Purpose <p>Laryngeal squamous cell carcinoma (LSCC) ranks among the most commonly diagnosed cancers of head and neck cancers. This study aimed to devise a nomogram capable of predicting cancer-specific survival (CSS) of LSCC patients.</p> Methods <p>From the Surveillance, Epidemiology, and End Results (SEER) database, 3866 patients with LSCC diagnosed between 2000 and 2020 were selected. These patients were evenly split into a training cohort (<i>n</i> = 1933) and a validation cohort (<i>n</i> = 1933). Univariable and multivariable Cox regression analyses were employed to identify independent prognostic factors for CSS, which were subsequently integrated to develop a nomogram. The nomogram's predictive accuracy and discriminative ability were thoroughly assessed using various metrics. Additionally, a comparative analysis was performed against the tumor-node-metastasis (TNM) staging system.</p> Results <p>Eight independent prognostic factors were integrated into the nomogram. Excellent discrimination was exhibited by both the training and validation cohorts, as evidenced by the C-index and calibration curves. In the training group, the area under the curve (AUC) values at 1, 3, and 5&#xa0;years were 0.728, 0.746, and 0.766, respectively, while in the validation group, they were 0.771, 0.751, and 0.763, respectively. When compared to the traditional TNM staging system, three metrics consistently demonstrated the superior performance of the nomogram.</p> Conclusion <p>This study successfully constructed a novel and well-calibrated nomogram, serving as a convenient, practical, and efficient clinical decision-making tool that offers precise prognostic information for patients with LSCC.</p>

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A nomogram for predicting cancer-specific survival in patients with laryngeal squamous cell carcinoma: a population-based study from SEER database

  • Hong-Lu Zhou,
  • Dan-Dan Chen

摘要

Purpose

Laryngeal squamous cell carcinoma (LSCC) ranks among the most commonly diagnosed cancers of head and neck cancers. This study aimed to devise a nomogram capable of predicting cancer-specific survival (CSS) of LSCC patients.

Methods

From the Surveillance, Epidemiology, and End Results (SEER) database, 3866 patients with LSCC diagnosed between 2000 and 2020 were selected. These patients were evenly split into a training cohort (n = 1933) and a validation cohort (n = 1933). Univariable and multivariable Cox regression analyses were employed to identify independent prognostic factors for CSS, which were subsequently integrated to develop a nomogram. The nomogram's predictive accuracy and discriminative ability were thoroughly assessed using various metrics. Additionally, a comparative analysis was performed against the tumor-node-metastasis (TNM) staging system.

Results

Eight independent prognostic factors were integrated into the nomogram. Excellent discrimination was exhibited by both the training and validation cohorts, as evidenced by the C-index and calibration curves. In the training group, the area under the curve (AUC) values at 1, 3, and 5 years were 0.728, 0.746, and 0.766, respectively, while in the validation group, they were 0.771, 0.751, and 0.763, respectively. When compared to the traditional TNM staging system, three metrics consistently demonstrated the superior performance of the nomogram.

Conclusion

This study successfully constructed a novel and well-calibrated nomogram, serving as a convenient, practical, and efficient clinical decision-making tool that offers precise prognostic information for patients with LSCC.