Evidence map›Paper›PMID 34636730›Full record

ArticleJMIR medical informatics2021

An Automated Line-of-Therapy Algorithm for Adults With Metastatic Non-Small Cell Lung Cancer: Validation Study Using Blinded Manual Chart Review.

Weilin Meng, Kelly M Mosesso, Kathleen A Lane, Anna R Roberts, Ashley Griffith, Wanmei Ou, Paul R Dexter

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

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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 3 institutions in 1 country.

Weilin MengCenter for Observational and Real-World Evidence, Merck & Co, Inc, Kenilworth, NJ, United States.ORCID https://orcid.org/0000-0002-9303-2786
Kelly M MosessoDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0003-3724-3172
Kathleen A LaneDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0001-8784-2590
Anna R RobertsRegenstrief Institute, Inc, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-6675-2761
Ashley GriffithRegenstrief Institute, Inc, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-4411-5331
Wanmei OuCenter for Observational and Real-World Evidence, Merck & Co, Inc, Kenilworth, NJ, United States.ORCID https://orcid.org/0000-0002-4947-9548
Paul R DexterRegenstrief Institute, Inc, Indianapolis, IN, United States.ORCID https://orcid.org/0000-0002-0399-0156
Regenstrief Institute · USIndiana University School of MedicineMerck & Co., Inc., Rahway, NJ, USA (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExtraction of line-of-therapy (LOT) information from electronic health record and claims data is essential for determining longitudinal changes in systemic anticancer therapy in real-world clinical settings.

objectiveThe aim of this retrospective cohort analysis is to validate and refine our previously described open-source LOT algorithm by comparing the output of the algorithm with results obtained through blinded manual chart review.

methodsWe used structured electronic health record data and clinical documents to identify 500 adult patients treated for metastatic non-small cell lung cancer with systemic anticancer therapy from 2011 to mid-2018; we assigned patients to training (n=350) and test (n=150) cohorts, randomly divided proportional to the overall ratio of simple:complex cases (n=254:246). Simple cases were patients who received one LOT and no maintenance therapy; complex cases were patients who received more than one LOT and/or maintenance therapy. Algorithmic changes were performed using the training cohort data, after which the refined algorithm was evaluated against the test cohort.

resultsFor simple cases, 16 instances of discordance between the LOT algorithm and chart review prerefinement were reduced to 8 instances postrefinement; in the test cohort, there was no discordance between algorithm and chart review. For complex cases, algorithm refinement reduced the discordance from 68 to 62 instances, with 37 instances in the test cohort. The percentage agreement between LOT algorithm output and chart review for patients who received one LOT was 89% prerefinement, 93% postrefinement, and 93% for the test cohort, whereas the likelihood of precise matching between algorithm output and chart review decreased with an increasing number of unique regimens. Several areas of discordance that arose from differing definitions of LOTs and maintenance therapy could not be objectively resolved because of a lack of precise definitions in the medical literature.

conclusionsOur findings identify common sources of discordance between the LOT algorithm and clinician documentation, providing the possibility of targeted algorithm refinement.

Indexed as

automated algorithmline of therapylongitudinal changesmanual chart reviewnon–small cell lung cancersystemic anticancer therapy

Identifiers

PMID34636730
PMCPMC8548977
OpenAlexW3206589224

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.