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Title: Risk-Based Selection of Individuals for Oral Cancer Screening.
Authors: Cheung LC,  Ramadas K,  Muwonge R,  Katki HA,  Thomas G,  Graubard BI,  Basu P,  Sankaranarayanan R,  Somanathan T,  Chaturvedi AK
Journal: J Clin Oncol
Date: 2021 Feb 20
Branches: BB, CGB
PubMed ID: 33449824
PMC ID: not available
Abstract: PURPOSE: We evaluated proof of principle for resource-efficient, risk-based screening through reanalysis of the Kerala Oral Cancer Screening Trial. METHODS: The cluster-randomized trial included three triennial rounds of visual inspection (seven clusters, n = 96,516) versus standard of care (six clusters, n = 95,354) and up to 9 years of follow-up. We developed a Cox regression-based risk prediction model for oral cancer incidence. Using this risk prediction model to adjust for the oral cancer risk imbalance between arms, through intention-to-treat (ITT) analyses that accounted for cluster randomization, we calculated the relative (hazard ratios [HRs]) and absolute (rate differences [RDs]) screening efficacy on oral cancer mortality and compared screening efficiency across risk thresholds. RESULTS: Oral cancer mortality was reduced by 27% in the screening versus control arms (HR = 0.73; 95% CI, 0.54 to 0.98), including a 29% reduction in ever-tobacco and/or ever-alcohol users (HR = 0.71; 95% CI, 0.51 to 0.99). This relative efficacy was similar across oral cancer risk quartiles (P interaction = .59); consequently, the absolute efficacy increased with increasing model-predicted risk-overall trial: RD in the lowest risk quartile (Q1) = 0.5/100,000 versus 13.4/100,000 in the highest quartile (Q4), P trend = .059 and ever-tobacco and/or ever-alcohol users: Q1 RD = 1.0/100,000 versus Q4 = 22.5/100,000; P trend = .026. In a population akin to the Kerala trial, screening of 100% of individuals would provide 27.1% oral cancer mortality reduction at number needed to screen (NNS) = 2,043. Restriction of screening to ever-tobacco and/or ever-alcohol users with no additional risk stratification would substantially enhance efficiency (43.4% screened for 23.3% oral cancer mortality reduction at NNS = 1,029), whereas risk prediction model-based screening of 50% of ever-tobacco and/or ever-alcohol users at highest risk would further enhance efficiency with little loss in program sensitivity (21.7% screened for 19.7% oral cancer mortality reduction at NNS = 610). CONCLUSION: In the Kerala trial, the efficacy of oral cancer screening was greatest in individuals at highest oral cancer risk. These results provide proof of principle that risk-based oral cancer screening could substantially enhance the efficiency of screening programs.