Abstract PO-065: National Clinical Trials Network biobanking during the COVID-19 pandemic
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.081 | 0.108 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.034 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".