Abstract
Introduction:
Maximum tumor diameter (MTD) is one of the key aggressiveness features of hepatocellular carcinoma (HCC). However, the clinical associations and causes of large size HCC are not well understood. The aims is to compare small and large MTD (≤/> 6cm) HCCs with respect to clinical associations.
Methods:
MTD ≤/> 6cm HCCs were compared by clinical characteristics and analyzed through logistical regression models, as well as Cox proportional hazard models for death, on clinical parameters.
Results:
Patients with larger HCCs had more portal vein thrombosis (PVT) and tumor multifocality, higher AST, ALKP and GGT levels and lower albumin levels. A logistic regression model of MTD (≤/> 6cm) showed the highest risk for PVT and platelet-lymphocyte ratio (PLR) >150, while albumin and female gender were protective. Combination male gender, PLR >150 plus PVT had an odds ratio of 12.124. In Cox proportional hazard models, the highest hazard ratio for death was for PVT, and only albumin was significantly protective. PVT plus low albumin had a hazard ratio of 4.254.
Conclusion:
PVT, albumin, PLR and gender were significant for ≤/> 6cm MTD. PVT and albumin were significant for survival.
Keywords: HCC, MTD, PVT, albumin, gender, PLR, survival
Introduction
Hepatocellular carcinoma (HCC) aggressiveness factors include maximum tumor diameter (MTD), malignant portal vein thrombosis (PVT), multifocality and serum alpha-fetoprotein (AFP) levels. HCC growth-dependent MTD is important as it determines and limits the choice of optimal therapy, with liver transplant and radiofrequency ablation having recommended size limitations associated with their optimal use [1–4]. Best treatment results across most tumor types are determined in large part (but not only) by how early in the disease progression the tumor is diagnosed [5–7]. However, even MTD is not a sole factor, as even large HCCs are heterogeneous, with variation in the associated inflammation being well-studied [9] and significant for survival [10]. Thus, large HCCs may or may not have differences in their associated Child-Pugh determined level of cirrhosis and thus their biology, which in turn will in-fluence treatment options, such as resectability), as well as survival [11], which is determined by both cirrhosis factors as well as by tumor factors.
The purpose of the present study was to attempt to identify clinical features associated with larger MTD and to also determine the clinical features associated with longer or shorter survival. We found that the features associated with both MTD>6cm and survival were remarkably similar and included malignant PVT and platelet-lymphocyte ratio (PLR), while protective features included albumin, while female gender appeared protective for larger HCCs but not survival.
Methods
Clinical.
A clinical HCC database with 6759 patients was examined, that we previously interrogated [9]. The data was collected from the Italian Liver Cancer (ITA.LI.CA) database of HCC patients. ITA.LI.CA database management conforms to Italian legislation on privacy and this study conforms to the ethical guidelines of the Declaration of Helsinki.
This study protocol was reviewed and approved by Independent Ethic Committee of S. Orsola-Malpighi hospital of Bologna, which operates as coordinating center of the ITA.LI.CA network., approval number [protocol n. 99/2012/O/Oss, 2022/3905], and Inonu university IRB, approval number [2022/3905], for analysis of de-identified and deceased HCC patients. All patients provided written informed consent.
Patients had routine hematology, liver functions tests, Child-Pugh score constituents (albumin, total bilirubin, prothrombin time, and presence/absence of ascites and encephalopathy) and AFP levels recorded on their initial clinic visit, as well as baseline tumor characteristics of maximum tumor diameter, tumor number, presence/absence of macroscopic malignant portal vein thrombosis by Computed Axial Tomography (CAT) scan evaluation. All patients were diagnosed according to EASL criteria and macroscopic portal vein thrombosis by HCC was assessed by presence of a heterogeneous contrast-enhanced portal vein thrombosis with enlargement (>23 mm) in proximity to vascular HCC.
Statistical Analysis
Patient’s characteristics are reported as mean and standard deviation (M±SD), or median and minimum and maximum values, or interquartile range (IQR) for continuous variables, and as frequency and percentage (%) for categorical variables. The data comes from the ITA.LI.CA system that is composed of >18 collaborating centers and each has slightly different ranges of normal. However, we have used the average of their participating laboratories ULN/upper limit of normal, for each of these parameters for the dichotomization split.
To test the association between the independent groups (MTD ≤ 6 cm vs MTD > 6 cm), a Chi-squared test was used for categorical variables, while to compare median values of platelets, albumin, GGT, PLR or AFP between MTD two independent categories, Wilcoxon rank sum test (Mann–Whitney) was used. The Kruskal–Wallis equality rank test was used to compare parameters for more than two MTD independent groups.
To evaluate the association of MTD with single parameters and relative combinations, a logistic regression model was built and the estimators were reported as odds ratios (ORs) and 95% confidence intervals.
The associations between mortality for HCC and parameters stratified for MTD categories were assessed using the Cox proportional hazards regression model, and the results were presented as Hazard Ratio (HR) with 95% confidence intervals (95% C.I.).
Final logistic and hazards models were obtained with the backward stepwise method and the variables that showed associations with p<0.10 were left in the models.
Survival probability of combination of albumin and PLR was explored using the non parametric Kaplan–Meier method, and the equality of survival curves was analyzed with the log-rank test.
To test the null hypothesis of non-association, the two-tailed probability level was set at 0.05. The analyses were conducted with StataCorp 2023 Stata Statistical Software: Re-lease 18 (College Station, TX, USA: StataCorp LLC.).
Results
Comparison between median blood parameters in MTD groups (≤6 cm/>6 cm).
A comparison was made between blood parameters in patients having MTD groups of <6 cm and >6 cm (Table 1). This 6 cm cut-off was chosen rather than the traditional 5 cm of the Milan criteria, due to the increase in MTD giving satisfactory survival in multiple reports of liver transplantation for HCC [1]. Patients with >6 cm HCCs had significantly higher AST (but not ALT, 39.25% vs 33.09%, p=0.001) levels, as well as higher ALKP (44.76% vs 27.97%, p<0.001), GGT (50.98% vs 31.38%, p<0.001), AFP (45.04% vs 22.12%, p<0.001), neutrophil (56.70% vs 42.62%, p<0.001), leukocytes (58.76% vs 51.32%, p=0.001), platelet levels (61.65% vs 40.49%, p<0.001) and PLR (105.94±120.63 versus 130.61±116.64, p<0.001), and significantly lower albumin (56.61% vs 63.74%, p<0.001) and hemoglobin (57.65% vs 63.10%, p=0.003) levels, compared with patients with < 6cm HCCs (Table 1). Interestingly, only 45.04% of the patients with large HCCs had elevated AFP levels (p<0.001). Bilirubin level differences were borderline statistically insignificant (p=0.07). The percent of patients with macroscopic portal vein invasion (PVT) (61.65% vs 40.49%, p<0.001) and tumor multifocality (31.04% vs 27.36%, p=0.03) was significantly greater in patients with larger HCCs compared with patients with smaller HCCs, as previously not-ed [9].
Table 1.
Comparison between median parameters in MTD groups (≤6 cm/>6 cm) in total cohort.
| Parameters * | MTD | p ^ | |
|---|---|---|---|
| ≤ 6 cm (n=5821) (86.1%) |
> 6 cm (n=938) (13.9%) |
||
| Age (yrs) | 67.07±10.26 | 66.78±11.62 | 0.76 † |
| Gender (M) (%) | 4423 (75.98) | 792 (84.43) | <0.001 |
| Total Bilirubin (mg/dL) | 0.07 | ||
| ≤ 1.30 | 3380 (64.90) | 535 (61.71) | |
| > 1.30 | 1828 (35.10) | 332 (38.29) | |
| AST (IU/mL) | 0.001 | ||
| ≤ 40.00 | 3167 (66.91) | 486 (60.75) | |
| > 40.00 | 1566 (33.09) | 314 (39.25) | |
| ALT (IU/mL) | 0.12 | ||
| ≤ 40.00 | 2541 (51.86) | 406 (48.92) | |
| > 40.00 | 2359 (48.14) | 424 (51.08) | |
| ALKP (IU/mL) | <0.001 | ||
| ≤ 150.00 | 3132 (72.03) | 395 (55.24) | |
| > 150.00 | 1216 (27.97) | 320 (44.76) | |
| GGT (IU/mL) | <0.001 | ||
| ≤ 30.00 | 3217 (68.62) | 375 (49.02) | |
| > 30.00 | 1471 (31.38) | 390 (50.98) | |
| Albumin (g/dL) | <0.001 | ||
| ≤ 3.50 | 1877 (36.26) | 374 (43.39) | |
| > 3.50 | 3299 (63.74) | 488 (56.61) | |
| Hemoglobin (g/dL) | 0.003 | ||
| ≤ 12.20 | 1727 (36.90) | 343 (42.35) | |
| > 12.20 | 2953 (63.10) | 467 (57.65) | |
| Lymphocytes (×109/L) | 0.20 | ||
| ≤ 1200.00 | 498 (42.93) | 85 (38.29) | |
| > 1200.00 | 662 (57.07) | 137 (61.71) | |
| Neutrophils (×109/L) | <0.001 | ||
| ≤ 3250.00 | 680 (57.38) | 97 (43.30) | |
| > 3250.00 | 505 (42.62) | 127 (56.70) | |
| Leukocytes (×109/L) | 0.001 | ||
| ≤ 4380.00 | 1645 (48.68) | 247 (41.24) | |
| > 4380.00 | 1734 (51.32) | 352 (58.76) | |
| Multifocality (> 1) | 1515 (27.36) | 248 (31.04) | 0.03 |
| PVT (Yes) | 765 (13.45) | 329 (35.84) | <0.001 |
| Platelets (×109/L) | <0.001 | ||
| ≤ 125 | 3019 (59.51) | 326 (38.35) | |
| > 125 | 2054 (40.49) | 524 (61.65) | |
| AFP (IU/mL) | <0.001 | ||
| ≤ 100 | 3675 (77.88) | 432 (54.96) | |
| > 100 | 1044 (22.12) | 354 (45.04) | |
| PLR | 105.94±120.63 | 130.61±116.64 | <0.0001† |
| PLR | <0.001 | ||
| ≤ 150 | 979 (84.62) | 159 (71.95) | |
| > 150 | 178 (15.38) | 62 (28.05) | |
As Mean and Standard Deviation (M±SD) for continuous variables, and frequency and percentage (%) for categorical.
Chi-Square test;
Mann–Whitney rank test.
Abbreviations: AST, Aspartate Transferase; ALT, Alanine Transaminase; ALKP, Alkaline Phosphatase; GGT, Gamma Glutamyl Transpeptidase; PVT, Portal Vein Thrombosis; AFP, Alpha-Fetoprotein; PLR, Platelet-Lymphocyte Ratio.
Logistic regression model of MTD (≤/> 6cm) on single and combination parameter variables.
A logistic regression model of MTD (≤/> 6cm) on single variables in HCC patients was then constructed, in order to identify the parameters associated with larger HCC size (Table 2A). In the total HCC cohort (left side of Table 2), parameters with significant odds ratios (ORs) for larger HCC size were presence of PVT (OR=3.595, 3.079 to 4.200 95% C.I., p<0.001) and PLR >150 (OR=2.159, 1.545 to 3.016 95% C.I., p<0.001). Protective parameters were female gender (OR=0.583, 0.484 to 0.703 95% C.I., p<0.001) and albumin (OR=0.708, 0.627 to 0.800 95% C.I., p<0.001). The highest OR of 3.917 (3.186 to 4.811 95% C.I., p<0.001) was for the combination of presence of PVT and low albumin (<3.50 g/dL). A final multiple logistic regression model in the stepwise method on variables included together in the model is shown in Table 2B, with PLR >150 having an OR of 1.922 (1.350 to 2.733 95% C.I., p<0.001) and presence of PVT having an OR=4.342 (3.142 to 6.002 95% C.I., p<0.001). Interestingly, in patients with MTD > 6 cm who had low serum AFP levels (OR=1.004, 1.002 to 1.006 95% C.I., p<0.001) the significant factors for MTD > 6 cm were the same (Table 2 right side), namely PVT (OR=3.680, 2.956 to 4.581 95% C.I., p<0.001), PLR >150 (OR=2.193, 1.428 to 3.366 95% C.I., p<0.001), gender (OR=0.527, 0.404 to 0.689 95% C.I., p<0.001) and albumin (OR=0.711, 0.603 to 0.837 95% C.I., p<0.001).
Table 2.
Logistic regression model of MTD (≤/> 6cm) on single variables in HCC patients (A). Final multiple logistic regression model in stepwise method on variables included together in the model (B).
| Parameters * | Total Cohort | AFP<200 (IU/mL) | ||||||
|---|---|---|---|---|---|---|---|---|
| OR | se (OR) | p | 95% C.I. | OR | se (OR) | p | 95% C.I. | |
| (A) | ||||||||
| Age | 0.997 | 0.003 | 0.422 | 0.991 to 1.004 | 1.005 | 0.005 | 0.295 | 0.995 to 1.014 |
| Gender (F) | 0.583 | 0.055 | <0.001 | 0.484 to 0.703 | 0.527 | 0.072 | <0.001 | 0.404 to 0.689 |
| PVT (Yes) | 3.595 | 0.284 | <0.001 | 3.079 to 4.200 | 3.680 | 0.411 | <0.001 | 2.956 to 4.581 |
| Total Bilirubin | 1.018 | 0.012 | 0.134 | 0.994 to 1.042 | 0.999 | 0.020 | 0.990 | 0.961 to 1.040 |
| AFP | 1.000 | 2.84e-06 | <0.001 | 1.000 to 1.001 | 1.004 | 0.001 | <0.001 | 1.002 to 1.006 |
| AST | 1.006 | 0.001 | <0.001 | 1.003 to 1.008 | 1.007 | 0.002 | <0.001 | 1.003 to 1.010 |
| ALT | 1.002 | 0.001 | 0.077 | 0.999 to 1.004 | 1.001 | 0.001 | 0.281 | 0.999 to 1.003 |
| ALKP | 1.004 | 0.001 | <0.001 | 1.002 to 1.005 | 1.005 | 0.001 | <0.001 | 1.003 to 1.006 |
| GGT | 1.002 | 0.001 | <0.001 | 1.001 to 1.003 | 1.002 | 0.001 | 0.001 | 1.000 to 1.003 |
| Albumin | 0.708 | 0.044 | <0.001 | 0.627 to 0.800 | 0.711 | 0.059 | <0.001 | 0.603 to 0.837 |
| Platelets | 1.003 | 0.001 | <0.001 | 1.002 to 1.003 | 1.002 | 0.001 | <0.001 | 1.002 to 1.003 |
| Lymphocytes | 1.000 | 0.001 | 0.192 | 0.999 to 1.000 | 1.000 | 0.001 | 0.320 | 0.999 to 1.000 |
| Neutrophils | 1.000 | 0.001 | <0.001 | 1.000 to 1.001 | 1.000 | 0.001 | <0.001 | 1.000 to 1.001 |
| Leukocytes | 1.000 | 1.53e-06 | 0.110 | 0.999 to 1.000 | 1.000 | 1.49e-06 | 0.083 | 0.999 to 1.000 |
| CRP | 1.037 | 0.018 | 0.037 | 1.002 to 1.073 | 1.015 | 0.019 | 0.418 | 0.978 to 1.054 |
| Multifocality (> 1) | 1.195 | 0.098 | 0.030 | 1.017 to 1.404 | 1.295 | 0.143 | 0.019 | 1.044 to 1.608 |
| PLR | 1.001 | 0.001 | 0.014 | 1.000 to 1.002 | 1.001 | 0.001 | 0.029 | 1.000 to 1.002 |
| PLR (>150) (Yes) | 2.159 | 0.368 | <0.001 | 1.545 to 3.016 | 2.193 | 0.479 | <0.001 | 1.428 to 3.366 |
| PVT & Albumin (<3.50) | 3.917 | 0.413 | <0.001 | 3.186 to 4.811 | 4.193 | 0.611 | <0.001 | 3.150 to 5.582 |
| (B) | ||||||||
| Neutrophils | -- | -- | -- | -- | 1.001 | 0.001 | 0.073 | 0.999 to 1.001 |
| ALKP | -- | -- | -- | -- | 1.036 | 0.021 | 0.082 | 0.995 to 1.078 |
| PLR (>150) (Yes) | 1.922 | 0.345 | <0.001 | 1.350 to 2.733 | -- | -- | -- | -- |
| PVT (Yes) | 4.342 | 0.717 | <0.001 | 3.142 to 6.002 | 5.139 | 0.014 | 0.016 | 1.354 to 19.506 |
Abbreviations: OR, Odds-Ratio; se(OR), standard error of OR; PVT, Portal Vein Thrombosis; AFP, Alpha-fetoprotein; AST, Aspartate Transferase; ALT, Alanine Transaminase; ALKP, Alkaline phosphatase; GGT, gamma glutamyl transpeptidase; CRP, C-Reactive Protein; PLR, Platelet-Lymphocyte Ratio.
Logistic regression model of MTD (≤/> 6cm) on 3-parameters combinations.
A logistic regression model of MTD (≤/> 6cm) on 3-parameters combinations was then constructed, each model containing both PVT and PLR (Table 3). In one model albumin was added (Table 3A) and in the other model gender was added (Table 3B). The highest ORs were for the combination of either low albumin plus high PLR plus presence of PVT (OR=6.517, 3.146 to 13.500 95% C.I., p<0.001) (Table 3A), or male gender plus PLR >150 plus presence of PVT (OR=12.124, 5.379 to 27.324 95% C.I., p<0.001) (Table 3B).
Table 3.
Logistic regression model of MTD (≤/> 6cm) on 3-parameters combinations of A), albumin plus PLR 150 plus PVT; and B), gender plus PLR plus PVT.
| Parameters | OR | se (OR) | p | 95% C.I. |
|---|---|---|---|---|
| (A) | ||||
| Albumin ≥ 3.5 & PLR≤150 & PVT − [Ref.] | -- | -- | -- | -- |
| Albumin ≥ 3.5 & PLR>150 & PVT − | 2.494 | 0.656 | 0.001 | 1.489 to 4.176 |
| Albumin ≥ 3.5 & PLR≤150 & PVT + | 5.648 | 1.594 | <0.001 | 3.248 to 9.822 |
| Albumin ≥ 3.5 & PLR>150 & PVT + | 6.517 | 2.421 | <0.001 | 3.146 to 13.500 |
| Albumin < 3.5 & PLR≤150 & PVT − | 1.327 | 0.293 | 0.201 | 0.860 to 2.046 |
| Albumin < 3.5 & PLR>150 & PVT − | 2.390 | 0.869 | 0.017 | 1.172 to 4.872 |
| Albumin < 3.5 & PLR≤150 & PVT + | 5.242 | 1.290 | <0.001 | 3.237 to 8.490 |
| Albumin < 3.5 & PLR>150 & PVT + | 9.776 | 4.381 | <0.001 | 4.062 to 23.529 |
| (B) | ||||
| Female & PLR≤150 & PVT − [Ref.] | -- | -- | -- | -- |
| Female & PLR>150 & PVT − | 5.025 | 2.380 | 0.001 | 1.985 to 12.717 |
| Female & PLR≤150 & PVT + | 3.127 | 1.556 | 0.022 | 1.178 to 8.295 |
| Female & PLR>150 & PVT + | 7.309 | 4.194 | 0.001 | 2.374 to 22.504 |
| Male & PLR≤150 & PVT − | 1.657 | 0.484 | 0.084 | 0.934 to 2.939 |
| Male & PLR>150 & PVT − | 3.101 | 1.054 | 0.001 | 1.592 to 6.038 |
| Male & PLR≤150 & PVT + | 8.255 | 2.775 | <0.001 | 4.678 to 16.273 |
| Male & PLR>150 & PVT + | 12.124 | 5.026 | <0.001 | 5.379 to 27.324 |
Abbreviations: OR, Odds-Ratio; se(OR), standard error of OR; PLR, Platelet-Lymphocyte Ratio; PVT+, Portal Vein Thrombosis present; PVT-, Portal Vein Thrombosis absent. Albumin units, g/dL.
Size terciles in relation to parameter values.
In order to assess parameter trends in relation to MTD, patients were divided in 3 size terciles and the means, or median (IQR), minimum and maximum values and distributions of the associated peripheral blood parameter values were then calculated (Figure S1). Figure S1A shows that mean platelet counts increased with increase in each tercile (p=0.0001). Parameter differences between each tercile were significant. Lower platelet numbers are known to be associated with the portal hypertension of cirrhosis and this platelet observation has been observed in other cohorts [12, 13, 14]. Other parameters have not been previously described in relation to MTD terciles, to our knowledge. Figure S1B shows the same approach for serum albumin levels, which significantly decreased with each increase in tercile (p=0.0001). Figure S1C shows that mean GGT counts also increased with increase in each tercile (p=0.0001) and parameter differences between each tercile were significant. Similar results were found for platelet-lymphocyte ratio (PLR) as shown in Figure S1D, and for AFP levels, as shown in Figure S1E.
Cox proportional hazard models for death on clinical parameter values.
A Cox proportional hazard models for death on HCC patient clinical parameters, stratified by MTD was then calculated (Table 4A). The highest hazard ratios (HRs) in patients with MTD <6cm were for PVT (HR=2.801, 2.564 to 3.060 95% C.I., p<0.001), and for albumin (HR=0.621, 0.585 to 0.660 95% C.I., p<0.001) which was protective. The combination of presence of PVT plus low albumin (<3.50 g/dL) had an HR of 4.254 (3.789 to 4.776 95% C.I., p<0.001). A Multinomial Cox regression model using the stepwise method on variables included together in the model was then calculated (Table 4B) and showed significant HRs for PVT (HR=2.407, 1.651 to 3.509 95% C.I., p<0.001), total bilirubin (HR=1.074, 1.039 to 1.109095% C.I., p<0.001), albumin (HR=0.692, 0.509 to 0.941 95% C.I., p<0.001) and C-reactive protein (CRP) (HR=1.061, 1.030 to 1.094 95% C.I., p<0.001).
Table 4.
Cox proportional hazard models for death on clinical parameters in HCC patients, stratified by MTD categories (A). Final Multinomial Cox regression model in stepwise method on variables included together in the model (B)^.
| Parameters | MTD (≤ 6.0 cm) |
MTD (> 6.0 cm) |
||||||
|---|---|---|---|---|---|---|---|---|
| HR | se (HR) | p | 95% C.I. | HR | se (HR) | p | 95% C.I. | |
| (A) | ||||||||
| Age | 1.005 | 0.002 | 0.005 | 1.001 to 1.008 | 1.004 | 0.003 | 0.257 | 0.997 to 1.011 |
| Gender (F) | 1.008 | 0.038 | 0.838 | 0.936 to 1.084 | 1.177 | 0.124 | 0.122 | 0.957 to 1.447 |
| PVT (Yes) | 2.801 | 0.126 | <0.001 | 2.564 to 3.060 | 2.120 | 0.169 | <0.001 | 1.814 to 2.479 |
| Total Bilirubin | 1.077 | 0.005 | <0.001 | 1.067 to 1.086 | 1.080 | 0.121 | <0.001 | 1.057 to 1.104 |
| AFP | 1.000 | 1.23e-06 | <0.001 | 1.000 to 1.001 | 1.000 | 9.09e-07 | 0.413 | 0.999 to 1.000 |
| AST | 1.002 | 0.001 | 0.014 | 1.000 to 1.004 | 1.001 | 0.001 | 0.421 | 0.999 to 1.003 |
| ALT | 1.001 | 0.001 | 0.317 | 0.999 to 1.003 | 1.001 | 0.002 | 0.651 | 0.997 to 1.005 |
| ALKP | 1.002 | 0.001 | <0.001 | 1.001 to 1.003 | 1.001 | 0.001 | 0.442 | 0.999 to 1.001 |
| GGT | 1.001 | 0.001 | 0.002 | 1.000 to 1.002 | 1.001 | 0.001 | 0.137 | 0.999 to 1.002 |
| Albumin | 0.621 | 0.019 | <0.001 | 0.585 to 0.660 | 0.597 | 0.041 | <0.001 | 0.522 to 0.683 |
| Platelets | 0.999 | 0.001 | 0.792 | 0.999 to 1.000 | 1.000 | 0.001 | 0.695 | 0.999 to 1.001 |
| Lymphocytes | 0.999 | 0.001 | 0.149 | 0.999 to 1.000 | 1.000 | 0.001 | 0.570 | 0.999 to 1.000 |
| Neutrophils | 1.000 | 0.001 | 0.991 | 0.999 to 1.000 | 1.000 | 0.001 | 0.022 | 1.000 to 1.001 |
| Leukocytes | 0.999 | 7.78e-06 | 0.554 | 0.999 to 1.000 | 0.999 | 1.04e-06 | 0.716 | 0.999 to 1.000 |
| CRP | 1.051 | 0.014 | <0.001 | 1.023 to 1.078 | 1.037 | 0.018 | 0.036 | 1.002 to 1.073 |
| Multifocality (> 1) | 1.337 | 0.0489 | <0.001 | 1.244 to 1.437 | 1.129 | 0.099 | 0.168 | 0.950 to 1.340 |
| PLR | 0.999 | 0.001 | 0.969 | 0.999 to 1.001 | 0.998 | 0.001 | 0.017 | 0.996 to 0.999 |
| PLR (>150) (Yes) | 1.140 | 0.139 | 0.283 | 0.897 to 1.448 | 0.726 | 0.142 | 0.101 | 0.495 to 1.064 |
| PVT & Albumin (<3.50) | 4.254 | 0.251 | <0.001 | 3.789 to 4.776 | 3.122 | 0.346 | <0.001 | 2.511 to 3.881 |
| (B) | ||||||||
| PVT (Yes) | 2.407 | 0.463 | <0.001 | 1.651 to 3.509 | 2.130 | 0.696 | 0.012 | 1.195 to 4.099 |
| Total Bilirubin | 1.074 | 0.018 | <0.001 | 1.039 to 1.109 | 1.181 | 0.069 | 0.004 | 1.054 to 1.322 |
| Albumin | 0.692 | 0.109 | 0.019 | 0.509 to 0.941 | -- | -- | -- | -- |
| CRP | 1.061 | 0.016 | <0.001 | 1.030 to 1.094 | 1.036 | 0.019 | 0.051 | 0.999 to 1.073 |
Abbreviations: HR, Hazard Ratio; se (HR), standard error of HR; PVT, Portal Vein Thrombosis; AFP, Alpha-fetoprotein; AST, Aspartate Transferase; ALT, Alanine Transaminase; ALKP, Alkaline phosphatase; GGT, gamma glutamyl transpeptidase; CRP, C-Reactive Protein; PLR, Platelet-Lymphocyte Ratio.
PVT (Yes); Total Bilirubin, Albumin, and CRP are included together in the models.
Survival in PLR plus albumin combinations.
Kaplan-Meier graphs were plotted for the 4 combinations of PLR 150 (high/low) plus serum albumin levels 3.5 g/dL (high/low), as shown in Figure 1 (Figure 1A, small HCCs; Figure 1B, large HCCs). For each MTD group, the longest survival was for combinations containing normal serum albumin levels, and conversely, the shortest survival was for combinations containing low serum albumin levels (p<0.0001, p=0.0002 respectively).
Fig. 1.
Cumulative survival for combinations of albumin <3.5/>3.5g/dL and PLR >150 in A, small and B, large HCCs.
Discussion
Patients with large HCCs typically have worse survival than patients with small HCCs. However, many patients with small (<6cm) and larger (>6cm) HCCs can be transplanted with reasonable 5-year survival rates, so that factors other than MTD alone are likely also to be involved in the survival differences. Although MTD of 6cm has been the accepted cutoff for the Milan HCC transplant criteria, multiple recent studies have also shown 5 year survival of 70% of patients with HCCs >5cm. In our Institution we have used 6cm and thus have incorporated that in our study, but similar results (not shown) were found using 5cm MTD. It has previously been shown that small and large HCCs can differ in various parameters, such as percentage of patients with PVT, platelet count [13] and bilirubin level, in addition to the MTD [12–14]. We also found this in the current study. A question is how to explain these differences in parameters associated with larger versus smaller MTD patients. Our patients with >6cm MTD HCCs had greater percent of PVT and multifocality and higher AFP levels than patients with <6 cm MTD HCCs (Table 1). Whether larger HCCs have more tumor stem cells than smaller HCCs [15–17] which might produce these features, is not answered here. Nor is it clear whether stem cells produce growth and aggressiveness features (PVT, multifocality, AFP), or conversely, whether the aggressiveness features such as secreted AFP, produce more tumor growth, in AFP-secreting HCCs.
The small MTD patients constituted 86.1% of the cohort and the large MTD patients constituted 13.9% of the cohort. Interestingly, only 38.25% of HCC patients with large MTD in this study had thrombocytopenia, compared to 59.51% of small MTD patients (Table 1). Previously, small HCC patients had lower median platelet counts than large HCC patients [13]. A simple explanation is that the same hepatocarcinogenic process can take place regardless of the degree of cirrhosis. On this view, the smaller percent of large MTD patients is because many of the small HCCs cannot grow larger, due to resultant parenchymal destruction of the underlying liver, leading to patient death. However, since the thrombocytopenia of cirrhosis is mainly irreversible, the small HCCs with thrombocytopenia must give rise only to larger HCCs with thrombocytopenia and not to the large HCCs without thrombocytopenia. Clearly, not all small HCCs progress to large HCCs. However, the lower percent of HCC patients having large MTD who also had thrombocytopenia, suggests the possibility of the presence of more than one pathway for HCC growth, one from cirrhosis-associated small HCCs with thrombocytopenia and at least one other pathway, from non thrombocytopenia-associated small HCCs, as reported in Ref 8. The percent of patients with elevated total bilirubin levels was similar in the patients with small and large size HCCs, but there was more hypo-albuminemia in the patients with large HCCs (Table 1), similar to reports of the Glasgow prognostic index of inflammation and cancer [18–20] in which hypo-albuminemia was shown to be significantly associated with poorer prognosis. We also found evidence of a greater inflammatory response in the HCC patients with larger MTDs, as judged by higher levels of serum AST, ALKP, GGT, neutrophils and lymphocytes and lower hemoglobin (Table 1). Since these findings occurred in about 45–55% of the patients with larger HCCs, there must be considerable heterogeneity amongst these patients, as shown elsewhere [21, 22]. Furthermore, the tumor microenvironment in general has received much attention in recent studies in relation to HCC growth [23, 24] and especially the immune microenvironment [25, 26] since the introduction of clinically effective immune checkpoint inhibitors. In addition, it has become increasingly clear that the non-tumor microenvironment is also important in relation to HCC prognosis [27–30]. In addition, comparison of HCC patients with similar MTD showed that those who had elevated AST levels also had more PVT and multifocality, markers of HCC aggressiveness [8].
The logistic regression model of MTD (≤/> 6cm) on single variables showed significant ORs for PVT (OR=3.595) and PLR >150 (OR=2.159), while both albumin and female gender were protective against larger MTD (Table 2); and a combination of PVT plus low albumin (<3.5 g/dL) had an OR of 3.917. The 3-parameter combinations had even higher ORs, being 6.517 for presence of PVT plus PLR >150 plus albumin <3.5g/dL, and 12.124 for presence of PVT plus PLR>150 plus male gender (Table 3). The Cox model on death also revealed the greatest HRs for PVT and for low albumin, with the combination having a HR of 4.254 (Table 4). Thus, both the regression model and the Cox analysis showed the importance of presence of PVT and low serum albumin, as shown in other series [17–20, 31]. Why is albumin so important? It is both an indicator of poor nutrition in advanced cancers, as well as of inflammation, which has been thought to be a poor prognosis factor for cancer since the time of Virchow [19, 20, 32]. It also seems to be a likely modulator of HCC growth in its own right [33, 34], in addition to its clinical use as a marker of hepatic synthetic function. The OR and HR of <1 for albumin in both the regression and the Cox analyses, suggest that it has a protective effect at normal clinical values. Low albumin has been shown to reflect a poor prognosis in several GI cancers, including HCC [18–20]. Presence of PVT has also been widely accepted as an important ad-verse prognostic factor for HCC [35]. Exactly how PVT causes decreased HCC patient survival is not certain, but its presence can be associated both with decreased liver function and with increased HCC metastasis. Both OR and HR models show significance for both presence of PVT and for low albumin. It is known from the literature is that large HCCs are associated with both increase in percent PVT and with low albumin (Glasgow index). What is new here is the suggestion that PVT might actually predispose to large size HCC (Tables 2 and 3). On this view, presence of PVT can be both a consequence and might also be a cause of increasing MTD. Patients in this study with smaller MTDs had lower per-centage of PVT (13.45%) compared to patients with larger MTDs (35.84%). This could be explained by the HCC growing mass causing an increased probability of PVT, or perhaps by a common factor that causes both HCC tumor mass growth as well as invasion and growth in the portal vein by the HCC cells.
PLR >150 was shown here to be significant in the regression analysis, but not in the Cox analysis, and is an inflammation marker for various cancers including HCC [36–39]. Angiogenesis has also been considered to be important in HCC cell growth, resulting from the actions of microenvironmental inflammatory cells as well as the specific growth factors vascular endothelial growth factor and platelet-derived growth factor, amongst others [40]. Many endogenous tumor factors have also been identified as being involved in tumor cell growth, whether as products of oncogenes or through increased synthesis of various growth factors [41] including epidermal growth factor and fibroblast growth factor produced as part of HCC-associated inflammation [42], as well as the several mitogens that are produced from and released from platelet alpha granules [43]. Female gender has long been known to relate to lower HCC incidence, especially in cirrhosis-associated HCC. It has also been reported in relation to better HCC survival in multiple studies [44–47], although whether this is due to social factors, or HCC biology such as smaller tumors, has not been made clear due to conflicting reports. Likewise, HCC in non-cirrhotic liver presents as larger tumors compared to HCC associated with cirrhosis [47], possibly due to different growth pathways.
Serum albumin levels in HCC patients have been shown to be associated both with inflammation as well as with prognosis [48] and albumin may actively participate in HCC growth control mechanisms [49, 50]. Furthermore, AFP and albumin, being from the same protein family, may reciprocally regulate each other experimentally [51] and likely do so in HCC patients [52]. These findings give rise tot he possibility that albumin infusions into HCC patients with low serum albumin levels (<3.5g/dL) might have thertapeutic potential, especially in patients with elevated AFP levels.
Conclusions
Presence of PVT and low serum albumin levels related significantly to HCC size and survival. Inflammation also appeared to be related to HCC size, but not convincingly to survival.
Supplementary Material
Funding Sources
This work was supported in part by NIH grant CA 82723 (B.I.C.), and Italian Ministry of Health Ricerca Corrente 2025.
Footnotes
Statement of Ethics
This study protocol was reviewed and approved by Independent Ethic Committee of S. Orsola-Malpighi hospital of Bologna, which operates as coordinating center of the ITA.LI.CA network., approval number [protocol n. 99/2012/O/Oss, 2022/3905], and Inonu university IRB, approval number [2022/3905]. All patients provided written informed consent.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Data Availability Statement
The data that support the findings of this study are not publicly available due to data are not public e.g. their containing information that could compromise the privacy of research participants, but are available from the corresponding author [RD, and BIC], [Rossella Donghia, National Institute of Gastroenterology - IRCCS “Saverio de Bellis”, 70013 Castellana Grotte (BA). E-mail: rossella.donghia@irccsdebellis.it.; Brian I. Carr MD, PhD, FRCP; Liver Transplant Institute, Inonu University, Bulgurlu Mah, Elazig Yolu 15 km, 44280, Malatya, Turkey E-mail: brianicarr@hotmail.com; Tel: 1 412 980 451] upon reasonable request].
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are not publicly available due to data are not public e.g. their containing information that could compromise the privacy of research participants, but are available from the corresponding author [RD, and BIC], [Rossella Donghia, National Institute of Gastroenterology - IRCCS “Saverio de Bellis”, 70013 Castellana Grotte (BA). E-mail: rossella.donghia@irccsdebellis.it.; Brian I. Carr MD, PhD, FRCP; Liver Transplant Institute, Inonu University, Bulgurlu Mah, Elazig Yolu 15 km, 44280, Malatya, Turkey E-mail: brianicarr@hotmail.com; Tel: 1 412 980 451] upon reasonable request].