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Purpose <p>To develop and validate a risk stratification model for severe postoperative cancer-related fatigue (CRF) in elderly survivors following early-stage non-small cell lung cancer (NSCLC) resection.</p> Methods <p>Elderly survivors (age ≥ 70 years) following NSCLC surgery were recruited from two tertiary medical centers in Shenyang. Data collected from medical records and self-reported questionnaires were divided into training and validation sets (7:3 ratio). Risk factors were selected utilizing the least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analysis, and were subsequently integrated into a nomogram. Model performance was assessed using area under the curve (AUC), calibration curves with the Hosmer-Lemeshow (HL) test, decision curve analysis (DCA), and clinical impact curve (CIC).</p> Results <p>A total of 32.7% (212/649) participants reported experiencing severe CRF. Five crucial risk factors were identified: fear of disease progression (FoP), caregivers, social support, activities of daily living (ADL), and nutrition status. The nomogram exhibited strong discrimination, with an AUC of 0.864 (95% confidence interval [CI]: 0.828, 0.900) in the training and 0.845 (95% CI: 0.786, 0.903) in the validation sets. Calibration curves indicated a satisfactory agreement between predicted and actual outcomes (HL test: <i>P</i> &gt; 0.05). DCA and CIC supported the nomogram’s favorable clinical utility.</p> Conclusion <p>This validated nomogram serves as an effective tool for stratifying the risk of severe postoperative CRF in elderly patients with NSCLC, facilitating healthcare practitioners in identifying high-risk individuals and implementing early timely interventions.</p>

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Risk stratification using a nomogram model for postoperative cancer-related fatigue in elderly survivors following early-stage non-small cell lung cancer resection

  • 期刊论文

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  • 发表日期：

    2025年12月11日

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  • Ying Cai,
  • Lijie Zhou

摘要

Purpose

To develop and validate a risk stratification model for severe postoperative cancer-related fatigue (CRF) in elderly survivors following early-stage non-small cell lung cancer (NSCLC) resection.

Methods

Elderly survivors (age ≥ 70 years) following NSCLC surgery were recruited from two tertiary medical centers in Shenyang. Data collected from medical records and self-reported questionnaires were divided into training and validation sets (7:3 ratio). Risk factors were selected utilizing the least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analysis, and were subsequently integrated into a nomogram. Model performance was assessed using area under the curve (AUC), calibration curves with the Hosmer-Lemeshow (HL) test, decision curve analysis (DCA), and clinical impact curve (CIC).

Results

A total of 32.7% (212/649) participants reported experiencing severe CRF. Five crucial risk factors were identified: fear of disease progression (FoP), caregivers, social support, activities of daily living (ADL), and nutrition status. The nomogram exhibited strong discrimination, with an AUC of 0.864 (95% confidence interval [CI]: 0.828, 0.900) in the training and 0.845 (95% CI: 0.786, 0.903) in the validation sets. Calibration curves indicated a satisfactory agreement between predicted and actual outcomes (HL test: P > 0.05). DCA and CIC supported the nomogram’s favorable clinical utility.

Conclusion

This validated nomogram serves as an effective tool for stratifying the risk of severe postoperative CRF in elderly patients with NSCLC, facilitating healthcare practitioners in identifying high-risk individuals and implementing early timely interventions.