumor status at the progression
BCLCp- B patients (reference compensated)10.00810.336
BCLCp- B patients decompensated1.4 [0.69 - 2.87] NA 
BCLCp- C patients compensated1.59 [0.73 - 3.45] 1.47 [0.67 - 3.2] 
BCLCp- C patients decompensated3.53 [1.61 - 7.73] NA 
Pattern of progression which determined the tumor progression
Intrahepatic growth (yes/no)1.75 [0.94 - 3.23]0.0761.3 [0.56 - 2.99]0.540
Extrahepatic growth (yes/no)1.17 [0.57 - 2.44]0.6671.75 [0.63 - 4.88]0.285
New intrahepatic lesion (yes/no)1.19 [0.61 - 2.33]0.6191.58 [0.6 - 4.19]0.355
New extrahepatic lesion (yes/no)1.9 [1.04 - 3.49]0.0383.01 [1.17 - 7.76]0.023
PPS in Potential Candidates for Second-Line Trials

The PPS of the previously defined subgroup of patients who would still be fit for second-line treatment was 13.6 months (95% CI: 9-18.2) (Fig. 3). PPS was significantly different (P = 0.034) according to BCLC stage at progression and according to progression pattern (P = 0.013) (Figs. A2 and A3 in Supporting Material). Thereby, BCLC-C patients with NEH had a significantly worse PPS than those without it (7.1 versus 14.9 months, P = 0.02) (Fig. 4).

image

Figure 3. PPS curve estimated from the Cox model in patients candidates for second-line trials. IHG: intrahepatic increase ≥20% of the tumor size in lesion previously documented. EHG: extrahepatic increase ≥20% of the tumor size in lesion previously documented. NIH: new intrahepatic lesion NEH: new extrahepatic lesion and/or vascular invasion.

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image

Figure 4. PPS curves estimated from the Cox model in BCLCp-C patients candidates to second-line trial divided according to the absence or presence of new extrahepatic lesions / vascular invasion (n = 25). BCLCp-C1: Patients BCLC-C under sorafenib treatment with progression due to growth of existing nodules or new intrahepatic sites. BCLCp-C2: Patients BCLC-C under sorafenib treatment with progression due to new extrahepatic lesion and/or vascular invasion.

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Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

Systematic review studies in lung,[6, 7] breast,[8] and colorectal[15] cancer have stressed the need to analyze PPS as a potential confounder for OS. Interestingly, no study has established the correlation between progression and survival in patients with HCC, and there are no data about the predictors of survival after progression. Furthermore, no investigation has focused on the potential outcome differences according to the pattern of progression. As a whole, the current use of TTP as a signal to detect therapeutic efficacy is not supported by robust data gathered using proper statistical methods that take into account time-dependent covariates.

Our results show for the first time that tumor progression at imaging has a significant correlation with OS in patients with HCC and, thus, validate the use of TTP as a valid endpoint in early phase studies to evaluate the potential efficacy of novel molecular agents. Together with this association, we show that survival after progression (PPS) is significantly different according to the progression patterns. Indeed, PPS may correlate better with OS than PFS.[5, 7, 8, 15] The review of www.clinicaltrials.gov and recently published trials in breast, lung, colorectal, and HCC shows that progression pattern is not considered in the evaluation of the patients to define prognosis and/or to stratify patients prior to randomization. Interestingly, a panel of several leading experts in oncology has stressed the need to further dissect the prognostic meaning of the different types of progression that may be encountered and has called for prospective studies to characterize PPS and its outcome predictors,[5] as we have done in our population of HCC patients.

HCC is a distinct cancer, as most cases occur in the setting of an underlying chronic liver disease.[10] HCC transitions from an early solitary nodule to multifocal intrahepatic spread associated or not with vascular invasion and/or extrahepatic dissemination to lymph nodes and other organs. This evolutionary profile is similar to that of other solid tumors that may progress, affecting the organ of primary origin or spread beyond it. This different tumor stage during the evolution is the backbone of the BCLC model[10] that has been widely endorsed for HCC patient stratification and treatment allocation.[2, 16, 17]

Our data reinforce the prognostic value of the baseline parameters of the BCLC model in patients under systemic treatment. Not unexpectedly, we saw the need to also consider the evolutionary events such as severe liver function impairment and definitive sorafenib interruption as predictors of poorer OS. However, the major novelty relies on the demonstration that the radiologic progression pattern should also be taken into account for prognostic assessment. This is so, even in patients already BCLC-C at baseline. As shown in Fig. 4, survival of BCLC C patients after imaging progression is significantly different according to the absence or presence of NEH. Thus, while the BCLC stage retains its value, it is necessary to refine the BCLC definitions at the time of radiologic progression in order to properly predict the prognosis of patients still fit to enter into second-line studies because of preserved liver function (Child-Pugh A) and preserved PS (0-1). This “BCLC upon progression” (BCLCp) proposal (Fig. 5) defines as BCLCp-B those patients who present radiologic progression due to growth of existing nodules ≥20% or new intrahepatic sites, but are still within BCLC-B because of the absence of vascular invasion or extrahepatic spread or cancer related symptoms (PS 0). By contrast, those patients who present radiologic progression and evolve to BCLC-C or progress within BCLC-C are divided at the time of progression into BCLCp-C1 (growth of existing nodules ≥20% or new intrahepatic sites) and BCLCp-C2: (progression due to new extrahepatic lesion and/or vascular invasion).

image

Figure 5. BCLC stratification upon radiology progression. This “BCLC upon progression” (BCLCp) proposal classifies as BCLCp-B those patients who present radiologic progression due to growth of existing nodules ≥20% or new intrahepatic sites but are still within BCLC-B because of the absence of vascular invasion or extrahepatic spread or cancer-related symptoms (PS 0). Those patients who present radiologic progression and evolve to BCLC-C or progress within BCLC-C are divided at the time of progression into: BCLCp-C1: those patients who present radiologic progression due to growth of existing nodules ≥20% or new intrahepatic sites, and BCLCp C2: those patients who present progression due to new extrahepatic lesion and/or vascular invasion.

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We decided to focus our interest on patients with at least one imaging evaluation because these are the patients who are considered for second-line trials. For this reason, the PPS analysis had to exclude the 23 patients without image follow-up. Patients to be considered for second-line trials are a selected population that is not well characterized. They may present a more indolent disease evolution that is not associated with an impaired PS or deteriorated liver function. Our data show that progression pattern is a major determinant of PPS. Thus, if pattern of progression is not considered in trial design and evaluation, the results of second-line trials with a survival endpoint may be flawed. It could be argued that clinical progression due to liver failure may be due to cancer progression that has not been detected by radiology. However, this does not diminish the value of our data for second-line research trials. In them, the starting time for potential recruitment for such trials is defined by the recognition of progression at radiology without simultaneous clinical impairment as per liver function and PS. It could also be argued that tumor progression is not regularly monitored in conventional practice, but this is not common, as patients and physicians are usually keen to ascertain whether the disease is progressing. In addition, in some settings radiologic progression is taken as treatment failure and sorafenib may be interrupted and/or not reimbursed. It could also be suggested that, in the absence of effective second-line options, there is no need to define progression pattern. Again, prognosis information is valued by patients and, most important, future trials should be designed taking into account this, up to now, neglected aspect. Finally, a potential confounder related to treatment received upon progression is not possible in our study because patients were not shifted to other options.

These results may also affect the understanding of the results of first-line trials. Sorafenib is the sole approved agent for systemic therapy and new agents are tested head-to-head, or in combination with sorafenib versus sorafenib alone following in most instances the design of the pivotal SHARP trial[1] based on the BCLC strategy. Overall survival is the accepted primary endpoint in such a setting, but some studies take PFS as the endpoint and treatment may be cancelled at the time of progression. In such instances, similar results in PFS may be followed by negative data on survival simply because of an unbalanced distribution of progression pattern and therefore PPS.[4] As a consequence, the PFS endpoint should probably be refined to accommodate the fact that tumor progression pattern implies a specific impact on prognosis and/or reflect the aggressiveness of the tumor itself either at baseline or modified because of the treatment applied.

It is interesting to note that our data do not demonstrate any predictive power of AFP either at baseline or during follow-up. We conducted a time-dependent covariates analysis[9] of AFP (determined every 4 weeks and not at predefined timepoints such as 1 or 3 months), as well as all the conventional laboratory parameters, and also applied a multivariate analysis to rule out relevant confounders such as impaired PS or Child-Pugh deterioration. This is likely the basis for the discrepancy with other studies that have suggested a value for AFP.[18-21] In addition, we also explored the impact of prior treatments for HCC. As shown, prior treatment or its absence due to initial diagnosis at an already advanced stage was not deemed significant. However, it has to be acknowledged that such data are not fully robust because of its retrospective nature, as is also the case in all phase 3 trials conducted on advanced HCC patients. Collection of data on prior therapeutic interventions (resection, ablation, locoregional therapies) with evaluation of initial response and time and type of recurrence before sorafenib treatment would be feasible only in population-based investigations with full control of information loss due to referral patterns and a confounding effect of the heterogeneous application of treatment in different centers.

In summary, our results using time-dependent covariate analysis establish for the first time the relationship between tumor progression and OS in HCC patients treated with sorafenib. In addition, we establish the correlation between progression pattern and PPS. Thus, these data need to be considered in daily practice for informing patients about their life expectancy and also in research on trial design and analysis in HCC patients.

Acknowledgment

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

We thank Mrs. Ingrid Rengel, Nuria Perez, and Jenny Brickman for contributions to this article.

References

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgment
  7. References
  8. Supporting Information

Additional Supporting Information may be found in the online version of this article.

FilenameFormatSizeDescription
hep26586-sup-0001-suppinfo.doc93KSupporting Information
hep26586-sup-0002-suppfig2.tif2147KSupporting Information Figure 2: Kaplan-Meier post-progression survival according to BCLCp in patients candidates for 2nd line trials.
hep26586-sup-0003-suppfig3.tif2700KSupporting Information Figure 3: Kaplan-Meier post-progression survival according to pattern of progression in patients candidates for 2nd line trials.

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