Abstract PO-029: Operationalizing a prioritized COVID-19 testing strategy at a Canadian tertiary care cancer center
Bibliographic record
Abstract
Abstract Background: Available data suggest that cancer patients who contract COVID-19 may have worse outcomes, including a higher mortality compared to noncancer patients. In an effort to inform and guide our clinicians in the ongoing management of cancer patients during the COVID-19 pandemic, CancerControl Alberta (CCA) implemented targeted fast-track testing for symptomatic, immunocompromised cancer patients in the ambulatory setting. We report the results of the first 7 weeks of testing at the Tom Baker Cancer Centre (TBCC), a comprehensive tertiary cancer center serving southern Alberta (population approximately 2 million). Methods: Referral for prioritized COVID-19 testing (results within 24 hours) was intended for ambulatory cancer patients who were identified to have symptoms consistent with an influenza-like illness and confirmed to meet at least one of the following criteria: stem cell transplant recipient, hematologic malignancy, cancer diagnosis receiving >0.5 mg/kg/day of prednisone or equivalent, patients on immunotherapy treatment, patients on active chemotherapy within the last 3 weeks, neutropenia (ANC <500), lung cancer, chronic lung disease (e.g., COPD), or patients receiving curative radiation. Testing occurred on site at the TBCC at a designated drive-through testing area where staff, using PPE, tested patients who remained in their cars. The assay for COVID-19 was nucleic acid-based test, and patients were also tested for a standard respiratory virus panel. Patients received either a nasopharyngeal or throat swab, for hematologic and solid tumors diagnoses, respectively. Descriptive analyses were performed. Results: Between April 15th and June 1st, 2020, 80 patients received prioritized testing at the Tom Baker Cancer Centre. Patients who were tested for COVID-19 had the following characteristics: median age of 60.5 years (range 19, 85) and 31% were male. The majority of tested patients (80%) met the criteria as outlined to prioritize testing. Patients with the following tumor types comprised over 80% of those tested: breast (n=22), hematologic (n=16), lung (n=9), gynecologic (n=9), and GI (n=9). The average time from screening to testing was 26.5 hours, and the average time from test to result was 12.8 hours. At the time of reporting, only one breast cancer patient, who just finished chemotherapy, tested positive via the fast-track testing process; this patient received repeat clearance testing, undergoing a total of 6 tests over one month before achieving 2 negative tests. Conclusions: Our experience demonstrates that prioritized testing for COVID-19 among those who are potentially the most susceptible, namely immunocompromised cancer patients, is feasible. Very few (1%) positive cases of COVID-19 were identified, among 80 patients tested in the first 47 days of operationalizing the fast-track testing process. Expedited testing should be considered as an ongoing strategy to provide guidance to clinicians in managing cancer patients during the COVID-19 pandemic. Citation Format: April A. Hildebrand, Desiree Hao, Safiya Karim, Winson Y. Cheung, Don Morris, Daniel Y. C. Heng. Operationalizing a prioritized COVID-19 testing strategy at a Canadian tertiary care cancer center [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-029.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".