A new prognostic model for predicting overall survival and progression-free survival in unresectable hepatocellular carcinoma treated with the FOLFOX-HAIC regimen based on patient clinical characteristics and blood biomarkers
Abstract Background We developed a prognostic model to evaluate the overall survival (OS) and progression-free survival (PFS) of patients with unresectable hepatocellular carcinoma (u-HCC) treated with Hepatic arterial infusion chemotherapy of infusion oxaliplatin, fluorouracil and leucovorin (FOLFO...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
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| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-024-13390-4 |
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| Summary: | Abstract Background We developed a prognostic model to evaluate the overall survival (OS) and progression-free survival (PFS) of patients with unresectable hepatocellular carcinoma (u-HCC) treated with Hepatic arterial infusion chemotherapy of infusion oxaliplatin, fluorouracil and leucovorin (FOLFOX-HAIC). Methods This model was based on a retrospective study of u-HCC patients treated with the FOLFOX-HAIC (oxaliplatin 130 mg/m2, leucovorin 400 mg/m2, fluorouracil bolus 400 mg/m2 on day 1, and fluorouracil infusion 2,400 mg/m2 for 23–46 h, once every 3–4 weeks). We divided the patients into a training cohort and a validation cohort, used LASSO regression construct prognostic models, predict patient’s OS and PFS based on nomograms of models. Patients were divided into high-risk, medium-risk, and low-risk groups according to their respective model risk scores. Kaplan-Meier survival analysis was used to assess the survival time between the three patient cohorts. Results A total of 333 patients were enrolled in the study and divided into a training cohort and a verification cohort at a ratio of 7:3 (233 in the training cohort and 100 in the validation cohort). The prognostic model we established contained nine prognostic variables. The results of concordance index (C-index) of the OS and PFS prognostic model was 0.75 and 0.71, respectively, higher than that of the TNM staging (0.57 and 0.55, p < 0.001), time-dependent ROC (td-ROC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) also showed that the model was better than the TNM staging for u-HCC predicting OS and PFS. Subsequently, the model was used to develop a nomogram to predict the individualized prognosis of patients with u-HCC treated with the FOLFOX-HAIC, with a higher net benefit than the TMN staging. According to the risk score, patients were divided into a low-risk group (risk score ≤ 0.458), the medium-risk group (risk score: 0.458–0.799) and the high-risk group (risk score > 0.799). There were significant differences in the OS and PFS between the three groups. Conclusions The model developed by our team enables risk stratification and personalized prognosis assessment for u-HCC patients undergoing FOLFOX-HAIC treatment, exhibiting superior predictive accuracy and discriminative capability compared to TNM staging. |
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| ISSN: | 1471-2407 |