Evidence map›Paper›PMID 38702684›Full record

ArticleBMC medicine2024

Histology-specific standardized incidence ratio improves the estimation of second primary lung cancer risk.

Marian Eberl, Luana F Tanaka, Klaus Kraywinkel, Stefanie J Klug

Abstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Marian EberlTUM School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 56, Munich, 80992, Germany. marian.eberl@tum.de.ORCID 0000-0001-6584-3197
Luana F TanakaTUM School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 56, Munich, 80992, Germany.ORCID 0000-0002-2086-7491
Klaus KraywinkelGerman Centre for Cancer Registry Data, Robert Koch-Institut, Nordufer 20, Berlin, 13353, Germany.ORCID 0000-0002-9250-6003
Stefanie J KlugTUM School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 56, Munich, 80992, Germany.ORCID 0000-0003-3523-1362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung 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.

methodsWe (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.

resultsThe 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.

conclusionsOur proposed histology-specific method makes the SIR metric more robust against MP rules and, thus, more suitable for cross-country comparisons.

Indexed as

Lung NeoplasmsNeoplasms, Second PrimaryAdultAgedAged, 80 and overFemaleGermanyHumansIncidenceMaleMiddle AgedRegistriesRisk AssessmentRisk FactorsUnited StatesCancer epidemiologyCancer registry dataLung cancerSecond primary cancerStandardized incidence ratio

Identifiers

PMID38702684
PMCPMC11069219

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.