Spontaneous Regression of Metastatic Renal Cell Carcinoma after SARS-CoV-2 Infection: A Report of Two Cases
Bibliographic record
Abstract
Spontaneous regression of metastatic renal cell carcinoma (mRCC) is a rare event, often associated with an activation of innate immunity by various triggers. SARS-CoV-2 infection induces a strong inflammatory response in some patients and a cytokine storm is one of the main causes of severe morbidity and mortality associated with the virus. Here, we describe two cases of patients with histologically and radiologically proven mRCC whose treatment was delayed due to COVID-19 and who experienced spontaneous tumour regression following the infection. Both patients reported here had predominantly pulmonary and mediastinal involvement and underwent nephrectomy. The interval between the diagnosis of COVID-19 and the detection of tumour regression was 3 and 4 months, respectively. Although approved vaccines and other measures are clearly the best way to prevent COVID-19-associated morbidity and mortality in cancer patients, we hypothesize that innate immunity activation by the infection can contribute to tumour regression in special circumstances.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".