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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Lung cancer (LC) survivors are at increased risk for developing a second primary cancer (SPC) compared to the general population. While this risk is particularly high for smoking-related SPCs, the published standardized incidence ratio (SIR) for lung cancer after lung cancer is unexpectedly low in countries that follow international multiple primary (IARC/IACR MP) rules when compared to the USA, where distinct rules are employed. IARC/IACR rules rely on histology-dependent documentation of SPC with the same location as the first cancer and only classify an SPC when tumors present different histology. Thus, SIR might be underestimated in cancer registries using these rules. This study aims to assess whether using histology-specific reference rates for calculating SIR improves risk estimates for second primary lung cancer (SPLC) in LC survivors.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We (i) use the distribution of histologic subtypes of LC in population-based cancer registry data of 11 regional cancer registries from Germany to present evidence that the conventional SIR metric underestimates the actual risk for SPLC in LC survivors in registries that use IARC/IACR MP rules, (ii) present updated risk estimates for SPLC in Germany using a novel method to calculate histological subtype-specific SIRs, and (iii) validate this new method using US SEER (Surveillance, Epidemiology, and End Results Program) data, where different MP rules are applied.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The adjusted relative risk for lung cancer survivors in Germany to develop an SPLC was 2.98 (95% CI 2.53–3.49) for females and 1.15 (95% CI 1.03–1.27) for males using the novel histology-specific SIR. When using IARC/IACR MP rules, the conventional SIR underestimates the actual risk for SPLC in LC survivors by approximately 30% for both sexes.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our proposed histology-specific method makes the SIR metric more robust against MP rules and, thus, more suitable for cross-country comparisons.</jats:p></jats:sec>
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1000
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Hinweis
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DeepGreen-ID: 2aaeb0092a9640cc9a4c698a59acb1d7 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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