4.6 Article

Conditional Survival of female patients with operable invasive Breast Cancer in US: A population-based study

Journal

JOURNAL OF CANCER
Volume 11, Issue 19, Pages 5782-5791

Publisher

IVYSPRING INT PUBL
DOI: 10.7150/jca.46183

Keywords

Invasive breast cancer; Disease-specific survival; Conditional survival; SEER database

Categories

Funding

  1. Beijing Municipal Natural Science Foundation [7204293, 7191009]
  2. Special Research Fund for Central Universities, Peking Union Medical College [3332019053, 3332019140]
  3. Beijing Hope Run Special Fund of Cancer Foundation of China [LC2019B03, LC2019L07]
  4. Natural Science Foundation of China [81872160]

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Background: Conditional survival (CS) is used to describe the dynamic possibility of survival, considering the changes of death risk with time lapsing. This study aimed to estimate the conditional disease-specific survival (CDS) for the female with operable invasive breast cancer. Methods: The data was obtained from Surveillance, Epidemiology, and End Result Program of the National Cancer Institute. The hazard rate was calculated using kernel density smoothing method. The disease-specific survival (DSS) rates were estimated and compared using Kaplan-Meier method and log-rank test. The Cox regression model was used to adjust confounding factors. The CDS was calculated by CDS(y vertical bar x)=DSS(x + y)/DSS(x), where DSS(x) representatives the DSS at x year. Results: The 5-year, 10-year, and 15-year DSS was 88.7%, 82.0%, and 78.3%, respectively. The hazard rate after surgery increased initially and peaked at about 1.5 years, then decreased gradually. Meanwhile, the CDS decreased just after surgery then increased continuously, which showed a contrary trend with hazard rate. Patients with high risk factors had greater survival gap between cumulative DSS and CDS. The changing trend of CDS in patients with high risk factors was more significant, and the CDS gap between low-risk patients and high-risk patients gradually decreased over time. Conclusion: CS could provide a more precise long-term prognostic evaluation compared to traditional cumulative survival, especially for long-time survivors with high risk.

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