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Development and validation of a prediction model for frailty in breast cancer patients with extended survival

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Abstract

Background

Breast cancer (BC) patients with extended survival show a higher incidence of frailty. This study aimed to develop and validate a novel model combining sociodemographic factors (SF) and disease-related factors (DRF) to identify frailty in BC patients with extended survival.

Methods

This cross-sectional study examined data from 1167 patients admitted to a large urban academic medical centre. Three types of predictive models were constructed in the training set (817 patients): the SF model, the DRF model, and the SF + DRF model (combined model). The model performance and effectiveness were assessed using receiver operating characteristic (ROC) curves, calibration plots and decision curves analysis (DCA). Then the model was subsequently validated on the validation set.

Results

The incidence of frailty in BC patients with extended survival was 35.8%. We identified six independent risk factors including age, health status, chemotherapy, endocrine therapy, number of comorbidities and oral medications. Ultimately, we constructed an optimal model (combined model C) for frailty. The predictive model showed significantly high discriminative accuracy in the training set AUC: 0.754, (95% CI, 0.719–0.789; sensitivity: 76.8%, specificity: 62.2%) and validation set AUC: 0.805, (95% CI, 0.76–0.85), sensitivity: 60.8%, specificity: 87.1%) respectively. A prediction nomogram was constructed for the training and validation sets. Calibration and DCA were performed, which indicated that the clinical model presented satisfactory calibration and clinical utility. Ultimately, we implemented the prediction model into a mobile-friendly web application that provides an accurate and individualized prediction for BC.

Conclusions

The present study demonstrated that the prevalence of frailty in BC patients with extended survival was 35.8%. We developed a novel model for screening frailty, which may provide evidence for frailty screening and prevention.

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Data availability

The data underlying this study are available and researchers may submit data requests to the corresponding author on reasonable request.

Abbreviations

BC:

Breast cancer

ASP:

Acute survival phase

ESP:

Extended survival phase

PSP:

Permanent survival phase

SF:

Sociodemographic factors

DRF:

Disease-related factors

LASSO:

Least absolute shrinkage and selection operator

AUC:

Area under the curve

ROC:

Receiver operating characteristics

DCA:

Decision curve analysis

NPV:

Negative predictive value

PPV:

Positive predictive value

SE:

Standard error

CI:

Confidence interval

BMI:

Body mass index

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Funding

This study was supported by the Fundamental Research Funds for the Central Universities (2042022kf1116), and the National Natural Science Foundation of China (NSFC) (Grant numbers: 82303843).

Author information

Author notes

  1. Shurui Wang and Difei Huang contributed equally to this work.

Authors and Affiliations

  1. Department of General Surgery, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei Province, People’s Republic of China

    Shurui Wang, Difei Huang, Maojun Di & **an Du

  2. Chinese Academy of Medical Sciences & Peking Union Medical College, Bei**g, China

    Shurui Wang & Yixin Ma

  3. National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tian**’s Clinical Research Center for Cancer, Tian** Medical University Cancer Institute and Hospital, Tian**, China

    Shurui Wang, Chenxi **, Huan Liu, Aomei Shen & Wanmin Qiang

  4. Keio University Shonan Fujisawa Campus Graduate School of Health Management, Fujisawa-Shi, Kanagawa, Japan

    **aofeng Liu

  5. The Second Affiliated Hospital of Zhejiang University School Medicine, Hang Zhou, China

    Qiang Tang

  6. Oncology Treatment Center, Affiliated Hospital of Jiangsu University, Jiangsu, China

    **ng Chen

  7. School of Nursing, Peking University, Haidian District, 38 Xueyuan Road, Bei**g, China

    Aomei Shen

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  1. Shurui Wang
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Contributions

All authors participated in the study design. XFL, QT, CXX, and YXM, HL collected and retrieved the data. SRW and DFH analysed the data and AMS evaluated the validity of the analysis. SRW and DFH drafted the manuscript, including the figures and tables. WMQ, XD provided intellectual input and edited the paper. All authors read and approved the final version of the manuscript.

Corresponding authors

Correspondence to Maojun Di, Wanmin Qiang or **an Du.

Ethics declarations

Ethical approval

This cross-sectional study was conducted following the Declaration of Helsinki guidelines, and the protocol was approved by the Medical Ethics Committee of Tian** Cancer Hospital with the ethics approval number bc2021084.

Competing interests

The authors declare no competing interests.

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Wang, S., Huang, D., Liu, X. et al. Development and validation of a prediction model for frailty in breast cancer patients with extended survival. Support Care Cancer 32, 393 (2024). https://doi.org/10.1007/s00520-024-08501-7

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