Evidence map›Paper›PMID 28476125›Full record

Observational studyBMC health services research2017

Performance of claims-based algorithms for identifying incident thyroid cancer in commercial health plan enrollees receiving antidiabetic drug therapies.

Donnie Funch, Douglas Ross, Betsey M Gardstein, Heather S Norman, Lauren A Sanders, Atheline Major-Pedersen, Helge Gydesen, David D Dore

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-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

11 citing papers in PubMed, 14 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

8 authors at 3 institutions in 2 countries.

Donnie FunchOptum Epidemiology, 1325 Boylston St., 10th floor, Boston, MA, 02215, USA. donnie.funch@optum.com.ORCID 0000-0003-3462-2716
Douglas RossMassachusetts General Hospital, Boston, MA, 02114, USA.
Betsey M GardsteinOptum Epidemiology, 1325 Boylston St., 10th floor, Boston, MA, 02215, USA.
Heather S NormanOptum Epidemiology, 1325 Boylston St., 10th floor, Boston, MA, 02215, USA.
Lauren A SandersOptum Epidemiology, 1325 Boylston St., 10th floor, Boston, MA, 02215, USA.
Atheline Major-PedersenGlobal Safety, Novo Nordisk A/S, Copenhagen, Denmark.
Helge GydesenEpidemiology, Novo Nordisk A/S, Copenhagen, Denmark.
David D DoreOptum Epidemiology, 1325 Boylston St., 10th floor, Boston, MA, 02215, USA.
New England College of Optometry · USNovo Nordisk (Denmark) · DKHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThyroid cancer incidence is increasing in the United States (US) and many other countries. The objective of this study was to develop and evaluate algorithms using administrative medical claims data for identification of incident thyroid cancer.

methodsThis effort was part of a prospective cohort study of adults initiating therapy on antidiabetic drugs and used administrative data from a large commercial health insurer in the US. Patients had at least 6 months of continuous enrollment prior to initiation during 2009-2013, with follow-up through March, 2014 or until disenrollment. Potential incident thyroid cancers were identified using International Classification of Diseases, 9

resultsCharts were requested for 170 patients, 150 (88%) were received and 141 (80%) had sufficient information to adjudicate. Of the 141 potential cases identified using ≥1 ICD-9 diagnosis code 193, 72 were confirmed as incident thyroid cancer (PPV of 51% (95% CI 43-60%)). Adding the requirement for thyroid surgery increased the PPV to 68% (95% CI 58-77%); including the presence of other therapies (chemotherapy, radio-iodine therapy) had no impact. When cases were required to have thyroid surgery during follow-up and ≥2 ICD-9 193 codes within 90 days of this surgery, the PPV was 91% (95% CI 81-96%); 62 (82%) of the true cases were identified and 63 (91%) of the non-cases were removed from consideration by the algorithm as potential cases.

conclusionsThese findings suggest a significant degree of misclassification results from relying only on ICD-9 diagnosis codes to detect thyroid cancer. An administrative claims-based algorithm was developed that performed well to identify true incident thyroid cancer cases.

Indexed as

AlgorithmsAdolescentAdultAgedDatabases, FactualFemaleHealth PlanningHospitalizationHumansHypoglycemic AgentsIncidenceInsurance Claim ReviewInternational Classification of DiseasesMaleMedical RecordsMiddle AgedHypoglycemic AgentsAlgorithmMethodsThyroid cancerValidation

Identifiers

PMID28476125
PMCPMC5420112
OpenAlexW2611080819

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.