Evidence map›Paper›PMID 38287392›Full record

ArticleBMC medicine2024

Isolating the effect of confounding from the observed survival benefit of screening participants - a methodological approach illustrated by data from the German mammography screening programme.

Laura Buschmann, Ina Wellmann, Nadine Bonberg, Jürgen Wellmann, Hans-Werner Hense, André Karch, Heike Minnerup

Open access · goldAbstract 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
0.3field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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 citations in OpenAlex.

  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

7 authors at 1 institution in 1 country.

Laura Buschmann *Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany. laura.buschmann@ukmuenster.de.ORCID 0000-0002-8389-1253
Ina Wellmann *Cancer Registry of North Rhine-Westphalia, Bochum, Germany.ORCID 0009-0001-1831-2542
Nadine BonbergInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Jürgen WellmannInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0003-3635-8584
Hans-Werner HenseInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0002-7381-1547
André Karch *Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0003-3014-8543
Heike Minnerup *Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0002-9706-7599
University of Münster · DE

Funding

The project was funded by the Federal Office for Radiation Protection from funds of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety, the Federal Ministry of Health and the Kooperationsgemeinschaft Mammographie (supported by 3617S42402The project was funded by the Federal Office for Radiation Protection from funds of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety, the Federal Ministry of Health and the Kooperationsgemeinschaft Mammographie (supported by 3621S42410
6 · The paper itself

Abstract

backgroundMammography screening programmes (MSP) aim to reduce breast cancer mortality by shifting diagnoses to earlier stages. However, it is difficult to evaluate the effectiveness of current MSP because analyses can only rely on observational data, comparing women who participate in screening with women who do not. These comparisons are subject to several biases: one of the most important is self-selection into the MSP, which introduces confounding and is difficult to control for. Here, we propose an approach to quantify confounding based on breast cancer survival analyses using readily available routine data sources.

methodsUsing data from the Cancer Registry of North Rhine-Westphalia, Germany, we estimate the relative contribution of confounding to the observed survival benefit of participants of the German MSP. This is accomplished by comparing non-participants, participants with screen-detected and participants with interval breast cancers for the endpoints "death from breast cancer" and "death from all causes other than breast cancer" - the latter being assumed to be unrelated to any MSP effect. By using different contrasts, we eliminate the effects of stage shift, lead and length time bias. The association of breast cancer detection mode with survival is analysed using Cox models in 68,230 women, aged 50-69 years, with breast cancer diagnosed in 2006-2014 and followed up until 2018.

resultsThe hazard of dying from breast cancer was lower in participants with screen-detected cancer than in non-participants (HR = 0.21, 95% CI: 0.20-0.22), but biased by lead and length time bias, and confounding. When comparing participants with interval cancers and non-participants, the survival advantage was considerably smaller (HR = 0.62, 95% CI: 0.58-0.66), due to the elimination of stage shift and lead time bias. Finally, considering only mortality from causes other than breast cancer in the latter comparison, length time bias was minimised, but a survival advantage was still present (HR = 0.63, 95% CI: 0.56-0.70), which we attribute to confounding.

conclusionsThis study shows that, in addition to stage shift, lead and length time bias, confounding is an essential component when comparing the survival of MSP participants and non-participants. We further show that the confounding effect can be quantified without explicit knowledge of potential confounders by using a negative control outcome.

Indexed as

Breast NeoplasmsMammographyAgedCausalityEarly Detection of CancerFemaleHumansMass ScreeningMiddle AgedSurvival AnalysisBiasBreast cancerConfoundingMammography screeningSurvival

Identifiers

PMID38287392
PMCPMC10826012
OpenAlexW4391329505

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.