Development and internal validation of a prognostic nomogram incorporating F-NLR and HAGR scores in patients with oral squamous cell carcinoma: a single-center retrospective cohort study - Scorecard - MDSpire
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Development and internal validation of a prognostic nomogram incorporating F-NLR and HAGR scores in patients with oral squamous cell carcinoma: a single-center retrospective cohort study
Clinical Scorecard: Creation and internal validation of a prognostic nomogram utilizing F-NLR and HAGR scores for patients diagnosed with oral squamous cell carcinoma: a retrospective cohort analysis from a single center
At a Glance
Category
Detail
Condition
Oral Squamous Cell Carcinoma (OSCC)
Key Mechanisms
Integration of F-NLR and HAGR scores with traditional clinical parameters for prognostic evaluation.
Target Population
Patients diagnosed with OSCC undergoing radical surgical resection.
Care Setting
Single center retrospective cohort study.
Key Highlights
Nomogram predicts 1-, 3-, and 5-year cancer-specific survival rates.
C-index of 0.73 indicates acceptable model discrimination.
F-NLR and HAGR scores identified as independent prognostic factors.
Calibration plots show high consistency between predicted and actual survival.
Internal validation suggests potential for individualized risk stratification.
Guideline-Based Recommendations
Diagnosis
Utilize TNM staging system for initial assessment.
Consider F-NLR and HAGR scores for enhanced prognostic evaluation.
Management
Incorporate nomogram findings into clinical decision-making for OSCC.
Monitoring & Follow-up
Regular follow-up based on nomogram predictions for survival.
Risks
Consider the impact of age, history of precancerous lesions, and postoperative therapy on prognosis.
Patient & Prescribing Data
292 patients with OSCC.
Radical surgical resection followed by consideration of adjuvant therapy based on nomogram results.
Clinical Best Practices
Integrate systemic inflammatory and nutritional markers in prognostic assessments.
Utilize nomograms for individualized patient risk stratification.
