Journal article

Outcomes of Active Surveillance for Ductal Carcinoma in Situ: A Computational Risk Analysis.

  • Ryser MD Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT).
  • Worni M Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT).
  • Turner EL Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT).
  • Marks JR Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT).
  • Durrett R Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT).
  • Hwang ES Department of Mathematics (MDR, RD) and Duke Global Health Institute (ELT), Duke University, Durham, NC; Division of Advanced Oncologic and GI Surgery (MDR, MW, ESH) and Division of Surgical Sciences (JRM), Department of Surgery, Duke University Medical Center, Durham, NC; Department of Visceral Surgery and Medicine, Inselspital, Berne University Hospital and University of Berne, Berne, Switzerland (MW); Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC (ELT). shelley.hwang@duke.edu.
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  • 2015-12-20
Published in:
  • Journal of the National Cancer Institute. - 2016
English BACKGROUND
Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS.


METHODS
Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed.


RESULTS
Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis.


CONCLUSION
AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging.
Language
  • English
Open access status
bronze
Identifiers
Persistent URL
https://sonar.ch/global/documents/269707
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