Cancer epidemiology · 2026
Is the standardized incidence ratio of second primary cancers robust to index-cancer survival gains? A simulation and SEER-based evaluation.
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Heudel Pierre-Etienne
Аннотация
BACKGROUND: The burden of second primary cancers (SPCs) is rising, partly because patients with a first cancer now survive longer. Two metrics coexist to quantify SPC risk: cumulative incidence, whose dependence on survival is well recognised, and the standardized incidence ratio (SIR), widely treated as survival-robust because it accounts for person-years at risk. Calendar-era SIR trends are increasingly reported and interpreted as real changes in risk, yet whether such trends could instead arise artefactually from concurrent gains in index-cancer survival has never been tested.
METHODS: We combined a calibrated simulation with an empirical analysis of SEER 17 (2000-2023). The simulation generated cohorts with strictly constant, stage-specific SPC risk, allowing only index-cancer 12-month survival to vary according to SEER-measured values, and applied a 12-month latency exclusion reproducing the SEER*Stat multiple-primary SIR procedure. Empirically, across 27 site × stage strata spanning wide survival-gain gradients, we related the observed 12-month survival gain (2004-09 vs 2015-18) to the calendar-year slope of the SPC SIR (Poisson regression), with six sensitivity analyses and a power calculation.
RESULTS: At constant stage-specific risk, the simulated SIR drifted with survival, but across 200 Monte-Carlo replications the median bias-attributable slope was more than an order of magnitude smaller than the observed SIR slope (0.28 vs 7.9 × 10⁻³ per year), despite per-stage SIRs differing enough for the mechanism to act. Empirically, survival gain and SIR slope were unrelated (Pearson r = -0.00, p = 0.99), robust across all sensitivity analyses; power was adequate to detect r ≥ 0.50.
CONCLUSIONS: Survivor-recomposition bias in the SPC SIR exists in principle but was small on average in the sites and calendar period studied. Unlike cumulative incidence, the SIR can generally be interpreted across calendar eras without major survival correction, although weak, site-specific, or longer-term effects cannot be excluded.
METHODS: We combined a calibrated simulation with an empirical analysis of SEER 17 (2000-2023). The simulation generated cohorts with strictly constant, stage-specific SPC risk, allowing only index-cancer 12-month survival to vary according to SEER-measured values, and applied a 12-month latency exclusion reproducing the SEER*Stat multiple-primary SIR procedure. Empirically, across 27 site × stage strata spanning wide survival-gain gradients, we related the observed 12-month survival gain (2004-09 vs 2015-18) to the calendar-year slope of the SPC SIR (Poisson regression), with six sensitivity analyses and a power calculation.
RESULTS: At constant stage-specific risk, the simulated SIR drifted with survival, but across 200 Monte-Carlo replications the median bias-attributable slope was more than an order of magnitude smaller than the observed SIR slope (0.28 vs 7.9 × 10⁻³ per year), despite per-stage SIRs differing enough for the mechanism to act. Empirically, survival gain and SIR slope were unrelated (Pearson r = -0.00, p = 0.99), robust across all sensitivity analyses; power was adequate to detect r ≥ 0.50.
CONCLUSIONS: Survivor-recomposition bias in the SPC SIR exists in principle but was small on average in the sites and calendar period studied. Unlike cumulative incidence, the SIR can generally be interpreted across calendar eras without major survival correction, although weak, site-specific, or longer-term effects cannot be excluded.