Can we use survival data from cancer registries to learn about disease recurrence? The case of breast cancer

Angela B. Mariotto, Zhaohui Zou, Fanni Zhang, Nadia Howlader, Allison W. Kurian, Ruth Etzioni

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background: Population-representative risks of metastatic recurrence are not generally available because cancer registries do not collect data on recurrence. This article presents a novel method that estimates the risk of recurrence using cancer registry disease-specific survival. Methods: The method is based on an illness-death process coupled with a mixture cure model for net cancer survival. The risk of recurrence is inferred from the estimated survival among the noncured fraction and published data on survival after recurrence. We apply the method to disease-specific survival curves from female breast cancer cases without a prior cancer diagnosis and with complete stage and hormone receptor (HR) status in Surveillance, Epidemiology and End Results registries (1992-2013). Results: The risk of recurrence is higher for women diagnosed with breast cancer at older age, earlier period, more advanced stage, and HR-negative tumors. For women diagnosed at ages 60-74 in 2000-2013, the projected percent recurring within 5 years is 2.5%, 9.6%, and 34.5% for stages I, II, and III HR-positive, and 6.5%, 20.2%, and 48.5% for stages I, II, and III HR-negative tumors. Although HR-positive cases have lower risk of recurrence soon after diagnosis, their risk persists longer than for HR-negative cases. Results show a high degree of robustness to model assumptions. Conclusions: The results show that it is possible to extract information about the risk of recurrence using disease-specific survival, and the methods can in principle be extended to other cancer sites. Impact: This study provides the first population-based summaries of the risk of breast cancer recurrence in U.S. women.

Original languageEnglish (US)
Pages (from-to)1332-1341
Number of pages10
JournalCancer Epidemiology Biomarkers and Prevention
Volume27
Issue number11
DOIs
StatePublished - Nov 1 2018
Externally publishedYes

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Registries
Breast Neoplasms
Recurrence
Survival
Hormones
Neoplasms
Population
Epidemiology

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Can we use survival data from cancer registries to learn about disease recurrence? The case of breast cancer. / Mariotto, Angela B.; Zou, Zhaohui; Zhang, Fanni; Howlader, Nadia; Kurian, Allison W.; Etzioni, Ruth.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 27, No. 11, 01.11.2018, p. 1332-1341.

Research output: Contribution to journalArticle

Mariotto, Angela B. ; Zou, Zhaohui ; Zhang, Fanni ; Howlader, Nadia ; Kurian, Allison W. ; Etzioni, Ruth. / Can we use survival data from cancer registries to learn about disease recurrence? The case of breast cancer. In: Cancer Epidemiology Biomarkers and Prevention. 2018 ; Vol. 27, No. 11. pp. 1332-1341.
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abstract = "Background: Population-representative risks of metastatic recurrence are not generally available because cancer registries do not collect data on recurrence. This article presents a novel method that estimates the risk of recurrence using cancer registry disease-specific survival. Methods: The method is based on an illness-death process coupled with a mixture cure model for net cancer survival. The risk of recurrence is inferred from the estimated survival among the noncured fraction and published data on survival after recurrence. We apply the method to disease-specific survival curves from female breast cancer cases without a prior cancer diagnosis and with complete stage and hormone receptor (HR) status in Surveillance, Epidemiology and End Results registries (1992-2013). Results: The risk of recurrence is higher for women diagnosed with breast cancer at older age, earlier period, more advanced stage, and HR-negative tumors. For women diagnosed at ages 60-74 in 2000-2013, the projected percent recurring within 5 years is 2.5{\%}, 9.6{\%}, and 34.5{\%} for stages I, II, and III HR-positive, and 6.5{\%}, 20.2{\%}, and 48.5{\%} for stages I, II, and III HR-negative tumors. Although HR-positive cases have lower risk of recurrence soon after diagnosis, their risk persists longer than for HR-negative cases. Results show a high degree of robustness to model assumptions. Conclusions: The results show that it is possible to extract information about the risk of recurrence using disease-specific survival, and the methods can in principle be extended to other cancer sites. Impact: This study provides the first population-based summaries of the risk of breast cancer recurrence in U.S. women.",
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