Impact of COVID-19 on the Diagnosis and Management of Multiple Myeloma: Experience from a Canadian Center
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The impact of coronavirus disease-19 on the management of multiple myeloma (MM) has been recognized. However, the real effect on clinical outcomes remains poorly understood. OBJECTIVE: We describe a local experience of the management of MM patients and report their outcomes during the current pandemic. METHODS: All consecutive symptomatic MM patients seen at our center since 03/20 were evaluated. RESULTS: A cohort of 156 patients diagnosed from 01/19 to 12/20 was analyzed to interrogate differences in presentation patterns. A total of 553 MM patients were seen and/or treated at Tom Baker Cancer Center in the year of 2020. From those, 47.1% (n = 261) were tested for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Sixteen patients tested positive and data are presented. In addition, a decrease of 21.7% in the rate of new smoldering MM/MM diagnosis was observed in 2020 as compared to 2019. Further, an increase in deaths was also observed in 2020. CONCLUSIONS: Our study confirms an increase lethality for MM patients infected with SARS-CoV-2. A balance between safety and need for cancer control should be emphasized.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it