Evidence map›Paper›PMID 25146089›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2014

A web tool for age-period-cohort analysis of cancer incidence and mortality rates.

Philip S Rosenberg, David P Check, William F Anderson

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 505 papers.

0numbers the graph read from it
0cells of the map it votes in
505citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

505 citing papers in PubMed.

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  12. Diverging trends in motor neuron disease burden in China: an ageing-driven increase despite declining age-standardised rates - a GBD 2021 analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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  14. Trends in Female Breast Cancer Incidence among Japanese, Korean, and US Populations: An Age-Period-Cohort Analysis.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  15. Trends in malignant mesothelioma incidence in Spain, 1999-2023: a joinpoint and age-period-cohort analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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445 more citing papers are in PubMed but not listed here.

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

3 authors.

Philip S RosenbergBiostatistics Branch, Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland. rosenbep@mail.nih.gov.
David P CheckBiostatistics Branch, Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland.
William F AndersonBiostatistics Branch, Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, NIH, Bethesda, Maryland.

Funding

Methods for Epidemiology StudiesZIACP010181 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBERT, PAUL · 2009 to 2025
$34.8M
Methods for Epidemiology StudiesZ01CP010181 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CHATTERJEE, NILANJAN · 2003 to 2008
$4.8M
Intramural NIH HHS Z01 CP010181
6 · The paper itself

Abstract

backgroundAge-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.

methodsWe 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.

resultsInput 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.

conclusionsAPC 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.

Indexed as

Data Interpretation, StatisticalInternetPopulation SurveillanceSoftwareAge FactorsCohort StudiesHumansIncidenceLearning CurveNeoplasms

Identifiers

PMID25146089
PMCPMC4221491

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.