Evidence map›Paper›PMID 38660298›Full record

ArticleFrontiers in immunology2024

A preliminary study of optimal treatment response rates in patients undergoing hepatic arterial infusion chemotherapy combined with molecular targeting and immunotherapy.

Mei Li, Jun Liao, Li Wang, Tianye Lv, Qianfu Sun, Yan Xu, Zhi Guo, Manman Quan, Hao Qin, Haoyang Yu and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 3 institutions in 2 countries.

Mei Li *Department of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Jun Liao *Department of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Li Wang *Department of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Tianye LvDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Qianfu SunDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Yan XuDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Zhi GuoDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Manman QuanDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Hao QinDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Haoyang YuNorman Bethune Second Clinical Medical College, Jilin University, Changchun, China.
Kai ZhangDepartment of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Langfang, China.
Wenge XingDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Haipeng YuDepartment of Interventional Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Tianjin Medical University Cancer Institute and Hospital · CNJilin University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to examine the effectiveness of the best response rate (BRR) as a surrogate for overall survival (OS), using the modified Response Evaluation Criteria in Solid Tumors (mRECIST), in patients with unresectable hepatocellular carcinoma (HCC) undergoing hepatic arterial infusion chemotherapy (HAIC) with fluorouracil, leucovorin, and oxaliplatin (FOLFOX) combined with molecular targeting and immunotherapy. Methods: This study enrolled 111 consecutive patients who had complete imaging data. The median age of patients was 58 years (IQR 50.5-65.0). Among the patients, those with Barcelona Clinic Liver Cancer (BCLC) stage A, BCLC stage B, and BCLC stage C comprised 6.4%, 19.1%, and 73.6%, respectively. The optimal threshold of BRR can be determined using restricted cubic splines (RCS) and the rank sum statistics of maximum selection. Survival curves of patients in the high rating and low rating groups were plotted. We then used the change-in-estimate (CIE) method to filter out confounders and the inverse probability of treatment weighting (IPTW) to balance confounders between the two groups to assess the robustness of the results. Results: The median frequency of the combination treatment regimens administered in the overall population was 3 times (IQR 2.0-3.0). The optimal BRR truncation value calculated was -0.2. Based on this value, 77 patients were categorized as the low rating group and 34 as the high rating group. The differences in the OS between the high and low rating groups were statistically significant (7 months [95%CI 6.0-14.0] vs. 30 months [95%CI 30.0-]; p< 0.001). Using the absolute 10% cut-off value, the CIE method was used to screen out the following confounding factors affecting prognosis: successful conversion surgery, baseline tumor size, BCLC stage, serum total bilirubin level, number of interventional treatments, alpha-fetoprotein level, presence of inferior vena cava tumor thrombus, and partial thrombin activation time. The survival curve was then plotted again using IPTW for confounding factors, and it was found that the low rating group continued to have better OS than the high rating group. Finally, the relationship between BRR and baseline factors was analyzed, and inferior vena cava tumor thrombus and baseline tumor size correlated significantly with BRR. Conclusions: BRR can be used as a surrogate endpoint for OS in unresectable HCC patients undergoing FOLFOX-HAIC in combination with molecular targeting and immunotherapy. Thus, by calculating the BRR, the prognosis of HCC patients after combination therapy can be predicted. Inferior vena cava tumor thrombus and baseline tumor size were closely associated with the BRR.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, HepatocellularFluorouracilImmunotherapyInfusions, Intra-ArterialLeucovorinLiver NeoplasmsAgedFemaleHepatic ArteryHumansMaleMiddle AgedMolecular Targeted TherapyOrganoplatinum CompoundsTreatment OutcomeFluorouracilLeucovorinOrganoplatinum Compoundscombination therapyFOLFOX-HAICimmunotherapyoverall survivalsurrogate endpointtargeted therapy

Identifiers

PMID38660298
PMCPMC11039827
OpenAlexW4394685001

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.