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Background <p>Sleep disorders and anxiety-depression symptoms can significantly impair the quality of life and treatment adherence among breast cancer patients undergoing chemotherapy, while also increasing the risk of disease recurrence and mortality. Early identification of the progression trajectory and underlying causes of these symptoms is essential for providing personalized interventions for deteriorating cases.</p> Objective <p>This study aims to analyze the trajectories of sleep disorders and anxiety-depression symptoms in breast cancer patients during chemotherapy using a group-based Multi-Trajectory Model (GBMTM) and to identify influencing factors through machine learning.</p> Methods <p>Prospective data from 150 breast cancer patients undergoing four cycles of chemotherapy were collected. A GBMTM was employed to identify distinct trajectories, with 70 predictive variables included in the analysis. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select the optimal subset of variables. Seven machine learning models were compared, and the optimal model was chosen for result interpretation using SHAP (SHapley Additive exPlanations) analysis.</p> Results <p>Among breast cancer patients undergoing chemotherapy, two distinct trajectories of sleep disorders and anxiety-depression symptoms were identified: the “stable group” (74.7%) and the “deteriorating group” (25.3%). SHAP analysis revealed that high levels of C-reactive protein, high uric acid, high hemoglobin, smoking, presence of invasive cancer with ductal carcinoma in situ, prior chemotherapy, being married, regular menstrual cycles in the past, and lack of family history were significant risk factors associated with the “deteriorating group.”</p> Conclusion <p>Our findings indicate two distinct trajectories of sleep disorders and anxiety-depression symptoms in breast cancer patients undergoing chemotherapy, with the majority falling into the “stable group”. The identified risk factors associated with the “deteriorating group” should be closely monitored to facilitate early intervention and improve patient outcomes.</p> Trial registration <p>The trial was registered on Chinese Clinical Trial Registry (Trial ID: ChiCTR2300077667 on 15 November 2023; available at <a href="https://www.chictr.org.cn/">https://www.chictr.org.cn/</a>).</p>

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Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Jiang Yuan,
  • Yinqing Yang,
  • Yuan Li,
  • Tumalisi Kayishaer,
  • Jie Chu,
  • Bingmei Zhu,
  • Zhizhen Tao,
  • Jinshu Han,
  • Xinyu Zhao,
  • Xiuying Hu,
  • Chao Tian,
  • Yi Yang

摘要

Background

Sleep disorders and anxiety-depression symptoms can significantly impair the quality of life and treatment adherence among breast cancer patients undergoing chemotherapy, while also increasing the risk of disease recurrence and mortality. Early identification of the progression trajectory and underlying causes of these symptoms is essential for providing personalized interventions for deteriorating cases.

Objective

This study aims to analyze the trajectories of sleep disorders and anxiety-depression symptoms in breast cancer patients during chemotherapy using a group-based Multi-Trajectory Model (GBMTM) and to identify influencing factors through machine learning.

Methods

Prospective data from 150 breast cancer patients undergoing four cycles of chemotherapy were collected. A GBMTM was employed to identify distinct trajectories, with 70 predictive variables included in the analysis. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select the optimal subset of variables. Seven machine learning models were compared, and the optimal model was chosen for result interpretation using SHAP (SHapley Additive exPlanations) analysis.

Results

Among breast cancer patients undergoing chemotherapy, two distinct trajectories of sleep disorders and anxiety-depression symptoms were identified: the “stable group” (74.7%) and the “deteriorating group” (25.3%). SHAP analysis revealed that high levels of C-reactive protein, high uric acid, high hemoglobin, smoking, presence of invasive cancer with ductal carcinoma in situ, prior chemotherapy, being married, regular menstrual cycles in the past, and lack of family history were significant risk factors associated with the “deteriorating group.”

Conclusion

Our findings indicate two distinct trajectories of sleep disorders and anxiety-depression symptoms in breast cancer patients undergoing chemotherapy, with the majority falling into the “stable group”. The identified risk factors associated with the “deteriorating group” should be closely monitored to facilitate early intervention and improve patient outcomes.

Trial registration

The trial was registered on Chinese Clinical Trial Registry (Trial ID: ChiCTR2300077667 on 15 November 2023; available at https://www.chictr.org.cn/).