Prediction of second malignant neoplasm incidence in a large cohort of long-term survivors of childhood cancers.
BACKGROUND
The ability to predict adverse-event occurrences accurately in long-term survivors of childhood cancer is of high importance in late effects research, both clinically and methodologically.


METHODS
This article considers a statistical prediction of future events in a cohort, taking second malignant neoplasm (SMN) incidence in a large cohort of long-term childhood cancer survivors as an example. The method consists of dividing the follow-up period of the cohort into two non-overlapping periods, using the first period as "training data," with which we model the patterns of SMN occurrences in the cohort, and the subsequent period as "testing data," with which we validate the model based on the training data. Future predictions are also applied beyond the testing-data period to calculate the SMN incidence of the cohort in the next five years for overall and specific types of SMNs.


RESULTS
The proposed statistical prediction is shown empirically to perform well with respect to the prediction accuracy. Overall, the models were able to predict the future second cancers rates very well, with exceptions of a few cancer types that had very small observed counts in the testing period.


CONCLUSIONS
Our proposed statistical method predicts future events in a cohort of long-term childhood cancer survivors and, as such, is a useful tool for late effects research on childhood cancer survivors.
Dinu
Irina
I
Department of Public Health Sciences, School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
Liu
Yan
Y
Leisenring
Wendy
W
Mertens
Ann C
AC
Neglia
Joseph P
JP
Hammond
Sue
S
Robison
Leslie L
LL
Yasui
Yutaka
Y
D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008499:Medical Records; D015233:Models, Statistical; D009369:Neoplasms / Q000150:complications* / Q000628:therapy; D016609:Neoplasms, Second Primary / Q000175:diagnosis / Q000453:epidemiology*; D012189:Retrospective Studies; D018426:SEER Program; D011795:Surveys and Questionnaires; D017741:Survivors