Open AccessImproved trends of lung cancer mortality‐to‐incidence ratios in countries with high healthcare expenditure
Author(s) -
Sung WenWei,
Au KwongKwok,
Wu HanRu,
Yu ChiaYing,
Wang YaoChen
Publication year - 2021
Publication title -
thoracic cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 28
eISSN - 1759-7714
pISSN - 1759-7706
DOI - 10.1111/1759-7714.13912
Subject(s) - medicine , lung cancer , per capita , gross domestic product , human development index , incidence (geometry) , rank correlation , spearman's rank correlation coefficient , cancer , health care , mortality rate , demography , oncology , environmental health , population , human development (humanity) , statistics , physics , mathematics , optics , sociology , economics , economic growth , political science , law
Background Lung cancer stage has a significant impact on prognosis, and early detection of lung cancer relies on screenings. Despite the strong relationship between screening and lung cancer staging, the role of healthcare expenditure in lung cancer outcomes remains unknown. The aim of this study was to evaluate the relationship between economic status and clinical outcomes in lung cancer. Methods Data were obtained from GLOBOCAN and the World Health Organization. Mortality‐to‐incidence ratios (MIRs) and their change over time, calculated as the difference between the MIRs of 2012 and 2018 ( δ MIR), were used to evaluate their correlation to expenditures on healthcare and human development index (HDI) disparities via Spearman's rank correlation coefficient. Results Regions such as North America have relatively high crude incidence rates but low MIR values. Furthermore, countries with lower crude incidence rates spent less on healthcare. The results show significant negative associations between HDI, current health expenditure (CHE) per capita, CHE as a percentage of gross domestic product (CHE/GDP), and MIR. As for MIR and δ MIR, countries with favorable MIRs also showed improving MIRs based on δ MIR. Conclusions HDI, CHE per capita, CHE/GDP, and development status play noticeable roles in the prognosis of lung cancer, leading to large disparities in clinical outcomes.