Study aid only. Verify against current guidelines, primary literature, staging manuals, and prescribing information before clinical use.

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Oral Cavity SCC: Definitive Treatment

Oral cavity SCC (incl. mucosal lip) Early T1–2 N0 Resection of primary ± neck dissection / SLN surgery preferred Definitive RT alternative Resectable locally advanced T3 N0 · T1–3 N1–3 · T4a N0–3 Surgery + neck dissection preferred Neoadjuvant pembrolizumab PD-L1 CPS ≥1, except N3 — KEYNOTE-689 ↗ Surgery → RT + pembrolizumab (+ cisplatin if ECE / + margin) → adjuvant pembrolizumab Clinical trial Adjuvant therapy by pathologic risk No positive node, no adverse features observe One node / pN1, no other risk consider RT Extranodal extension ± positive margin chemoRT (cisplatin) Positive margin re-resect, or chemoRT / RT Other risk features RT ± concurrent chemo

Oral Cavity SCC: Definitive Treatment: overview

This algorithm covers definitive treatment of oral cavity squamous cell carcinoma, including mucosal lip, by stage, with a final step for adjuvant therapy by pathologic risk. Early disease (T1-2 N0) is treated preferentially with resection of the primary, with or without neck dissection or sentinel lymph node biopsy, and definitive radiotherapy is the alternative. For resectable locally advanced disease (T3 N0, T1-3 N1-3, T4a N0-3), surgery with neck dissection is preferred, and a clinical trial is also listed.

For tumors with PD-L1 CPS 1 or higher, excluding N3 disease, the chart adds a perioperative pembrolizumab pathway: neoadjuvant pembrolizumab, surgery, radiotherapy plus pembrolizumab (with cisplatin for extranodal extension or a positive margin), then adjuvant pembrolizumab, supported by KEYNOTE-689, which improved event-free survival in high-risk resected disease. Adjuvant therapy follows pathologic risk: observation without nodal disease or adverse features, consideration of radiotherapy for a single node, and cisplatin chemoradiation for extranodal extension with or without a positive margin, an approach supported by RTOG 9501.

Step by step

Trials behind this algorithm