Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study

Abstract Background Identifying the temporal trends of kidney cancer (KC) incidence in both the past and the future at the global and national levels is critical for KC prevention. Methods We retrieved annual KC case data between 1990 and 2017 from the Global Burden of Disease (GBD) online database....

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Main Authors: Zhebin Du, Wei Chen, Qier Xia, Oumin Shi, Qi Chen
Format: Article
Language:English
Published: BMC 2020-05-01
Series:Biomarker Research
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40364-020-00195-3
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spelling doaj-a855bf6d4d4048d4aca72f2410dcbb182020-11-25T03:49:28ZengBMCBiomarker Research2050-77712020-05-018111010.1186/s40364-020-00195-3Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling studyZhebin Du0Wei Chen1Qier Xia2Oumin Shi3Qi Chen4Department of Urology, Renji Hospital affiliated to Shanghai Jiaotong University School of MedicineDepartment of Urology, Renji Hospital affiliated to Shanghai Jiaotong University School of MedicineDepartment of Urology, Pudong New Area People’s HospitalHealth Science Center, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen UniversityDepartment of Urology, Renji Hospital affiliated to Shanghai Jiaotong University School of MedicineAbstract Background Identifying the temporal trends of kidney cancer (KC) incidence in both the past and the future at the global and national levels is critical for KC prevention. Methods We retrieved annual KC case data between 1990 and 2017 from the Global Burden of Disease (GBD) online database. The average annual percentage change (AAPC) was used to quantify the temporal trends of KC age-standardized incidence rates (ASRs) from 1990 to 2017. Bayesian age-period-cohort models were used to predict KC incidence through 2030. Results Worldwide, the number of newly diagnosed KC cases increased from 207.3 thousand in 1990 to 393.0 thousand in 2017. The KC ASR increased from 4.72 per 100,000 to 4.94 per 100,000 during the same period. Between 2018 and 2030, the number of KC cases is projected to increase further to 475.4 thousand (95% highest density interval [HDI] 423.9, 526.9). The KC ASR is predicted to decrease slightly to 4.46 per 100,000 (95% HDI 4.06, 4.86). A total of 90, 2, and 80 countries or territories are projected to experience increases, remain stable, and experience decreases in KC ASR between 2018 and 2030, respectively. In most developed countries, the KC incidence is forecasted to decrease irrespective of past trends. In most developing countries, the KC incidence is predicted to increase persistently through 2030. Conclusions KC incidence is predicted to decrease in the next decade, and this predicted decrease is mainly driven by the decreases in developed countries. More attention should be placed on developing countries.http://link.springer.com/article/10.1186/s40364-020-00195-3Kidney cancerIncidencePredictionTemporal trendsModeling study
collection DOAJ
language English
format Article
sources DOAJ
author Zhebin Du
Wei Chen
Qier Xia
Oumin Shi
Qi Chen
spellingShingle Zhebin Du
Wei Chen
Qier Xia
Oumin Shi
Qi Chen
Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
Biomarker Research
Kidney cancer
Incidence
Prediction
Temporal trends
Modeling study
author_facet Zhebin Du
Wei Chen
Qier Xia
Oumin Shi
Qi Chen
author_sort Zhebin Du
title Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
title_short Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
title_full Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
title_fullStr Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
title_full_unstemmed Trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a Bayesian age-period-cohort modeling study
title_sort trends and projections of kidney cancer incidence at the global and national levels, 1990–2030: a bayesian age-period-cohort modeling study
publisher BMC
series Biomarker Research
issn 2050-7771
publishDate 2020-05-01
description Abstract Background Identifying the temporal trends of kidney cancer (KC) incidence in both the past and the future at the global and national levels is critical for KC prevention. Methods We retrieved annual KC case data between 1990 and 2017 from the Global Burden of Disease (GBD) online database. The average annual percentage change (AAPC) was used to quantify the temporal trends of KC age-standardized incidence rates (ASRs) from 1990 to 2017. Bayesian age-period-cohort models were used to predict KC incidence through 2030. Results Worldwide, the number of newly diagnosed KC cases increased from 207.3 thousand in 1990 to 393.0 thousand in 2017. The KC ASR increased from 4.72 per 100,000 to 4.94 per 100,000 during the same period. Between 2018 and 2030, the number of KC cases is projected to increase further to 475.4 thousand (95% highest density interval [HDI] 423.9, 526.9). The KC ASR is predicted to decrease slightly to 4.46 per 100,000 (95% HDI 4.06, 4.86). A total of 90, 2, and 80 countries or territories are projected to experience increases, remain stable, and experience decreases in KC ASR between 2018 and 2030, respectively. In most developed countries, the KC incidence is forecasted to decrease irrespective of past trends. In most developing countries, the KC incidence is predicted to increase persistently through 2030. Conclusions KC incidence is predicted to decrease in the next decade, and this predicted decrease is mainly driven by the decreases in developed countries. More attention should be placed on developing countries.
topic Kidney cancer
Incidence
Prediction
Temporal trends
Modeling study
url http://link.springer.com/article/10.1186/s40364-020-00195-3
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