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Abstract PO-065: National Clinical Trials Network biobanking during the COVID-19 pandemic

2020· article· en· W3109580766 on OpenAlexaffabout
Heather A. Lankes, Mark A. Watson, Richard C. Jordan, Nilsa C. Ramirez, Ignacio I. Wistuba, Lois Shepherd, Irina A. Lubensky, Hala R. Makhlouf

Bibliographic record

VenueClinical Cancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiobankReceiptStaffingClinical trialPandemicMedicineTissue bankFamily medicineCoronavirus disease 2019 (COVID-19)BusinessDiseasePathologyBioinformaticsNursingAccountingBiology

Abstract

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Abstract The National Cancer Institute (NCI) has a large portfolio of ongoing cancer clinical trials that involve biospecimen collection and are supported by the NCI-funded National Clinical Trials Network (NCTN) Biospecimen Banks located across the United States and Canada. At the start of the COVID-19 pandemic, NCTN biobanks rapidly responded to staffing consequences of state- and institution-issued stay-at-home orders. Many of the NCTN biobanks were deemed essential by their institutions, allowing for limited and/or socially distanced operations. NCTN biobanks quickly worked with NCI and their respective groups to advise participating sites of changes to usual biospecimen collection procedures in order to accommodate limited staffing at the biobanks. In many instances, participating sites were navigating their own institutional process change due to the pandemic. NCTN cancer clinical trials experienced an approximate 40% decrease in enrollment from March 11 to May 19, 2020, compared to the same time frame in 2019. Likewise, NCTN biobanks saw an approximate 40% and 60% decrease in biospecimen receipt and distribution, respectively. The decrease in biospecimen receipt was likely due to two factors: (1) participating site COVID-19 policies limiting patient enrollment on NCI cancer clinical trials and/or biospecimen collection for those trials, and (2) NCTN biobank requests for participating sites to hold nonurgent and/or nonmandatory biospecimens during the initial phase of the pandemic. Decrease in biospecimen distributions was mainly due to receiving laboratory closures as dictated by their institutional COVID-19 policies. On May 20, 2020, all states had begun initial reopening phases to some extent. At this time, several, but not all, NCTN biobanks had begun measured return to full operations, following institutional guidance. NCTN biobanks are making numerous considerations toward returning to full operations and will continue to work with NCI and their respective groups to responsibly collect and distribute biospecimens collected during the COVID-19 pandemic. Likely, some patients enrolled on NCTN cancer clinical trials may have had clinical or subclinical COVID-19 at the time of biospecimen collection. Additionally, biospecimens will be collected on two recently activated NCI COVID-19 studies: (1) the NCI COVID-19 in Cancer Patients Study (NCCAPS): A Longitudinal Natural History Study (NCT04387656), and (2) a tocilizumab treatment trial for COVID-19-related acute respiratory distress syndrome in cancer patients (NCT04370834). Retrospective annotation of these biospecimens may provide a unique resource for translational research efforts and will also be a needed caveat for interpreting biomarker studies conducted using these biospecimens, as the impact of COVID-19 on various biomarkers is currently unknown. Citation Format: Heather A. Lankes, Mark A. Watson, Richard C. Jordan, Nilsa C. Ramirez, Ignacio I. Wistuba, Lois Shepherd, Irina A. Lubensky, Hala Makhlouf. National Clinical Trials Network biobanking during the COVID-19 pandemic [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr PO-065.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.070
metaresearch head score (Gemma)0.053
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0700.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.858
GPT teacher head0.701
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes2
Has abstractyes

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