Background Recurrent breast cancer (BC) has poor prognosis. To ascertain the survival time after recurrence (STR) is necessary for improving QOL and for selecting appropriate treatment. An investigation was conducted to determine whether certain biomarkers would improve prognosis and whether the disease-free interval (DFI) and biomarkers can predict STR. Methods Cases (n = 1,254) with recurrent BC from January 2000 to December 2023 were enrolled in this study. The cases were divided into the 2000–2005 group (n = 182), 2006–2011 group (n = 331), 2012–2017 group (n = 369), and 2018–2023 group (n = 366). A simple linear regression model was used to identify the relationship between STR and DFI. Results Survival rates after recurrence significantly increased in cases after 2012. No improvement was observed in cases with a HER2-0 status and a Ki-67 index value < 15%. A multivariate analysis revealed that the Ki-67 index value was a significant factor in the 2000–2005 group. The ER and HER2 status were significant after 2012. The most significant correlation was found between DFI and STR in deceased patients with a Ki-67 index value > 30%, followed by HER2-low, tumor size ≤ 2 cm and ER < 1%. The following formula was developed to predict STR; <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="12282_2025_1677_Article_IEq1.gif" Format="GIF" Height="23" Rendition="HTML" Resolution="72" Type="Linedraw" Width="394" /> </InlineMediaObject> <EquationSource Format="TEX">$\text{STR (mons)}={\alpha }_{0}+{\beta }_{0}\bullet {\text{DFI}}+\sum_{i=1}^{5}{F}_{i} \left({\alpha }_{i}+{\beta }_{i}\bullet {\text{DFI}}\right)$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mtext>STR (mons)</mtext> <mo>=</mo> <msub> <mi>α</mi> <mn>0</mn> </msub> <mo>+</mo> <msub> <mi>β</mi> <mn>0</mn> </msub> <mo>∙</mo> <mtext>DFI</mtext> <mo>+</mo> <msubsup> <mo>∑</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>5</mn> </msubsup> <msub> <mi>F</mi> <mi>i</mi> </msub> <mfenced close=")" open="("> <msub> <mi>α</mi> <mi>i</mi> </msub> <mo>+</mo> <msub> <mi>β</mi> <mi>i</mi> </msub> <mo>∙</mo> <mtext>DFI</mtext> </mfenced> </mrow> </math></EquationSource> </InlineEquation> Conclusion Prognosis after recurrence clearly improved from 2012. In recurrent deceased patients, there was a strong correlation between DFI and STR in cases with a Ki-67 index value > 30% and a HER2-low status. Further studies need to be conducted in clinical settings to verify the accuracy of the predictive formula developed for STR.

A novel formula to improve the accuracy and prognostic ability of determining the survival time after recurrent breast cancer

期刊论文
发表日期：

2025年2月18日

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Reiki Nishimura,
Yasuaki Sagara,
Reiko Mitsueda,
Tetsuhiko Taira,
Toshiko Miyaki,
Shuichi Kanemitsu,
Megumi Teraoka,
Junko Kawano,
Naomi Gondo,
Yoshitaka Fujiki,
Ryutaro Higashi,
Akiko Semba,
Yasuyo Ohi,
Yoshiaki Rai,
Yoshiaki Sagara,
Shinji Ohno

摘要

Background

Recurrent breast cancer (BC) has poor prognosis. To ascertain the survival time after recurrence (STR) is necessary for improving QOL and for selecting appropriate treatment. An investigation was conducted to determine whether certain biomarkers would improve prognosis and whether the disease-free interval (DFI) and biomarkers can predict STR.

Methods

Cases (n = 1,254) with recurrent BC from January 2000 to December 2023 were enrolled in this study. The cases were divided into the 2000–2005 group (n = 182), 2006–2011 group (n = 331), 2012–2017 group (n = 369), and 2018–2023 group (n = 366). A simple linear regression model was used to identify the relationship between STR and DFI.

Results

Survival rates after recurrence significantly increased in cases after 2012. No improvement was observed in cases with a HER2-0 status and a Ki-67 index value < 15%. A multivariate analysis revealed that the Ki-67 index value was a significant factor in the 2000–2005 group. The ER and HER2 status were significant after 2012. The most significant correlation was found between DFI and STR in deceased patients with a Ki-67 index value > 30%, followed by HER2-low, tumor size ≤ 2 cm and ER < 1%. The following formula was developed to predict STR; $\text{STR (mons)}={\alpha }_{0}+{\beta }_{0}\bullet {\text{DFI}}+\sum_{i=1}^{5}{F}_{i} \left({\alpha }_{i}+{\beta }_{i}\bullet {\text{DFI}}\right)$ $STR (mons) = α_{0} + β_{0} ∙ DFI + \sum_{i = 1}^{5} F_{i} (α_{i} + β_{i} ∙ DFI)$

Conclusion

Prognosis after recurrence clearly improved from 2012. In recurrent deceased patients, there was a strong correlation between DFI and STR in cases with a Ki-67 index value > 30% and a HER2-low status. Further studies need to be conducted in clinical settings to verify the accuracy of the predictive formula developed for STR.