<scp>Short‐term</scp> safety of an <scp>anti‐severe</scp> acute respiratory syndrome coronavirus 2 messenger <scp>RNA</scp> vaccine for patients with advanced lung cancer treated with anticancer drugs: A multicenter, prospective, observational study
Bibliographic record
Abstract
BACKGROUND: Since 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become prevalent worldwide. In severe cases, the case fatality rate is high, and vaccine prevention is important. This study evaluated the safety of receiving SARS-CoV-2 vaccine in patients with advanced lung cancer receiving anticancer therapy. METHODS: We prospectively enrolled patients receiving anticancer drugs for advanced lung cancer who planned to receive SARS-CoV-2 vaccination. Early adverse events within 7 days of vaccine injection were evaluated using patient-reported surveys. The chi-square test and multivariate logistic regression analyses were used. RESULTS: Among 120 patients receiving lung cancer treatment, 73 were men; the mean age of the patients was 73.5 years. The treatments received for lung cancer at the time of the first vaccine injection were chemotherapy, ICIs, combined chemotherapy and ICIs, and targeted therapies, including tyrosine kinase inhibitors, in 30, 28, 17, and 45 patients, respectively. All patients received SARS-CoV-2 messenger RNA (mRNA) vaccine. After the second mRNA vaccine dose, 15.4% of patients had fever of 38°C (95% confidence interval: 9.34%-23.2%); this rate was slightly higher than that for healthy participants at the time of the BNT162b2 trial. Patients treated with cytotoxic anticancer drugs tended to have high fever. In the multivariate analyses, male sex was associated with higher fever frequencies. However, there were no serious early adverse events due to vaccination. CONCLUSIONS: Anti-SARS-CoV-2 mRNA vaccination tends to be safe, but fever following vaccination tends to be more common among patients undergoing lung cancer treatment than among healthy individuals.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".