A Web Tool for Age-period-cohort Analysis of Cancer Incidence and Mortality Rates

Overview

Journal Cancer Epidemiol Biomarkers Prev

Specialties Biochemistry
Oncology
Public Health

Date 2014 Aug 23

PMID 25146089

Citations 245

Authors

Philip S Rosenberg

David P Check

William F Anderson

Affiliations

Soon will be listed here.

Abstract

Background: Age-period-cohort (APC) analysis can inform registry-based studies of cancer incidence and mortality, but concerns about statistical identifiability and interpretability, as well as the learning curves of statistical software packages, have limited its uptake.

Methods: We implemented a panel of easy-to-interpret estimable APC functions and corresponding Wald tests in R code that can be accessed through a user-friendly Web tool.

Results: Input data for the Web tool consist of age-specific numbers of events and person-years over time, in the form of a rate matrix of paired columns. Output functions include model-based estimators of cross-sectional and longitudinal age-specific rates, period and cohort rate ratios that incorporate the overall annual percentage change (net drift), and estimators of the age-specific annual percentage change (local drifts). The Web tool includes built-in examples for teaching and demonstration. User data can be input from a Microsoft Excel worksheet or by uploading a comma-separated-value file. Model outputs can be saved in a variety of formats, including R and Excel.

Conclusions: APC methodology can now be carried out through a freely available user-friendly Web tool. The tool can be accessed at http://analysistools.nci.nih.gov/apc/.

Impact: The Web tool can help cancer surveillance researchers make important discoveries about emerging cancer trends and patterns.

Citing Articles

Burden, risk factors, and projections of ischemic heart disease in China (1990-2021): findings from the 2021 GBD study.

Xu S, Liu Z, Tang M, Xu C Front Cardiovasc Med. 2025; 12:1549147.

PMID: 40078456 PMC: 11897495. DOI: 10.3389/fcvm.2025.1549147.

Mortality of Head and Neck Cancer in China From 1990 to 2019: A Secondary Data Analysis.

Zhu Z, Yuan J, Fu L, Zhang W, Liu S, Liu Y Cancer Rep (Hoboken). 2025; 8(3):e70116.

PMID: 40071521 PMC: 11897804. DOI: 10.1002/cnr2.70116.

Osteoarthritis burden and inequality from 1990 to 2021: a systematic analysis for the global burden of disease Study 2021.

Wu R, Guo Y, Chen Y, Zhang J Sci Rep. 2025; 15(1):8305.

PMID: 40065123 PMC: 11894191. DOI: 10.1038/s41598-025-93124-z.

Trends in the burden of urolithiasis in China: an analysis from the global burden of disease study 2021.

Lin Y, Lin Q, Zhou Q, Xu N, Zheng D, Wang X Front Surg. 2025; 12:1537706.

PMID: 40040815 PMC: 11876551. DOI: 10.3389/fsurg.2025.1537706.

Trends in the global, regional, and national burden of bladder cancer from 1990 to 2021: an observational study from the global burden of disease study 2021.

Su X, Tao Y, Chen F, Han X, Xue L Sci Rep. 2025; 15(1):7655.

PMID: 40038504 PMC: 11880295. DOI: 10.1038/s41598-025-92033-5.

References

Parkin D, Bray F, Devesa S . Cancer burden in the year 2000. The global picture. Eur J Cancer. 2001; 37 Suppl 8:S4-66. DOI: 10.1016/s0959-8049(01)00267-2. View

Tarone R, Chu K . Nonparametric evaluation of birth cohort trends in disease rates. J Epidemiol Biostat. 2000; 5(3):177-91. View

Anderson W, Rosenberg P, Petito L, Katki H, Ejlertsen B, Ewertz M . Divergent estrogen receptor-positive and -negative breast cancer trends and etiologic heterogeneity in Denmark. Int J Cancer. 2013; 133(9):2201-6. PMC: 3749265. DOI: 10.1002/ijc.28222. View

Robertson C, Boyle P . Age-period-cohort analysis of chronic disease rates. I: Modelling approach. Stat Med. 1998; 17(12):1305-23. DOI: 10.1002/(sici)1097-0258(19980630)17:12<1305::aid-sim853>3.0.co;2-w. View

McNally R, Cairns D, Eden O, Kelsey A, Taylor G, Birch J . Examination of temporal trends in the incidence of childhood leukaemias and lymphomas provides aetiological clues. Leukemia. 2001; 15(10):1612-8. DOI: 10.1038/sj.leu.2402252. View

Liu S, Semenciw R, Waters C, Wen S, Mery L, Mao Y . Clues to the aetiological heterogeneity of testicular seminomas and non-seminomas: time trends and age-period-cohort effects. Int J Epidemiol. 2000; 29(5):826-31. DOI: 10.1093/ije/29.5.826. View

Bergstrom R, Adami H, Mohner M, Zatonski W, Storm H, Ekbom A . Increase in testicular cancer incidence in six European countries: a birth cohort phenomenon. J Natl Cancer Inst. 1996; 88(11):727-33. DOI: 10.1093/jnci/88.11.727. View

Clayton D, Schifflers E . Models for temporal variation in cancer rates. I: Age-period and age-cohort models. Stat Med. 1987; 6(4):449-67. DOI: 10.1002/sim.4780060405. View

Holford T . The estimation of age, period and cohort effects for vital rates. Biometrics. 1983; 39(2):311-24. View

10.

Anderson W, Rosenberg P, Menashe I, Mitani A, Pfeiffer R . Age-related crossover in breast cancer incidence rates between black and white ethnic groups. J Natl Cancer Inst. 2008; 100(24):1804-14. PMC: 2639327. DOI: 10.1093/jnci/djn411. View

11.

de Vries E, Bray F, Coebergh J, Parkin D . Changing epidemiology of malignant cutaneous melanoma in Europe 1953-1997: rising trends in incidence and mortality but recent stabilizations in western Europe and decreases in Scandinavia. Int J Cancer. 2003; 107(1):119-26. DOI: 10.1002/ijc.11360. View

12.

Anderson W, Jatoi I, Tse J, Rosenberg P . Male breast cancer: a population-based comparison with female breast cancer. J Clin Oncol. 2009; 28(2):232-9. PMC: 2815713. DOI: 10.1200/JCO.2009.23.8162. View

13.

Anderson W, Pfeiffer R, Tucker M, Rosenberg P . Divergent cancer pathways for early-onset and late-onset cutaneous malignant melanoma. Cancer. 2009; 115(18):4176-85. PMC: 2741537. DOI: 10.1002/cncr.24481. View

14.

Anderson W, Chu K, Chang S, Sherman M . Comparison of age-specific incidence rate patterns for different histopathologic types of breast carcinoma. Cancer Epidemiol Biomarkers Prev. 2004; 13(7):1128-35. View

15.

Grimley P, Matsuno R, Rosenberg P, Henson D, Schwartz A, Anderson W . Qualitative age interactions between low-grade and high-grade serous ovarian carcinomas. Cancer Epidemiol Biomarkers Prev. 2009; 18(8):2256-61. DOI: 10.1158/1055-9965.EPI-09-0240. View

16.

Holford T . Approaches to fitting age-period-cohort models with unequal intervals. Stat Med. 2005; 25(6):977-93. DOI: 10.1002/sim.2253. View

17.

Bray F, Richiardi L, Ekbom A, Forman D, Pukkala E, Cuninkova M . Do testicular seminoma and nonseminoma share the same etiology? Evidence from an age-period-cohort analysis of incidence trends in eight European countries. Cancer Epidemiol Biomarkers Prev. 2006; 15(4):652-8. DOI: 10.1158/1055-9965.EPI-05-0565. View

18.

Holford T, Cronin K, Mariotto A, Feuer E . Changing patterns in breast cancer incidence trends. J Natl Cancer Inst Monogr. 2006; (36):19-25. DOI: 10.1093/jncimonographs/lgj016. View

19.

Tarone R, Chu K . The greater impact of menopause on ER- than ER+ breast cancer incidence: a possible explanation (United States). Cancer Causes Control. 2002; 13(1):7-14. DOI: 10.1023/a:1013960609008. View

20.

Spix C, Eletr D, Blettner M, Kaatsch P . Temporal trends in the incidence rate of childhood cancer in Germany 1987-2004. Int J Cancer. 2007; 122(8):1859-67. DOI: 10.1002/ijc.23281. View