# Estimating the burden of recurrent events in the presence of competing risks

## The method of mean cumulative count

Huiru Dong, Leslie L. Robison, Wendy M. Leisenring, Leah J. Martin, Gregory Armstrong, Yutaka Yasui

Research output: Contribution to journalArticle

16 Citations (Scopus)

### Abstract

Cumulative incidence has been widely used to estimate the cumulative probability of developing an event of interest by a given time, in the presence of competing risks. When it is of interest to measure the total burden of recurrent events in a population, however, the cumulative incidence method is not appropriate because it considers only the first occurrence of the event of interest for each individual in the analysis: Subsequent occurrences are not included. Here, we discuss a straightforward and intuitive method termed "mean cumulative count," which reflects a summarization of all events that occur in the population by a given time, not just the first event for each subject. We explore the mathematical relationship between mean cumulative count and cumulative incidence. Detailed calculation of mean cumulative count is described by using a simple hypothetical example, and the computation code with an illustrative example is provided. Using follow-up data from January 1975 to August 2009 collected in the Childhood Cancer Survivor Study, we show applications of mean cumulative count and cumulative incidence for the outcome of subsequent neoplasms to demonstrate different but complementary information obtained from the 2 approaches and the specific utility of the former.

Original language English (US) 532-540 9 American Journal of Epidemiology 181 7 https://doi.org/10.1093/aje/kwu289 Published - Apr 1 2015

Incidence
Population
Neoplasms

• Epidemiology

### Cite this

Estimating the burden of recurrent events in the presence of competing risks : The method of mean cumulative count. / Dong, Huiru; Robison, Leslie L.; Leisenring, Wendy M.; Martin, Leah J.; Armstrong, Gregory; Yasui, Yutaka.

In: American Journal of Epidemiology, Vol. 181, No. 7, 01.04.2015, p. 532-540.

Research output: Contribution to journalArticle

Dong, Huiru ; Robison, Leslie L. ; Leisenring, Wendy M. ; Martin, Leah J. ; Armstrong, Gregory ; Yasui, Yutaka. / Estimating the burden of recurrent events in the presence of competing risks : The method of mean cumulative count. In: American Journal of Epidemiology. 2015 ; Vol. 181, No. 7. pp. 532-540.
@article{b583584058b7476d87feaa081414ed12,
title = "Estimating the burden of recurrent events in the presence of competing risks: The method of mean cumulative count",
abstract = "Cumulative incidence has been widely used to estimate the cumulative probability of developing an event of interest by a given time, in the presence of competing risks. When it is of interest to measure the total burden of recurrent events in a population, however, the cumulative incidence method is not appropriate because it considers only the first occurrence of the event of interest for each individual in the analysis: Subsequent occurrences are not included. Here, we discuss a straightforward and intuitive method termed {"}mean cumulative count,{"} which reflects a summarization of all events that occur in the population by a given time, not just the first event for each subject. We explore the mathematical relationship between mean cumulative count and cumulative incidence. Detailed calculation of mean cumulative count is described by using a simple hypothetical example, and the computation code with an illustrative example is provided. Using follow-up data from January 1975 to August 2009 collected in the Childhood Cancer Survivor Study, we show applications of mean cumulative count and cumulative incidence for the outcome of subsequent neoplasms to demonstrate different but complementary information obtained from the 2 approaches and the specific utility of the former.",
author = "Huiru Dong and Robison, {Leslie L.} and Leisenring, {Wendy M.} and Martin, {Leah J.} and Gregory Armstrong and Yutaka Yasui",
year = "2015",
month = "4",
day = "1",
doi = "10.1093/aje/kwu289",
language = "English (US)",
volume = "181",
pages = "532--540",
journal = "American Journal of Epidemiology",
issn = "0002-9262",
publisher = "Oxford University Press",
number = "7",

}

TY - JOUR

T1 - Estimating the burden of recurrent events in the presence of competing risks

T2 - The method of mean cumulative count

AU - Dong, Huiru

AU - Robison, Leslie L.

AU - Leisenring, Wendy M.

AU - Martin, Leah J.

AU - Armstrong, Gregory

AU - Yasui, Yutaka

PY - 2015/4/1

Y1 - 2015/4/1

N2 - Cumulative incidence has been widely used to estimate the cumulative probability of developing an event of interest by a given time, in the presence of competing risks. When it is of interest to measure the total burden of recurrent events in a population, however, the cumulative incidence method is not appropriate because it considers only the first occurrence of the event of interest for each individual in the analysis: Subsequent occurrences are not included. Here, we discuss a straightforward and intuitive method termed "mean cumulative count," which reflects a summarization of all events that occur in the population by a given time, not just the first event for each subject. We explore the mathematical relationship between mean cumulative count and cumulative incidence. Detailed calculation of mean cumulative count is described by using a simple hypothetical example, and the computation code with an illustrative example is provided. Using follow-up data from January 1975 to August 2009 collected in the Childhood Cancer Survivor Study, we show applications of mean cumulative count and cumulative incidence for the outcome of subsequent neoplasms to demonstrate different but complementary information obtained from the 2 approaches and the specific utility of the former.

AB - Cumulative incidence has been widely used to estimate the cumulative probability of developing an event of interest by a given time, in the presence of competing risks. When it is of interest to measure the total burden of recurrent events in a population, however, the cumulative incidence method is not appropriate because it considers only the first occurrence of the event of interest for each individual in the analysis: Subsequent occurrences are not included. Here, we discuss a straightforward and intuitive method termed "mean cumulative count," which reflects a summarization of all events that occur in the population by a given time, not just the first event for each subject. We explore the mathematical relationship between mean cumulative count and cumulative incidence. Detailed calculation of mean cumulative count is described by using a simple hypothetical example, and the computation code with an illustrative example is provided. Using follow-up data from January 1975 to August 2009 collected in the Childhood Cancer Survivor Study, we show applications of mean cumulative count and cumulative incidence for the outcome of subsequent neoplasms to demonstrate different but complementary information obtained from the 2 approaches and the specific utility of the former.

UR - http://www.scopus.com/inward/record.url?scp=84926661312&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84926661312&partnerID=8YFLogxK

U2 - 10.1093/aje/kwu289

DO - 10.1093/aje/kwu289

M3 - Article

VL - 181

SP - 532

EP - 540

JO - American Journal of Epidemiology

JF - American Journal of Epidemiology

SN - 0002-9262

IS - 7

ER -