Evidence map›Paper›PMID 30873729›Full record

Observational studyPharmacoepidemiology and drug safety2019

An evaluation of the impact of missing deaths on overall survival analyses of advanced non-small cell lung cancer patients conducted in an electronic health records database.

Gillis Carrigan, Samuel Whipple, Michael D Taylor, Aracelis Z Torres, Anala Gossai, Brandon Arnieri, Melisa Tucker, Philip P Hofmeister, Peter Lambert, Sandra D Griffith and 1 more

Erratum issuedAbstract readObservational Study
In one paragraph

Observational study in Pharmacoepidemiology and drug safety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
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

31 citing papers in PubMed.

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  11. Comparing prospectively assigned trial and real-world lung cancer patients.Journal of comparative effectiveness research · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Gillis CarriganGenentech, Inc, South San Francisco, CA, USA.ORCID 0000-0002-7973-3607
Samuel WhippleGenentech, Inc, South San Francisco, CA, USA.
Michael D TaylorGenentech, Inc, South San Francisco, CA, USA.
Aracelis Z TorresFlatiron Health, New York, NY, USA.
Anala GossaiFlatiron Health, New York, NY, USA.
Brandon ArnieriGenentech, Inc, South San Francisco, CA, USA.
Melisa TuckerFlatiron Health, New York, NY, USA.
Philip P HofmeisterFlatiron Health, New York, NY, USA.
Peter LambertGenentech, Inc, South San Francisco, CA, USA.
Sandra D GriffithFlatiron Health, New York, NY, USA.
William B CapraGenentech, Inc, South San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to assess the impact of missing death data on survival analyses conducted in an oncology EHR-derived database.

methodsThe study was conducted using the Flatiron Health oncology database and the National Death Index (NDI) as a gold standard. Three analytic frameworks were evaluated in advanced non-small cell lung cancer (aNSCLC) patients: median overall survival [mOS]), relative risk estimates conducted within the EHR-derived database, and "external control arm" analyses comparing an experimental group augmented with mortality data from the gold standard to a control group from the EHR-derived database only. The hazard ratios (HRs) obtained within the EHR-derived database (91% sensitivity) and the external control arm analyses, were compared with results when both groups were augmented with mortality data from the gold standard. The above analyses were repeated using simulated lower mortality sensitivities to understand the impact of more extreme levels of missing deaths.

resultsBias in mOS ranged from modest (0.6-0.9 mos.) in the EHR-derived cohort with (91% sensitivity) to substantial when lower sensitivities were generated through simulation (3.3-9.7 mos.). Overall, small differences were observed in the HRs for the EHR-derived cohort across comparative analyses when compared with HRs obtained using the gold standard data source. When only one treatment arm was subject to estimation bias, the bias was slightly more pronounced, but increased substantially when lower sensitivities were simulated.

conclusionsThe impact on survival analysis is minimal with high mortality sensitivity with only modest impact associated within external control arm applications.

Indexed as

Death CertificatesSurvival AnalysisAgedCarcinoma, Non-Small-Cell LungCohort StudiesDatabases, FactualElectronic Health RecordsFemaleHumansInformation Storage and RetrievalLung NeoplasmsMaleMiddle AgedRetrospective Studieslung cancermissing deathsoverall survivalpharmacoepidemiologysurvival analyses

Identifiers

PMID30873729
PMCPMC6594237

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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.