Evidence map›Paper›PMID 37941298›Full record

ArticleThoracic cancer2023

Secular trends of morbidity and mortality of thyroid cancer in five Asian countries from 1990 to 2019 and their predictions to 2035.

Shi-Di Tang, Hao Zi, Hua Tao, Qiao Huang, Xing-Pei Guo, Tong Deng, Fei Li

Abstract read
In one paragraph

Article in Thoracic cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

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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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. [Results of active surveillance of clinical progression in low-risk papillary thyroid microcarcinoma: a single center prospective cohort study].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025
    Observational
  4. Review
  5. Article
  6. 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

7 authors.

Shi-Di TangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.ORCID 0009-0008-0451-0012
Hao ZiCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Hua TaoDepartment of Medical Social Services, Zhengzhou Second Hospital, Zhengzhou, China.
Qiao HuangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xing-Pei GuoDepartment of General Surgery, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Tong DengCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.ORCID 0000-0001-5871-1348
Fei LiCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.ORCID 0009-0009-3269-5007

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rising burden of thyroid cancer (TC) is a public health problem in Asia. Predicting the future burden of TC in Asian countries is essential for disease prevention.

methodsData were obtained from the Global Burden of Disease 2019 for five Asian countries. We applied Bayesian age-period-cohort models to predict morbidity and mortality to 2035 and calculated age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR). Furthermore, the estimated annual percentage change was calculated to evaluate the variation of ASIR and ASMR.

resultsBy 2035, predictions suggest that cases of TC will reach 75.56 × 10

conclusionThe disease burden caused by TC will further increase in five Asian countries, especially for men. It is necessary to develop more rational and timely disease prevention and manage strategies facing this disease trend.

Indexed as

Thyroid NeoplasmsAsiaBayes TheoremChinaFemaleHumansIncidenceMaleMorbidityAsian countriesmorbiditymortalitypredictionthyroid cancer

Identifiers

PMID37941298
PMCPMC10733153

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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.