Nanoparticles based on photothermal effects in the treatment of hepatocellular carcinoma (HCC): a meta-analysis and systematic review.
메타분석
1/5 보강
[BACKGROUND] Hepatocellular carcinoma (HCC) is a highly lethal form of cancer with a global mortality rate that is unparalleled among malignant tumours.
- 연구 설계 systematic review
APA
Zhang W, Mao X, et al. (2026). Nanoparticles based on photothermal effects in the treatment of hepatocellular carcinoma (HCC): a meta-analysis and systematic review.. BMC cancer, 26(1). https://doi.org/10.1186/s12885-026-15575-5
MLA
Zhang W, et al.. "Nanoparticles based on photothermal effects in the treatment of hepatocellular carcinoma (HCC): a meta-analysis and systematic review.." BMC cancer, vol. 26, no. 1, 2026.
PMID
41612267
Abstract
[BACKGROUND] Hepatocellular carcinoma (HCC) is a highly lethal form of cancer with a global mortality rate that is unparalleled among malignant tumours. The photothermal effect exhibited by nanoparticles offers a novel approach for the treatment of HCC. To perform a systematic review and meta-analysis on the therapeutic effects of nanoparticles on hepatocellular carcinoma (HCC) under the photothermal effect.
[METHODS] We conducted a comprehensive literature search across four major databases (PubMed, Embase, Web of Science, and Scopus) and performed bibliometric analysis to demonstrate the remarkable therapeutic efficacy of photothermal effect-driven nanoparticles in hepatocellular carcinoma (HCC) treatment within the near-infrared (NIR) biological tissue optical window (wavelength range: 650-1350 nm). The study selection, quality assessment, and data extraction were rigorously performed according to standardized protocols, with particular emphasis on key parameters including control group descriptions, sample sizes of control and experimental groups, tumor volume and weight, as well as therapeutic outcome measures. Sensitivity analysis and bias assessment were implemented, ultimately yielding research conclusions with high reliability.
[RESULTS] A total of 36 studies were included, all of which were assessed as high-quality studies. Based on the data of tumor volume and mass, Meta-analysis and sensitivity analysis revealed the significant therapeutic effect of photothermal effect-driven nanoparticles in the treatment of HCC, with a high degree of stability in general. In terms of tumor volume, 34 data sets were obtained from 31 studies, with a WMD of -0.95, a 95% confidence interval of (-1.10, -0.80), an I² value of 98.3%, and a p-value of less than 0.001, indicating that photothermal effect-driven nanoparticles have significant efficacy in reducing tumor volume. Regarding tumor mass, 25 studies provided 29 data sets, with a WMD of -0.90, a 95% confidence interval of (-1.03, -0.77), an I² value of 99.0%, and a p-value of less than 0.001. Sensitivity analysis revealed that excluding the data from Dun et al. (2022) significantly influenced the overall effect sizes for both tumor volume (WMD = -3.49) and tumor mass (WMD = -3.98). Funnel plot analysis indicated good symmetry for tumor volume data, suggesting no significant publication bias, whereas asymmetry was observed for tumor mass data, implying potential bias from small-sample studies.
[CONCLUSION] Photothermal effect-driven nanoparticles exhibit positive therapeutic effects in HCC, primarily manifested in the reduction of tumor volume and mass, offering new ideas and strategies for the treatment of advanced hepatocellular carcinoma.
[METHODS] We conducted a comprehensive literature search across four major databases (PubMed, Embase, Web of Science, and Scopus) and performed bibliometric analysis to demonstrate the remarkable therapeutic efficacy of photothermal effect-driven nanoparticles in hepatocellular carcinoma (HCC) treatment within the near-infrared (NIR) biological tissue optical window (wavelength range: 650-1350 nm). The study selection, quality assessment, and data extraction were rigorously performed according to standardized protocols, with particular emphasis on key parameters including control group descriptions, sample sizes of control and experimental groups, tumor volume and weight, as well as therapeutic outcome measures. Sensitivity analysis and bias assessment were implemented, ultimately yielding research conclusions with high reliability.
[RESULTS] A total of 36 studies were included, all of which were assessed as high-quality studies. Based on the data of tumor volume and mass, Meta-analysis and sensitivity analysis revealed the significant therapeutic effect of photothermal effect-driven nanoparticles in the treatment of HCC, with a high degree of stability in general. In terms of tumor volume, 34 data sets were obtained from 31 studies, with a WMD of -0.95, a 95% confidence interval of (-1.10, -0.80), an I² value of 98.3%, and a p-value of less than 0.001, indicating that photothermal effect-driven nanoparticles have significant efficacy in reducing tumor volume. Regarding tumor mass, 25 studies provided 29 data sets, with a WMD of -0.90, a 95% confidence interval of (-1.03, -0.77), an I² value of 99.0%, and a p-value of less than 0.001. Sensitivity analysis revealed that excluding the data from Dun et al. (2022) significantly influenced the overall effect sizes for both tumor volume (WMD = -3.49) and tumor mass (WMD = -3.98). Funnel plot analysis indicated good symmetry for tumor volume data, suggesting no significant publication bias, whereas asymmetry was observed for tumor mass data, implying potential bias from small-sample studies.
[CONCLUSION] Photothermal effect-driven nanoparticles exhibit positive therapeutic effects in HCC, primarily manifested in the reduction of tumor volume and mass, offering new ideas and strategies for the treatment of advanced hepatocellular carcinoma.
MeSH Terms
Carcinoma, Hepatocellular; Liver Neoplasms; Humans; Nanoparticles; Photothermal Therapy; Animals; Treatment Outcome
같은 제1저자의 인용 많은 논문 (5)
- USP32 Promotes Cancer Cell Invasion, Macrophage M2 Polarization, and CD8+ T Cell Apoptosis in Gastric Cancer Through Upregulation of DAPK1.
- Challenges to case-only analysis for interaction detection using polygenic risk scores: model assumptions and biases in large biobanks.
- United multi-omics and machine learning refine regulatory T cell-defined hepatocellular carcinoma subtypes.
- A SLC7A5-Specific Near-Infrared Fluorescent Probe for Cancer-Targeted Imaging Applications.
- Dynamic liver dysfunction predicts poor survival in patients with EGFR-mutant non-small cell lung cancer and liver metastases treated with EGFR tyrosine kinase inhibitors.