Predictive factors for survival following stereotactic body radiotherapy for hepatocellular carcinoma with portal vein tumour thrombosis and construction of a nomogram

Outcomes with radiotherapy in multimodality treatment for hepatocellular carcinoma with portal vein tumour thrombosis

Objectives

The purpose of the present study was to evaluate outcomes with radiation therapy (RT) in multimodality treatment for inoperable hepatocellular carcinoma (HCC) with portal vein tumour thrombosis (PVTT).

Methods

The present retrospective study included 24 patients without extrahepatic metastases. The patients had received drug eluting beads - transarterial chemoembolization (DEB-TACE) (n = 10) and systemic treatment (n = 14) before RT. The dose fractionation was 12-31.5 Gy in 3-7 fractions of 4-5 Gy to PVTT or PVTT plus the liver parenchymal tumour. All patients were advised systemic treatment with sorafenib, lenvatinib, or nivolumab after RT. After RT, patients had received DEB-TACE within 8 weeks (n = 2) or at 5-10 months (n = 3). Treatment response was evaluated as per mRECIST and PERCIST, and Kaplan-Meier survival analysis was performed.

Results

The disease control rate in PVTT was 50% at 3 months. The median overall survival (OS) was 10.9 months (95% CI, 0.74-21) for all patients. The 6-month, 1-year, 2-year, and 3-year OS rates were 75%, 45.8%, 25%, and 12.5%, respectively. The median OS was 30.4 months (95% CI, 12.1-48.7) versus 18.1 months (0.00-38.8) with complete or partial response versus stable or progressive disease in PVTT (P = .036). Eleven patients had a decline in Child Pugh score of 2 or more points within 3 months after RT. One patient underwent live donor liver transplantation (LDLT) and complete necrosis with no viable tumour was observed in the explant. The patient is cancer- and liver disease-free at 1 year after LDLT.

Conclusions

The present study showed the benefit of radiotherapy with systemic therapy and DEB-TACE in patients with HCC with PVTT.

Advances in knowledge

Radiotherapy as part of the multimodality treatment offers the potential to improve disease control and survival in patients with HCC with PVTT.

Development and verification of a nomogram for predicting portal vein tumor thrombosis in hepatocellular carcinoma

OBJECTIVE

To develop a nomogram to predict the risk of portal vein tumor thrombosis (PVTT) in hepatocellular carcinoma (HCC) patients.

METHODS

Patients diagnosed with HCC at Hunan Provincial People's Hospital between January 2010 and January 2022 were enrolled. Data on demographic characteristics, comorbidities, and laboratory tests were collected. Multivariate logistic regression was used to identify independent risk factors for PVTT, which were then incorporated into a predictive nomogram. The nomogram's discriminative ability was evaluated using the area under the receiver operating characteristic (AUC) curve. Clinical utility was assessed through decision curve analysis (DCA).

RESULTS

Being male (OR 1.991, 95% CI 1.314-3.017, P = 0.001), Barcelona Clinic Liver Cancer (BCLC) staging (stage C: OR 8.043, 95% CI 4.334-14.926, P<0.001; stage D: OR 7.977, 95% CI 3.532-18.017, P<0.001), tumor size >5 cm (OR 1.792, 95% CI 1.116-2.876, P = 0.016), and D-dimer (OR 1.126, 95% CI 1.083-1.171, P<0.001) were identified as independent risk factors for PVTT. The nomogram formula is: Logit = -2.8961 + 0.6586 (male) + BCLC staging (-0.1922 for B, 1.9251 for C, or 1.7938 for D) + 0.5418 (tumor size >5 cm) + 0.1051 DDi. The nomogram achieved an AUC of 0.798 (95% CI 0.774-0.822) in the training set and 0.822 (95% CI 0.782-0.862) in the validation set. Sensitivities were 86.6% and 90.7%, while specificies were 68.2% and 71.8% in the training and validation sets, respectively, demonstrating strong discrimination and predictive accuracy. DCA indicated a favorable risk threshold probability.

CONCLUSION

A nomogram incorporating male sex, BCLC staging, tumor size, and D-dimer demonstrated good predictive performance for PVTT. This tool may aid in the early comprehensive assessment of PVTT risk in HCC patients.

Stereotactic body radiotherapy versus lenvatinib for hepatocellular carcinoma with portal vein tumor thrombosis: a propensity matching score analysis

BACKGROUND AND OBJECTIVES

The purpose of this study was to investigate the survival benefit of Stereotactic Body Radiotherapy (SBRT) versus lenvatinib as first-line therapy in the treatment of hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT).

MATERIALS AND METHODS

147 HCC patients with PVTT were included in this retrospective study, 70 were treated with SBRT and 77 of were treated with lenvatinib. Propensity score matching (PSM) analysis was employed to balance the differences in baseline characteristics between the two groups. Overall survival (OS), progression-free survival (PFS) and objective response rate (ORR) were compared between the two groups. In addition, the safety of patients in both groups was also evaluated.

RESULTS

After PSM, 38 patients were matched in each of the two groups. The median OS was 14.5 (95% CI: 10.1-18.9) and 11.1 (95% CI: 9.3-12.9) months in the SBRT and lenvatinib groups, respectively (P = 0.014). The median PFS was 6.8 (95% CI: 5.1-8.5) and 5.0 (95% CI: 3.0-7.0) months, respectively (P = 0.010). The 1-, 2-years OS rates in the two groups were 65.8% vs. 39.5% and 31.6% vs. 10.5%, respectively. The 6-, 12-months PFS rates in the two groups were 57.9% vs. 44.7% and 28.9% vs. 10.5%, respectively. In addition, the SBRT group had a better ORR than the lenvatinib group (52.6% vs. 23.7%, P = 0.009). Patients with good response to SBRT had better survival. Cox proportional hazard model showed that SBRT was an important prognostic factor for OS and PFS. The incidence of hypertension (34.2% vs. 0%) was higher in the LEN group, however, both treatment modalities were well tolerated in the two groups of patients.

CONCLUSION

In HCC patients with PVTT, SBRT had a better survival benefit than Lenvatinib treatment as first-line therapy.

Prognostic Index for Liver Radiation (PILiR)

A Prognostic Index for Liver Radiation (PILiR) for improved patient selection for stereotactic liver-directed radiotherapy (SBRT) was developed. Using a large single-center database, 195 patients treated with SBRT for local control, including 66 with hepatocellular carcinoma (HCC) and 129 with metastatic liver disease, were analyzed. Only patients ineligible for alternative treatments were included. Overall survival was 11.9 months and 9.4 months in the HCC group and metastatic groups, respectively. In the combined dataset, Child-Pugh Score (CPS) (p = 0.002), serum albumin (p = 0.039), and presence of extrahepatic disease (p = 0.012) were significant predictors of early death on multivariable analysis and were included in the PILiR (total score 0 to 5). Median survival was 23.8, 9.1, 4.5, and 2.6 months for patients with 0, 1-2, 3, and 4-5 points, respectively. In the HCC dataset, CPS (p < 0.001) and gross tumor volume (p = 0.013) were predictive of early death. In the metastatic dataset, serum albumin (p < 0.001) and primary disease site (p = 0.003) were predictive of early death. The AUC for the combined, HCC, and metastatic datasets are 0.78, 0.84, and 0.80, respectively. Poor liver function (defined by CPS and serum albumin) and extrahepatic disease were most predictive of early death, providing clinically important expected survival information for patients and caregivers.

Prognostic nomogram of overall survival for radiation therapy in hepatocellular carcinoma: a population study based on the SEER database and an external cohort

PURPOSE

Radiotherapy (RT) plays an important role in the treatment of hepatocellular carcinoma (HCC). To screen patients who benefit most from RT, a nomogram for survival prediction of RT based on a large sample of patients with HCC was created and validated.

METHODS

A total of 2,252 cases collected from the Surveillance, Epidemiology, and End Results (SEER) database were separated into a training or an internal validation cohort in a 7:3 ratio (n = 1,565:650). An external validation cohort of cases from our institute was obtained (n = 403). LASSO regression and Cox analyses were adopted to develop a nomogram for survival prediction. The decision curve analysis (DCA), calibration curve, and time-dependent receiver operating characteristic curves (TROCs) demonstrated the reliability of the predictive model.

RESULTS

For patients with HCC who received RT, the analyses revealed that the independent survival prediction factors were T stage {T2 vs. T1, hazard ratio (HR) =1.452 [95% CI, 1.195-1.765], p < 0.001; T3 vs. T1, HR = 1.469 [95% CI, 1.168-1.846], p < 0.001; T4 vs. T1, HR = 1.291 [95% CI, 0.951-1.754], p = 0.101}, N stage (HR = 1.555 [95% CI, 1.338-1.805], p < 0.001), M stage (HR = 3.007 [95% CI, 2.645-3.418], p < 0.001), max tumor size (>2 and ≤5 vs. ≤2 cm, HR = 1.273 [95% CI, 0.992-1.633], p = 0.057; >5 and ≤10 vs. ≤2 cm, HR = 1.625 [95% CI, 1.246-2.118], p < 0.001; >10 vs. ≤2 cm, HR = 1.784 [95% CI, 1.335-2.385], p < 0.001), major vascular invasion (MVI) (HR = 1.454 [95% CI, 1.028-2.057], p = 0.034), alpha fetoprotein (AFP) (HR = 1.573 [95% CI, 1.315-1.882], p < 0.001), and chemotherapy (HR = 0.511 [95% CI, 0.454-0.576], p < 0.001). A nomogram constructed with these prognostic factors demonstrated outstanding predictive accuracy. The area under the curve (AUC) in the training cohort for predicting overall survival (OS) at 6, 12, 18, and 24 months was 0.824 (95% CI, 0.803-0.846), 0.824 (95% CI, 0.802-0.845), 0.816 (95% CI, 0.792-0.840), and 0.820 (95% CI, 0.794-0.846), respectively. The AUCs were similar in the other two cohorts. The DCA and calibration curve demonstrated the reliability of the predictive model.

CONCLUSION

For patients who have been treated with RT, a nomogram constructed with T stage, N stage, M stage, tumor size, MVI, AFP, and chemotherapy has good survival prediction ability.

A Nomogram Model to Predict Deep Vein Thrombosis Risk After Surgery in Patients with Hip Fractures

Aims

This study aimed to establish a nomogram model for predicting the probability of postoperative deep vein thrombosis (DVT) risk in patients with hip fractures.

Methods

504 patients were randomly assigned to the training set and validation set, and then divided into a DVT group and a non-DVT group. The study analysed the risk factors for DVT using univariate and multivariate analyses. Based on these parameters, a nomogram model was constructed and validated. The predicting performance of nomogram was evaluated by discrimination, calibration, and clinical usefulness.

Results

The predictors contained in the nomogram model included age, surgical approach, 1-day postoperative D-dimer value and admission ultrasound diagnosis of the lower limb vein. Furthermore, the area under the ROC curve (AUC) for the specific DVT risk-stratification nomogram model (0.815; 95% CI 0.746-0.884) was significantly higher than the current model (Caprini) (0.659; 95% CI 0.572-0.746, P < 0.05). According to the calibration plots, the prediction and actual observation were in good agreement. In the range of threshold probabilities of 0.2-0.8, the predictive performance of the model on DVT risk could be maximized.

Conclusions

The current predictive model could serve as a reliable tool to quantify the possibility of postoperative DVT in hip fractures patients.

Prognostic Value of a CT Radiomics-Based Nomogram for the Overall Survival of Patients with Nonmetastatic BCLC Stage C Hepatocellular Carcinoma after Stereotactic Body Radiotherapy

Purpose

This study aimed to investigatie the feasibility of pretherapeutic CT radiomics-based nomograms to predict the overall survival (OS) of patients with nondistant metastatic Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) undergoing stereotactic body radiotherapy (SBRT).

Methods

A retrospective review of 137 patients with nondistant metastatic BCLC-C HCC who underwent SBRT was made. Radiomics features distilled from pretherapeutic CT images were selected by the method of LASSO regression for radiomics signature construction. Then, the clinical model was constructed based on clinical characteristics. A radiomics nomogram was constructed using the radiomics score (Rad-score) and clinical characteristics to predict post-SBRT OS in BCLC-C HCC patients. An analysis of discriminatory ability and calibration was performed to confirm the efficacy of the radiomics nomogram.

Results

In order to construct the radiomic signature, seven significant features were selected. Patients were divided into low-risk (Rad-score < -0.03) and high-risk (Rad-score ≥ -0.03) groups based on the best Rad-score cutoff value. There were statistically significant differences in OS both in the training set (p < 0.0001) and the validation set (p=0.03) after stratification. The C-indexes of the radiomics nomogram were 0.77 (95% CI: 0.72-0.82) in the training set and 0.71 (95% CI: 0.61-0.81) in the validation set, which outperformed the clinical model and radiomics signature. An AUC of 0.76, 0.79, and 0.84 was reached for 6-, 12-, and 18-month survival predictions, respectively.

Conclusions

The predictive nomogram that combines radiomic features with clinical characteristics has great prospects for application in the prediction of post-SBRT OS in nondistant metastatic BCLC-C HCC patients.

A web-based nomogram model for predicting the overall survival of hepatocellular carcinoma patients with external beam radiation therapy: A population study based on SEER database and a Chinese cohort

BACKGROUND

External beam radiation therapy (EBRT) for hepatocellular carcinoma (HCC) is rarely used in clinical practice. This study aims to develop and validate a prognostic nomogram model to predict overall survival (OS) in HCC patients treated with EBRT.

METHOD

We extracted eligible data of HCC patients between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Those patients were randomly divided into a training cohort (n=1004) and an internal validation cohort (n=429), and an external validation cohort composed of a Chinese cohort (n=95). A nomogram was established based on the independent prognostic variables identified from univariate and multivariate Cox regression analyses. The effective performance of the nomogram was evaluated using the concordance index (C-index), receiver operating characteristic curve (ROC), and calibration curves. The clinical practicability was evaluated using decision curve analysis (DCA).

RESULTS

T stage, N stage, M stage, AFP, tumor size, surgery, and chemotherapy were independent prognostic risk factors that were all included in the nomogram to predict OS in HCC patients with EBRT. In the training cohort, internal validation cohort, and external validation cohort, the C-index of the prediction model was 0.728 (95% confidence interval (CI): 0.716-0.740), 0.725 (95% CI:0.701-0.750), and 0.696 (95% CI:0.629-0.763), respectively. The 6-, 12-,18- and 24- month areas under the curves (AUC) of ROC in the training cohort were 0.835 、0.823 、0.810, and 0.801, respectively; and 0.821 、0.809 、0.813 and 0.804 in the internal validation cohort, respectively; and 0.749 、0.754 、0.791 and 0.798 in the external validation cohort, respectively. The calibration curves indicated that the predicted value of the prediction model performed well. The DCA curves showed better clinical practicability. In addition, based on the nomogram, we established a web-based nomogram to predict the OS of these patients visually.

CONCLUSION

Based on the SEER database and an independent external cohort from China, we established and validated a nomogram to predict OS in HCC patients treated with EBRT. In addition, for the first time, a web-based nomogram model can help clinicians judge the prognoses of these patients and make better clinical decisions.

The α-RECIST (RECIST 1.1 Combined With Alpha Fetoprotein): A Novel Tool for Identifying Tumor Response of Conversion-Radiotherapy for Unresectable Hepatocellular Carcinoma Before Hepatectomy

Purpose

To develop a novel criterion based on the response evaluation criteria in solid tumors (RECIST) 1.1 and alpha fetoprotein (AFP) and evaluate its performance in tumor response for patients with unresectable hepatocellular carcinoma (uHCC) receiving conversion-radiotherapy before hepatectomy.

Method

From June 2012 to December 2020, a total of 39 patients with uHCC, who received intensity-modulated radiotherapy (IMRT) before hepatectomy, were retrospectively included in this study. Pre- and post-treatment contrast-enhanced magnetic resonance imaging (CE-MRI) scans were performed in all patients. Eight modified criteria were developed with the combination of RECIST 1.1, modified RECIST (mRECIST), and the percentage change of AFP, baseline AFP. The endpoint events were recurrence-free survival (RFS).

Results

The median RFS and OS was 26.5 (IQR, 15.7-43.1), 38.8 (IQR, 18.4-53.6) months. An optimal revised evaluation criterion named α-RECIST (alpha fetoprotein-RECIST 1.1) was developed by combining the RECIST 1.1 with the AFPΔ (cut-off value, 76%). Patients defined as responders by α-RECIST showed significantly better RFS and OS than those defined as non-responders (p = 0.035, 0.048). The other criteria (RECIST 1.1, mRECIST, αΔ-mRECIST, α&Δ-RECIST, α&Δ-mRECIST, αBL-RECIST, αBL-mRECIST, α&BL-RECIST, α&BL-mRECIST) all failed to identify responders from non-responders (p = 0.405, 0.201, 0.773, 0.424, 0.266, 0.060, 0.721, 0.644, 0.910, respectively) when correlated with RFS. Responders according to α-RECIST showed significant better RFS compared to non-responders [HR, 0.31 (95% CI: 0.10, 0.98); p=0.046], but no statistical significance was observed in terms of OS [HR, 0.33 (95% CI: 0.11, 1.05); p = 0.06].

Conclusions

Patients identified as responders by α-RECIST provided significant better RFS. The α-RECIST criteria might be a promising tool for identifying tumor response of conversion-radiotherapy for unresectable hepatocellular carcinoma before hepatectomy.