Clinical Scorecard: Creation and assessment of a predictive model for recurrence in postoperative patients with stage ⅠA1-ⅢA non-small cell lung carcinoma

At a Glance

Key Highlights

• NSCLC accounts for over 85% of lung cancer cases with high postoperative recurrence rates (34%-82%) in stage ⅠA1-ⅢA patients.
• The study developed a multidimensional nomogram integrating clinical, pathological, radiological, and 56-gene LungCore panel genetic data to predict recurrence.
• The 56-gene LungCore panel offers a cost-effective genetic profiling method with predictive value for tumor mutational burden and recurrence risk.

Guideline-Based Recommendations

Diagnosis

• Use postoperative pathological diagnosis confirming stage ⅠA1-ⅢA NSCLC.
• Incorporate preoperative CT imaging features (density, pleural indentation, lobulation, spicule, cavitary signs) for risk assessment.
• Apply targeted genetic profiling using the 56-gene LungCore panel to identify mutation burden.

Management

• Perform radical surgical resection with mediastinal lymph node dissection or systematic sampling as standard treatment.
• Utilize the integrated nomogram model to stratify recurrence risk and guide personalized follow-up and adjuvant therapy decisions.

Monitoring & Follow-up

• Conduct at least five years of postoperative follow-up using imaging (PET-CT) and pathological confirmation to detect recurrence or metastasis.
• Monitor patients for new lesions in ipsilateral/contralateral lungs or extrapulmonary organs.

Risks

• Recognize that exclusive reliance on TNM staging is insufficient for accurate prognosis.
• Account for potential loss to follow-up (~14%) but note minimal impact on study results based on sensitivity analysis.

Patient & Prescribing Data

Stage ⅠA1-ⅢA NSCLC patients post radical surgery with available 56-gene LungCore panel results

Integration of clinical, radiological, and genetic data improves individualized recurrence risk prediction, facilitating tailored postoperative management.

Clinical Best Practices

• Combine clinical, pathological, radiological, and genetic data for comprehensive risk stratification in postoperative NSCLC patients.
• Employ cost-effective targeted genetic panels like the 56-gene LungCore panel for mutation profiling instead of extensive WES/WGS.
• Ensure rigorous and long-term follow-up (minimum five years) with objective imaging and pathological assessments to detect recurrence early.
• Use LASSO regression with cross-validation for selecting predictive variables in model development.
• Address missing data with appropriate imputation methods and conduct sensitivity analyses to assess follow-up completeness impact.

References

• Global lung cancer incidence and mortality data
• TNM staging system for NSCLC prognosis
• 56-gene LungCore panel study
• TRIPOD reporting standards