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Original Investigation |

Nomogram for Preoperative Estimation of Microvascular Invasion Risk in Hepatitis B Virus–Related Hepatocellular Carcinoma Within the Milan Criteria

Zhengqing Lei, MD1; Jun Li, MD1; Dong Wu, MD1; Yong Xia, MD1; Qing Wang, MD1; Anfeng Si, MD1; Kui Wang, MD1; Xuying Wan, MD2; Wan Yee Lau, MD, FRCS1,3; Mengchao Wu, MD1; Feng Shen, MD, PhD1
[+] Author Affiliations
1Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
2Department of Chinese Traditional Medicine, the Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China
3Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
JAMA Surg. 2016;151(4):356-363. doi:10.1001/jamasurg.2015.4257.
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Importance  The presence of microvascular invasion (MVI) decreases surgical outcomes of hepatocellular carcinoma (HCC). An accurate preoperative prediction of MVI can help surgeons to better choose surgical procedures, but accuracy is still difficult to achieve.

Objective  To develop a nomogram to predict MVI presence before liver resection for hepatitis B virus (HBV)–related HCC within the Milan criteria (solitary nodule ≤5 cm; ≤3 nodules, none >3 cm; and no macrovascular invasion).

Design, Setting, and Participants  Data on 1004 consecutive patients who underwent liver resection for HBV-related HCC within the Milan criteria at the Eastern Hepatobiliary Surgery Hospital between April 6, 2004, and February 22, 2011, were prospectively collected. Of these, patients who underwent surgery in an earlier period formed the training cohort (n = 707) for nomogram development, and those who underwent surgery thereafter formed the validation cohort (n = 297) to confirm the model’s performance. Data analysis was conducted from August 1 to November 11, 2014.

Exposures  Liver resection for HCC.

Main Outcomes and Measures  Overall survival and time to recurrence after liver resection were measured. Multivariate logistic regression was used to identify the independent risk factors associated with MVI that then were incorporated into the nomogram.

Results  Histopathologically identified MVI was found in 211 of 707 patients (29.8%) and 89 of 297 patients (30.0%) in the training and validation cohorts, respectively. In the training cohort, the 5-year recurrence and overall survival rates were 78.5% and 46.9%, respectively, in patients with MVI and 58.4%, and 70.9%, respectively, in patients without MVI (both P < .001). The preoperative factors associated with MVI were large tumor diameter, multiple nodules, incomplete capsule, α-fetoprotein level greater than 20 ng/mL, platelet count less than 100 × 103/µL, hepatitis B virus DNA load greater than 104 IU/mL, and a typical dynamic pattern of tumors on contrast-enhanced magnetic resonance imaging. Incorporating these 7 factors, the nomogram achieved good concordance indexes of 0.81 (95% CI, 0.78-0.85) and 0.80 (95% CI, 0.75-0.86) in predicting MVI in the training and validation cohorts, respectively, and had well-fitted calibration curves. The positive and negative predictive values (95% CIs) of the nomogram were calculated, resulting in positive predictive values of 57.2% (52.0%-64.9%) and 57.9% (49.2%-68.5%) and negative predictive values of 87.2% (83.2%-89.4%) and 83.2% (76.0%-87.7%) for the training and validation cohorts, respectively. Patients who had a nomogram score of less than 200 or 200 or greater were considered to have low or high risks of MVI presence, respectively.

Conclusions and Relevance  The nomogram achieved an optimal preoperative prediction of MVI in HBV-related HCC within the Milan criteria. Using the model, the risk for an individual patient to harbor MVI can be determined, which can lead to a rational therapeutic choice.

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Figure.
Nomogram for Preoperative Estimation of Microvascular Invasion (MVI) Risk and Its Predictive Performance

A, Nomogram to estimate the risk of MVI presence preoperatively in hepatitis B virus (HBV)–related hepatocellular carcinoma within the Milan criteria. To use the nomogram, find the position of each variable on the corresponding axis, draw a line to the points axis for the number of points, add the points from all of the variables, and draw a line from the total points axis to determine the MVI probabilities at the lower line of the nomogram. B, Validity of the predictive performance of the nomogram in estimating the risk of MVI presence in the training cohort (n = 707). C, Validity of the predictive performance of the nomogram in estimating the risk of MVI presence in the validation cohort (n = 297). The distribution of the predicted probabilities of MVI presence is shown at the bottom of the graphs, separating those with (+) and without (−) MVI. The triangles indicate the observed frequencies of MVI presence by the deciles of the predicted probability. AFP indicates α-fetoprotein; C index, concordance index; and ROC, receiver operating characteristic.

aPreoperative imaging was based on contrast-enhanced magnetic resonance imaging.

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