Evidence map›Paper›PMID 42558864›Full record

ArticleOpen forum infectious diseases2026

Harmonization of Real-World Data for Vaccine-Preventable Infectious Diseases: Integration of SARS-CoV-2 Diagnostic and Serologic Data From Multiple Sources.

Yonah C Ziemba, Suhyeon Yoon, Harvey W Kaufman, William A Meyer, Laura Gillim, Nkemakonam Okoye, Cheryl B Schleicher, Shahidul Islam, Cristina P Sison, Ligia A Pinto and 2 more

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Yonah C ZiembaNorthwell Health, Department of Pathology and Laboratory Medicine, New Hyde Park, New York, USA.ORCID https://orcid.org/0000-0002-9308-2695
Suhyeon YoonIntegrated Data Sciences Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Harvey W KaufmanDepartment of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-2850-9047
William A MeyerQuest Diagnostics, Secaucus, New Jersey, USA.ORCID https://orcid.org/0000-0003-2791-995X
Laura GillimLabcorp, Burlington, North Carolina, USA.ORCID https://orcid.org/0009-0005-0965-6043
Nkemakonam OkoyeNorthwell Health, Department of Pathology and Laboratory Medicine, New Hyde Park, New York, USA.
Cheryl B SchleicherNorthwell Health, Department of Pathology and Laboratory Medicine, New Hyde Park, New York, USA.ORCID https://orcid.org/0009-0002-2089-0613
Shahidul IslamNorthwell Health, Feinstein Institutes for Medical Research, Manhasset, New York, USA.ORCID https://orcid.org/0000-0002-9385-101X
Cristina P SisonNorthwell Health, Feinstein Institutes for Medical Research, Manhasset, New York, USA.
Ligia A PintoFrederick National Laboratory for Cancer Research, Frederick, Maryland, USA.
Lynne PenberthyData Axle, Inc., Dallas, Texas, USA.
James M CrawfordNorthwell Health, Department of Pathology and Laboratory Medicine, New Hyde Park, New York, USA.ORCID https://orcid.org/0000-0002-8581-1093

Funding

WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · PI BRISCOE, LYNN · 2019 to 2025
$3932.6M
NIH HHS 75N91019D00024
6 · The paper itself

Abstract

Background: The COVID-19 Real World Data infrastructure (CRWDi) was established to study the impact of coronavirus disease 2019 (COVID-19) on patients with immunocompromising conditions. A key challenge was harmonizing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) laboratory test results. Methods: There were 27 different test names for SARS-CoV-2 nucleic acid amplification tests (NAATs), and there were 34 and 26 for SARS-CoV-2 qualitative and semiquantitative serologic tests, respectively. We validated a strategy to eliminate the multiplicity of test names and results, and harmonized SARS-CoV-2 semiquantitative serology test results by target antigen and antibody using published conversion factors to report Binding Arbitrary Units (BAU) on a uniform scale. Results: For 5 200 000 patients, the numbers of unique SARS-CoV-2 test events were 4 865 431 NAAT, 3 092 198 qualitative, and 834 487 semiquantitative serology tests, of which 378 522 were antispike (anti-S) semiquantitative serology. In achieving harmonization of semiquantitative serologic results, semi-log cumulative ordinal plots demonstrated that test results from patients with transplantation exhibited a significantly higher proportion of negative-and-submaximal SARS-CoV-2 anti-S BAU values when compared with patients with cancer or systemic autoimmune or rheumatic diseases (SARDs) or with a general nonimmunocompromised population. Conclusions: Complex and heterogeneous test name and result conventions can represent a significant barrier to understanding the clinical relevance of real-world laboratory data. The generalizable methodology described herein permitted successful harmonization of SARS-CoV-2 diagnostic and serologic test data from multiple laboratory sources with administrative claims data, vital status data, and structured data on cancer diagnostics and treatment. This methodology supports exploration of the clinical utility of semiquantitative serologic data, especially in patients with immunocompromising conditions.

Indexed as

cancerLOINCSARDsstandardizationtransplantation

Identifiers

PMID42558864
PMCPMC13439318

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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.