Authors
Krishnakumar Thankappan, Lakshmi Ravunniarth Menon, Tejal Patel, Sujha Subramanian, Subramania Iyer
Published in
Value in health regional issues. Pages 101686. Aug 07, 2026. Epub Aug 07, 2026.
Abstract
To conduct a cost-utility analysis comparing sentinel node biopsy (SNB) with selective neck dissection (SND) for clinically node-negative early-stage oral cancer from the Indian healthcare system perspective.
A hybrid decision-tree-Markov model compared SNB with SND over a 10-year horizon, incorporating 18 clinical pathways, time-trade-off utilities from an Indian population, and costs from Indian settings. Model and R code construction were assisted by a large language model (Claude-3.5-Sonnet) with author verification. Effectiveness was measured in quality-adjusted life-years (QALYs). Deterministic and probabilistic sensitivity analyses were conducted. The primary outcome was net monetary benefit at the India-specific willingness-to-pay threshold of INR 212 307/QALY.
SNB yielded 6.145 QALYs versus 6.032 for SND (incremental 0.114) at INR 332 865 versus INR 336 433 (incremental -INR 3568). SNB dominated SND in the deterministic base case. Under probabilistic sensitivity analysis, SNB was cost-effective in 78.5% of iterations at the India-specific threshold (mean incremental net monetary benefit INR 15 944; 95% CrI -INR 22 141 to INR 54 287) and 81.8% at 1× gross domestic product per capita (INR 245 000/QALY). A lifetime-horizon scenario (cohort age 55-100; 45 cycles) confirmed SNB dominance with incremental cost -INR 5466 and incremental QALYs 0.1767. Results were robust across deterministic and scenario analyses.
SNB is a cost-effective alternative to SND for clinically node-negative early-stage oral cancer in Indian tertiary cancer centers with appropriate technical expertise, dominating in the deterministic base case and remaining cost-effective in 78.5% of probabilistic iterations at the India-specific threshold. These findings support adoption of SNB as the preferred staging strategy at such centers.
PMID:
42565769
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.
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