Development and validation of a nomogram based on LASSO regression for predicting early postoperative polyp recurrence in patients with chronic rhinosinusitis with nasal polyps - Report - MDSpire

Development and validation of a nomogram based on LASSO regression for predicting early postoperative polyp recurrence in patients with chronic rhinosinusitis with nasal polyps

  • By

  • Hanshuang Zhang

  • Huizhen Zheng

  • Siqi Wang

  • Shile Xu

  • July 14, 2026

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Clinical Report: Nomogram for Predicting Early Recurrence of Polyps in CRSwNP

Overview

A nomogram model was developed to predict early postoperative polyp recurrence in patients with chronic rhinosinusitis with nasal polyps (CRSwNP).

Background

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent condition that can lead to significant morbidity due to its chronic nature and high recurrence rates post-surgery. Current prediction methods for postoperative recurrence are limited, often relying on single clinical indicators that do not comprehensively assess risk. The development of a nomogram model aims to provide a more accurate approach to predicting recurrence.

Data Highlights

CohortAUC (95% CI)
Training Cohort0.923 (0.882–0.963)
Internal Validation Cohort0.881 (0.827–0.936)
External Validation Cohort0.890 (0.841–0.939)

Key Findings

  • Asthma, stage 3 sinusitis, Lund-Mackay score, eosinophils (EOS), and immunoglobulin E (IgE) were identified as independent risk factors for early postoperative recurrence (P < 0.05).
  • The nomogram model showed AUCs of 0.923, 0.881, and 0.890 for the training, internal validation, and external validation cohorts, respectively.
  • Calibration curves indicated good calibration of the nomogram model.
  • The study utilized LASSO regression for variable selection to address multicollinearity issues.

Clinical Implications

The nomogram model can assist clinicians in identifying patients at high risk for early postoperative recurrence of polyps, allowing for tailored postoperative management. By utilizing commonly available clinical indicators, the model enhances the precision of risk assessment in CRSwNP patients.

Conclusion

The developed nomogram model offers a tool for predicting early postoperative polyp recurrence in CRSwNP.

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  3. Frontiers in Neurology — Development and external validation of a LASSO-based parsimonious nomogram for predicting BPPV recurrence: a multi-center retrospective cohort study
  4. Creation and assessment of a nomogram based on systemic inflammation to predict surgical site infections in colorectal cancer patients prior to surgery
  5. Forecasting Postoperative Complications After Transanal Total Mesorectal Excision in Middle and Low Rectal Cancer: Creation and Internal Validation of a Clinical Prediction Tool
  6. 2025 AAO-HNSF Clinical Practice Guideline on Surgical Management of Chronic Rhinosinusitis
  7. Rhinology systematic review and meta-analysis on recurrence predictors
  8. Development and validation of a nomogram model for the prediction of recurrence after endoscopic sinus surgery in patients with chronic rhinosinusitis with nasal polyps

Original Source(s)

Development and validation of a nomogram based on LASSO regression for predicting early postoperative polyp recurrence in patients with chronic rhinosinusitis with nasal polyps

  • by Hanshuang Zhang, Huizhen Zheng, Siqi Wang, Shile Xu

  • July 14, 2026

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