Risk-Based Selection of Individuals for Oral Cancer Screening
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.
| Errataetall: |
CommentIn: Nat Rev Clin Oncol. 2021 Aug;18(8):471-472. - PMID 33883701 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:39 |
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| Enthalten in: |
Journal of clinical oncology : official journal of the American Society of Clinical Oncology - 39(2021), 6 vom: 20. Feb., Seite 663-674 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Cheung, Li C [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 15.09.2021 Date Revised 24.03.2024 published: Print-Electronic ClinicalTrials.gov: NCT04494620 CommentIn: Nat Rev Clin Oncol. 2021 Aug;18(8):471-472. - PMID 33883701 Citation Status MEDLINE |
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| doi: |
10.1200/JCO.20.02855 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 245 | 1 | 0 | |a Risk-Based Selection of Individuals for Oral Cancer Screening |
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| 500 | |a Date Completed 15.09.2021 | ||
| 500 | |a Date Revised 24.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a ClinicalTrials.gov: NCT04494620 | ||
| 500 | |a CommentIn: Nat Rev Clin Oncol. 2021 Aug;18(8):471-472. - PMID 33883701 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a PURPOSE: We evaluated proof of principle for resource-efficient, risk-based screening through reanalysis of the Kerala Oral Cancer Screening Trial | ||
| 520 | |a 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 | ||
| 520 | |a 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) | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Intramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 700 | 1 | |a Ramadas, Kunnambath |e verfasserin |4 aut | |
| 700 | 1 | |a Muwonge, Richard |e verfasserin |4 aut | |
| 700 | 1 | |a Katki, Hormuzd A |e verfasserin |4 aut | |
| 700 | 1 | |a Thomas, Gigi |e verfasserin |4 aut | |
| 700 | 1 | |a Graubard, Barry I |e verfasserin |4 aut | |
| 700 | 1 | |a Basu, Partha |e verfasserin |4 aut | |
| 700 | 1 | |a Sankaranarayanan, Rengaswamy |e verfasserin |4 aut | |
| 700 | 1 | |a Somanathan, Thara |e verfasserin |4 aut | |
| 700 | 1 | |a Chaturvedi, Anil K |e verfasserin |4 aut | |
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