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Not yet recruitingNCT06311916Updated Mar 15, 2024

Efficacy and Safety of Neoadjuvant Therapy in Patients With Resectable HCC Screened by a Multimodal Deep Learning Model.

A Phase 4 interventional study of HAIC + Tirelizumab +lenvatinib +liver resection and liver resection in HCC, sponsored by Chen Xiaoping. Not yet recruiting. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2024-03-15.

Sponsored by Chen Xiaoping · Phase 4, Interventional, and Treatment

Phase
Phase 4
Study type
Interventional
Enrollment
312
Allocation
Randomized
Ages
18 Years to 75 Years
Sex
All
01

Study summary

Primary liver cancer is one of the most common malignant tumors in the world, and more than 90% of primary liver cancers are pathologically characterized as hepatocellular carcinoma (HCC). The intermediate stage (BCLC-B) HCC is highly heterogeneous, and there is no consensus on the treatment of this stage of the tumor in Western and Eastern countries. New tools are urgently needed to guide the choice of treatment options for patients with this stage of the tumor in order to reduce the risk of postoperative recurrence and the overall survival rate.

Read the detailed description

Primary liver cancer is one of the most common malignant tumors in the world, and more than 90% of primary liver cancers are pathologically characterized as hepatocellular carcinoma (HCC). Intermediate stage (BCLC-B) HCC is heterogeneous, and there is no uniform consensus on the treatment of this stage of the tumor in Western and Chinese countries, while the European guidelines recommend liver transplantation, transarterial chemoembolization (TACE), and systemic medication as the first line of treatment. In Eastern countries, such as China, BCLC-B is further categorized into stages IIa and IIb, and surgical resection is recommended as the first-line treatment option for stage IIa, while surgical resection can also be considered for stage IIb. Retrospective studies have found that surgical resection has an overall better prognosis than non-surgical treatment. However, the rate of postoperative recurrence is higher than that of early HCC. To address this issue, new tools are urgently needed to guide the selection of appropriate treatment regimens to reduce the risk of postoperative recurrence and overall survival.

Our multidisciplinary team used deep learning technology to construct an artificial intelligence prediction model of neoadjuvant therapy benefit based on pre-treatment genetic testing data, digital pathology slides and imaging data (enhanced MRI) of 536 intermediate-stage HCC patients treated with HAIC in combination with lenvatinib and PD-1 monoclonal antibody in six centers, and external center data validated the model's good ability to identify the beneficiary population of the combination regimen ( AUC 0.89, Accuracy 0.86). The aim of this study is to study the effectiveness and safety of New-adj-Net in improving the progression of intermediate-stage HCC patients during neoadjuvant therapy and postoperative recurrence by observing the benefit of the combined neoadjuvant regimen in patients who are potentially benefited from neoadjuvant therapy and direct surgery from the perspective of precision therapy.

02

Conditions studied

  • HCC

Keywords

  • Hepatocellular carcinoma
  • Neoadjuvant tehrapy
  • recurrence
  • Deep learning
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In context

Lead sponsor

Chen Xiaoping is the lead sponsor of 17 studies on the registry; 5 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years to 75 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  1. Aged 18-75.
  2. No previous local or systemic treatment for hepatocellular carcinoma.
  3. Child-Pugh liver function score ≤ 7.
  4. ECOG PS 0-1.
  5. No serious organic diseases of the heart, lungs, brain, kidneys, etc.
  6. Enhanced MRI determines that the tumor stage is intermediate (BCLC stage B) and is safe for radical hepatectomy.
  7. Pathologic type of hepatocellular carcinoma confirmed by puncture biopsy.
  8. Multimodal Deep Learning Model Screening Based on Pathology, Imaging, and Genetic Data Suggests Benefit from HAIC in Combination with Lenvatinib and PD-1 inhibitors.

Exclusion criteria

Exclusion Criteria:

  1. Pregnant and lactating women.
  2. Tumor distribution in two liver lobes, diffuse growth, or other reasons why radical R0 resection is not possible.
  3. Suffering from a condition that interferes with the absorption, distribution, metabolism, or clearance of the study drug (e.g., severe vomiting, chronic diarrhea, intestinal obstruction, impaired absorption, etc.).
  4. A history of gastrointestinal bleeding within the previous 4 weeks or a definite predisposition to gastrointestinal bleeding (e.g., known locally active ulcer lesions, fecal occult blood ++ or more, or gastroscopy if persistent fecal occult blood +) that has not been targeted, or other conditions that may have caused gastrointestinal bleeding (e.g., severe fundoplication/esophageal varices), as determined by the investigator.
  5. Active infection.
  6. Other significant clinical and laboratory abnormalities that affect the safety evaluation.
  7. Inability to follow the study protocol for treatment or follow up as scheduled.
05

Study design

Phase
Phase 4
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
312 participants (estimated)

Study arms

  • Experimental
    Neoadjuvant therapy group

    Patients in the neoadjuvant therapy group received neoadjuvant therapy before undergoing liver resection.

    Drug: HAIC + Tirelizumab +lenvatinib +liver resection

  • Active comparator
    Direct surgical resection group

    Patients in the control group undergoing liver resection directly.

    Procedure: liver resection

Interventions

  • DrugHAIC + Tirelizumab +lenvatinib +liver resection

    Patients in the neoadjuvant group received two cycles of neoadjuvant hepatic arterial infusion chemotherapy (HAIC, adoption of the FOFOLX6 program, Folinic acid+5-fluorouracil+Oxaliplatin, 21 days between second HAIC treatments with a window of ±3 days) + Tirelizumab (First treatment with Tirelizumab was started 0-1 days after HAIC, 200 mg IV, followed by a second treatment 21 days later)+ lenvatinib (Oral 8 mg or 12mg once a day depending body weight). Assessment of tumor status and surgical safety after receiving neoadjuvant therapy, and eligible patients then underwent surgical resection.

    Also known as: Non

  • Procedureliver resection

    Direct liver resection or laparoscopic liver resection depending on tumor status.

06

What researchers measure

Primary outcomes

  1. Disease-free survival

    DFS defined as the time after surgical resection until tumor recurrence or death

    Time frame: From date of include in this research until the date of first documented recurrence or date of death from any cause, whichever came first, assessed up to 60 months.

Secondary outcomes

  1. Safety Assessment

    Any adverse event during treatment that is incompatible with the therapeutic purpose of the medication.

    Time frame: 2 months

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Study locations

No study locations are listed for this record.

08

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Mar 15, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT06311916
Lead sponsor
Chen Xiaoping
Responsible party
Chen Xiaoping (Professor, Tongji Hospital) — Sponsor-investigator
First posted
Mar 15, 2024
Start date
May 1, 2024 (estimated)
Primary completion
Dec 31, 2027 (estimated)
Completion
Dec 31, 2028 (estimated)
Last update
Mar 15, 2024

Study contacts

WanGuang Zhang
Contact
wgzhang@tjh.tjmu.edu.cn
+8613886195965
Xiaoping Chen
principal investigator · Tongji Hospital

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Mar 2024. You cannot join it, but the record below documents what was studied.

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