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Background <p>The optimal timing of surgery following breast cancer diagnosis remains unclear. While early intervention is traditionally favored, the influence of diagnosis-to-surgery interval (DSI) on survival outcomes is not fully defined. This study aimed to assess the impact of DSI on overall survival (OS) and cancer-specific survival (CSS) in a large population of non-metastatic breast cancer patients using advanced modeling techniques.</p> Method <p>In this retrospective cohort study, data from 365,050 female patients diagnosed with Stage I–III breast cancer between 2010 and 2022 were extracted from the SEER database. All patients underwent definitive breast surgery. Patients were categorized into four DSI groups: 1–30, 31–45, 46–60, and 61–90&#xa0;days. OS and CSS were evaluated using Kaplan–Meier analysis and multivariable Cox regression. Restricted cubic spline (RCS) modeling was applied to assess the non-linear effects of DSI on survival.</p> Results <p>Patients who underwent surgery between 31 and 60&#xa0;days had the highest OS (92.0–92.2%) and CSS (96.8–97.0%) rates. Both early (&lt; 10&#xa0;days) and delayed (&gt; 60&#xa0;days) surgeries were associated with increased mortality. RCS modeling confirmed a U-shaped relationship between DSI and survival risk. Subgroup analyses revealed that triple-negative and HR–/HER2 + tumors were more sensitive to surgical timing than other subtypes.</p> Conclusion <p>This large-scale study demonstrates a non-linear association between surgical timing and survival, identifying 30–60&#xa0;days as the optimal DSI window. Findings challenge the “earlier is better” paradigm, particularly in patients managed with upfront surgery without neoadjuvant systemic therapy and suggest surgical timing should be individualized based on tumor biology and patient characteristics. These findings may help inform surgical scheduling decisions in patients with non-metastatic breast cancer.</p>

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Diagnosis-to-Surgery Interval and Survival in Non-Metastatic Breast Cancer: A U-Shaped Association

  • 期刊论文

  • 发表日期：

    2026年1月26日

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  • Ahmet Necati Sanli,
  • Bilal Turan,
  • Deniz Esin Tekcan Sanli,
  • Serdar Acar,
  • MKadri Altundag,
  • Fatih Aydogan

摘要

Background

The optimal timing of surgery following breast cancer diagnosis remains unclear. While early intervention is traditionally favored, the influence of diagnosis-to-surgery interval (DSI) on survival outcomes is not fully defined. This study aimed to assess the impact of DSI on overall survival (OS) and cancer-specific survival (CSS) in a large population of non-metastatic breast cancer patients using advanced modeling techniques.

Method

In this retrospective cohort study, data from 365,050 female patients diagnosed with Stage I–III breast cancer between 2010 and 2022 were extracted from the SEER database. All patients underwent definitive breast surgery. Patients were categorized into four DSI groups: 1–30, 31–45, 46–60, and 61–90 days. OS and CSS were evaluated using Kaplan–Meier analysis and multivariable Cox regression. Restricted cubic spline (RCS) modeling was applied to assess the non-linear effects of DSI on survival.

Results

Patients who underwent surgery between 31 and 60 days had the highest OS (92.0–92.2%) and CSS (96.8–97.0%) rates. Both early (< 10 days) and delayed (> 60 days) surgeries were associated with increased mortality. RCS modeling confirmed a U-shaped relationship between DSI and survival risk. Subgroup analyses revealed that triple-negative and HR–/HER2 + tumors were more sensitive to surgical timing than other subtypes.

Conclusion

This large-scale study demonstrates a non-linear association between surgical timing and survival, identifying 30–60 days as the optimal DSI window. Findings challenge the “earlier is better” paradigm, particularly in patients managed with upfront surgery without neoadjuvant systemic therapy and suggest surgical timing should be individualized based on tumor biology and patient characteristics. These findings may help inform surgical scheduling decisions in patients with non-metastatic breast cancer.