Global development and validation of the Lung Cancer Prevention Score (LCPS): A quantitative framework linking policy strength, incidence, and outcomes across 40 countries.

10518 Background: Lung cancer is the leading cause of cancer worldwide. Despite advances in tobacco control, national prevention efforts remain fragmented. We developed and validated the Lung Cancer Prevention Score (LCPS), a 0–100 composite linking prevention policy strength with real-world outcomes for global benchmarking and equity tracking. Methods: Two LCPS models were created. Policy LCPS quantified 12 weighted domains: smoke-free laws, TAPS bans, ≥50% pictorial warnings, ≥75% excise tax, plain packaging, legal-age limits, e-cigarette control, LDCT screening, asbestos ban, radon plan, clean-cooking access, and occupational carcinogen controls. Data-Driven LCPS combined age-standardized incidence (ASIR), mortality (ASMR), mortality-to-incidence ratio (MIR), smoking prevalence, GDP, health expenditure, and HDI (normalized 0–1; higher = stronger prevention). Data from GLOBOCAN 2022, WHO GTCR 2023, World Bank, and UNDP HDR 2023 covered 40 countries (G20 + 20 others). Analyses included correlation, regression (adjusted for GDP, HDI), Bland–Altman agreement, and ROC AUC for MIR ≤0.60. Results: Among 32 complete datasets, Policy and Data-Driven LCPS correlated moderately (r = 0.31; 95% CI –0.04–0.60). Discrimination of favorable outcomes (MIR ≤0.60) showed AUC 0.68 vs 0.77. High-policy countries (≥75) had lower smoking (17%) and MIR (0.45) than those &lt;60 (27%, 0.65; p &lt;0.001). Policy LCPS inversely correlated with ASIR (r = –0.42; p = 0.004); Data-Driven LCPS showed a stronger link (r = –0.55; p &lt;0.001). Each 10-point LCPS-D increase predicted 2.4 fewer cases per 100 000 (β = –0.24 ± 0.07; p = 0.002). Results were consistent across income tiers. Conclusions: LCPS provides a validated, reproducible framework connecting prevention policy to measurable cancer burden. Data-Driven LCPS reflected performance most accurately, while Policy LCPS defined actionable tiers linked to lower smoking, incidence, and MIR. LCPS serves as a quantitative global benchmark for policy evaluation. Policy-driven lung cancer prevention score (LCPS-P) and data-driven lung cancer prevention score (LCPS-D): Domains and scoring weights. Component Type Wt Rule / Effect Smoke-free law P 1 Yes = 1 TAPS ban P 1 Yes = 1; Partial = 0.5 Pictorial ≥ 50 % P 1 Yes = 1 Excise ≥ 75 % P 1 Yes = 1 Plain pack P 0.5 Yes = 1 Legal age P 0.5 18–19 = 0.5; ≥ 21 = 1 E-cig reg P 0.5 Full/Prescr = 1; None = 0 LDCT screen P 2 Nat = 1; Reg = 0.5 Asbestos ban P 1 Yes = 1 Radon plan P 1 Yes = 1 Clean-cook &gt; 90 % P 1 Yes = 1 Occ carcinogen ctrl P 1.5 Yes = 1 ASIR D 1 Lower = better (1–scaled ASIR) ASMR D 1 Lower = better (1–scaled ASMR) MIR D 1 Lower = better (1–scaled MIR) Smoking prev D 1</ja

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Journal
Journal of Clinical Oncology
Published
2026-05-27
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.10518
Primary Topic
Economic and Financial Impacts of Cancer
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article
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article

Global development and validation of the Lung Cancer Prevention Score (LCPS): A quantitative framework linking policy strength, incidence, and outcomes across 40 countries.

Adarsh Vardhan Tangella, Ashwin Gajre, Shamanth Manjunatha Reddy
Journal of Clinical Oncology
Economic and Financial Impacts of Cancer
article

Global development and validation of the Lung Cancer Prevention Score (LCPS): A quantitative framework linking policy strength, incidence, and outcomes across 40 countries.

Adarsh Vardhan Tangella, Ashwin Gajre, Shamanth Manjunatha Reddy
article en

Abstract

10518 Background: Lung cancer is the leading cause of cancer worldwide. Despite advances in tobacco control, national prevention efforts remain fragmented. We developed and validated the Lung Cancer Prevention Score (LCPS), a 0–100 composite linking prevention policy strength with real-world outcomes for global benchmarking and equity tracking. Methods: Two LCPS models were created. Policy LCPS quantified 12 weighted domains: smoke-free laws, TAPS bans, ≥50% pictorial warnings, ≥75% excise tax, plain packaging, legal-age limits, e-cigarette control, LDCT screening, asbestos ban, radon plan, clean-cooking access, and occupational carcinogen controls. Data-Driven LCPS combined age-standardized incidence (ASIR), mortality (ASMR), mortality-to-incidence ratio (MIR), smoking prevalence, GDP, health expenditure, and HDI (normalized 0–1; higher = stronger prevention). Data from GLOBOCAN 2022, WHO GTCR 2023, World Bank, and UNDP HDR 2023 covered 40 countries (G20 + 20 others). Analyses included correlation, regression (adjusted for GDP, HDI), Bland–Altman agreement, and ROC AUC for MIR ≤0.60. Results: Among 32 complete datasets, Policy and Data-Driven LCPS correlated moderately (r = 0.31; 95% CI –0.04–0.60). Discrimination of favorable outcomes (MIR ≤0.60) showed AUC 0.68 vs 0.77. High-policy countries (≥75) had lower smoking (17%) and MIR (0.45) than those &lt;60 (27%, 0.65; p &lt;0.001). Policy LCPS inversely correlated with ASIR (r = –0.42; p = 0.004); Data-Driven LCPS showed a stronger link (r = –0.55; p &lt;0.001). Each 10-point LCPS-D increase predicted 2.4 fewer cases per 100 000 (β = –0.24 ± 0.07; p = 0.002). Results were consistent across income tiers. Conclusions: LCPS provides a validated, reproducible framework connecting prevention policy to measurable cancer burden. Data-Driven LCPS reflected performance most accurately, while Policy LCPS defined actionable tiers linked to lower smoking, incidence, and MIR. LCPS serves as a quantitative global benchmark for policy evaluation. Policy-driven lung cancer prevention score (LCPS-P) and data-driven lung cancer prevention score (LCPS-D): Domains and scoring weights. Component Type Wt Rule / Effect Smoke-free law P 1 Yes = 1 TAPS ban P 1 Yes = 1; Partial = 0.5 Pictorial ≥ 50 % P 1 Yes = 1 Excise ≥ 75 % P 1 Yes = 1 Plain pack P 0.5 Yes = 1 Legal age P 0.5 18–19 = 0.5; ≥ 21 = 1 E-cig reg P 0.5 Full/Prescr = 1; None = 0 LDCT screen P 2 Nat = 1; Reg = 0.5 Asbestos ban P 1 Yes = 1 Radon plan P 1 Yes = 1 Clean-cook &gt; 90 % P 1 Yes = 1 Occ carcinogen ctrl P 1.5 Yes = 1 ASIR D 1 Lower = better (1–scaled ASIR) ASMR D 1 Lower = better (1–scaled ASMR) MIR D 1 Lower = better (1–scaled MIR) Smoking prev D 1</ja

Journal of Clinical OncologyVol. 44(16_suppl)
MedStar Washington Hospital Center (US), Lokmanya Tilak Municipal General Hospital and Lokmanya Tilak Municipal Medical College (IN), University of Oklahoma Medical Center (US)
Openalex Percentile: Top 3%
Economic and Financial Impacts of Cancer
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