Trends in disability-adjusted life years of lung cancer among women from 2004 to 2030 in Guangzhou, China: A population-based study.

Trends in disability-adjusted life years of lung cancer among women from 2004 to 2030 in Guangzhou, China: A population-based study.

Lin, Xiao;Bloom, Michael S;Du, Zhicheng;Hao, Yuantao;
Cancer epidemiology 2019 Vol. 63 pp. 101586
322
lin2019trendscancer

Abstract

Forecast of disease burden in lung cancer is an important health agenda. One of the main challenges is to predict the evolution of trends in disability-adjusted life year (DALY) of lung cancer so as to anticipate the future burden and to coordinate the supply of sufficient health services and care.Using 2004-2013 cancer registry data in Guangzhou, we fitted Bayesian age-period-cohort models with age, period, and cohort effects to analyze trends of lung cancer among women, and then made forecast for DALY of lung cancer until 2030.During 2004-2013, there was an annual average of 10,582 DALYs for lung cancer (15.84% of total DALY). In 2014-2030, DALY is expected to reach 234,752 person-years for lung cancer (12.25% of total DALY), with an annual mean of 13,809 DALYs. Lung cancer crude DALY rate is projected to rise steadily from 257.56 (95% uncertainty interval: 165.97-361.22) in 2014 to 316.99 (219.96-419.41) per 100,000 women in 2030, and the rise is mainly seen in 45-64 years age group. Lung cancer DALY rate remains the highest in the 65-89 years age group.Women at 65-89 years carry the highest lung cancer burden among other age groups in Guangzhou. The DALY rate of lung cancer is projected to increase most precipitously for the 45-64 years age group. This indicates that concerted efforts are needed to develop adequate cancer services, and to reassess health resources for control and care of lung cancer in these populations.

Citation

ID: 48052
Ref Key: lin2019trendscancer
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
48052
Unique Identifier:
S1877-7821(19)30097-9
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet