Evidence map›Paper›PMID 34077578›Full record

ReviewJournal of the European Academy of Dermatology and Venereology : JEADV2021

A Bayesian network meta-analysis of comparison of cancer therapeutic vaccines for melanoma.

P Lau, M Shen, F Ma, Y Chen, J Zhang, J Su, X Chen, H Liu

Open access · bronzeAbstract readReviewNetwork Meta-Analysis
In one paragraph

Review in Journal of the European Academy of Dermatology and Venereology : JEADV, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
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

8 authors at 3 institutions in 1 country.

P LauDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
M ShenDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0003-0441-9303
F MaDepartment of Health Management Center, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Y ChenDepartment of Musculoskeletal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
J ZhangDepartment of Dermatology, Shenzhen People's Hospital, The Second Clinical Medical College, The First Affiliated Hospital, Jinan University, Southern University of Science and Technology, Shenzhen, Guangdong, China.
J SuDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-7035-2560
X ChenDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
H LiuDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-9976-2985
Central South University · CNJinan University · CNShanghai Medical College of Fudan University · CN

Funding

National Key Research and Development Program of China 2019YFA0111600National Key Research and Development Program of China 2019YFE0120800National Natural Science Foundation of China 31800979National Natural Science Foundation of China 81874242Natural Science Foundation of China for outstanding Young Scholars 82022060Natural Science Foundation of Hunan Province for outstanding Young Scholars 2019JJ30040
6 · The paper itself

Abstract

Several approaches to active immunotherapy for melanoma, including peptide-based vaccines (PVs), autologous tumour cell vaccines (TCVs), allogeneic TCVs and autologous dendritic cell vaccines (DCVs), have been investigated in clinical trials. However, comprehensive evidence comparing these interventions remains unavailable. The objective of this study was to expand previous work to compare and rank the immunotherapeutic strategies for melanoma in terms of overall survival and toxic effects with a Bayesian network meta-analysis. Methodologically, we performed a network meta-analysis of head-to-head randomized controlled trials comparing and ranking cancer vaccine approaches for patients with melanoma. PubMed, MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the WHO International Clinical Trials Registry Platform and ClinicalTrials.gov were searched up to 31 July 2020. We estimated summary hazard ratios for death and risk ratios for toxicity. The effects of the underlying prognostic variable on survival benefits were examined by meta-regression. We performed subgroup analysis for the outcomes based on metastatic categories. Overall, we identified 4776 citations, of which 15 head-to-head randomized controlled trials (3162 participants) were included in the analysis. In terms of efficacy, allogeneic tumour cell vaccines plus immunotherapy adjuvants, peptide-based vaccines plus immunotherapy adjuvants and standard therapy were more effective than peptide vaccines. The proportion of women was inversely associated with mortality risk. For safety, all treatments were inferior to allogeneic tumour cell vaccines except for allogeneic tumour cell vaccines plus chemotherapy. Peptide vaccines plus immunotherapy adjuvants led to an increased risk of adverse events compared to allogeneic tumour cell vaccines plus immunotherapy adjuvants. These results suggest that allogeneic TCV and autologous DCV are better than standard therapy. PV plus immune modulators are the most effective strategy among all comparable strategies but is associated with increased toxicity. Any combination regimens for cancer therapeutic vaccines need to be balanced between risk and benefit profiles.

Indexed as

Cancer VaccinesMelanomaBayes TheoremFemaleHumansImmunotherapyCancer Vaccines

Identifiers

PMID34077578
PMCPMC8518424
OpenAlexW3164821508

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.