Evidence map›Paper›PMID 35005708›Full record

ArticleMedComm2022

Criteria for judging the immune markers of COVID-19 disease vaccines.

Nan Lin, Haoxuan Fu, Dan Pu, Yuxin Quan, Yueyi Li, Xiaomeng Yin, Yuhao Wei, Hang Wang, Xuelei Ma, Xiawei Wei

Open access · goldAbstract read
In one paragraph

Article in MedComm, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

10 authors at 2 institutions in 2 countries.

Nan LinWest China School of Medicine West China Hospital Sichuan University Chengdu China.
Haoxuan FuDepartment of Statistics University of Illinois at Urbana Champaign Urbana Illinois USA.
Dan PuDepartment of Radiation Oncology Cancer Center, West China Hospital, Sichuan University Chengdu China.
Yuxin QuanWest China School of Medicine West China Hospital Sichuan University Chengdu China.
Yueyi LiDepartment of Biotherapy Cancer Center, West China Hospital, Sichuan University Chengdu China.
Xiaomeng YinDepartment of Biotherapy Cancer Center, West China Hospital, Sichuan University Chengdu China.
Yuhao WeiWest China School of Medicine West China Hospital Sichuan University Chengdu China.
Hang WangWest China School of Medicine West China Hospital Sichuan University Chengdu China.
Xuelei MaDepartment of Biotherapy Cancer Center, West China Hospital, Sichuan University Chengdu China.
Xiawei WeiLaboratory of Aging Research and Nanotoxicology, State Key Laboratory of Biotherapy National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University Chengdu China.ORCID https://orcid.org/0000-0002-6513-6422
Sichuan University · CNUniversity of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sweeping the world, effective and affordable vaccines are in urgent need. A reliable system for the assessment of SARS-CoV-2 vaccines would boost the development of vaccines and reduce the research cost. We constructed a logistic regression model and analyzed the relationship between antibody (Ab) level and efficacy of different vaccine types. The relationship between assessment dates and Ab levels was depicted by plotting the mean of Ab levels evolved over time and a fitted cubic polynomial model. Anti-spike immunoglobulin G (IgG) could best estimate the vaccine efficacy (VE) (adjusted

Indexed as

assessmentneutralizing antibodiesSARS‐CoV‐2vaccine

Identifiers

PMID35005708
PMCPMC8719528
OpenAlexW4205478085

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.