| Literature DB >> 28057916 |
Michał Grąt1, Jan Stypułkowski1, Waldemar Patkowski1, Emil Bik1, Maciej Krasnodębski1, Karolina M Wronka1, Zbigniew Lewandowski2, Michał Wasilewicz3, Karolina Grąt4, Łukasz Masior1, Joanna Ligocka1, Marek Krawczyk1.
Abstract
Microvascular invasion (MVI) is well known to negatively influence outcomes following surgical treatment of hepatocellular cancer (HCC) patients. The aim of this study was to evaluate the rationale for prediction of MVI before liver transplantation (LT). Data of 200 HCC patients after LT were subject to retrospective analysis. MVI was present in 57 patients (28.5%). Tumor number (p = 0.001) and size (p = 0.009), and alpha-fetoprotein (p = 0.049) were independent predictors of MVI used to create a prediction model, defined as: 0.293x(tumor number) + 0.283x(tumor size in cm) + 0.164xloge(alpha-fetoprotein in ng/ml) (c statistic = 0.743). The established cut-off (≥2.24) was associated with sensitivity and specificity of 72%. MVI was not an independent risk factor for recurrence (p = 0.307), in contrast to tumor number (p = 0.047) and size (p < 0.001), alpha-fetoprotein (p < 0.001) and poor differentiation (p = 0.039). Recurrence-free survival at 5 years for patients without MVI was 85.9% as compared to 83.3% (p = 0.546) and 55.3% (p = 0.001) for patients with false negative and true positive prediction of MVI, respectively. The use of both morphological and biological tumor features enables effective pre-transplant prediction of high-risk MVI. Provided that these parameters are combined in selection of HCC patients for LT, pre-transplant identification of all patients with MVI does not appear necessary.Entities:
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Year: 2017 PMID: 28057916 PMCID: PMC5216407 DOI: 10.1038/srep39881
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Baseline characteristics of 200 patients after liver transplantation for hepatocellular cancer included in the final study cohort.
| Characteristics | n (%) or median (IQR) |
|---|---|
| Recipient gender | |
| male | 143 (71.5%) |
| female | 57 (28.5%) |
| Recipient age (years) | 57 (52–61) |
| MELD | 11 (8–13) |
| HCV infection | 137 (68.5%) |
| HBV infection | 81 (40.5%) |
| Within Milan criteria | 120 (60.0%) |
| Within UCSF criteria | 144 (72.0%) |
| Within Up-to-7 criteria | 154 (77.0%) |
| Number of tumors | 1 (1–3) |
| Size of the largest tumor (cm) | 3.0 (2.0–4.5) |
| Total tumor volume (cm3) | 22.5 (5.3–54.2) |
| Pre-transplant AFP (ng/ml) | 16 (6–114) |
| Poor tumor differentiation | 24 (12.0%) |
| Microvascular invasion | 57 (28.5%) |
| Neoadjuvant treatment | 86 (43.0%) |
| Total ischemic time (hours) | 9.0 (8.0–10.3) |
| Piggyback transplantations | 175 (87.5%) |
| Intraoperative PRBC transfusions (units) | 3.0 (1.5–6.0) |
| Intraoperative FFP transfusions (units) | 7.0 (5.0–10.0) |
| Donor age (years) | 49.5 (38.0–57.5) |
IQR – interquartile range; UCSF – University of California, San Francisco; AFP – alpha-fetoprotein; MELD – model for end-stage liver disease; HCV – hepatitis C virus; HBV – hepatitis B virus; PRBC – packed red blood cells; FFP – fresh frozen plasma.
Results of the analyses of predictors of the presence of microvascular invasion in patients with hepatocellular cancer undergoing liver transplantation.
| Factors | Univariable | Multivariable | ||
|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | |
| Recipient male gender | 1.02 (0.72–1.43) | 0.932 | ||
| Recipient age | 1.03 (0.99–1.07) | 0.192 | ||
| MELD | 0.94 (0.88–1.01) | 0.088 | ||
| HCV infection | 0.84 (0.61–1.17) | 0.306 | ||
| HBV infection | 0.72 (0.52–1.01) | 0.054 | ||
| Alcoholic liver disease | 1.31 (0.89–1.92) | 0.177 | ||
| Number of tumors | 1.28 (1.12–1.46) | <.001 | 1.34 (1.13–1.59) | 0.001 |
| Size of the largest tumor | 1.31 (1.09–1.56) | 0.004 | 1.33 (1.07–1.64) | 0.009 |
| Total tumor volume | 1.08 (1.02–1.15) | 0.005 | ||
| Pre-transplant AFP | 1.20 (1.04–1.38) | 0.013 | 1.18 (1.01–1.39) | 0.049 |
| Poor tumor differentiation | 1.55 (1.01–2.39) | 0.050 | ||
| Neoadjuvant treatment | 1.16 (0.63–2.15) | 0.638 | ||
Odds ratios were given per: 1 year increase for recipient age; 1 point increase for model for end-stage liver disease; 1 tumor more for number of tumors; 1 cm increase for the size of the largest tumor; 10 cm3 increase for total tumor volume; 1 loge increase for alpha-fetoprotein. OR – odds ratio; 95% CI – 95% confidence interval; MELD – model for end-stage liver disease; HCV – hepatitis C virus; HBV – hepatitis B virus; AFP – alpha-fetoprotein.
Figure 1Assessment of the optimal variables cut-offs in prediction of microvascular invasion.
Receiver operating characteristics curve for pre-transplant alpha-fetoprotein concentration (a), number of tumors (b), size of the largest tumor (c), and microvascular invasion index (d) in prediction of microvascular invasion. AUROC – area under the receiver operating characteristics curve; SE – standard error.
Characteristics of the MVI index and two previously published scores in prediction of microvascular invasion in patients with hepatocellular cancer undergoing liver transplantation.
| Score | Prediction of microvascular invasion | |||||||
|---|---|---|---|---|---|---|---|---|
| AUROC (SE) | AUROC (reported previously) | Cut-off | Accuracy | Sensitivity | Specificity | PPV | NPV | |
| MVI index | 0.743 (0.039) | — | ≥2.24 | 72.1% | 71.9% | 72.1% | 51.3% | 86.3% |
| Cucchetti | 0.690a (0.041) | 0.850 | ≥3.407 | 66.3% | 69.1% | 65.2% | 44.7% | 83.8% |
| Zhao | 0.674b (0.039) | 0.832 | ≥3 | 77.5% | 38.0% | 93.5% | 70.4% | 78.8% |
MVI index = 0.293 x (number of tumors) + 0.283 x (size of the largest tumor in cm) + 0.164 x loge(pre-transplant alpha-fetoprotein concentration in ng/ml)
Cucchetti et al. score34 = −5.087 + 2.417 x log10(pre-transplant alpha-fetoprotein concentration in ng/ml) + 0.778 x (size of the largest tumor in cm) + 1.550 x log10(total tumor volume in cm3)
Zhao et al score32 = 1 point if pre-transplant alpha-fetoprotein concentration > 400 μg/L + 2 points if pre-transplant γ-glutamyl-transpeptidase activity > 130 U/L + 1 point if total tumor size > 8 cm + 2 if >3 tumors
a – p = 0.062 as compared to MVI index; b – p = 0.104 as compared to MVI index
AUROC – area under the receiver operating characteristics curve; SE – standard error; PPV – positive predictive value; NPV – negative predictive value
Figure 2The impact of low- and high-risk microvascular invasion on outcomes after liver transplantation.
Recurrence-free survival curves after liver transplantation in (a) patients with (dashed line) and without (solid line) microvascular invasion, and (b) in patients without microvascular invasion (solid line), patients with microvascular invasion unpredicted by the model (dashed line), and patients with microvascular invasion predicted by the model (dotted line). Numbers of patients at risk are presented below the graphs.
Figure 3The impact of microvascular invasion predicted and unpredicted by the scores proposed by Cucchetti et al.34 and Zhao et al.32 on outcomes after liver transplantation.
Recurrence-free survival curves after liver transplantation in (a) patients without microvascular invasion (solid line), patients with microvascular invasion unpredicted by the model proposed by Cucchetti et al. (dashed line), and patients with microvascular invasion predicted by the model (dotted line) and (b) in patients without microvascular invasion (solid line), patients with microvascular invasion unpredicted by the model proposed by Zhao et al. (dashed line), and patients with microvascular invasion predicted by the model (dotted line). Numbers of patients at risk are presented below the graphs.
Results of the analyses of factors associated with 5-year recurrence-free survival after liver transplantation for hepatocellular cancer.
| Factors | Univariable | Multivariable | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| Recipient male gender | 1.21 (0.45–3.23) | 0.701 | ||
| Recipient age | 0.98 (0.94–1.02) | 0.380 | ||
| MELD | 0.95 (0.86–1.06) | 0.361 | ||
| HCV infection | 0.80 (0.36–1.78) | 0.583 | ||
| HBV infection | 1.80 (0.82–3.95) | 0.142 | ||
| Alcoholic liver disease | 1.08 (0.40–2.88) | 0.879 | ||
| Number of tumors | 1.27 (1.13–1.43) | <.001 | 1.18 (1.01–1.38) | 0.047 |
| Size of the largest tumor | 1.39 (1.19–1.62) | <.001 | 1.33 (1.13–1.56) | <.001 |
| Total tumor volume | 1.03 (1.01–1.04) | <.001 | ||
| Pre-transplant AFP | 1.43 (1.23–1.66) | <0.001 | 1.45 (1.20–1.75) | <.001 |
| Poor tumor differentiation | 3.53 (1.47–8.48) | 0.005 | 2.95 (1.05–8.25) | 0.039 |
| Microvascular invasion | 2.52 (1.15–5.52) | 0.021 | ||
| Neoadjuvant treatment | 1.82 (0.83–4.01) | 0.136 | ||
| Donor age (years) | 0.99 (0.96–1.02) | 0.573 | ||
Hazard ratios were given per: 1 year increase for recipient and donor age; 1 point increase for model for end-stage liver disease; 1 tumor more for number of tumors; 1 cm increase for the size of the largest tumor; 10 cm3 increase for total tumor volume; 1 loge increase for alpha-fetoprotein. HR – hazard ratio; 95% CI – 95% confidence interval; MELD – model for end-stage liver disease; HCV – hepatitis C virus; HBV – hepatitis B virus; AFP – alpha-fetoprotein.