Evidence map›Paper›PMID 35089494›Full record

ArticleCurrent medical science2022

The 2010-2020 National Natural Science Foundation of China: Radiation Therapy.

Jun Liu, Yang Li, Rong Shi

Abstract read
PubMed Publisher
In one paragraph

Article in Current medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 41% 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

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

  1. Pooled it
  2. Trial
  3. 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

3 authors at 2 institutions in 1 country.

Jun LiuDivision VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China.
Yang LiDivision VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China.
Rong ShiDivision VII, Department of Health Sciences, National Natural Science Foundation of China, Beijing, 100085, China. shirong@nsfc.gov.cn.
National Natural Science Foundation of China · CNAnhui Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study explains the application number and funding rate of oncology projects undertaken by the National Natural Science Foundation of China (NSFC), with focus on tumor radiotherapy-related research over the past 11 years.

methodsA stratified analysis was carried out on the application and funding status of tumor radiotherapy studies in different NSFC project categories, different research areas, and different tumor types. Research areas that required specific focus, such as immunology-related radiotherapy, multimodality imaging and radiomics, and post-radiotherapy organ injury, were separately analyzed.

resultsThe status and development trends of various related research fields were studied, and the research results were presented with the support of the NSFC, in order to provide reference for future applications and funding allocations.

conclusionThe number of applications for funding increases every year. Although the total number of funded projects has also increased every year, the funding rate has decreased year by year. Projects on radiotherapy and immunization have been at the forefront in recent years, and the funding rate for these projects increases yearly.

Indexed as

Natural Science DisciplinesNeoplasmsChinaFoundationsHumansfunding rateNational Natural Science Foundation of Chinaradiation therapy

Identifiers

PMID35089494
OpenAlexW4210258735

What OpenQuestion holds

Textmetadata
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.