COVID-19 Related Publications Focusing on Cancer: Systematic Review of a Delicate Balance
Bibliographic record
Abstract
Background:: The ongoing COVID-19 pandemic has forced oncologists to alter their daily practice, despite the lack of substantial evidence, in order to reduce the risk of transmission among patients with underlying malignant and other concurrent medical conditions. Objective:: This systematic review compares the characteristics of oncology-focused COVID-19 manuscripts published from January 1st to April 30th, 2020, and from September 1st to September 30th, 2020, to identify the variation of publications between the start of the pandemic and our current state. Methods:: The PubMed database was searched on two different occasions using the search string “Cancer OR Tumor” AND “COVID-19 OR SARS-CoV-2”. All manuscripts pertaining to COVID-19 and oncological topics were included in this review. Results:: The search from January 1st to April 30th, 2020 and from September 1st to September 30th, 2020, resulted in 299 and 249 articles pertaining to our objective, respectively. Comparing the earlier with later publication period, the proportion of articles containing original data increased from 22.4% to 44.2%, whereas the proportion of Editorials/Correspondences decreased from 43.5% to 20.5%. Cancer patient management guidelines accounted for the majority of publications during both periods (59.2% versus 43.4%, respectively). Conclusion:: The study revealed a rapidly increasing number of COVID-19 and oncological-focused publications throughout the pandemic thus far. Given the unprecedented nature of the COVID-19 pandemic, future analyses are expected to reveal rapidly evolving publication patterns.
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How this classification was reachedexpand
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".